id int64 0 3.35k | market stringclasses 2
values | category stringclasses 3
values | question stringlengths 58 620 | answer float64 -13,969,234,422.09 113B | difficulty stringclasses 3
values | sub-category stringclasses 21
values | formula stringclasses 208
values | data stringlengths 43 29.2k | data_indicator stringlengths 64 28.2k ⌀ |
|---|---|---|---|---|---|---|---|---|---|
3,200 | US | technical | What is the value of Expected Shortfall (Historical Simulation) for Weyerhaeuser from April 29, 2019 to March 19, 2020? (1-day ES; default confidence 95%) Using unadjusted prices, write down the indicator formula, collect the raw data, calculate the answer, and keep four decimal places. Please list the raw data and key... | 0.0834 | easy | risk | ES_c = -E[r | r \le Q_{1-c}(r)] | date,close
2019-04-26,27.3700008392334
2019-04-29,26.459999084472656
2019-04-30,26.799999237060547
2019-05-01,26.63999938964844
2019-05-02,26.459999084472656
2019-05-03,26.780000686645508
2019-05-06,26.600000381469727
2019-05-07,26.030000686645508
2019-05-08,25.6299991607666
2019-05-09,25.65999984741211
2019-05-10,25.5... | null |
3,201 | US | technical | From April 01, 2021 to December 21, 2021, what is Paramount Skydance Corporation's Expected Shortfall (Historical Simulation)? (1-day ES; default confidence 95%) Using unadjusted prices, write down the indicator formula, collect the raw data, calculate the answer, and keep four decimal places. Please list the raw data ... | 0.0418 | easy | risk | ES_c = -E[r | r \le Q_{1-c}(r)] | date,close
2021-03-31,45.09999847412109
2021-04-01,44.63999938964844
2021-04-05,42.900001525878906
2021-04-06,44.34999847412109
2021-04-07,43.88999938964844
2021-04-08,42.290000915527344
2021-04-09,41.880001068115234
2021-04-12,39.77000045776367
2021-04-13,40.4900016784668
2021-04-14,40.220001220703125
2021-04-15,39.25... | null |
3,202 | US | technical | What was Targa Resources's Expected Shortfall (Historical Simulation) during the period February 19, 2020 to March 31, 2020? (1-day ES; default confidence 95%) Using unadjusted prices, write down the indicator formula, collect the raw data, calculate the answer, and keep four decimal places. Please list the raw data an... | 0.4365 | easy | risk | ES_c = -E[r | r \le Q_{1-c}(r)] | date,close
2020-02-18,36.86000061035156
2020-02-19,36.95000076293945
2020-02-20,39.45000076293945
2020-02-21,39.13999938964844
2020-02-24,37.7599983215332
2020-02-25,35.66999816894531
2020-02-26,34.7400016784668
2020-02-27,32.27000045776367
2020-02-28,32.400001525878906
2020-03-02,33.90999984741211
2020-03-03,33.069999... | null |
3,203 | US | technical | For Expected Shortfall (Historical Simulation), what is T-Mobile US's value from March 17, 2023 to January 26, 2024? (1-day ES; default confidence 95%) Using unadjusted prices, write down the indicator formula, collect the raw data, calculate the answer, and keep four decimal places. Please list the raw data and key ca... | 0.0277 | easy | risk | ES_c = -E[r | r \le Q_{1-c}(r)] | date,close
2023-03-16,141.50999450683594
2023-03-17,142.4499969482422
2023-03-20,145.61000061035156
2023-03-21,144.6699981689453
2023-03-22,143.4600067138672
2023-03-23,142.3000030517578
2023-03-24,142.5399932861328
2023-03-27,143.89999389648438
2023-03-28,142.7899932861328
2023-03-29,143.80999755859375
2023-03-30,144.... | null |
3,204 | US | technical | Calculate Intercontinental Exchange's Expected Shortfall (Historical Simulation) from November 20, 2023 to June 09, 2024. (1-day ES; default confidence 95%) Using unadjusted prices, write down the indicator formula, collect the raw data, calculate the answer, and keep four decimal places. Please list the raw data and k... | 0.0172 | easy | risk | ES_c = -E[r | r \le Q_{1-c}(r)] | date,close
2023-11-17,111.4000015258789
2023-11-20,112.1500015258789
2023-11-21,113.4499969482422
2023-11-22,114.31999969482422
2023-11-24,114.38999938964844
2023-11-27,113.13999938964844
2023-11-28,112.77999877929688
2023-11-29,112.69000244140624
2023-11-30,113.83999633789062
2023-12-01,114.23999786376952
2023-12-04,1... | null |
3,205 | US | technical | What is the percentage of days with long alignment for the 10, 20, 30-day Simple Moving Average lines for Mondelez International from January 08, 2020 to October 29, 2020? (Unit: %) Using unadjusted prices, write down the indicator formula, collect the raw data, calculate the answer, and keep four decimal places. Pleas... | 41.7476 | hard | moving average | SMA_n = 1 / n * \sum_{i=0}^{n-1} P_{t-i} | date,close,low,open
2019-11-25,52.040000915527344,51.70000076293945,51.84999847412109
2019-11-26,52.619998931884766,51.95000076293945,52.09999847412109
2019-11-27,52.72999954223633,52.43999862670898,52.72999954223633
2019-11-29,52.540000915527344,52.22999954223633,53.09999847412109
2019-12-02,52.84000015258789,52.11999... | date,10-day,20-day,30-day
2020-01-08,54.58900032043457,54.38550033569336,53.95900026957194
2020-01-09,54.50900001525879,54.39200019836426,54.03066685994466
2020-01-10,54.44900016784668,54.40800018310547,54.08500022888184
2020-01-13,54.380000305175784,54.48850021362305,54.147000249226885
2020-01-14,54.29900016784668,54.... |
3,206 | US | technical | From August 30, 2022 to June 22, 2023, what proportion of days had the 10, 20, 30-day Simple Moving Average lines of EQT Corporation in long alignment? (Unit: %) Using unadjusted prices, write down the indicator formula, collect the raw data, calculate the answer, and keep four decimal places. Please list the raw data ... | 27.451 | hard | moving average | SMA_n = 1 / n * \sum_{i=0}^{n-1} P_{t-i} | date,close,low,open
2022-07-20,41.209999084472656,38.58000183105469,38.86000061035156
2022-07-21,42.43999862670898,40.060001373291016,40.43000030517578
2022-07-22,42.22999954223633,42.15999984741211,43.31999969482422
2022-07-25,44.97999954223633,42.18999862670898,43.02000045776367
2022-07-26,45.56999969482422,45.0,46.2... | date,10-day,20-day,30-day
2022-08-30,48.57299957275391,46.21199951171875,45.235999552408856
2022-08-31,48.64199943542481,46.46249942779541,45.45566622416178
2022-09-01,48.44899940490723,46.71549949645996,45.58466631571452
2022-09-02,48.40699920654297,46.96549949645996,45.75299962361654
2022-09-06,48.03799934387207,47.1... |
3,207 | US | technical | During August 29, 2023 to March 27, 2024, what percentage of trading days showed short alignment of Leidos's 5, 10, 20-day Simple Moving Average lines? Using unadjusted prices, write down the indicator formula, collect the raw data, calculate the answer, and keep four decimal places. Please list the raw data and key ca... | 14.3836 | hard | moving average | SMA_n = 1 / n * \sum_{i=0}^{n-1} P_{t-i} | date,close,low,open
2023-08-02,98.5500030517578,98.3000030517578,99.98999786376952
2023-08-03,98.4000015258789,97.5999984741211,98.70999908447266
2023-08-04,97.0999984741211,96.80999755859376,99.08000183105467
2023-08-07,97.62999725341795,96.93000030517578,97.23999786376952
2023-08-08,97.0,96.36000061035156,97.44000244... | date,5-day,10-day,20-day
2023-08-29,96.27800140380859,96.24500045776367,96.97250022888184
2023-08-30,96.77000122070312,96.3620002746582,96.94300003051758
2023-08-31,96.99000091552735,96.48200073242188,96.89850006103515
2023-09-01,97.6,96.75600051879883,96.98549995422363
2023-09-05,97.71999969482422,96.85500030517578,96... |
3,208 | US | technical | For Costco from July 28, 2022 to August 13, 2022, what percentage of days were the 10, 20, 30-day Simple Moving Average lines in short alignment? (Unit: %) Using unadjusted prices, write down the indicator formula, collect the raw data, calculate the answer, and keep four decimal places. Please list the raw data and ke... | 0 | hard | moving average | SMA_n = 1 / n * \sum_{i=0}^{n-1} P_{t-i} | date,close,low,open
2022-06-15,458.7900085449219,451.3900146484375,458.5
2022-06-16,451.760009765625,447.9700012207031,450.30999755859375
2022-06-17,446.6900024414063,443.2000122070313,451.0499877929688
2022-06-21,463.1099853515625,449.1400146484375,450.5499877929688
2022-06-22,459.9599914550781,458.5,459.3900146484375... | date,10-day,20-day,30-day
2022-07-28,524.2419982910156,508.9245010375977,494.6123331705729
2022-07-29,526.0769958496094,512.0255004882813,497.3626658121745
2022-08-01,529.1279968261719,515.0779998779296,500.5309987386068
2022-08-02,531.4510009765625,517.8380004882813,503.7566660563151
2022-08-03,533.7320007324219,520.5... |
3,209 | US | technical | Calculate the percentage of days with long alignment in the 5, 10, 20-day Simple Moving Average lines for Arch Capital Group from December 09, 2021 to April 16, 2022. Using unadjusted prices, write down the indicator formula, collect the raw data, calculate the answer, and keep four decimal places. Please list the raw ... | 48.8636 | hard | moving average | SMA_n = 1 / n * \sum_{i=0}^{n-1} P_{t-i} | date,close,low,open
2021-11-11,41.470001220703125,41.18000030517578,41.7599983215332
2021-11-12,42.02000045776367,40.959999084472656,41.52000045776367
2021-11-15,42.36000061035156,42.18000030517578,42.18000030517578
2021-11-16,42.68999862670898,42.54999923706055,42.59999847412109
2021-11-17,42.150001525878906,41.979999... | date,5-day,10-day,20-day
2021-12-09,43.12200012207031,42.263000106811525,42.38450031280517
2021-12-10,43.35800018310547,42.417000198364256,42.48250026702881
2021-12-13,43.4,42.579000091552736,42.54900016784668
2021-12-14,43.47799987792969,42.91599998474121,42.6185001373291
2021-12-15,43.58799972534179,43.23699989318847... |
3,210 | US | technical | What is the percentage of days with long alignment for the 5, 20, 60-day Weighted Moving Average lines for Travelers Companies (The) from January 21, 2025 to June 13, 2025? (Unit: %) (Weights are 1, 2, ..., n) Using unadjusted prices, write down the indicator formula, collect the raw data, calculate the answer, and kee... | 55.4455 | hard | moving average | WMA_n = \sum_{i=0}^{n-1} (n-i) * P_{t-i} / \sum_{j=1}^{n} j | date,close,open,low,high
2024-10-23,257.3500061035156,258.8500061035156,254.41000366210935,258.8800048828125
2024-10-24,256.4200134277344,260.0,255.2899932861328,260.1499938964844
2024-10-25,250.5,257.3099975585937,250.44000244140625,257.3999938964844
2024-10-28,252.3699951171875,253.75999450683597,252.1499938964844,25... | date,5-day,20-day,60-day
2025-01-21,239.8586669921875,239.60552251906623,246.41634378068434
2025-01-22,242.23466796875,240.23676082066126,246.31908153262947
2025-01-23,242.221332804362,240.32890327090308,246.05680813815425
2025-01-24,242.22266642252603,240.450808207194,245.81415790495325
2025-01-27,245.30799763997396,2... |
3,211 | US | technical | From May 01, 2023 to May 13, 2023, what proportion of days had the 5, 20, 60-day Weighted Moving Average lines of Texas Pacific Land Corporation in short alignment? (Unit: %) (Weights are 1, 2, ..., n) Using unadjusted prices, write down the indicator formula, collect the raw data, calculate the answer, and keep four d... | 100 | hard | moving average | WMA_n = \sum_{i=0}^{n-1} (n-i) * P_{t-i} / \sum_{j=1}^{n} j | date,close,open,low,high
2023-02-03,223.25999450683597,215.1522216796875,215.1522216796875,223.27444458007807
2023-02-06,212.7077789306641,222.35667419433597,204.3800048828125,222.35667419433597
2023-02-07,221.05667114257807,215.6499938964844,209.1922149658203,221.76222229003903
2023-02-08,210.9577789306641,218.2844390... | date,5-day,20-day,60-day
2023-05-01,163.89881388346353,174.9008292788551,185.20609787070686
2023-05-02,162.2825907389323,172.7894058227539,184.1438694604759
2023-05-03,161.13229573567708,170.83804117838542,183.10614399727575
2023-05-04,158.3590342203776,168.4973157610212,181.90838299527195
2023-05-05,157.2896301269531,... |
3,212 | US | technical | During May 28, 2024 to November 16, 2024, what percentage of trading days showed long alignment of Jack Henry & Associates's 5, 10, 20-day Weighted Moving Average lines? (Weights are 1, 2, ..., n) Using unadjusted prices, write down the indicator formula, collect the raw data, calculate the answer, and keep four decima... | 40.4959 | hard | moving average | WMA_n = \sum_{i=0}^{n-1} (n-i) * P_{t-i} / \sum_{j=1}^{n} j | date,close,open,low,high
2024-04-30,162.69000244140625,165.02999877929688,162.24000549316406,165.0399932861328
2024-05-01,162.52000427246094,162.5800018310547,162.1999969482422,164.38999938964844
2024-05-02,162.50999450683594,163.16000366210938,161.0,164.0
2024-05-03,164.17999267578125,163.07000732421875,162.4299926757... | date,5-day,10-day,20-day
2024-05-28,166.70800374348957,167.7167302911932,167.5357637677874
2024-05-29,164.67000223795574,166.54836592240767,167.04500165666852
2024-05-30,163.0086659749349,165.38654618696734,166.52357243129185
2024-05-31,163.0893300374349,164.98799910111862,166.34485742478142
2024-06-03,162.939995320638... |
3,213 | US | technical | For Vici Properties from May 31, 2020 to December 31, 2020, what percentage of days were the 10, 20, 30-day Weighted Moving Average lines in long alignment? (Unit: %) (Weights are 1, 2, ..., n) Using unadjusted prices, write down the indicator formula, collect the raw data, calculate the answer, and keep four decimal p... | 55.3333 | hard | moving average | WMA_n = \sum_{i=0}^{n-1} (n-i) * P_{t-i} / \sum_{j=1}^{n} j | date,close,open,low,high
2020-04-20,15.68000030517578,15.710000038146973,15.5,16.1299991607666
2020-04-21,15.350000381469728,15.029999732971191,14.899999618530272,15.6850004196167
2020-04-22,15.5,15.760000228881836,15.217000007629396,15.845000267028809
2020-04-23,15.279999732971191,15.619999885559082,15.1899995803833,1... | date,10-day,20-day,30-day
2020-06-01,19.44090909090909,18.197761921655562,17.684150533778695
2020-06-02,19.736727107654918,18.484999929155624,17.904709614989578
2020-06-03,20.224545288085938,18.89090467634655,18.20853756525183
2020-06-04,20.685636138916017,19.301190349033902,18.51890313138244
2020-06-05,21.206545222889... |
3,214 | US | technical | Calculate the percentage of days with short alignment in the 10, 20, 30-day Weighted Moving Average lines for Cognizant from September 11, 2024 to August 08, 2025. (Weights are 1, 2, ..., n) Using unadjusted prices, write down the indicator formula, collect the raw data, calculate the answer, and keep four decimal plac... | 44.2982 | hard | moving average | WMA_n = \sum_{i=0}^{n-1} (n-i) * P_{t-i} / \sum_{j=1}^{n} j | date,close,open,low,high
2024-07-31,75.68000030517578,76.30999755859375,75.12000274658203,76.30999755859375
2024-08-01,76.30999755859375,78.0,75.4000015258789,80.2699966430664
2024-08-02,74.0,76.11000061035156,73.62999725341797,76.11000061035156
2024-08-05,71.7300033569336,73.19000244140625,71.55000305175781,73.6900024... | date,10-day,20-day,30-day
2024-09-11,76.55581817626953,76.61461879185268,76.17718244983304
2024-09-12,76.47672687877308,76.60538050333659,76.22462317353936
2024-09-13,76.5714541348544,76.67266616821288,76.32877367901546
2024-09-16,76.78490933504972,76.79452362060547,76.47356957876553
2024-09-17,76.6965459650213,76.7496... |
3,215 | US | technical | What is the percentage of days with long alignment for the 5, 10, 20-day Exponential Moving Average lines for Ross Stores from October 16, 2022 to July 31, 2023? (Unit: %) (Smoothing factor alpha = 2 / (n + 1); Require 4n data points to warm up; Use the first data point as the initial value) Using unadjusted prices, wr... | 50.7752 | hard | moving average | EMA_t = \alpha * P_t + (1 - \alpha) * EMA_{t-1}, \quad \alpha = 2 / (n + 1) | date,close,high,open
2022-06-23,73.9800033569336,74.27999877929688,73.29000091552734
2022-06-24,77.52999877929688,78.2699966430664,74.98999786376953
2022-06-27,76.33999633789062,78.27999877929688,77.51000213623047
2022-06-28,72.77999877929688,77.30999755859375,76.61000061035156
2022-06-29,71.80999755859375,72.709999084... | date,5-day,10-day,20-day
2022-07-21,81.16231289588445,79.13885796734887,77.19633207938706
2022-07-22,81.85487455184615,79.88451976669808,77.77191929694729
2022-07-25,82.11324878570343,80.38369749155623,78.23459338803973
2022-07-26,80.72883221862651,79.94302505390466,78.20844154960477
2022-07-27,80.57588702677315,80.002... |
3,216 | US | technical | From September 20, 2022 to October 06, 2022, what proportion of days had the 5, 10, 20-day Exponential Moving Average lines of Welltower in short alignment? (Unit: %) (Smoothing factor alpha = 2 / (n + 1); Require 4n data points to warm up; Use the first data point as the initial value) Using unadjusted prices, write d... | 71.6216 | hard | moving average | EMA_t = \alpha * P_t + (1 - \alpha) * EMA_{t-1}, \quad \alpha = 2 / (n + 1) | date,close,high,open
2022-05-25,88.94999694824219,89.25,88.12000274658203
2022-05-26,88.58000183105469,90.18000030517578,89.72000122070312
2022-05-27,90.16999816894533,90.3499984741211,88.94000244140625
2022-05-31,89.08999633789062,89.68000030517578,89.25
2022-06-01,88.16000366210938,89.1500015258789,88.94999694824219
... | date,5-day,10-day,20-day
2022-06-23,79.94293407101091,80.6221288030605,82.7365608703476
2022-06-24,81.08195625079114,81.11992367711343,82.79593608368131
2022-06-27,81.7779702235092,81.49266449381014,82.83156104418265
2022-06-28,82.14531256681212,81.74490681373884,82.83617401649077
2022-06-29,82.50687616351928,82.014924... |
3,217 | US | technical | During March 02, 2025 to July 08, 2025, what percentage of trading days showed long alignment of Intercontinental Exchange's 5, 20, 60-day Exponential Moving Average lines? (Smoothing factor alpha = 2 / (n + 1); Require 4n data points to warm up; Use the first data point as the initial value) Using unadjusted prices, w... | 68.7732 | hard | moving average | EMA_t = \alpha * P_t + (1 - \alpha) * EMA_{t-1}, \quad \alpha = 2 / (n + 1) | date,close,high,open
2024-03-15,134.63999938964844,135.9199981689453,134.2100067138672
2024-03-18,134.39999389648438,135.6300048828125,135.1199951171875
2024-03-19,135.5,136.50999450683594,134.52000427246094
2024-03-20,136.10000610351562,136.4199981689453,135.27000427246094
2024-03-21,138.10000610351562,138.63999938964... | date,5-day,20-day,60-day
2024-06-10,134.20196361525217,134.37250583090008,134.184462174606
2024-06-11,134.33130785613167,134.39321921251823,134.19775837668092
2024-06-12,134.90420625467374,134.55100814958868,134.25848771028998
2024-06-13,135.02280233872781,134.6185306598027,134.29132399870133
2024-06-14,135.23853428213... |
3,218 | US | technical | For Cigna from May 06, 2022 to November 30, 2022, what percentage of days were the 5, 20, 60-day Exponential Moving Average lines in short alignment? (Unit: %) (Smoothing factor alpha = 2 / (n + 1); Require 4n data points to warm up; Use the first data point as the initial value) Using unadjusted prices, write down the... | 15.0769 | hard | moving average | EMA_t = \alpha * P_t + (1 - \alpha) * EMA_{t-1}, \quad \alpha = 2 / (n + 1) | date,close,high,open
2021-05-25,259.6000061035156,262.17999267578125,261.67999267578125
2021-05-26,259.3900146484375,261.07000732421875,259.8800048828125
2021-05-27,259.5,260.4800109863281,260.260009765625
2021-05-28,258.8500061035156,261.5400085449219,261.0400085449219
2021-06-01,257.67999267578125,260.6300048828125,2... | date,5-day,20-day,60-day
2021-08-18,209.24780476635732,217.911363904047,231.4018841482369
2021-08-19,208.2252007361653,216.79409045373598,230.57493688684488
2021-08-20,207.99346675054252,215.9117960085513,229.8193651456138
2021-08-23,207.90897966474972,215.13353024518108,229.09545171438592
2021-08-24,209.23598623971597... |
3,219 | US | technical | Calculate the percentage of days with long alignment in the 10, 20, 30-day Exponential Moving Average lines for American Water Works from July 15, 2022 to May 29, 2023. (Smoothing factor alpha = 2 / (n + 1); Require 4n data points to warm up; Use the first data point as the initial value) Using unadjusted prices, write... | 42.9032 | hard | moving average | EMA_t = \alpha * P_t + (1 - \alpha) * EMA_{t-1}, \quad \alpha = 2 / (n + 1) | date,close,high,open
2022-01-21,161.38999938964844,165.33999633789062,164.0800018310547
2022-01-24,159.7899932861328,162.63999938964844,160.8000030517578
2022-01-25,157.0,159.8800048828125,157.77999877929688
2022-01-26,155.5500030517578,159.47000122070312,157.4499969482422
2022-01-27,156.14999389648438,159.410003662109... | date,10-day,20-day,30-day
2022-03-04,153.09825147585445,152.8870839051802,153.7827680280234
2022-03-07,154.21129688400876,153.49021888761095,154.13355726626082
2022-03-08,154.21833381418898,153.5625789935528,154.1410697006956
2022-03-09,154.14045371817875,153.58423749760803,154.1184196094335
2022-03-10,153.956735748112... |
3,220 | US | technical | What is the percentage of days with long alignment for the 5, 20, 60-day Double Exponential Moving Average lines for Labcorp from October 31, 2022 to May 26, 2023? (Unit: %) (Smoothing factor alpha = 2 / (n + 1); Require 5n data points to warm up; Use the first data point as the initial value) Using unadjusted prices, ... | 30.0613 | hard | moving average | DEMA = 2 * EMA1 - EMA2; EMA1 = EMA_n(P); EMA2 = EMA_n(EMA1) | date,close,high,open
2021-08-23,260.91925048828125,263.6082458496094,263.6082458496094
2021-08-24,259.544677734375,260.7474365234375,260.5670166015625
2021-08-25,261.3917541503906,261.62371826171875,259.7508544921875
2021-08-26,259.1322937011719,261.58074951171875,261.3917541503906
2021-08-27,258.1786804199219,260.1288... | date,5-day,20-day,60-day
2022-02-09,240.71940376233064,234.35575653342923,239.9924040219736
2022-02-10,242.11649861373584,235.47629640406137,240.01930640886886
2022-02-11,239.9421282584722,235.53247552171462,239.71847750197395
2022-02-14,236.97758720901084,235.03689566306426,239.23611846410003
2022-02-15,231.5113043785... |
3,221 | US | technical | From July 23, 2022 to February 06, 2023, what proportion of days had the 5, 10, 20-day Double Exponential Moving Average lines of Caterpillar Inc. in long alignment? (Unit: %) (Smoothing factor alpha = 2 / (n + 1); Require 5n data points to warm up; Use the first data point as the initial value) Using unadjusted prices... | 33.8384 | hard | moving average | DEMA = 2 * EMA1 - EMA2; EMA1 = EMA_n(P); EMA2 = EMA_n(EMA1) | date,close,high,open
2022-03-01,182.8300018310547,188.22000122070312,187.7700042724609
2022-03-02,192.6100006103516,193.55999755859372,185.1999969482422
2022-03-03,194.8500061035156,196.5800018310547,193.32000732421875
2022-03-04,195.66000366210935,196.00999450683597,191.1000061035156
2022-03-07,196.6999969482422,203.5... | date,5-day,10-day,20-day
2022-04-25,220.31127511775105,224.1646777200476,224.93344585478195
2022-04-26,214.21018828407244,219.69277183381874,222.5855951489463
2022-04-27,213.09746447779665,217.598595755898,221.21617070398784
2022-04-28,211.85431177209253,215.57394460401255,219.7536146441526
2022-04-29,210.3113155576625... |
3,222 | US | technical | During October 30, 2020 to January 16, 2021, what percentage of trading days showed long alignment of Garmin's 10, 20, 30-day Double Exponential Moving Average lines? (Smoothing factor alpha = 2 / (n + 1); Require 5n data points to warm up; Use the first data point as the initial value) Using unadjusted prices, write d... | 19.3103 | hard | moving average | DEMA = 2 * EMA1 - EMA2; EMA1 = EMA_n(P); EMA2 = EMA_n(EMA1) | date,close,high,open
2020-03-30,76.69000244140625,77.2300033569336,73.87000274658203
2020-03-31,74.95999908447266,76.9800033569336,76.04000091552734
2020-04-01,71.41000366210938,74.4800033569336,71.98999786376953
2020-04-02,73.45999908447266,73.66000366210938,70.91000366210938
2020-04-03,71.55999755859375,74.0999984741... | date,10-day,20-day,30-day
2020-06-22,97.43062762564747,97.6835374165934,96.54361752321549
2020-06-23,97.81798604254872,98.08717761012562,97.03510534699598
2020-06-24,97.26777119436932,97.97172458867405,97.16343059035746
2020-06-25,97.14480932526479,98.02341338657858,97.38531207208112
2020-06-26,96.5793610183716,97.8009... |
3,223 | US | technical | For Cadence Design Systems from December 30, 2020 to January 11, 2021, what percentage of days were the 10, 20, 30-day Double Exponential Moving Average lines in long alignment? (Unit: %) (Smoothing factor alpha = 2 / (n + 1); Require 5n data points to warm up; Use the first data point as the initial value) Using unadj... | 37 | hard | moving average | DEMA = 2 * EMA1 - EMA2; EMA1 = EMA_n(P); EMA2 = EMA_n(EMA1) | date,close,high,open
2020-05-28,88.05999755859375,89.6500015258789,84.80999755859375
2020-05-29,91.29000091552734,91.58000183105467,88.2300033569336
2020-06-01,91.68000030517578,92.86000061035156,90.8000030517578
2020-06-02,92.37999725341795,92.38999938964844,91.5
2020-06-03,92.95999908447266,93.3000030517578,92.900001... | date,10-day,20-day,30-day
2020-08-19,109.1079459080402,110.01877848546076,109.64167088185857
2020-08-20,109.94490271793333,110.51448080027232,110.11411771860246
2020-08-21,110.32055397097699,110.80185138004173,110.44617914878285
2020-08-24,110.81497957238881,111.16378629912045,110.82594900841093
2020-08-25,111.15472076... |
3,224 | US | technical | Calculate the percentage of days with short alignment in the 5, 20, 60-day Double Exponential Moving Average lines for Progressive Corporation from February 26, 2022 to July 03, 2022. (Smoothing factor alpha = 2 / (n + 1); Require 5n data points to warm up; Use the first data point as the initial value) Using unadjuste... | 30.1115 | hard | moving average | DEMA = 2 * EMA1 - EMA2; EMA1 = EMA_n(P); EMA2 = EMA_n(EMA1) | date,close,high,open
2020-12-17,96.30999755859376,98.55999755859376,96.66000366210938
2020-12-18,96.9499969482422,97.26000213623048,96.36000061035156
2020-12-21,97.94000244140624,98.06999969482422,96.83999633789062
2020-12-22,97.98999786376952,98.66000366210938,97.6999969482422
2020-12-23,97.51000213623048,98.849998474... | date,5-day,20-day,60-day
2021-06-09,95.4161133078148,98.09309051825971,101.27551230740387
2021-06-10,94.33303337796488,97.24407702574217,100.89332217984321
2021-06-11,93.58355034473989,96.44364608278264,100.50130479292234
2021-06-14,92.98561005127168,95.67555125501354,100.09619414423753
2021-06-15,93.09034654790274,95.... |
3,225 | US | technical | What is the percentage of days with long alignment for the 5, 20, 60-day Triple Exponential Moving Average lines for Teledyne Technologies from October 25, 2019 to October 09, 2020? (Unit: %) (Smoothing factor alpha = 2 / (n + 1); Require 6n data points to warm up; Use the first data point as the initial value) Using u... | 23.5294 | hard | moving average | TEMA = 3 * EMA1 - 3 * EMA2 + EMA3; EMA1 = EMA_n(P); EMA2 = EMA_n(EMA1); EMA3 = EMA_n(EMA2) | date,close,open
2018-05-22,196.58999633789065,199.75
2018-05-23,199.19000244140625,195.41000366210935
2018-05-24,201.4900054931641,199.0
2018-05-25,198.94000244140625,201.0
2018-05-29,198.00999450683597,197.63999938964844
2018-05-30,204.0500030517578,199.0
2018-05-31,201.4600067138672,203.25
2018-06-01,205.600006103515... | date,5-day,20-day,60-day
2019-02-05,226.55918173780165,227.67335866560865,218.02707104997188
2019-02-06,227.12402922127083,228.3100325231996,218.9701452043607
2019-02-07,227.41761759051107,228.83072052257685,219.87493765174116
2019-02-08,228.53740318894847,229.59949646280174,220.86890790951765
2019-02-11,229.6795452613... |
3,226 | US | technical | From November 29, 2022 to May 27, 2023, what proportion of days had the 5, 10, 20-day Triple Exponential Moving Average lines of PTC Inc. in short alignment? (Unit: %) (Smoothing factor alpha = 2 / (n + 1); Require 6n data points to warm up; Use the first data point as the initial value) Using unadjusted prices, write ... | 28.3422 | hard | moving average | TEMA = 3 * EMA1 - 3 * EMA2 + EMA3; EMA1 = EMA_n(P); EMA2 = EMA_n(EMA1); EMA3 = EMA_n(EMA2) | date,close,open
2022-06-08,115.5199966430664,117.43000030517578
2022-06-09,113.02999877929688,114.29000091552734
2022-06-10,109.08999633789062,110.86000061035156
2022-06-13,102.44000244140624,105.1999969482422
2022-06-14,99.88999938964844,102.91999816894533
2022-06-15,103.41999816894533,101.23999786376952
2022-06-16,10... | date,5-day,10-day,20-day
2022-08-30,114.03008852617211,113.48775666043147,116.28509696202227
2022-08-31,114.41890651522264,113.47474919126674,115.64512792925797
2022-09-01,114.70038620219454,113.57667610218252,115.14534771752184
2022-09-02,114.95225815125096,113.78047487149989,114.78371512357661
2022-09-06,114.84108087... |
3,227 | US | technical | During April 12, 2023 to December 25, 2023, what percentage of trading days showed long alignment of PPL Corporation's 10, 20, 30-day Triple Exponential Moving Average lines? (Smoothing factor alpha = 2 / (n + 1); Require 6n data points to warm up; Use the first data point as the initial value) Using unadjusted prices,... | 30.2583 | hard | moving average | TEMA = 3 * EMA1 - 3 * EMA2 + EMA3; EMA1 = EMA_n(P); EMA2 = EMA_n(EMA1); EMA3 = EMA_n(EMA2) | date,close,open
2022-07-25,27.850000381469727,27.290000915527344
2022-07-26,28.040000915527344,27.850000381469727
2022-07-27,28.07999992370605,27.959999084472656
2022-07-28,28.790000915527344,28.299999237060547
2022-07-29,29.07999992370605,28.71999931335449
2022-08-01,29.0,29.040000915527344
2022-08-02,29.1000003814697... | date,10-day,20-day,30-day
2022-11-25,29.188219577181766,29.08139254245927,28.506373441854556
2022-11-28,29.292478309732523,29.257597229674424,28.72463680137088
2022-11-29,29.300682778255936,29.368631940731817,28.896303958959997
2022-11-30,29.509232271221556,29.57666327468171,29.13202136360709
2022-12-01,29.522805207237... |
3,228 | US | technical | For Smurfit Westrock from March 13, 2022 to April 14, 2022, what percentage of days were the 5, 20, 60-day Triple Exponential Moving Average lines in short alignment? (Unit: %) (Smoothing factor alpha = 2 / (n + 1); Require 6n data points to warm up; Use the first data point as the initial value) Using unadjusted price... | 22.7053 | hard | moving average | TEMA = 3 * EMA1 - 3 * EMA2 + EMA3; EMA1 = EMA_n(P); EMA2 = EMA_n(EMA1); EMA3 = EMA_n(EMA2) | date,close,open
2020-10-07,39.93000030517578,39.93000030517578
2020-10-08,39.84999847412109,39.36000061035156
2020-10-09,39.95000076293945,42.0
2020-10-12,40.83000183105469,40.83000183105469
2020-10-13,39.70000076293945,39.720001220703125
2020-10-14,40.38999938964844,40.38999938964844
2020-10-15,40.38999938964844,40.38... | date,5-day,20-day,60-day
2021-06-22,52.04147606742071,52.57464205556204,54.16741172972539
2021-06-23,51.95700034052078,52.36780715834804,54.05941775479364
2021-06-24,51.95516388553361,52.20216290992286,53.955818866459055
2021-06-25,55.26884012901722,53.282378305343926,54.30090569010718
2021-06-28,54.43286789595531,53.3... |
3,229 | US | technical | Calculate the percentage of days with short alignment in the 5, 20, 60-day Triple Exponential Moving Average lines for Paccar from April 27, 2022 to June 17, 2022. (Smoothing factor alpha = 2 / (n + 1); Require 6n data points to warm up; Use the first data point as the initial value) Using unadjusted prices, write down... | 20.9091 | hard | moving average | TEMA = 3 * EMA1 - 3 * EMA2 + EMA3; EMA1 = EMA_n(P); EMA2 = EMA_n(EMA1); EMA3 = EMA_n(EMA2) | date,close,open
2020-11-19,60.026668548583984,59.52000045776367
2020-11-20,59.186668395996094,58.76666641235352
2020-11-23,59.706668853759766,60.48666763305664
2020-11-24,60.27333450317383,59.220001220703125
2020-11-25,59.21333312988281,60.393333435058594
2020-11-27,58.49333190917969,59.23333358764648
2020-11-30,58.040... | date,5-day,20-day,60-day
2021-08-05,53.45560538238971,54.102876996889556,55.52977673535899
2021-08-06,53.238355755560676,53.67090177907602,55.19180311387481
2021-08-09,53.13950735874275,53.31330900063881,54.870094890532705
2021-08-10,53.0771903337434,53.015771663807456,54.56313370719186
2021-08-11,54.51109323989202,53.... |
3,230 | US | technical | What is the percentage of days with short alignment for the 5, 10, 20-day Hull Moving Average lines for American Water Works from November 14, 2021 to May 16, 2022? (Unit: %) Using unadjusted prices, write down the indicator formula, collect the raw data, calculate the answer, and keep four decimal places. Please list ... | 31.3433 | hard | moving average | HMA = WMA_{\sqrt{n}}(2 * WMA_{n/2}(P) - WMA_n(P)) | date,close,high,open
2021-10-04,170.91000366210938,171.72999572753906,168.58999633789062
2021-10-05,171.60000610351562,172.44000244140625,171.38999938964844
2021-10-06,174.17999267578125,174.1999969482422,171.16000366210938
2021-10-07,172.47000122070312,175.8800048828125,174.52000427246094
2021-10-08,170.8300018310547,... | date,5-day,10-day,20-day
2021-11-03,171.55955505371094,173.4117055719549,174.9668688634567
2021-11-04,166.92244432237413,171.41212104257912,173.8499946554605
2021-11-05,167.55667114257812,169.60026423907038,172.5842709251503
2021-11-08,168.7591101752387,168.44092021903606,171.2842398857348
2021-11-09,169.30311041937932... |
3,231 | US | technical | From July 27, 2025 to August 13, 2025, what proportion of days had the 5, 20, 60-day Hull Moving Average lines of Williams-Sonoma in long alignment? (Unit: %) Using unadjusted prices, write down the indicator formula, collect the raw data, calculate the answer, and keep four decimal places. Please list the raw data and... | 57.8947 | hard | moving average | HMA = WMA_{\sqrt{n}}(2 * WMA_{n/2}(P) - WMA_n(P)) | date,close,high,open
2025-03-18,172.27999877929688,176.25,171.14999389648438
2025-03-19,166.27000427246094,167.16000366210938,157.8000030517578
2025-03-20,164.99000549316406,170.3300018310547,165.05999755859375
2025-03-21,163.64999389648438,165.2899932861328,161.13999938964844
2025-03-24,170.3000030517578,171.080001831... | date,5-day,20-day,60-day
2025-06-20,160.4306660970052,155.90131785867533,162.51094213484134
2025-06-23,158.67355448404948,156.55115745049017,161.87501217169026
2025-06-24,157.56622551812066,157.09690563713835,161.24838958003056
2025-06-25,158.2042215983073,157.6139734679383,160.6479909226005
2025-06-26,161.048214043511... |
3,232 | US | technical | During September 27, 2024 to July 02, 2025, what percentage of trading days showed short alignment of General Motors's 5, 20, 60-day Hull Moving Average lines? Using unadjusted prices, write down the indicator formula, collect the raw data, calculate the answer, and keep four decimal places. Please list the raw data an... | 22.3256 | hard | moving average | HMA = WMA_{\sqrt{n}}(2 * WMA_{n/2}(P) - WMA_n(P)) | date,close,high,open
2024-05-20,45.11000061035156,45.90999984741211,45.75
2024-05-21,44.91999816894531,45.18000030517578,44.970001220703125
2024-05-22,43.970001220703125,44.63999938964844,44.59999847412109
2024-05-23,43.72999954223633,44.060001373291016,43.970001220703125
2024-05-24,44.11000061035156,44.31999969482422,... | date,5-day,20-day,60-day
2024-08-22,46.76577826605902,46.19111412907059,43.14071782976362
2024-08-23,48.028888363308376,46.89564350408909,43.29862224421749
2024-08-26,49.295333014594185,47.63403739483325,43.52223380828407
2024-08-27,49.69577780829536,48.38062870686188,43.81030012529488
2024-08-28,49.530221811930346,49.... |
3,233 | US | technical | For PepsiCo from October 20, 2019 to March 24, 2020, what percentage of days were the 5, 20, 60-day Hull Moving Average lines in long alignment? (Unit: %) Using unadjusted prices, write down the indicator formula, collect the raw data, calculate the answer, and keep four decimal places. Please list the raw data and key... | 20.4545 | hard | moving average | HMA = WMA_{\sqrt{n}}(2 * WMA_{n/2}(P) - WMA_n(P)) | date,close,high,open
2019-06-13,132.94000244140625,133.7899932861328,133.4499969482422
2019-06-14,132.72999572753906,133.5399932861328,133.00999450683594
2019-06-17,132.52000427246094,133.24000549316406,132.72000122070312
2019-06-18,132.05999755859375,134.4199981689453,134.4199981689453
2019-06-19,132.85000610351562,13... | date,5-day,20-day,60-day
2019-09-16,135.46489359537762,137.22845342264546,136.15697098869578
2019-09-17,134.89844631618925,136.77530206721582,136.48816099943767
2019-09-18,135.29555392795137,136.31499891338927,136.76925009510163
2019-09-19,135.45977410210503,135.93952847765635,137.0009352041922
2019-09-20,134.964446343... |
3,234 | US | technical | Calculate the percentage of days with long alignment in the 10, 20, 30-day Hull Moving Average lines for Occidental Petroleum from November 04, 2020 to October 20, 2021. Using unadjusted prices, write down the indicator formula, collect the raw data, calculate the answer, and keep four decimal places. Please list the r... | 37.7953 | hard | moving average | HMA = WMA_{\sqrt{n}}(2 * WMA_{n/2}(P) - WMA_n(P)) | date,close,high,open
2020-09-01,12.479999542236328,12.619999885559082,12.59000015258789
2020-09-02,12.399999618530272,12.65999984741211,12.31999969482422
2020-09-03,12.59000015258789,12.899999618530272,12.350000381469728
2020-09-04,12.25,12.84000015258789,12.720000267028809
2020-09-08,11.0600004196167,11.97999954223632... | date,10-day,20-day,30-day
2020-10-19,10.174666536697233,10.574115560622442,10.35492728609338
2020-10-20,9.980171473339349,10.450342767228296,10.33208386373349
2020-10-21,9.791030011995874,10.271545748566135,10.273698154059788
2020-10-22,9.76604019030176,10.129538803265723,10.222779132132036
2020-10-23,9.815303020284633... |
3,235 | US | technical | What is the percentage of days where the low price is greater than the lower channel of Bollinger Bands for International Flavors & Fragrances from June 12, 2023 to July 05, 2023? (Unit: %) (Standard parameters: middle band SMA(20), band width multiplier 2, use population standard deviation) Using unadjusted prices, wr... | 81.25 | medium | channel | Middle = SMA_n(P); Upper = Middle + 2 * \sigma_n(P); Lower = Middle - 2 * \sigma_n(P) | date,close,low
2023-05-15,84.36000061035156,82.41000366210938
2023-05-16,81.12000274658203,81.0999984741211
2023-05-17,82.2699966430664,81.0199966430664
2023-05-18,84.16999816894531,82.33000183105469
2023-05-19,83.68000030517578,83.56999969482422
2023-05-22,83.4000015258789,83.0999984741211
2023-05-23,83.02999877929688... | date,Upper,Middle,Lower,low
2023-06-12,85.15730639554707,80.42849998474121,75.69969357393535,77.66000366210938
2023-06-13,84.57262872714989,80.19549980163575,75.8183708761216,78.05000305175781
2023-06-14,84.48477905126579,80.05449981689453,75.62422058252328,77.93000030517578
2023-06-15,84.23230095345352,79.915999984741... |
3,236 | US | technical | From May 13, 2022 to March 20, 2023, what proportion of days had Verizon's high less than the middle of Bollinger Bands? (Unit: %) (Standard parameters: middle band SMA(20), band width multiplier 2, use population standard deviation) Using unadjusted prices, write down the indicator formula, collect the raw data, calcu... | 55.3991 | medium | channel | Middle = SMA_n(P); Upper = Middle + 2 * \sigma_n(P); Lower = Middle - 2 * \sigma_n(P) | date,close,low,high
2022-04-18,53.38999938964844,53.220001220703125,54.27999877929688
2022-04-19,53.75,53.459999084472656,53.90999984741211
2022-04-20,54.40999984741211,53.70000076293945,54.4900016784668
2022-04-21,55.0099983215332,54.470001220703125,55.5099983215332
2022-04-22,51.90999984741211,51.459999084472656,53.5... | date,Upper,Middle,Lower,high
2022-05-13,54.74521009013349,49.503499794006345,44.2617894978792,48.45000076293945
2022-05-16,54.216343913261376,49.285999870300294,44.35565582733921,49.20000076293945
2022-05-17,53.53052100452573,49.04549980163574,44.56047859874575,49.209999084472656
2022-05-18,52.519163105932336,48.769499... |
3,237 | US | technical | During March 31, 2022 to June 15, 2022, what percentage of days had Eversource Energy's open price less the upper channel of Bollinger Bands? (Standard parameters: middle band SMA(20), band width multiplier 2, use population standard deviation) Using unadjusted prices, write down the indicator formula, collect the raw ... | 96.2264 | medium | channel | Middle = SMA_n(P); Upper = Middle + 2 * \sigma_n(P); Lower = Middle - 2 * \sigma_n(P) | date,close,low,high,open
2022-03-04,85.94000244140625,82.91000366210938,86.55000305175781,83.22000122070312
2022-03-07,86.66000366210938,84.86000061035156,86.91000366210938,85.7699966430664
2022-03-08,85.08999633789062,84.45999908447266,86.9000015258789,86.56999969482422
2022-03-09,84.19000244140625,84.01000213623047,8... | date,Upper,Middle,Lower,open
2022-03-31,88.51236554632905,85.31399993896484,82.11563433160063,88.62999725341797
2022-04-01,89.2634630959164,85.50899963378906,81.75453617166171,88.19000244140625
2022-04-04,89.67902152704038,85.63199958801269,81.584977648985,89.44999694824219
2022-04-05,90.35909463667173,85.8819995880126... |
3,238 | US | technical | For D. R. Horton from November 25, 2024 to July 03, 2025, what percentage of days had the close less than the Bollinger Bands lower channel? (Unit: %) (Standard parameters: middle band SMA(20), band width multiplier 2, use population standard deviation) Using unadjusted prices, write down the indicator formula, collect... | 10 | medium | channel | Middle = SMA_n(P); Upper = Middle + 2 * \sigma_n(P); Lower = Middle - 2 * \sigma_n(P) | date,close,low,high,open
2024-10-29,167.32000732421875,152.99000549316406,167.72999572753906,153.19000244140625
2024-10-30,169.2899932861328,166.27999877929688,171.77000427246094,166.3000030517578
2024-10-31,169.0,167.32000732421875,170.41000366210938,167.94000244140625
2024-11-01,167.63999938964844,166.6199951171875,1... | date,Upper,Middle,Lower,close
2024-11-25,173.75823603552377,166.09200134277344,158.42576665002312,172.94000244140625
2024-11-26,173.8959065297124,166.16150131225587,158.42709609479934,168.7100067138672
2024-11-27,173.9144642833342,166.1685012817383,158.42253828014236,169.42999267578125
2024-11-29,173.8879582352896,166.... |
3,239 | US | technical | Calculate the percentage of days where Cigna's open was less than the upper channel of Bollinger Bands from April 12, 2021 to February 01, 2022. (Standard parameters: middle band SMA(20), band width multiplier 2, use population standard deviation) Using unadjusted prices, write down the indicator formula, collect the r... | 96.6019 | medium | channel | Middle = SMA_n(P); Upper = Middle + 2 * \sigma_n(P); Lower = Middle - 2 * \sigma_n(P) | date,close,low,high,open
2021-03-15,245.4900054931641,243.08999633789065,247.6300048828125,243.3699951171875
2021-03-16,241.69000244140625,241.6199951171875,245.47999572753903,245.47999572753903
2021-03-17,241.91000366210935,239.66000366210935,244.17999267578125,242.0500030517578
2021-03-18,243.82000732421875,241.94000... | date,Upper,Middle,Lower,open
2021-04-12,247.76080568852416,242.6250015258789,237.48919736323364,245.63999938964844
2021-04-13,247.72456186466906,242.6135009765625,237.50244008845596,246.07000732421875
2021-04-14,248.88929214998015,243.0010009765625,237.11270980314484,245.6100006103516
2021-04-15,251.28439295289087,243.... |
3,240 | US | technical | What is the percentage of days where the close price is less than the upper channel of Keltner Channel for Vulcan Materials Company from July 16, 2024 to May 03, 2025? (Unit: %) (Standard parameters: middle EMA(20), requiring 4n data points to warm up, using the first data point as the initial value; ATR(10) using Wild... | 88.5496 | medium | channel | Middle = EMA_{n_{ema}}(C); Upper = Middle + 1.5 * ATR_{n_{atr}}^{Wilder}; Lower = Middle - 1.5 * ATR_{n_{atr}}^{Wilder} | date,close,high,low
2024-03-20,271.739990234375,272.260009765625,268.9599914550781
2024-03-21,275.5899963378906,275.8699951171875,270.3800048828125
2024-03-22,274.3599853515625,275.1499938964844,272.260009765625
2024-03-25,272.6199951171875,274.8299865722656,272.04998779296875
2024-03-26,273.8699951171875,275.350006103... | date,Upper,Middle,Lower,close
2024-04-17,273.17741212659735,266.1725654309617,259.16771873532605,258.260009765625
2024-04-18,272.3075429848375,265.11517894460525,257.922814904373,255.07000732421875
2024-04-19,271.26445670504455,263.87182833641367,256.4791999677828,252.05999755859372
2024-04-22,270.31323407748084,262.97... |
3,241 | US | technical | From December 06, 2021 to August 02, 2022, what proportion of days had Qualcomm's high greater than the lower of Keltner Channel? (Unit: %) (Standard parameters: middle EMA(20), requiring 4n data points to warm up, using the first data point as the initial value; ATR(10) using Wilder smoothing, multiplier 1.5) Using un... | 91.1504 | medium | channel | Middle = EMA_{n_{ema}}(C); Upper = Middle + 1.5 * ATR_{n_{atr}}^{Wilder}; Lower = Middle - 1.5 * ATR_{n_{atr}}^{Wilder} | date,close,high,low
2021-08-12,147.14999389648438,148.0,146.38999938964844
2021-08-13,148.63999938964844,149.30999755859375,146.92999267578125
2021-08-16,148.1300048828125,149.0800018310547,146.72000122070312
2021-08-17,144.41000366210938,147.0,143.57000732421875
2021-08-18,142.17999267578125,144.66000366210938,141.979... | date,Upper,Middle,Lower,high
2021-09-09,147.87050653588213,144.55509790076727,141.2396892656524,143.5399932861328
2021-09-10,148.02338394771374,144.37651645076858,140.7296489538234,146.0
2021-09-13,147.97164790324038,144.2844676137534,140.59728732426643,144.72999572753906
2021-09-14,147.93195707630213,143.9849944495529... |
3,242 | US | technical | During December 10, 2022 to October 01, 2023, what percentage of days had Consolidated Edison's open price greater the middle channel of Keltner Channel? (Standard parameters: middle EMA(20), requiring 4n data points to warm up, using the first data point as the initial value; ATR(10) using Wilder smoothing, multiplier... | 46.5649 | medium | channel | Middle = EMA_{n_{ema}}(C); Upper = Middle + 1.5 * ATR_{n_{atr}}^{Wilder}; Lower = Middle - 1.5 * ATR_{n_{atr}}^{Wilder} | date,close,high,low,open
2022-08-18,100.93000030517578,101.30999755859376,100.5,100.79000091552734
2022-08-19,100.5500030517578,101.56999969482422,100.30999755859376,101.2300033569336
2022-08-22,99.41000366210938,100.5999984741211,99.1999969482422,100.25
2022-08-23,98.76000213623048,99.75,98.33999633789062,99.569999694... | date,Upper,Middle,Lower,open
2022-09-15,102.55262512551717,99.66299526966306,96.77336541380895,99.58999633789062
2022-09-16,102.21859224306282,99.44842464037224,96.67825703768166,97.87999725341795
2022-09-19,102.12889156754626,99.35524145754661,96.58159134754696,97.1500015258789
2022-09-20,101.96095588268653,99.1661711... |
3,243 | US | technical | For Best Buy from March 28, 2024 to May 16, 2024, what percentage of days had the high greater than the Keltner Channel upper channel? (Unit: %) (Standard parameters: middle EMA(20), requiring 4n data points to warm up, using the first data point as the initial value; ATR(10) using Wilder smoothing, multiplier 1.5) Usi... | 13.5417 | medium | channel | Middle = EMA_{n_{ema}}(C); Upper = Middle + 1.5 * ATR_{n_{atr}}^{Wilder}; Lower = Middle - 1.5 * ATR_{n_{atr}}^{Wilder} | date,close,high,low,open
2023-12-01,73.41999816894531,73.5,70.77999877929688,70.97000122070312
2023-12-04,74.69000244140625,74.98999786376953,73.19000244140625,73.2699966430664
2023-12-05,74.0,74.4000015258789,73.5,73.5999984741211
2023-12-06,75.08999633789062,75.75,74.20999908447266,74.4000015258789
2023-12-07,74.5599... | date,Upper,Middle,Lower,high
2023-12-29,78.5641752827795,76.14105981909178,73.71794435540406,78.94999694824219
2024-01-02,78.79742953404723,76.24762575405737,73.69782197406751,79.54000091552734
2024-01-03,78.7990805692186,76.16975666368769,73.54043275815678,76.95999908447266
2024-01-04,78.57181463866796,76.086922986361... |
3,244 | US | technical | Calculate the percentage of days where Vistra Corp.'s open was greater than the upper channel of Keltner Channel from September 22, 2022 to April 13, 2023. (Standard parameters: middle EMA(20), requiring 4n data points to warm up, using the first data point as the initial value; ATR(10) using Wilder smoothing, multipli... | 5.9701 | medium | channel | Middle = EMA_{n_{ema}}(C); Upper = Middle + 1.5 * ATR_{n_{atr}}^{Wilder}; Lower = Middle - 1.5 * ATR_{n_{atr}}^{Wilder} | date,close,high,low,open
2022-05-27,26.309999465942383,26.325000762939453,25.73500061035156,25.979999542236328
2022-05-31,26.3700008392334,26.68600082397461,25.8799991607666,26.5
2022-06-01,25.899999618530277,26.459999084472656,25.27199935913086,26.36000061035156
2022-06-02,25.979999542236328,26.239999771118164,25.5949... | date,Upper,Middle,Lower,open
2022-06-27,25.479802474027892,24.292423929262682,23.105045384497473,23.38999938964844
2022-06-28,25.403536104321418,24.193145459809095,22.982754815296772,23.799999237060547
2022-06-29,25.2881378559988,24.069036310269986,22.84993476454117,23.21999931335449
2022-06-30,25.176878938543354,23.95... |
3,245 | US | technical | What is the percentage of days where the low price is greater than the lower channel of Moving Average Envelope for Dow Inc. from December 25, 2021 to January 19, 2022? (Unit: %) (Standard parameters: middle band SMA(20), upper and lower bands +/- 10%) Using unadjusted prices, write down the indicator formula, collect ... | 100 | medium | channel | Middle = SMA_n(P); Upper = Middle * 1.1; Lower = Middle * 0.9 | date,close,low
2021-11-29,56.86000061035156,56.380001068115234
2021-11-30,54.93000030517578,54.40999984741211
2021-12-01,52.7599983215332,52.70000076293945
2021-12-02,53.18000030517578,52.06999969482422
2021-12-03,53.06999969482422,52.72999954223633
2021-12-06,53.880001068115234,53.84000015258789
2021-12-07,54.86000061... | date,Upper,Middle,Lower,low
2021-12-27,59.75254978179932,54.32049980163574,48.888449821472165,55.16999816894531
2021-12-28,59.73989980697632,54.30899982452392,48.878099842071535,55.90999984741211
2021-12-29,59.857049865722665,54.41549987792969,48.97394989013672,56.560001373291016
2021-12-30,60.07814989089966,54.6164999... |
3,246 | US | technical | From September 14, 2019 to April 10, 2020, what proportion of days had Corteva's close greater than the middle of Moving Average Envelope? (Unit: %) (Standard parameters: middle band SMA(20), upper and lower bands +/- 10%) Using unadjusted prices, write down the indicator formula, collect the raw data, calculate the an... | 42.3611 | medium | channel | Middle = SMA_n(P); Upper = Middle * 1.1; Lower = Middle * 0.9 | date,close,low
2019-08-19,30.56999969482422,30.25
2019-08-20,30.26000022888184,30.09000015258789
2019-08-21,30.57999992370605,30.280000686645508
2019-08-22,30.290000915527344,30.209999084472656
2019-08-23,29.049999237060547,28.809999465942383
2019-08-26,29.020000457763672,28.670000076293945
2019-08-27,28.72999954223632... | date,Upper,Middle,Lower,close
2019-09-16,32.241549844741826,29.3104998588562,26.379449872970582,29.399999618530277
2019-09-17,32.15409983634949,29.230999851226805,26.307899866104126,28.979999542236328
2019-09-18,32.09304980278015,29.175499820709227,26.257949838638304,29.149999618530277
2019-09-19,32.01384977340698,29.1... |
3,247 | US | technical | During June 08, 2023 to July 18, 2023, what percentage of days had Deckers Brands's low price less the middle channel of Moving Average Envelope? (Standard parameters: middle band SMA(20), upper and lower bands +/- 10%) Using unadjusted prices, write down the indicator formula, collect the raw data, calculate the answe... | 0 | medium | channel | Middle = SMA_n(P); Upper = Middle * 1.1; Lower = Middle * 0.9 | date,close,low
2023-05-11,81.73999786376953,81.57167053222656
2023-05-12,81.76333618164062,80.9366683959961
2023-05-15,81.91999816894531,81.2699966430664
2023-05-16,78.88833618164062,77.88500213623047
2023-05-17,78.3949966430664,77.40333557128906
2023-05-18,78.75166320800781,77.81666564941406
2023-05-19,75.798332214355... | date,Upper,Middle,Lower,low
2023-06-08,86.86672397613525,78.96974906921386,71.07277416229248,80.91166687011719
2023-06-09,86.84738258361817,78.95216598510743,71.05694938659668,80.96666717529297
2023-06-12,86.94189075469971,79.03808250427247,71.13427425384522,81.2750015258789
2023-06-13,86.93455753326417,79.031415939331... |
3,248 | US | technical | For Campbell's Company (The) from August 05, 2020 to October 03, 2020, what percentage of days had the open greater than the Moving Average Envelope lower channel? (Unit: %) (Standard parameters: middle band SMA(20), upper and lower bands +/- 10%) Using unadjusted prices, write down the indicator formula, collect the r... | 92.8571 | medium | channel | Middle = SMA_n(P); Upper = Middle * 1.1; Lower = Middle * 0.9 | date,close,low,open
2020-07-09,49.40999984741211,49.2599983215332,49.34000015258789
2020-07-10,50.27999877929688,49.5,49.5
2020-07-13,49.83000183105469,49.709999084472656,50.31999969482422
2020-07-14,50.310001373291016,49.5099983215332,49.5099983215332
2020-07-15,49.209999084472656,49.08000183105469,50.5099983215332
20... | date,Upper,Middle,Lower,open
2020-08-05,54.66065031051637,49.6915002822876,44.72235025405884,50.290000915527344
2020-08-06,54.68650037765504,49.71500034332276,44.743500308990484,49.75
2020-08-07,54.669450511932375,49.699500465393065,44.72955041885376,49.900001525878906
2020-08-10,54.7008004951477,49.728000450134275,44.... |
3,249 | US | technical | Calculate the percentage of days where Las Vegas Sands's high was greater than the lower channel of Moving Average Envelope from December 21, 2022 to April 11, 2023. (Standard parameters: middle band SMA(20), upper and lower bands +/- 10%) Using unadjusted prices, write down the indicator formula, collect the raw data,... | 100 | medium | channel | Middle = SMA_n(P); Upper = Middle * 1.1; Lower = Middle * 0.9 | date,close,low,open,high
2022-11-23,43.060001373291016,42.27000045776367,42.84000015258789,43.209999084472656
2022-11-25,43.16999816894531,42.54999923706055,43.34000015258789,43.34000015258789
2022-11-28,43.650001525878906,42.59000015258789,44.34999847412109,44.650001525878906
2022-11-29,44.65999984741211,44.1699981689... | date,Upper,Middle,Lower,high
2022-12-21,51.426650352478035,46.75150032043457,42.07635028839112,47.56999969482422
2022-12-22,51.616950302124025,46.9245002746582,42.23205024719238,47.220001220703125
2022-12-23,51.80120042800903,47.09200038909912,42.38280035018921,46.7400016784668
2022-12-27,52.06575029373169,47.332500267... |
3,250 | US | technical | What is the percentage of days where the open price is less than the middle channel of Donchian Channel for Vici Properties from April 27, 2021 to November 16, 2021? (Unit: %) (Standard parameters: 20-period high/low, middle band is their average) Using unadjusted prices, write down the indicator formula, collect the r... | 52.4476 | medium | channel | Upper = max_{i=0}^{n-1} H_{t-i}; Lower = min_{i=0}^{n-1} L_{t-i}; Middle = (Upper + Lower) / 2 | date,high,low,open
2021-03-30,28.21999931335449,27.6299991607666,27.770000457763672
2021-03-31,28.684999465942383,28.020000457763672,28.15999984741211
2021-04-01,28.850000381469727,28.309999465942383,28.670000076293945
2021-04-05,29.030000686645508,28.670000076293945,29.0
2021-04-06,29.239999771118164,28.78000068664550... | date,Upper,Middle,Lower,open
2021-04-27,31.15999984741211,29.394999504089355,27.6299991607666,31.0
2021-04-28,31.700000762939453,29.860000610351562,28.020000457763672,31.26000022888184
2021-04-29,31.8799991607666,30.094999313354492,28.309999465942383,31.700000762939453
2021-04-30,31.8799991607666,30.114999771118164,28.... |
3,251 | US | technical | From July 21, 2019 to June 29, 2020, what proportion of days had Micron Technology's open less than the upper of Donchian Channel? (Unit: %) (Standard parameters: 20-period high/low, middle band is their average) Using unadjusted prices, write down the indicator formula, collect the raw data, calculate the answer, and ... | 100 | medium | channel | Upper = max_{i=0}^{n-1} H_{t-i}; Lower = min_{i=0}^{n-1} L_{t-i}; Middle = (Upper + Lower) / 2 | date,high,low,open
2019-06-24,34.08000183105469,33.02000045776367,33.20000076293945
2019-06-25,33.880001068115234,32.61000061035156,33.349998474121094
2019-06-26,37.61000061035156,35.70000076293945,35.869998931884766
2019-06-27,38.33000183105469,36.5099983215332,36.84999847412109
2019-06-28,39.400001525878906,38.049999... | date,Upper,Middle,Lower,open
2019-07-22,47.43000030517578,40.02000045776367,32.61000061035156,46.5
2019-07-23,47.43000030517578,40.02000045776367,32.61000061035156,46.77999877929688
2019-07-24,48.22999954223633,41.96500015258789,35.70000076293945,46.95000076293945
2019-07-25,48.70000076293945,42.60499954223633,36.50999... |
3,252 | US | technical | During January 20, 2022 to November 28, 2022, what percentage of days had Molson Coors Beverage Company's open price greater the upper channel of Donchian Channel? (Standard parameters: 20-period high/low, middle band is their average) Using unadjusted prices, write down the indicator formula, collect the raw data, cal... | 0 | medium | channel | Upper = max_{i=0}^{n-1} H_{t-i}; Lower = min_{i=0}^{n-1} L_{t-i}; Middle = (Upper + Lower) / 2 | date,high,low,open
2021-12-22,45.33000183105469,44.540000915527344,44.540000915527344
2021-12-23,45.650001525878906,44.88999938964844,44.88999938964844
2021-12-27,45.77000045776367,45.209999084472656,45.540000915527344
2021-12-28,46.11000061035156,45.41999816894531,45.41999816894531
2021-12-29,46.02000045776367,45.5800... | date,Upper,Middle,Lower,open
2022-01-20,52.150001525878906,48.345001220703125,44.540000915527344,49.93999862670898
2022-01-21,52.150001525878906,48.52000045776367,44.88999938964844,49.720001220703125
2022-01-24,52.150001525878906,48.68000030517578,45.209999084472656,48.130001068115234
2022-01-25,52.150001525878906,48.7... |
3,253 | US | technical | For GoDaddy from February 26, 2023 to April 23, 2023, what percentage of days had the open greater than the Donchian Channel middle channel? (Unit: %) (Standard parameters: 20-period high/low, middle band is their average) Using unadjusted prices, write down the indicator formula, collect the raw data, calculate the an... | 53.8462 | medium | channel | Upper = max_{i=0}^{n-1} H_{t-i}; Lower = min_{i=0}^{n-1} L_{t-i}; Middle = (Upper + Lower) / 2 | date,high,low,open
2023-01-30,82.19999694824219,81.08000183105469,81.75
2023-01-31,82.48999786376953,81.38999938964844,81.7300033569336
2023-02-01,83.2030029296875,81.48999786376953,82.1500015258789
2023-02-02,85.31999969482422,83.51000213623047,84.1500015258789
2023-02-03,83.93000030517578,82.16999816894531,82.3099975... | date,Upper,Middle,Lower,open
2023-02-27,85.31999969482422,80.14500045776367,74.97000122070312,76.27999877929688
2023-02-28,85.31999969482422,80.14500045776367,74.97000122070312,75.73999786376953
2023-03-01,85.31999969482422,80.14500045776367,74.97000122070312,75.68000030517578
2023-03-02,85.31999969482422,79.8899993896... |
3,254 | US | technical | Calculate the percentage of days where TransDigm Group's high was greater than the upper channel of Donchian Channel from May 25, 2022 to September 16, 2022. (Standard parameters: 20-period high/low, middle band is their average) Using unadjusted prices, write down the indicator formula, collect the raw data, calculate... | 0 | medium | channel | Upper = max_{i=0}^{n-1} H_{t-i}; Lower = min_{i=0}^{n-1} L_{t-i}; Middle = (Upper + Lower) / 2 | date,high,low,open
2022-04-28,624.239990234375,609.02001953125,620.5499877929688
2022-04-29,617.7999877929688,593.6099853515625,614.5499877929688
2022-05-02,607.4099731445312,586.1500244140625,594.989990234375
2022-05-03,613.0399780273438,597.2899780273438,607.75
2022-05-04,624.1799926757812,596.5800170898438,602.78997... | date,Upper,Middle,Lower,high
2022-05-25,624.239990234375,577.7349853515625,531.22998046875,593.8300170898438
2022-05-26,624.1799926757812,577.7049865722656,531.22998046875,607.1699829101562
2022-05-27,624.1799926757812,577.7049865722656,531.22998046875,614.1500244140625
2022-05-31,624.1799926757812,577.7049865722656,53... |
3,255 | US | technical | What is the percentage of days where the low price is less than the middle channel of SuperTrend for Extra Space Storage from January 23, 2022 to August 07, 2022? (Unit: %) (Standard parameters: period 10, multiplier 3; Require 5n data points to warm up) Using unadjusted prices, write down the indicator formula, collec... | 100 | medium | channel | Mid_t = (H_t + L_t) / 2; BasicUpper_t = Mid_t + m * ATR_n^{Wilder}; BasicLower_t = Mid_t - m * ATR_n^{Wilder}; in long state Lower_t = max(BasicLower_t, Lower_{t-1}), flip to short if C_t < Lower_t; in short state Upper_t = min(BasicUpper_t, Upper_{t-1}), flip to long if C_t > Upper_t | date,high,low,close
2021-11-10,199.1100006103516,196.8999938964844,197.1499938964844
2021-11-11,198.5800018310547,196.0399932861328,198.38999938964844
2021-11-12,199.9499969482422,196.57000732421875,197.9600067138672
2021-11-15,199.9900054931641,195.91000366210935,199.92999267578125
2021-11-16,200.47000122070312,196.78... | date,Middle,Upper,Lower,low
2021-11-24,202.01499938964844,211.28700103759772,190.4962019348144,199.3500061035156
2021-11-26,200.07500457763672,211.28700103759772,190.4962019348144,197.3500061035156
2021-11-29,201.88999938964844,211.28700103759772,190.4962019348144,198.8000030517578
2021-11-30,200.49000549316406,211.287... |
3,256 | US | technical | From December 05, 2019 to January 21, 2020, what proportion of days had Waste Management's low less than the lower of SuperTrend? (Unit: %) (Standard parameters: period 10, multiplier 3; Require 5n data points to warm up) Using unadjusted prices, write down the indicator formula, collect the raw data, calculate the ans... | 50.7042 | medium | channel | Mid_t = (H_t + L_t) / 2; BasicUpper_t = Mid_t + m * ATR_n^{Wilder}; BasicLower_t = Mid_t - m * ATR_n^{Wilder}; in long state Lower_t = max(BasicLower_t, Lower_{t-1}), flip to short if C_t < Lower_t; in short state Upper_t = min(BasicUpper_t, Upper_{t-1}), flip to long if C_t > Upper_t | date,high,low,close
2019-09-25,115.45999908447266,113.83000183105467,113.91999816894533
2019-09-26,115.69000244140624,113.70999908447266,115.08999633789062
2019-09-27,115.72000122070312,112.68000030517578,113.58999633789062
2019-09-30,115.20999908447266,113.52999877929688,115.0
2019-10-01,115.97000122070312,114.5,114.8... | date,Middle,Upper,Lower,low
2019-10-09,115.2599983215332,120.41800384521483,110.07779815673828,114.56999969482422
2019-10-10,116.625,120.41800384521483,111.26201930236816,115.45999908447266
2019-10-11,117.28000259399414,120.41800384521483,111.84131969146729,116.26000213623048
2019-10-14,116.81500244140625,120.418003845... |
3,257 | US | technical | During March 03, 2024 to March 20, 2024, what percentage of days had Lululemon Athletica's low price less the lower channel of SuperTrend? (Standard parameters: period 10, multiplier 3; Require 5n data points to warm up) Using unadjusted prices, write down the indicator formula, collect the raw data, calculate the answ... | 88.6792 | medium | channel | Mid_t = (H_t + L_t) / 2; BasicUpper_t = Mid_t + m * ATR_n^{Wilder}; BasicLower_t = Mid_t - m * ATR_n^{Wilder}; in long state Lower_t = max(BasicLower_t, Lower_{t-1}), flip to short if C_t < Lower_t; in short state Upper_t = min(BasicUpper_t, Upper_{t-1}), flip to long if C_t > Upper_t | date,high,low,close
2023-12-19,509.3299865722656,502.8299865722656,506.8599853515625
2023-12-20,511.6000061035156,503.9500122070313,505.1499938964844
2023-12-21,511.2699890136719,505.510009765625,511.0299987792969
2023-12-22,510.4800109863281,502.2200012207031,510.0
2023-12-26,513.5,505.5199890136719,506.3200073242188
... | date,Middle,Upper,Lower,low
2024-01-04,498.5050048828125,521.734017944336,478.90599670410165,495.010009765625
2024-01-05,494.9499969482422,521.734017944336,478.90599670410165,490.6900024414063
2024-01-08,485.80999755859375,521.734017944336,478.90599670410165,478.1300048828125
2024-01-09,486.50999450683594,521.734017944... |
3,258 | US | technical | For Microsoft from August 04, 2022 to November 12, 2022, what percentage of days had the close less than the SuperTrend upper channel? (Unit: %) (Standard parameters: period 10, multiplier 3; Require 5n data points to warm up) Using unadjusted prices, write down the indicator formula, collect the raw data, calculate th... | 73.8739 | medium | channel | Mid_t = (H_t + L_t) / 2; BasicUpper_t = Mid_t + m * ATR_n^{Wilder}; BasicLower_t = Mid_t - m * ATR_n^{Wilder}; in long state Lower_t = max(BasicLower_t, Lower_{t-1}), flip to short if C_t < Lower_t; in short state Upper_t = min(BasicUpper_t, Upper_{t-1}), flip to long if C_t > Upper_t | date,high,low,close
2022-05-23,261.5,253.42999267578125,260.6499938964844
2022-05-24,261.3299865722656,253.5,259.6199951171875
2022-05-25,264.5799865722656,257.1300048828125,262.5199890136719
2022-05-26,267.1099853515625,261.42999267578125,265.8999938964844
2022-05-27,273.3399963378906,267.5599975585937,273.23999023437... | date,Middle,Upper,Lower,close
2022-06-07,269.5350036621094,293.54197387695314,247.85802001953124,272.5
2022-06-08,271.30499267578125,293.54197387695314,249.84468630981445,270.4100036621094
2022-06-09,268.6699981689453,293.54197387695314,249.84468630981445,264.7900085449219
2022-06-10,256.55499267578125,293.541973876953... |
3,259 | US | technical | Calculate the percentage of days where Starbucks's high was less than the lower channel of SuperTrend from December 16, 2023 to March 20, 2024. (Standard parameters: period 10, multiplier 3; Require 5n data points to warm up) Using unadjusted prices, write down the indicator formula, collect the raw data, calculate the... | 45.1923 | medium | channel | Mid_t = (H_t + L_t) / 2; BasicUpper_t = Mid_t + m * ATR_n^{Wilder}; BasicLower_t = Mid_t - m * ATR_n^{Wilder}; in long state Lower_t = max(BasicLower_t, Lower_{t-1}), flip to short if C_t < Lower_t; in short state Upper_t = min(BasicUpper_t, Upper_{t-1}), flip to long if C_t > Upper_t | date,high,low,close
2023-10-06,93.33999633789062,91.68000030517578,92.8499984741211
2023-10-09,92.79000091552734,91.43000030517578,92.68000030517578
2023-10-10,93.97000122070312,92.87000274658205,93.18000030517578
2023-10-11,93.62999725341795,91.8499984741211,91.9499969482422
2023-10-12,92.25,90.7699966430664,91.419998... | date,Middle,Upper,Lower,high
2023-10-20,94.61499786376953,99.57099990844728,90.25900192260741,95.08999633789062
2023-10-23,94.15999984741211,99.57099990844728,90.25900192260741,95.02999877929688
2023-10-24,94.52000045776367,99.57099990844728,90.25900192260741,94.9800033569336
2023-10-25,94.66500091552734,99.57099990844... |
3,260 | US | technical | From April 04, 2021 to May 28, 2021, how many times did a death cross occur between the 5-day and 30-day Simple Moving Average lines for Waters Corporation? Using unadjusted prices, write down the indicator formula, collect the raw data, calculate the answer, and keep four decimal places. Please list the raw data and k... | 0 | medium | moving average | SMA_n = 1 / n * \sum_{i=0}^{n-1} P_{t-i} | date,close
2021-02-22,279.8099975585937
2021-02-23,278.8800048828125
2021-02-24,279.8999938964844
2021-02-25,278.2300109863281
2021-02-26,273.8800048828125
2021-03-01,277.0400085449219
2021-03-02,274.0299987792969
2021-03-03,265.7799987792969
2021-03-04,261.6300048828125
2021-03-05,266.44000244140625
2021-03-08,264.670... | date,5-day,30-day
2021-04-05,286.21400146484376,274.3993347167969
2021-04-06,289.856005859375,275.14666849772135
2021-04-07,292.62400512695314,275.7290018717448
2021-04-08,296.6160034179687,276.5366689046224
2021-04-09,301.1000061035156,277.5003356933594
2021-04-12,303.3780090332031,278.605669148763
2021-04-13,304.5140... |
3,261 | US | technical | How many death cross occurred between the 5-day and 10-day Simple Moving Average lines for Conagra Brands from July 05, 2024 to December 20, 2024? Using unadjusted prices, write down the indicator formula, collect the raw data, calculate the answer, and keep four decimal places. Please list the raw data and key calcula... | 7 | medium | moving average | SMA_n = 1 / n * \sum_{i=0}^{n-1} P_{t-i} | date,close
2024-06-21,28.81999969482422
2024-06-24,29.34000015258789
2024-06-25,29.06999969482422
2024-06-26,28.489999771118164
2024-06-27,28.34000015258789
2024-06-28,28.420000076293945
2024-07-01,28.299999237060547
2024-07-02,28.32999992370605
2024-07-03,28.1299991607666
2024-07-05,28.239999771118164
2024-07-08,28.39... | date,5-day,10-day
2024-07-05,28.283999633789062,28.547999763488768
2024-07-08,28.27999954223633,28.505999755859374
2024-07-09,28.367999649047853,28.445999717712404
2024-07-10,28.463999557495118,28.41999969482422
2024-07-11,28.51399955749512,28.408999633789062
2024-07-12,28.53599967956543,28.409999656677247
2024-07-15,2... |
3,262 | US | technical | During May 06, 2024 to October 18, 2024, how many times did Salesforce's 5-day and 30-day Simple Moving Average lines form a death cross? Using unadjusted prices, write down the indicator formula, collect the raw data, calculate the answer, and keep four decimal places. Please list the raw data and key calculation proc... | 3 | medium | moving average | SMA_n = 1 / n * \sum_{i=0}^{n-1} P_{t-i} | date,close
2024-03-25,306.0599975585937
2024-03-26,305.8299865722656
2024-03-27,301.3800048828125
2024-03-28,301.17999267578125
2024-04-01,302.260009765625
2024-04-02,304.0
2024-04-03,304.739990234375
2024-04-04,294.1400146484375
2024-04-05,301.9100036621094
2024-04-08,301.7300109863281
2024-04-09,302.3699951171875
202... | date,5-day,30-day
2024-05-06,271.81000366210935,286.5503346761068
2024-05-07,273.4580017089844,285.58766784667966
2024-05-08,275.5140014648438,284.6923350016276
2024-05-09,276.12200317382815,283.81866861979165
2024-05-10,276.7240051269531,283.0016693115234
2024-05-13,277.102001953125,282.177001953125
2024-05-14,277.026... |
3,263 | US | technical | For Deckers Brands, how many times did the 60-day and 20-day Simple Moving Average lines produce a golden cross between May 12, 2021 and December 01, 2021? Using unadjusted prices, write down the indicator formula, collect the raw data, calculate the answer, and keep four decimal places. Please list the raw data and ke... | 2 | medium | moving average | SMA_n = 1 / n * \sum_{i=0}^{n-1} P_{t-i} | date,close
2021-02-17,53.94333267211914
2021-02-18,53.87166595458984
2021-02-19,55.19333267211914
2021-02-22,54.67333221435547
2021-02-23,54.05833435058594
2021-02-24,55.24666595458984
2021-02-25,53.176666259765625
2021-02-26,54.35166549682617
2021-03-01,55.255001068115234
2021-03-02,54.28166580200195
2021-03-03,53.494... | date,60-day,20-day
2021-05-12,55.34205551147461,56.43700008392334
2021-05-13,55.34113883972168,56.30200004577637
2021-05-14,55.37591660817464,56.25774993896484
2021-05-17,55.403916613260904,56.29091663360596
2021-05-18,55.416361045837405,56.32983322143555
2021-05-19,55.413055483500166,56.24808330535889
2021-05-20,55.35... |
3,264 | US | technical | From June 03, 2022 to July 04, 2022, count the number of golden cross occurrences between the 10-day and 30-day Simple Moving Average lines for Thermo Fisher Scientific. Using unadjusted prices, write down the indicator formula, collect the raw data, calculate the answer, and keep four decimal places. Please list the r... | 0 | medium | moving average | SMA_n = 1 / n * \sum_{i=0}^{n-1} P_{t-i} | date,close
2022-04-22,561.280029296875
2022-04-25,544.1599731445312
2022-04-26,516.4400024414062
2022-04-27,520.47998046875
2022-04-28,558.8900146484375
2022-04-29,552.9199829101562
2022-05-02,545.52001953125
2022-05-03,546.3200073242188
2022-05-04,562.97998046875
2022-05-05,550.510009765625
2022-05-06,546.679992675781... | date,10-day,30-day
2022-06-03,555.7899963378907,546.0603291829427
2022-06-06,555.5629943847656,545.7803283691406
2022-06-07,556.1079895019532,546.3303283691406
2022-06-08,556.4319885253906,547.5176615397136
2022-06-09,556.9869873046875,548.1623291015625
2022-06-10,555.6639892578125,547.0953287760417
2022-06-13,549.6199... |
3,265 | US | technical | From November 03, 2019 to September 30, 2020, how many times did a death cross occur between the 60-day and 20-day Weighted Moving Average lines for Ares Management? (Weights are 1, 2, ..., n) Using unadjusted prices, write down the indicator formula, collect the raw data, calculate the answer, and keep four decimal pl... | 2 | medium | moving average | WMA_n = \sum_{i=0}^{n-1} (n-i) * P_{t-i} / \sum_{j=1}^{n} j | date,close
2019-08-12,27.600000381469727
2019-08-13,28.059999465942383
2019-08-14,27.209999084472656
2019-08-15,27.100000381469727
2019-08-16,28.32999992370605
2019-08-19,29.06999969482422
2019-08-20,28.690000534057617
2019-08-21,28.90999984741211
2019-08-22,28.8799991607666
2019-08-23,27.93000030517578
2019-08-26,27.6... | date,60-day,20-day
2019-11-04,28.4449070060188,29.0842380069551
2019-11-05,28.55284145021699,29.428523772103446
2019-11-06,28.666038174446815,29.766904731023878
2019-11-07,28.781999975736024,30.091952505565825
2019-11-08,28.87690162137558,30.334714426313127
2019-11-11,28.978202189252677,30.579666864304315
2019-11-12,29... |
3,266 | US | technical | How many death cross occurred between the 60-day and 10-day Weighted Moving Average lines for West Pharmaceutical Services from September 28, 2025 to November 20, 2025? (Weights are 1, 2, ..., n) Using unadjusted prices, write down the indicator formula, collect the raw data, calculate the answer, and keep four decimal... | 1 | medium | moving average | WMA_n = \sum_{i=0}^{n-1} (n-i) * P_{t-i} / \sum_{j=1}^{n} j | date,close
2025-07-07,221.47999572753903
2025-07-08,220.47999572753903
2025-07-09,226.17999267578125
2025-07-10,229.22999572753903
2025-07-11,227.17999267578125
2025-07-14,224.4900054931641
2025-07-15,221.0500030517578
2025-07-16,224.3800048828125
2025-07-17,221.58999633789065
2025-07-18,210.88999938964844
2025-07-21,2... | date,60-day,10-day
2025-09-29,249.44418577600698,256.9849096124822
2025-09-30,250.05257878538038,258.0612704190341
2025-10-01,250.9366830627775,260.7180000998757
2025-10-02,251.85000012507203,263.42236439098014
2025-10-03,252.71797271895278,265.6870910644531
2025-10-06,253.41505492163486,266.8134560324929
2025-10-07,25... |
3,267 | US | technical | During September 09, 2019 to August 09, 2020, how many times did Norwegian Cruise Line Holdings's 10-day and 60-day Weighted Moving Average lines form a death cross? (Weights are 1, 2, ..., n) Using unadjusted prices, write down the indicator formula, collect the raw data, calculate the answer, and keep four decimal pl... | 3 | medium | moving average | WMA_n = \sum_{i=0}^{n-1} (n-i) * P_{t-i} / \sum_{j=1}^{n} j | date,close
2019-06-14,54.27999877929688
2019-06-17,53.040000915527344
2019-06-18,53.75
2019-06-19,53.90999984741211
2019-06-20,52.560001373291016
2019-06-21,51.11000061035156
2019-06-24,50.83000183105469
2019-06-25,50.86000061035156
2019-06-26,50.40999984741211
2019-06-27,51.84000015258789
2019-06-28,53.630001068115234... | date,10-day,60-day
2019-09-09,51.432000038840556,50.00626215700243
2019-09-10,52.13363605846058,50.147409641286714
2019-09-11,52.728181249445136,50.28604893918897
2019-09-12,53.18981732455167,50.41793413005892
2019-09-13,53.610544724897906,50.55797786191513
2019-09-16,53.7067266290838,50.65366639726149
2019-09-17,53.86... |
3,268 | US | technical | For HCA Healthcare, how many times did the 20-day and 5-day Weighted Moving Average lines produce a death cross between January 22, 2024 and October 30, 2024? (Weights are 1, 2, ..., n) Using unadjusted prices, write down the indicator formula, collect the raw data, calculate the answer, and keep four decimal places. P... | 6 | medium | moving average | WMA_n = \sum_{i=0}^{n-1} (n-i) * P_{t-i} / \sum_{j=1}^{n} j | date,close
2023-12-21,268.75
2023-12-22,269.989990234375
2023-12-26,271.70001220703125
2023-12-27,271.2200012207031
2023-12-28,270.4800109863281
2023-12-29,270.67999267578125
2024-01-02,275.32000732421875
2024-01-03,272.0799865722656
2024-01-04,273.1000061035156
2024-01-05,275.8399963378906
2024-01-08,281.489990234375
... | date,20-day,5-day
2024-01-22,280.43885628836495,285.5779988606771
2024-01-23,281.1598090762184,285.9079996744792
2024-01-24,281.23428460984,283.9719970703125
2024-01-25,281.9414264497303,284.32932739257814
2024-01-26,282.3337116059803,283.7433268229167
2024-01-29,282.98214140392486,284.5466654459635
2024-01-30,284.9684... |
3,269 | US | technical | From March 11, 2020 to June 28, 2020, count the number of golden cross occurrences between the 10-day and 5-day Weighted Moving Average lines for Lamb Weston. (Weights are 1, 2, ..., n) Using unadjusted prices, write down the indicator formula, collect the raw data, calculate the answer, and keep four decimal places. P... | 6 | medium | moving average | WMA_n = \sum_{i=0}^{n-1} (n-i) * P_{t-i} / \sum_{j=1}^{n} j | date,close
2020-02-27,89.44999694824219
2020-02-28,86.88999938964844
2020-03-02,86.6500015258789
2020-03-03,85.5
2020-03-04,88.08999633789062
2020-03-05,86.36000061035156
2020-03-06,83.37000274658203
2020-03-09,73.37999725341797
2020-03-10,72.7300033569336
2020-03-11,71.43000030517578
2020-03-12,63.36000061035156
2020-... | date,10-day,5-day
2020-03-11,79.33254574862393,74.75400085449219
2020-03-12,75.87345497824928,70.05600077311198
2020-03-13,72.97781829833984,67.05466664632162
2020-03-16,68.42654529918323,61.55133285522461
2020-03-17,64.62272734208541,57.67399978637695
2020-03-18,59.93109068437056,52.39666595458984
2020-03-19,56.713636... |
3,270 | US | technical | From July 05, 2023 to May 07, 2024, how many times did a golden cross occur between the 10-day and 5-day Exponential Moving Average lines for American International Group? (Smoothing factor alpha = 2 / (n + 1); Require 4n data points to warm up; Use the first data point as the initial value) Using unadjusted prices, wr... | 10 | medium | moving average | EMA_t = \alpha * P_t + (1 - \alpha) * EMA_{t-1}, \quad \alpha = 2 / (n + 1) | date,close
2023-05-05,53.790000915527344
2023-05-08,53.75
2023-05-09,53.09999847412109
2023-05-10,52.61000061035156
2023-05-11,52.810001373291016
2023-05-12,52.4900016784668
2023-05-15,52.540000915527344
2023-05-16,52.310001373291016
2023-05-17,53.7400016784668
2023-05-18,54.310001373291016
2023-05-19,53.84999847412109... | date,10-day,5-day
2023-05-18,53.304631020773996,53.432380009768295
2023-05-19,53.403788739564376,53.57158616455256
2023-05-22,53.50491789318406,53.701057137859266
2023-05-23,53.916751086743986,54.39070491116074
2023-05-24,54.03552356094039,54.450469839048566
2023-05-25,53.97088296898319,54.19364666109097
2023-05-26,53.... |
3,271 | US | technical | How many death cross occurred between the 30-day and 10-day Exponential Moving Average lines for IQVIA from April 06, 2022 to March 22, 2023? (Smoothing factor alpha = 2 / (n + 1); Require 4n data points to warm up; Use the first data point as the initial value) Using unadjusted prices, write down the indicator formula... | 6 | medium | moving average | EMA_t = \alpha * P_t + (1 - \alpha) * EMA_{t-1}, \quad \alpha = 2 / (n + 1) | date,close
2021-10-14,246.82000732421875
2021-10-15,248.8500061035156
2021-10-18,248.4600067138672
2021-10-19,249.0200042724609
2021-10-20,251.5200042724609
2021-10-21,254.83999633789065
2021-10-22,256.8900146484375
2021-10-25,257.25
2021-10-26,256.0899963378906
2021-10-27,254.2899932861328
2021-10-28,257.1900024414062... | date,30-day,10-day
2021-11-24,257.4152976369789,263.01296644900805
2021-11-26,257.7149556964379,262.8396993780236
2021-11-29,258.2939909703069,263.5397544804568
2021-11-30,258.34792735175887,262.73798182633965
2021-12-01,258.4061255871293,262.1038033124597
2021-12-02,258.6850859354647,262.21765925316305
2021-12-03,258.... |
3,272 | US | technical | During March 11, 2020 to December 04, 2020, how many times did Darden Restaurants's 10-day and 60-day Exponential Moving Average lines form a death cross? (Smoothing factor alpha = 2 / (n + 1); Require 4n data points to warm up; Use the first data point as the initial value) Using unadjusted prices, write down the indi... | 5 | medium | moving average | EMA_t = \alpha * P_t + (1 - \alpha) * EMA_{t-1}, \quad \alpha = 2 / (n + 1) | date,close
2019-03-28,121.12999725341795
2019-03-29,121.47000122070312
2019-04-01,120.4800033569336
2019-04-02,119.18000030517578
2019-04-03,118.4499969482422
2019-04-04,118.51000213623048
2019-04-05,118.9800033569336
2019-04-08,119.33000183105467
2019-04-09,117.02999877929688
2019-04-10,117.01000213623048
2019-04-11,1... | date,10-day,60-day
2019-06-21,119.01106426949332,119.27437724706483
2019-06-24,119.55268855936171,119.36341398859612
2019-06-25,120.20492689214112,119.48723646076178
2019-06-26,120.16948602743008,119.50437631897387
2019-06-27,120.41867055253866,119.5711181090248
2019-06-28,120.65709469879226,119.64190123190704
2019-07-... |
3,273 | US | technical | For Albemarle Corporation, how many times did the 5-day and 10-day Exponential Moving Average lines produce a golden cross between October 06, 2023 and May 24, 2024? (Smoothing factor alpha = 2 / (n + 1); Require 4n data points to warm up; Use the first data point as the initial value) Using unadjusted prices, write do... | 9 | medium | moving average | EMA_t = \alpha * P_t + (1 - \alpha) * EMA_{t-1}, \quad \alpha = 2 / (n + 1) | date,close
2023-08-10,191.6699981689453
2023-08-11,187.4900054931641
2023-08-14,185.5399932861328
2023-08-15,184.0399932861328
2023-08-16,181.52999877929688
2023-08-17,182.67999267578125
2023-08-18,183.38999938964844
2023-08-21,188.07000732421875
2023-08-22,188.16000366210935
2023-08-23,191.77999877929688
2023-08-24,19... | date,5-day,10-day
2023-08-23,188.14127885263906,187.65435085981778
2023-08-24,189.0075210661474,188.21537897497166
2023-08-25,189.25168254181966,188.4925837964612
2023-08-28,189.38112149109594,188.70120481340433
2023-08-29,192.17074766073063,190.34644030187627
2023-08-30,194.310497219784,191.84526867206068
2023-08-31,1... |
3,274 | US | technical | From July 07, 2021 to October 25, 2021, count the number of death cross occurrences between the 20-day and 5-day Exponential Moving Average lines for Dow Inc.. (Smoothing factor alpha = 2 / (n + 1); Require 4n data points to warm up; Use the first data point as the initial value) Using unadjusted prices, write down the... | 7 | medium | moving average | EMA_t = \alpha * P_t + (1 - \alpha) * EMA_{t-1}, \quad \alpha = 2 / (n + 1) | date,close
2021-03-12,64.33999633789062
2021-03-15,62.900001525878906
2021-03-16,63.18000030517578
2021-03-17,66.01000213623047
2021-03-18,64.72000122070312
2021-03-19,63.90999984741211
2021-03-22,63.5099983215332
2021-03-23,60.75
2021-03-24,62.040000915527344
2021-03-25,63.2400016784668
2021-03-26,63.9900016784668
202... | date,20-day,5-day
2021-04-09,63.85965318567718,63.64501100570462
2021-04-12,63.8530196361391,63.693340975645526
2021-04-13,63.80130361110595,63.56556110819403
2021-04-14,63.84308401612153,63.790373360052534
2021-04-15,63.91231408075988,64.05024880497643
2021-04-16,63.98542705451378,64.26016597170955
2021-04-19,64.03919... |
3,275 | US | technical | From April 28, 2022 to June 04, 2022, how many times did a golden cross occur between the 5-day and 10-day Double Exponential Moving Average lines for D. R. Horton? (Smoothing factor alpha = 2 / (n + 1); Require 5n data points to warm up; Use the first data point as the initial value) Using unadjusted prices, write dow... | 8 | medium | moving average | DEMA = 2 * EMA1 - EMA2; EMA1 = EMA_n(P); EMA2 = EMA_n(EMA1) | date,close
2022-02-15,84.80999755859375
2022-02-16,85.30000305175781
2022-02-17,82.75
2022-02-18,83.44000244140625
2022-02-22,80.4000015258789
2022-02-23,78.1500015258789
2022-02-24,82.30999755859375
2022-02-25,86.0199966430664
2022-02-28,85.4000015258789
2022-03-01,85.83000183105469
2022-03-02,87.58000183105469
2022-0... | date,5-day,10-day
2022-03-14,78.92477503582174,80.22126187270352
2022-03-15,79.40300695113599,80.05234656382625
2022-03-16,80.4663286600839,80.39076190630956
2022-03-17,81.8915454891773,81.14455157531694
2022-03-18,84.08147030618566,82.55677290839458
2022-03-21,83.67238456746301,82.67514348697159
2022-03-22,83.33474949... |
3,276 | US | technical | How many death cross occurred between the 5-day and 60-day Double Exponential Moving Average lines for GE Aerospace from June 11, 2022 to May 21, 2023? (Smoothing factor alpha = 2 / (n + 1); Require 5n data points to warm up; Use the first data point as the initial value) Using unadjusted prices, write down the indicat... | 15 | medium | moving average | DEMA = 2 * EMA1 - EMA2; EMA1 = EMA_n(P); EMA2 = EMA_n(EMA1) | date,close
2021-04-06,66.78740692138672
2021-04-07,66.73756408691406
2021-04-08,67.03661346435547
2021-04-09,67.78423309326172
2021-04-12,67.73439025878906
2021-04-13,66.98677062988281
2021-04-14,68.18296813964844
2021-04-15,67.53502655029297
2021-04-16,66.73756408691406
2021-04-19,67.08645629882812
2021-04-20,65.09280... | date,5-day,60-day
2021-09-22,61.050613846700735,63.34992714768126
2021-09-23,62.59928665234319,63.36982945475573
2021-09-24,63.750165446550234,63.42303694235301
2021-09-27,64.90026298060022,63.53643705166293
2021-09-28,65.62456214996156,63.66004866062546
2021-09-29,66.16428480687816,63.800165906780606
2021-09-30,65.284... |
3,277 | US | technical | During June 18, 2022 to January 04, 2023, how many times did Lilly (Eli)'s 20-day and 10-day Double Exponential Moving Average lines form a golden cross? (Smoothing factor alpha = 2 / (n + 1); Require 5n data points to warm up; Use the first data point as the initial value) Using unadjusted prices, write down the indic... | 9 | medium | moving average | DEMA = 2 * EMA1 - EMA2; EMA1 = EMA_n(P); EMA2 = EMA_n(EMA1) | date,close
2022-01-26,237.8600006103516
2022-01-27,236.72000122070312
2022-01-28,245.1000061035156
2022-01-31,245.38999938964844
2022-02-01,248.27999877929688
2022-02-02,250.8300018310547
2022-02-03,244.80999755859372
2022-02-04,242.2700042724609
2022-02-07,243.5500030517578
2022-02-08,239.91000366210935
2022-02-09,243... | date,20-day,10-day
2022-03-22,282.11520696127434,288.0510093260959
2022-03-23,283.6914308491789,288.3345293689165
2022-03-24,285.62116125712095,289.54433941650683
2022-03-25,287.4608595967705,290.7325768449782
2022-03-28,289.4598817966709,292.3441261533952
2022-03-29,290.52303005184575,292.31932816554206
2022-03-30,291... |
3,278 | US | technical | For Aptiv, how many times did the 30-day and 5-day Double Exponential Moving Average lines produce a death cross between February 07, 2025 and November 10, 2025? (Smoothing factor alpha = 2 / (n + 1); Require 5n data points to warm up; Use the first data point as the initial value) Using unadjusted prices, write down t... | 13 | medium | moving average | DEMA = 2 * EMA1 - EMA2; EMA1 = EMA_n(P); EMA2 = EMA_n(EMA1) | date,close
2024-07-03,69.79000091552734
2024-07-05,70.18000030517578
2024-07-08,69.68000030517578
2024-07-09,69.08000183105469
2024-07-10,69.5999984741211
2024-07-11,71.75
2024-07-12,72.72000122070312
2024-07-15,72.26000213623047
2024-07-16,73.41000366210938
2024-07-17,72.41000366210938
2024-07-18,71.68000030517578
202... | date,30-day,5-day
2024-09-25,69.98576709603563,71.31505844610882
2024-09-26,70.2919163215097,71.98522821008565
2024-09-27,70.80923563492607,73.3913893134517
2024-09-30,70.99777788694881,72.87175312746132
2024-10-01,70.98093321657271,71.71727277179326
2024-10-02,70.90558530290218,70.8100321597997
2024-10-03,70.701225111... |
3,279 | US | technical | From July 22, 2024 to April 02, 2025, count the number of death cross occurrences between the 60-day and 5-day Double Exponential Moving Average lines for Align Technology. (Smoothing factor alpha = 2 / (n + 1); Require 5n data points to warm up; Use the first data point as the initial value) Using unadjusted prices, w... | 8 | medium | moving average | DEMA = 2 * EMA1 - EMA2; EMA1 = EMA_n(P); EMA2 = EMA_n(EMA1) | date,close
2023-05-10,305.260009765625
2023-05-11,296.0799865722656
2023-05-12,293.7099914550781
2023-05-15,297.2799987792969
2023-05-16,292.29998779296875
2023-05-17,291.3599853515625
2023-05-18,293.4200134277344
2023-05-19,290.989990234375
2023-05-22,300.8299865722656
2023-05-23,282.54998779296875
2023-05-24,281.2300... | date,60-day,5-day
2023-10-27,270.44609952522677,199.28153205787402
2023-10-30,264.1202480410385,187.025231580108
2023-10-31,257.98055113592807,180.35184560517746
2023-11-01,252.0689562271274,177.09014101771896
2023-11-02,247.05221408009595,181.3815910619492
2023-11-03,242.6304432086327,187.34872350918562
2023-11-06,238... |
3,280 | US | technical | From July 24, 2019 to April 03, 2020, how many times did a golden cross occur between the 60-day and 20-day Triple Exponential Moving Average lines for Parker Hannifin? (Smoothing factor alpha = 2 / (n + 1); Require 6n data points to warm up; Use the first data point as the initial value) Using unadjusted prices, write... | 7 | medium | moving average | TEMA = 3 * EMA1 - 3 * EMA2 + EMA3; EMA1 = EMA_n(P); EMA2 = EMA_n(EMA1); EMA3 = EMA_n(EMA2) | date,close
2018-02-15,184.6300048828125
2018-02-16,183.22000122070312
2018-02-20,181.6100006103516
2018-02-21,181.3000030517578
2018-02-22,183.9199981689453
2018-02-23,183.57000732421875
2018-02-26,185.5500030517578
2018-02-27,181.88999938964844
2018-02-28,178.47000122070312
2018-03-01,177.3000030517578
2018-03-02,175.... | date,60-day,20-day
2018-10-29,162.0685964290774,143.2021462651536
2018-10-30,160.36613411217263,142.50831231055315
2018-10-31,159.09818792284833,142.95155426053645
2018-11-01,158.6563654406604,145.4589721312837
2018-11-02,158.4719862937236,148.2342453448091
2018-11-05,158.54277613860964,151.246289648698
2018-11-06,158.... |
3,281 | US | technical | How many golden cross occurred between the 10-day and 20-day Triple Exponential Moving Average lines for Centene Corporation from April 26, 2021 to April 01, 2022? (Smoothing factor alpha = 2 / (n + 1); Require 6n data points to warm up; Use the first data point as the initial value) Using unadjusted prices, write down... | 16 | medium | moving average | TEMA = 3 * EMA1 - 3 * EMA2 + EMA3; EMA1 = EMA_n(P); EMA2 = EMA_n(EMA1); EMA3 = EMA_n(EMA2) | date,close
2020-10-30,59.09999847412109
2020-11-02,62.380001068115234
2020-11-03,64.63999938964844
2020-11-04,63.9900016784668
2020-11-05,67.87999725341797
2020-11-06,67.93000030517578
2020-11-09,68.81999969482422
2020-11-10,71.12000274658203
2020-11-11,69.4000015258789
2020-11-12,68.83000183105469
2020-11-13,69.050003... | date,10-day,20-day
2021-01-25,61.21148501348134,63.22580874191223
2021-01-26,60.30513528443383,62.39078156277963
2021-01-27,58.99861119653604,61.27428045808432
2021-01-28,59.25961701739682,60.97773578419702
2021-01-29,59.29484811891804,60.62432424168088
2021-02-01,59.06440286036592,60.16588964372087
2021-02-02,58.98543... |
3,282 | US | technical | During December 09, 2022 to January 20, 2023, how many times did AvalonBay Communities's 60-day and 30-day Triple Exponential Moving Average lines form a golden cross? (Smoothing factor alpha = 2 / (n + 1); Require 6n data points to warm up; Use the first data point as the initial value) Using unadjusted prices, write ... | 2 | medium | moving average | TEMA = 3 * EMA1 - 3 * EMA2 + EMA3; EMA1 = EMA_n(P); EMA2 = EMA_n(EMA1); EMA3 = EMA_n(EMA2) | date,close
2021-07-08,217.2700042724609
2021-07-09,220.8300018310547
2021-07-12,223.97000122070312
2021-07-13,221.22000122070312
2021-07-14,224.07000732421875
2021-07-15,224.92999267578125
2021-07-16,225.8699951171875
2021-07-19,223.1699981689453
2021-07-20,228.7400054931641
2021-07-21,228.17999267578125
2021-07-22,224... | date,60-day,30-day
2022-03-21,242.21284178707793,242.66088749572845
2022-03-22,242.24563694105447,242.77349809599562
2022-03-23,242.12127443362832,242.57535871268172
2022-03-24,242.17256712799082,242.72011041678758
2022-03-25,242.60521510264178,243.5784424671339
2022-03-28,243.27169564484015,244.82604826596344
2022-03-... |
3,283 | US | technical | For CenterPoint Energy, how many times did the 5-day and 30-day Triple Exponential Moving Average lines produce a death cross between July 15, 2019 and January 28, 2020? (Smoothing factor alpha = 2 / (n + 1); Require 6n data points to warm up; Use the first data point as the initial value) Using unadjusted prices, writ... | 16 | medium | moving average | TEMA = 3 * EMA1 - 3 * EMA2 + EMA3; EMA1 = EMA_n(P); EMA2 = EMA_n(EMA1); EMA3 = EMA_n(EMA2) | date,close
2018-10-23,27.670000076293945
2018-10-24,27.90999984741211
2018-10-25,27.75
2018-10-26,27.170000076293945
2018-10-29,27.21999931335449
2018-10-30,27.299999237060547
2018-10-31,27.01000022888184
2018-11-01,27.190000534057617
2018-11-02,26.959999084472656
2018-11-05,27.489999771118164
2018-11-06,27.79999923706... | date,5-day,30-day
2019-03-01,30.153234289587317,31.132842480503548
2019-03-04,30.188096445533578,31.029147701774964
2019-03-05,30.112273555240897,30.90505271358042
2019-03-06,30.051747446320707,30.781643795661232
2019-03-07,29.99508474794871,30.659251731961568
2019-03-08,29.986661251412897,30.55084228327842
2019-03-11,... |
3,284 | US | technical | From August 05, 2019 to April 15, 2020, count the number of golden cross occurrences between the 20-day and 30-day Triple Exponential Moving Average lines for Booking Holdings. (Smoothing factor alpha = 2 / (n + 1); Require 6n data points to warm up; Use the first data point as the initial value) Using unadjusted price... | 8 | medium | moving average | TEMA = 3 * EMA1 - 3 * EMA2 + EMA3; EMA1 = EMA_n(P); EMA2 = EMA_n(EMA1); EMA3 = EMA_n(EMA2) | date,close
2018-11-13,76.4031982421875
2018-11-14,75.53479766845703
2018-11-15,75.55480194091797
2018-11-16,74.21279907226562
2018-11-19,71.19999694824219
2018-11-20,70.01719665527344
2018-11-21,70.41600036621094
2018-11-23,70.56320190429688
2018-11-26,72.09760284423828
2018-11-27,72.9843978881836
2018-11-28,74.7779998... | date,20-day,30-day
2019-03-22,69.1657067253861,69.42925957145562
2019-03-25,69.23234769801243,69.39127911471118
2019-03-26,69.47091011289953,69.48461826267817
2019-03-27,69.5037755084935,69.45147075026686
2019-03-28,69.2998564850798,69.26047294990286
2019-03-29,69.30907199700705,69.21601768292194
2019-04-01,69.47502053... |
3,285 | US | technical | From March 18, 2020 to August 11, 2020, how many times did a death cross occur between the 60-day and 30-day Hull Moving Average lines for Caterpillar Inc.? Using unadjusted prices, write down the indicator formula, collect the raw data, calculate the answer, and keep four decimal places. Please list the raw data and k... | 4 | medium | moving average | HMA = WMA_{\sqrt{n}}(2 * WMA_{n/2}(P) - WMA_n(P)) | date,close
2019-11-06,145.49000549316406
2019-11-07,147.00999450683594
2019-11-08,148.16000366210938
2019-11-11,148.0
2019-11-12,146.33999633789062
2019-11-13,144.49000549316406
2019-11-14,143.44000244140625
2019-11-15,145.30999755859375
2019-11-18,143.58999633789062
2019-11-19,143.17999267578125
2019-11-20,141.5200042... | date,60-day,30-day
2020-02-11,136.83131535730786,131.56280040125694
2020-02-12,136.26510315469747,131.79396650854406
2020-02-13,135.8335544469467,132.3681298510917
2020-02-14,135.47045341215616,133.1129892312327
2020-02-18,135.14208297252065,133.84800916610226
2020-02-19,134.85826786816762,134.52204444803218
2020-02-20... |
3,286 | US | technical | How many golden cross occurred between the 10-day and 30-day Hull Moving Average lines for Invesco from January 23, 2020 to October 02, 2020? Using unadjusted prices, write down the indicator formula, collect the raw data, calculate the answer, and keep four decimal places. Please list the raw data and key calculation ... | 11 | medium | moving average | HMA = WMA_{\sqrt{n}}(2 * WMA_{n/2}(P) - WMA_n(P)) | date,close
2019-11-15,17.450000762939453
2019-11-18,17.3700008392334
2019-11-19,17.520000457763672
2019-11-20,17.190000534057617
2019-11-21,17.06999969482422
2019-11-22,17.329999923706055
2019-11-25,17.75
2019-11-26,17.549999237060547
2019-11-27,17.700000762939453
2019-11-29,17.559999465942383
2019-12-02,17.29000091552... | date,10-day,30-day
2020-01-06,17.82641416029497,18.200711909605182
2020-01-07,17.775515384866736,18.150171088762182
2020-01-08,17.754929542541504,18.092607658960485
2020-01-09,17.800242649425158,18.045794052684606
2020-01-10,17.814666996580183,17.993370436528252
2020-01-13,17.88043452176181,17.961250702847718
2020-01-1... |
3,287 | US | technical | During March 15, 2020 to March 03, 2021, how many times did Cencora's 10-day and 5-day Hull Moving Average lines form a golden cross? Using unadjusted prices, write down the indicator formula, collect the raw data, calculate the answer, and keep four decimal places. Please list the raw data and key calculation process. | 35 | medium | moving average | HMA = WMA_{\sqrt{n}}(2 * WMA_{n/2}(P) - WMA_n(P)) | date,close
2020-02-24,94.93000030517578
2020-02-25,92.93000030517578
2020-02-26,93.70999908447266
2020-02-27,86.58999633789062
2020-02-28,84.31999969482422
2020-03-02,87.16000366210938
2020-03-03,85.87000274658203
2020-03-04,90.37999725341795
2020-03-05,86.97000122070312
2020-03-06,85.80999755859375
2020-03-09,83.26999... | date,10-day,5-day
2020-03-10,85.32815950952396,83.87133110894098
2020-03-11,84.74254336886936,85.19466620551215
2020-03-12,83.40259390166311,82.12266540527344
2020-03-13,84.09514997848356,85.59666578504773
2020-03-16,83.77769615866922,84.94955579969617
2020-03-17,84.97303010574495,85.98133375379774
2020-03-18,85.568232... |
3,288 | US | technical | For Cisco, how many times did the 30-day and 10-day Hull Moving Average lines produce a death cross between November 30, 2021 and October 29, 2022? Using unadjusted prices, write down the indicator formula, collect the raw data, calculate the answer, and keep four decimal places. Please list the raw data and key calcul... | 14 | medium | moving average | HMA = WMA_{\sqrt{n}}(2 * WMA_{n/2}(P) - WMA_n(P)) | date,close
2021-09-27,56.220001220703125
2021-09-28,55.52000045776367
2021-09-29,55.47999954223633
2021-09-30,54.43000030517578
2021-10-01,55.13999938964844
2021-10-04,54.22999954223633
2021-10-05,54.68999862670898
2021-10-06,53.93999862670898
2021-10-07,55.02000045776367
2021-10-08,55.08000183105469
2021-10-11,54.9300... | date,30-day,10-day
2021-11-11,57.479964977797636,57.36425179760865
2021-11-12,57.54446520801941,57.18359520652078
2021-11-15,57.59480028090938,57.08580755368629
2021-11-16,57.60872678503768,57.01861596540971
2021-11-17,57.57936610997792,56.912888509576966
2021-11-18,57.33133745692536,56.060353385077576
2021-11-19,56.89... |
3,289 | US | technical | From October 21, 2020 to August 29, 2021, count the number of golden cross occurrences between the 10-day and 5-day Hull Moving Average lines for Globe Life. Using unadjusted prices, write down the indicator formula, collect the raw data, calculate the answer, and keep four decimal places. Please list the raw data and ... | 28 | medium | moving average | HMA = WMA_{\sqrt{n}}(2 * WMA_{n/2}(P) - WMA_n(P)) | date,close
2020-09-30,79.9000015258789
2020-10-01,80.5199966430664
2020-10-02,80.79000091552734
2020-10-05,82.16999816894531
2020-10-06,81.05999755859375
2020-10-07,82.13999938964844
2020-10-08,82.97000122070312
2020-10-09,81.79000091552734
2020-10-12,82.44000244140625
2020-10-13,81.31999969482422
2020-10-14,81.5199966... | date,10-day,5-day
2020-10-15,81.98612151483093,82.22066599527996
2020-10-16,82.33291881831005,83.42000003390842
2020-10-19,82.6758277199485,83.32266608344183
2020-10-20,83.09318051579022,83.29710913764107
2020-10-21,83.60192732377486,84.03044094509549
2020-10-22,84.61261489559907,86.02933400472006
2020-10-23,85.6228378... |
3,290 | US | technical | What is the percentage of days where the low price is greater than the 5-day Simple Moving Average line for Quest Diagnostics from June 16, 2019 to February 12, 2020? (Unit: %) Using unadjusted prices, write down the indicator formula, collect the raw data, calculate the answer, and keep four decimal places. Please lis... | 76.6467 | medium | moving average | SMA_n = 1 / n * \sum_{i=0}^{n-1} P_{t-i} | date,close,low
2019-06-11,98.91999816894533,98.51000213623048
2019-06-12,99.5,98.36000061035156
2019-06-13,100.86000061035156,99.19000244140624
2019-06-14,101.02999877929688,100.76000213623048
2019-06-17,101.94000244140624,100.9000015258789
2019-06-18,100.56999969482422,100.33999633789062
2019-06-19,101.91999816894533,... | date,5-day,low
2019-06-17,100.45,100.9000015258789
2019-06-18,100.78000030517578,100.33999633789062
2019-06-19,101.26399993896484,100.31999969482422
2019-06-20,101.15999908447266,99.94000244140624
2019-06-21,101.20999908447266,100.08000183105467
2019-06-24,101.00199890136719,100.18000030517578
2019-06-25,101.0939987182... |
3,291 | US | technical | From March 13, 2025 to August 20, 2025, what proportion of days had Cigna's low price greater than its 5-day Simple Moving Average line? (Unit: %) Using unadjusted prices, write down the indicator formula, collect the raw data, calculate the answer, and keep four decimal places. Please list the raw data and key calcula... | 79.2793 | medium | moving average | SMA_n = 1 / n * \sum_{i=0}^{n-1} P_{t-i} | date,close,low
2025-03-07,321.0199890136719,313.8999938964844
2025-03-10,326.67999267578125,319.19000244140625
2025-03-11,317.8699951171875,316.3299865722656
2025-03-12,311.04998779296875,307.7699890136719
2025-03-13,311.989990234375,309.70001220703125
2025-03-14,312.8999938964844,309.54998779296875
2025-03-17,316.7999... | date,5-day,low
2025-03-13,317.72199096679685,309.70001220703125
2025-03-14,316.0979919433594,309.54998779296875
2025-03-17,314.1219909667969,312.04998779296875
2025-03-18,315.03399047851565,316.3900146484375
2025-03-19,316.989990234375,317.2799987792969
2025-03-20,318.8699951171875,319.239990234375
2025-03-21,319.61999... |
3,292 | US | technical | During January 16, 2020 to December 18, 2020, what percentage of trading days had Huntington Bancshares's low less the 10-day Simple Moving Average line? Using unadjusted prices, write down the indicator formula, collect the raw data, calculate the answer, and keep four decimal places. Please list the raw data and key ... | 38.2979 | medium | moving average | SMA_n = 1 / n * \sum_{i=0}^{n-1} P_{t-i} | date,close,low
2020-01-03,14.8100004196167,14.600000381469728
2020-01-06,14.56999969482422,14.479999542236328
2020-01-07,14.40999984741211,14.3100004196167
2020-01-08,14.529999732971191,14.399999618530272
2020-01-09,14.5600004196167,14.460000038146973
2020-01-10,14.380000114440918,14.329999923706056
2020-01-13,14.46000... | date,10-day,low
2020-01-16,14.544000053405762,14.529999732971191
2020-01-17,14.534000015258789,14.609999656677246
2020-01-21,14.538000011444092,14.479999542236328
2020-01-22,14.569999980926514,14.5600004196167
2020-01-23,14.544000053405762,13.93000030517578
2020-01-24,14.460000038146973,13.68000030517578
2020-01-27,14.... |
3,293 | US | technical | For NRG Energy from November 12, 2021 to January 04, 2022, what percentage of days had the open greater than the 5-day Simple Moving Average line? (Unit: %) Using unadjusted prices, write down the indicator formula, collect the raw data, calculate the answer, and keep four decimal places. Please list the raw data and k... | 25 | medium | moving average | SMA_n = 1 / n * \sum_{i=0}^{n-1} P_{t-i} | date,close,low,open
2021-11-08,35.630001068115234,35.029998779296875,36.22999954223633
2021-11-09,34.88999938964844,34.7400016784668,35.810001373291016
2021-11-10,34.970001220703125,34.709999084472656,34.79999923706055
2021-11-11,35.11000061035156,34.70000076293945,34.939998626708984
2021-11-12,35.70000076293945,35.020... | date,5-day,open
2021-11-12,35.26000061035156,35.130001068115234
2021-11-15,35.470000457763675,36.060001373291016
2021-11-16,35.816000366210936,36.84000015258789
2021-11-17,36.10999984741211,36.43999862670898
2021-11-18,36.29799957275391,36.43999862670898
2021-11-19,36.41599960327149,35.970001220703125
2021-11-22,36.387... |
3,294 | US | technical | Calculate the percentage of days where Church & Dwight's low was greater than its 20-day Simple Moving Average line from August 27, 2023 to May 14, 2024. (Unit: %) Using unadjusted prices, write down the indicator formula, collect the raw data, calculate the answer, and keep four decimal places. Please list the raw dat... | 45.5556 | medium | moving average | SMA_n = 1 / n * \sum_{i=0}^{n-1} P_{t-i} | date,close,low,open
2023-08-01,96.37000274658205,95.8000030517578,95.8000030517578
2023-08-02,96.77999877929688,95.91999816894533,96.5500030517578
2023-08-03,95.11000061035156,95.0999984741211,97.12000274658205
2023-08-04,94.62999725341795,94.37999725341795,94.93000030517578
2023-08-07,95.68000030517578,94.650001525878... | date,20-day,low
2023-08-28,94.40550003051757,93.95999908447266
2023-08-29,94.35900001525879,93.83999633789062
2023-08-30,94.32050018310547,95.37999725341795
2023-08-31,94.40349998474122,95.83999633789062
2023-09-01,94.48500022888183,96.02999877929688
2023-09-05,94.45950012207031,94.77999877929688
2023-09-06,94.39050025... |
3,295 | US | technical | What is the percentage of days where the open price is greater than the 20-day Weighted Moving Average line for Biogen from July 19, 2024 to March 22, 2025? (Unit: %) (Weights are 1, 2, ..., n) Using unadjusted prices, write down the indicator formula, collect the raw data, calculate the answer, and keep four decimal p... | 73.9645 | medium | moving average | WMA_n = \sum_{i=0}^{n-1} (n-i) * P_{t-i} / \sum_{j=1}^{n} j | date,close,open
2024-06-21,224.0,227.3500061035156
2024-06-24,226.6000061035156,225.7400054931641
2024-06-25,223.19000244140625,225.47999572753903
2024-06-26,224.4600067138672,221.7899932861328
2024-06-27,228.72000122070312,223.42999267578125
2024-06-28,231.82000732421875,229.5
2024-07-01,231.7700042724609,231.41000366... | date,20-day,open
2024-07-19,227.8462866646903,225.6699981689453
2024-07-22,227.74933457147506,227.72999572753903
2024-07-23,227.41700039818173,226.2899932861328
2024-07-24,227.26138109479632,224.1000061035156
2024-07-25,227.22652406238373,227.1999969482422
2024-07-26,225.6279523577009,211.3800048828125
2024-07-29,224.4... |
3,296 | US | technical | From October 29, 2023 to February 09, 2024, what proportion of days had Meta Platforms's low price less than its 60-day Weighted Moving Average line? (Unit: %) (Weights are 1, 2, ..., n) Using unadjusted prices, write down the indicator formula, collect the raw data, calculate the answer, and keep four decimal places. ... | 87.3239 | medium | moving average | WMA_n = \sum_{i=0}^{n-1} (n-i) * P_{t-i} / \sum_{j=1}^{n} j | date,close,open,low
2023-08-07,316.5599975585937,313.2300109863281,310.4599914550781
2023-08-08,312.6400146484375,314.3999938964844,310.1099853515625
2023-08-09,305.2099914550781,312.8800048828125,302.8500061035156
2023-08-10,305.739990234375,307.94000244140625,303.8699951171875
2023-08-11,301.6400146484375,302.5700073... | date,60-day,low
2023-10-30,305.9282511893517,299.04998779296875
2023-10-31,305.86278633159367,296.8599853515625
2023-11-01,306.15256247598614,301.8500061035156
2023-11-02,306.41063881128866,308.3299865722656
2023-11-03,306.7879176905898,311.0199890136719
2023-11-06,307.1996986931139,314.45001220703125
2023-11-07,307.70... |
3,297 | US | technical | During December 21, 2024 to June 23, 2025, what percentage of trading days had Consolidated Edison's high less the 5-day Weighted Moving Average line? (Weights are 1, 2, ..., n) Using unadjusted prices, write down the indicator formula, collect the raw data, calculate the answer, and keep four decimal places. Please li... | 87.8049 | medium | moving average | WMA_n = \sum_{i=0}^{n-1} (n-i) * P_{t-i} / \sum_{j=1}^{n} j | date,close,open,low,high
2024-12-17,90.83999633789062,90.80999755859376,90.43000030517578,91.91999816894533
2024-12-18,88.87000274658203,90.6999969482422,88.76000213623047,90.79000091552734
2024-12-19,89.06999969482422,88.68000030517578,88.37000274658203,90.25
2024-12-20,90.02999877929688,88.77999877929688,88.779998779... | date,5-day,high
2024-12-23,89.6173324584961,89.88999938964844
2024-12-24,89.57866668701172,89.7300033569336
2024-12-26,89.62733205159505,90.12999725341795
2024-12-27,89.61799825032553,89.95999908447266
2024-12-30,89.44266662597656,89.4800033569336
2024-12-31,89.34866790771484,89.63999938964844
2025-01-02,89.21733398437... |
3,298 | US | technical | For Honeywell from January 28, 2022 to June 04, 2022, what percentage of days had the low less than the 5-day Weighted Moving Average line? (Unit: %) (Weights are 1, 2, ..., n) Using unadjusted prices, write down the indicator formula, collect the raw data, calculate the answer, and keep four decimal places. Please lis... | 14.7727 | medium | moving average | WMA_n = \sum_{i=0}^{n-1} (n-i) * P_{t-i} / \sum_{j=1}^{n} j | date,close,open,low,high
2022-01-24,192.6955718994141,192.4599456787109,187.54005432128903,193.006591796875
2022-01-25,190.66917419433597,189.17059326171875,186.5315704345703,192.07351684570312
2022-01-26,189.11404418945312,191.4703063964844,187.2949981689453,194.0527801513672
2022-01-27,189.11404418945312,191.39491271... | date,5-day,low
2022-01-28,189.98114827473958,184.77850341796875
2022-01-31,190.75777486165364,187.85108947753903
2022-02-01,191.80270385742188,189.9246063232422
2022-02-02,193.350927734375,192.8746490478516
2022-02-03,189.49858805338542,180.5655059814453
2022-02-04,186.1306935628255,177.2196044921875
2022-02-07,183.729... |
3,299 | US | technical | Calculate the percentage of days where Hasbro's low was less than its 5-day Weighted Moving Average line from April 15, 2021 to March 31, 2022. (Unit: %) (Weights are 1, 2, ..., n) Using unadjusted prices, write down the indicator formula, collect the raw data, calculate the answer, and keep four decimal places. Please... | 15.5738 | medium | moving average | WMA_n = \sum_{i=0}^{n-1} (n-i) * P_{t-i} / \sum_{j=1}^{n} j | date,close,open,low,high
2021-04-09,95.23999786376952,96.33000183105467,94.7300033569336,96.83000183105467
2021-04-12,97.11000061035156,94.79000091552734,94.36000061035156,97.2699966430664
2021-04-13,98.83999633789062,96.62999725341795,95.66999816894533,100.47000122070312
2021-04-14,99.98999786376952,98.26000213623048,... | date,5-day,low
2021-04-15,98.732666015625,98.83999633789062
2021-04-16,98.71999969482422,97.97000122070312
2021-04-19,98.52666727701823,96.87999725341795
2021-04-20,97.84666849772135,96.1500015258789
2021-04-21,97.62733561197916,96.56999969482422
2021-04-22,97.82466939290364,97.1500015258789
2021-04-23,97.6140024820963... |
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