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I am curious to know if there have been studies on when selling occurs and if any useful patterns exist. I am particularly interested in the behavior of sellers when they are under water on their purchase since while an asset may theoretically be unbounded on the profit side, they can only lose 100% of purchase which ... |
Reseach on when people/institutions sell? |
I am curious to know if there have been studies on when selling occurs and if any useful patterns exist. I am particularly interested in the behavior of sellers when they are under water on their purchase since while an asset may theoretically be unbounded on the profit side, they can only lose 100% of purchase which ... |
I somewhat disagree (partially) with the other answers so I offer my own. First, most importantly is that you specify exactly what underlying asset you really talk about. Even for non-interest bearing assets an unhedged rho can sometimes have devastating results on your profitability. Imagine a stock denominated in a h... |
I highly doubt there are useful studies around. Think about it, the answers of such data sets must be highly skewed simply because there are price takers in the market that are extremely secretive about profits and losses. You will only get one side of the story and it most likely skews the results by quite a bit.
... |
I highly doubt there are useful studies around. Think about it, the answers of such data sets must be highly skewed simply because there are price takers in the market that are extremely secretive about profits and losses. You will only get one side of the story and it most likely skews the results by quite a bit.
... |
Suppose a fairly simple problem: You have to buy (resp sell) a given number of shares V in a fixed time horizon H with the aim to minimize your capital spent (resp maximize your revenue).
There are some research papers on the web that claim that using reiforcement learning algorithms can help make decision. See for ... |
Suppose a fairly simple problem: You have to buy (resp sell) a given number of shares V in a fixed time horizon H with the aim to minimize your capital spent (resp maximize your revenue).
There are some research papers on the web that claim that using reiforcement learning algorithms can help make decision. See for ... |
Suppose a fairly simple problem: You have to buy (resp sell) a given number of shares V in a fixed time horizon H with the aim to minimize your capital spent (resp maximize your revenue).
There are some research papers on the web that claim that using reiforcement learning algorithms can help make decision. See for ... |
> I believe that beta will be the covariance of the factor with the underlying asset. Is this correct?
Close, it's the covariance divided by the variance of the factor.
\begin{equation}
\beta_{f,a} = \frac{\sigma_{f,a}}{\sigma^2_f}
\end{equation}
> Also how is the return attributable to a specific factor cal... |
I am studying Arbitrage Pricing Theory (APT) and I have a question about calculating factor exposures.
Assume:
\begin{equation}
r = \beta_1r_1 + \beta_2r_2 + ... + \beta_kr_k + r_e
\end{equation}
Where:
$\beta_i$ is the exposure of the asset to a factor
$r$ is the return attributable to a factor
I ... |
I have been asked to perform a factor analysis on a given portfolio, assume it's a Swiss portfolio in CHF.
**First step**, I chose which factors I would like to see in my analysis.
The first factors I would add are components of the portfolio (and used the hedged performance)
- Performance of a global equity ... |
What are the steps to perform properly a risk factor analysis on a portfolio? |
One simple method, based on the principles of mean-variance optimization, is to set the weights proportional to the product of the inverse of the covariance matrix and a vector of standard deviations. This implicitly assumes that the normalized expected return of each stock is equal. If you wish, you can take only the ... |
Down Jones and UBS publish one of the most popular commodity index families, the Dow Jones-UBS Commodity Index and its subindices. They provide a detailed manual describing the composition of the index and its daily changes, available at http://www.djindexes.com/commodity/
I have tried to implement code that follows... |
Dow Jones and UBS publish one of the most popular commodity index families, the Dow Jones-UBS Commodity Index and its subindices. They provide a detailed manual describing the composition of the index and its daily changes, available at http://www.djindexes.com/commodity/
I have tried to implement code that follows ... |
First, we are few quants and academics to use the full toolkit of machine learning: stochastic algorithms, to optimal trading. Here are at least two papers:
- [Optimal split of orders across liquidity pools: a stochastic algorithm approach, Sophie Laruelle (PMA), Charles-Albert Lehalle, Gilles Pagès (PMA)][1]
- [... |
Suppose a fairly simple problem: You have to buy (resp sell) a given number of shares V in a fixed time horizon H with the aim to minimize your capital spent (resp maximize your revenue).
There are some research papers on the web that claim that using reiforcement learning algorithms can help make decision. See for ... |
I highly doubt there are useful studies around. Think about it, the answers of such data sets must be highly skewed simply because there are price takers in the market that are extremely secretive about profits and losses. You will only get one side of the story and it most likely skews the results by quite a bit.
... |
I don't have much to add, but wanted to address the "price of risk" question.
APT is kind of "economics"-free and tries to price assets without the utility maximization required in CAPM/ICAPM. Ross's APT observes that groups of assets move together (e.g., tech stocks) and that is the risk you're bearing because the ... |
Dow Jones and UBS publish one of the most popular commodity index families, the Dow Jones-UBS Commodity Index and its subindices. They provide a detailed manual describing the composition of the index and its daily changes, available at http://www.djindexes.com/commodity/
I have tried to implement code that follows ... |
Dow Jones and UBS publish one of the most popular commodity index families, the Dow Jones-UBS Commodity Index and its subindices. They provide a detailed manual describing the composition of the index and its daily changes, available at http://www.djindexes.com/commodity/
I have tried to implement code that follows ... |
First, we are few quants and academics to use the full toolkit of machine learning: stochastic algorithms, to optimal trading. Here are at least two papers:
- [Optimal split of orders across liquidity pools: a stochastic algorithm approach, Sophie Laruelle (PMA), Charles-Albert Lehalle, Gilles Pagès (PMA)][1]
- [... |
When Finite Element method provides considerable advantage over Finite Differences for option pricing? |
Trading Strategies and Portfolio Constructions based on Cross Sectional Regression?
Hi all,
I often see trading strategies and portfolio construction that are based on cross-sectional regression.
For example, I often see regressing some numbers against some factors.
I was wondering how cross-sectional regre... |
Trading Strategies and Portfolio Constructions based on Cross Sectional Regression? |
I often see trading strategies and portfolio construction that are based on cross-sectional regression. For example, I often see regressing some numbers against some factors.
I was wondering how cross-sectional regression is used in these scenarios? And how does a cross-sectional regression have forecasting power? ... |
When do Finite Element method provide considerable advantage over Finite Differences for option pricing? |
I am simulating a market for my trading system. I have no ask-bid prices in my dataset and use adjusted close for both buy and sell price. To account for this I plan to use a relative transaction cost.
The question is how large such a relative transaction cost should be to be realistic?
This is an academic appr... |
I am simulating a market for my trading system. I have no ask-bid prices in my dataset and use adjusted close for both buy and sell price. To account for this I plan to use a relative transaction cost.
The question is how large such a relative transaction cost should be to be realistic?
This is an academic appr... |
We're developing an HFT strategy for highly liquid futures traded at Eurex. We are planning colocate our server and to use data feed of QuantHouse and execution API of ObjectTrading. Backtesting is performed on tick data bought from QuantHouse, where timestamps have millisecond resolution (BTW, trades and quotes are so... |
I'm looking for a commercial delayed quote feed that will allow us to distribute delayed US stock market quotes to the public (ie. that will allow us to display US delayed quotes on the Internet). We are only interested in stocks listed on the NYSE, AMEX, and NASDAQ. The best that I could find were Xignite and BarChar... |
Commerical delayed stock quote feed that is redistributable? |
We're developing an HFT strategy for highly liquid futures traded at Eurex. We are planning to colocate our server and to use data feed of QuantHouse and execution API of ObjectTrading. Backtesting is performed on tick data bought from QuantHouse, where timestamps have millisecond resolution (BTW, trades and quotes are... |
What is the best/cheapest service to get real-time (as real-time as you can get) on stock options.
I'm looking for the fastest update on the ENTIRE market, with a few stocks prioritized, so I need the data to come in as fast as my internet connection will let it.
The API can be in any language, although I would prefe... |
dxFeed does offer level 2 historical data on demand. You can try it out for free. For example, to see how all market makers pulled out their quotes on ACN (Accenture) during May 6, 2010 Flash Crash go to the following URL: http://demo.dxfeed.com:7070/onDemand/data?categories=E-M&symbols=ACN&start=20100506-1447&end=2010... |
I defined such a model for stock price
(1)....
$$dS = \mu\ S\ dt + \sigma\ S\ dW + \rho\ S(dH - \mu) $$
, where H is a so call "resettable poisson process" defined as
(2)....
$$dH(t) = dN_{\lambda}(t) - H(t-)dN_{\eta}(t) $$
, and $\mu := \frac{\lambda}{\eta}$.
Is it possible to derive some analytic r... |
How to get an analytic result for option price based on this model? |
I defined such a model for stock price
(1)....
$$dS = \mu\ S\ dt + \sigma\ S\ dW + \rho\ S(dH - \mu) $$
, where $H$ is a so-called "resettable poisson process" defined as
(2)....
$$dH(t) = dN_{\lambda}(t) - H(t-)dN_{\eta}(t) $$
, and $\mu := \frac{\lambda}{\eta}$.
Is it possible to derive some analyt... |
You question is quite strange: so you do not want to use methods inspired by bioinfo and genetics (neural networks, GA, geometry of folding, etc) but methods that are used in these fields?
In terms of modeling, the problematics in genetics are mainly:
* tree or graph matching (to build metrics in the space of mol... |
You question is quite strange: so you do not want to use methods inspired by bioinfo and genetics (neural networks, GA, geometry of folding, etc) but methods that are used in these fields?
In terms of modeling, the problematics in genetics are mainly:
* tree or graph matching (to build metrics in the space of mol... |
I am hoping any answers can be threaded somewhere between "don't be naive" and starting a quasi-political flame.
Transparency is suppose to be good for markets and also a social good. The market reflecting the availability of all known information is a premise accepted by many. Why then is the disparity between ac... |
Why isn't all market data free? |
I have a pair trading strategy with positions that last 3-5 days and trades 2-3 times a month. By design, all the trades are profitable until the cointegration is broken.
**Should I calculate the Sharpe ratio with daily or monthly returns?** (annualizing afterwards in each case)
With monthly returns, most positio... |
Sharpe should only be computed from daily returns because finer granularity leads to a larger sample size. The larger sample makes the standard deviation metric more accurate. As a counter-example, how reliable would the Sharpe be using yearly returns? |
I have a pair trading strategy with positions that last 3-5 days and trades 2-3 times a month. By design, all the trades are profitable until the cointegration is broken.
**Should I calculate the Sharpe ratio with daily or monthly returns?** (annualizing afterwards in each case)
With monthly returns, most positio... |
I think Lehalle answer is very good but I would like to answer in a slightly different manner, maybe from an economical point of view.
I think the real question is *What are market data fees charged for?*.
Assume the whole data was available to anybody for free, then nobody would be willing to pay for it. There a... |
I have two backtesting algorithms:
1. One that uses bid and ask prices for signal generation. For example: Buy when $ask < threshold_1 $ and sell when $bid > threshold_2$. Bid and ask prices are calculated from the closing price using a 20 basis-point spread.
2. One that uses closing prices for signal generation.... |
How should I include the bid-ask spread as a transaction cost in a backtest? |
How should I compute the Sharpe Ratio for mid-frequency pair trading strategy? |
How to account for transaction costs in a simulated market environment? |
What is the best/cheapest service to get real-time (as real-time as you can get) on stock options?
I'm looking for the fastest update on the ENTIRE market, with a few stocks prioritized, so I need the data to come in as fast as my internet connection will let it.
The API can be in any language, although I would pre... |
What is the best live options data API? |
Is the binomial model wrong? |
What is a real world example of negative forward interest rate? |
We're developing an HFT strategy for highly liquid futures traded at Eurex. We are planning to colocate our server and to use data feed of QuantHouse and execution API of ObjectTrading. Backtesting is performed on tick data bought from QuantHouse, where timestamps have millisecond resolution (BTW, trades and quotes are... |
What latency should I use for backtesting a high-frequency strategy? |
Is there an open source alternative to Reuters Kondor+? |
How to perform risk factor calculation? |
What is the precision of standard deviation estimates with small samples? |
How to represent constraints for optimization problems in a data model? |
Here's an [approach][1] by Kritzman et al on Tactical Asset Allocation using Markov regime switching models.
[1]: http://papers.ssrn.com/sol3/papers.cfm?abstract_id=2066848 |
Looking at quant roles I keep seeing 'Flow Interest Rates' or 'Interest Rate Flow' - what does this refer to? |
What is "Flow Interest Rates"? |
Today I was speaking with someone involved in high frequency trading. They were mentioning hidden orders, queue positions (which can be lost in the orderbook based on certain order modifications), partial cancels, fills, uncrossing the book. What would be a good hopefully consolidated source to learn about all of this ... |
What is a good source to learn the different nuances of electronic orders and their nature? |
You question is quite strange: so you do not want to use methods inspired by bioinfo and genetics (neural networks, GA, geometry of folding, etc) but methods that are used in these fields?
In terms of modeling, the problematics in bioinfo and genetics are mainly:
* tree or graph matching (to build metrics in the ... |
What are the advantages/disadvantages of using the arithmetic Sharpe Ratio vs the geometric Sharpe Ratio? Is one more correct? Or is one better in certain circumstances? |
Here's an [approach][1] by Kritzman et al on Tactical Asset Allocation using Markov regime switching models. Here's another approach that uses [relative strength in TAA][2].
[1]: http://papers.ssrn.com/sol3/papers.cfm?abstract_id=2066848
[2]: http://papers.ssrn.com/sol3/papers.cfm?abstract_id=2025699 |
I am attempting to write a function that will calculate the annualized rate of return for individual dividends made by illiquid investments. These dividends are not at a static interval and the illiquid investment does not have a marketable value.
I have looked at using:
[(1 + YTD ROR)1/(#of days/365)] – ... |
Should I use an arithmetic or a geometric calculation for the Sharpe Ratio? |
I am new to this. I am confused on what consists of a tick data.
I have a trading platform in which I could collect data of exchange traded product like futures and stocks. While I am intending to use the platform for trading, I think I could collect the data directly from platform. The data consist of:
1. Every ... |
I have two backtesting algorithms:
1. One that uses bid and ask prices for signal generation. For example: Buy when $ask < threshold_1 $ and sell when $bid > threshold_2$. Bid and ask prices are calculated from the closing price using a 20 basis-point spread.
2. One that uses closing prices for signal generation.... |
I am simulating a market for my trading system. I have no ask-bid prices in my dataset and use adjusted close for both buy and sell price. To account for this I plan to use a relative transaction cost.
The question is how large such a relative transaction cost should be to be realistic?
- I trade stocks only fr... |
I am attempting to write a function that will calculate the annualized rate of return for individual dividends made by illiquid investments. These dividends are paid at varying intervals and the illiquid investment does not have an observable market price.
I have looked at using:
[(1 + YTD ROR)1/(#of days... |
How to annualize dividends paid at varying intervals? |
Let's say we have an equity liquidity-providing model that was fitted on 1 minute bar periods. The model forecasts the 1-min next period return given the activity of the previous bars. Now, when we move to trading strategy implementation the forecasted returns can be calculated at any time, say once every second. This ... |
Let's say we have an equity liquidity-providing model that was fitted on 1 minute bar periods. The model forecasts the 1-min next period return given the activity of the previous bars. Now, when we move to trading strategy implementation the forecasted returns can be calculated at any time, say once every second. This ... |
Let's say we have an equity liquidity-providing model that was fitted on 1 minute bar periods. The model forecasts the 1-min next period return given the activity of the previous bars. Now, when we move to trading strategy implementation the forecasted returns can be calculated at any time, say once every second. This ... |
Let's say we have an equity liquidity-providing model that was fitted on 1 minute bar periods. The model forecasts the 1-min next period return given the activity of the previous bars. Now, when we move to trading strategy implementation the forecasted returns can be calculated at any time, say once every second. This ... |
The answer depends on the reasoning behind your forecast. Is this a mean-reversion signal? If so, perhaps the presence of a short signal shortly after a long signal indicates that the long signal was very profitable, and you should take profits immediately. Is it a momentum signal? If so, then perhaps the momentum o... |
http://lobster.wiwi.hu-berlin.de/forum/viewtopic.php?f=4&t=30
R code, pictures and discussion, it's easy to modify it |
What are the best sources of quantitative finance research in equities?
I will list a couple and note an asterisk if the research is available by request (i.e. non-clients) or online:
1. BAC-Merrill Lynch - Savita Subramanian
2. Deutsche Bank - Yin Luo*
3. Credit Suisse - Pankaj Patel
4. Barclay's - Matt... |
If two time series follow GARCH process, and the third is linear combination of them is it also GARCH process ?
I think that is generally quite interesting question, because there are many time series which are created as averages of others. |
If two time series follow GARCH process, and the third is linear combination of them is it also follow GARCH process? |
Is there a way to determine a government bill's or bond's maturity date by looking at its CUSIP? For example, the CUSIP for US T-Bills with a maturity of 12/1/11 is 9127953V1. As you probably know, the first six characters of a CUSIP represent the item in question (e.g. US TBills); the last digit is an error correction... |
How do I determine maturity date from a CUSIP? [US T-Bills] |
I am new to this. I trained and tested my data using SVM in Matlab with the autoscale option true => the data would be normalized with unit SD. Let's say the training data have the price around 200.
During real time, let's say the price is around 300. I am wondering what is the practise in obtaining the mean and st... |
I am new to this. I trained and tested my data using SVM in Matlab with the autoscale option true => the data would be normalized with unit SD. Let's say the training data have the price around 200.
During real time, let's say the price is around 300. I am wondering what is the practise in obtaining the mean and st... |
If two time series follow a GARCH process, and a third is a linear combination of them, is the third also GARCH process? |
Is a linear combination of GARCH processes also a GARCH process? |
I'm attempting to construct a spot rate and forward rate curve from the 2011 daily treasury yield curve rates provided by the US Treasury. All US Treasury securities (1m, 3m, 6m, 1y, 2y, 3y, 5y, 7y, 10y, 20y, 30y) are being taken into consideration.
Using the bootstrapping process, step 1 is to obtain all of the sp... |
I am thinking about the time-scaling of **Cornish-Fisher VaR** (see e.g. page 130 in http://cran.r-project.org/web/packages/PerformanceAnalytics/PerformanceAnalytics.pdf
for the formula).
It involves the **skewness** and the **excess-kurtosis** of returns. The formula is clear and well studied (also criticize) in ... |
How does Cornish-Fisher VaR (aka modified VaR) scale with time? |
I am thinking about the time-scaling of **Cornish-Fisher VaR** (see e.g. page 130 [here][1] for the formula).
It involves the **skewness** and the **excess-kurtosis** of returns. The formula is clear and well studied (and criticized) in various papers for a single time period (e.g. daily returns and a VaR with one-... |
Skewness decays with time, but the rate of that skewness decay will vary based on the instruments and how they are traded, so a simple estimator such as the square root of time rule is not appropriate.
I typically recommend that to scale VaR or ES is makes more sense to *lower* your confidence level (raise the alpha... |
Skewness decays with time, but the rate of that skewness decay will vary based on the instruments and how they are traded, so a simple estimator such as the square root of time rule is not appropriate.
I typically recommend that to scale VaR or ES it makes more sense to *lower* your confidence level (raise the alpha... |
Skewness decays with time, but the rate of that skewness decay will vary based on the instruments and how they are traded, so a simple estimator such as the square root of time rule is not appropriate.
I typically recommend that to scale VaR or ES it makes more sense to *lower* your confidence level (raise the alpha... |
Could someone kindly provide some idea on how i can go about solving the following Quadratic Programming Problem:
Min[X’VX+X’GX]
In this case, X is a list of coefficient to be solved for, V is a square matrix of Price returns, and G is a square matrix of Income returns.
Also, in this case, both V and G should ... |
Why do some people claim the delta of an ATM call option is 0.5? |
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