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The term *high frequency trading* has been used quite often recently to refer to trading using real-time tick data (or data aggregated to few seconds) and having an intra-day holding period.
How are medium and low frequency trading strategies defined? Do they use real-time data, or do they use end-of-day (OHLC, volu... |
What is a medium to low frequency trading strategy and why is it less hyped? |
> Which is/are the most extensible?
RapidMiner and R. Besides, RapidMiner offers extensions for seamlessly integrating R and Weka, hence can combine the power and extensibility of all three platforms within RapidMiner. And you can download RapidMiner and its extension for R and Weka for free.
> Which is the mo... |
What procedure do leveraged ETFs use to limit losses? |
In a covered call strategy, should I hold the call or sell/roll if the delta becomes too small? |
For most financial instruments we can go long or short and make a punt on the price, in the case of options we can bet on its derivations, theta and interest rates.
Is there an instrument or a strategy that can benefit from the change in trading volume, besides buying and selling the shares of an exchange?
|
I'm trying to get my head around pricing a CMS. Let's imagine the following deal: 6m LIBOR in one direction, 10y swap rate in the other. And I have some Discount curve, say from OIS.
Naively I would just price this as PV'ing the cash flows from the forward 6m LIBOR rates and PV'ing the cash flows from the forward 1... |
I'm trying to wrap my head around pricing a Constant Maturity Swap (CMS). Let's imagine the following deal: 6m LIBOR in one direction, 10y swap rate in the other. The discount curve is derived from OIS.
Naively I would just price this by taking the difference between the present value of cash flows from the forward ... |
What is the reason for the convexity adjustment when pricing a constant maturity swap (CMS)? |
This is a follow-up to my previous question regarding anyone whom wanted to ['donate' data][1].
So far no one has stepped up *(learning more about buying and selling data, I realize that I'm going to have to buy the data if I want to re-sell it, or give it away for that matter - re: licensing agreements?)*
So I'm... |
Which data service to buy for redistributable data? |
For most financial instruments we can go long or short and make a bet on the price. In the case of options we can bet on derivatives of price and other factors (e.g., interest rates).
Is there an instrument or a strategy that can benefit from changes in trading volume, besides buying and selling equity in an exchang... |
Are there financial instruments that make a bet on traded volume instead of price or its derivatives? |
Estimation of model-free implied volatility is highly dependent upon the extrapolation procedure for non-traded options at extreme out-of-the-money points.
[Jiang and Tian (2007)][1] propose that the slope at the last traded point from a cubic spline interpolation be used to extrapolate Black-Scholes implied volatil... |
How to extrapolate implied volatility for out of the money options? |
Estimation of model-free implied volatility is highly dependent upon the extrapolation procedure for non-traded options at extreme out-of-the-money points.
[Jiang and Tian (2007)][1] propose that the *slope* at the lowest/highest moneyness traded point from a cubic spline interpolation be used to extrapolate Black-S... |
When doing Cointegration tests should I use the adjusted close price or just close price for the time series?
The dividend of each stock is on different dates and can cause jumps in the data.
Thanks in advance! |
When doing cointegration tests should I use the adjusted close price or just close price for the time series?
The dividend of each stock is on different dates and can cause jumps in the data. |
Should cointegration be tested using close or adjusted close prices? |
It isn't clear from this post or your last post what data you want and what you want it for. The only thing you are going to get permission to distribute is the higher level data feeds like EOD data, or last sale (probably can't offer history).
Exchanges typically have this information available on their websites, f... |
I've skimmed through more than one ETF prospectus trying to find the procedure for clamping losses at the limits of an ETF, and so far, no help. Has anyone found a description of the "clamping" procedure?
For example, if the S&P drops 35% in one day, how will Direxion's BGU (3X Bull ETF) "clamp" the loss to that 9... |
There's no rule to answer this question for you. You need some combination of:
- Judgment: Are the parameters you're including reasonable?
- Sniff test: Is there theory to justify your parameter choices, or are you just hunting for chance associations?
- Hold-outs: You correctly mention that the problem is... |
There's no rule to answer this question for you. You need some combination of:
- Judgment: Are the parameters you're including reasonable?
- Sniff test: Is there theory to justify your parameter choices, or are you just hunting for chance associations?
- Hold-outs: You correctly mention that the problem is... |
What are the most common/popular exotics in the interest rate markets these days? |
What is the consensus on which risk measure to use in measuring portfolio risk? I am researching what is the best risk measure to use in a portfolio construction process for a long/short equity portfolio.
Since the late '90s thru today, it seems that VaR is the dominant risk measure but is losing ground.
[Artzner... |
cVaR vs. Var - appropriate choice of risk measurement in utility function? |
Imagine that you have the fastest connection to stock exchange (receive quotes 1 ms earlier than everyone else) - to both stocks and derivatives
How would you benefit from this?
Of course almost any strategy would work better on faster connection, but i'm looking for strategies that:
- will only work on faste... |
how to benefit from the fastest connection to stock exchange (suggest strategy)? |
At strikes distant from the forward value, pretending that options *have* some meaningful implied volatility gets kind of silly. Options really have prices (both bids and offers), and we all just translate that to volatility because doing so provides a convenient normalization.
Just to take one example, discrete pr... |
What is the consensus on which risk measure to use in measuring portfolio risk? I am researching what is the best risk measure to use in a portfolio construction process for a long/short equity portfolio.
Since the late '90s thru today, it seems that VaR is the dominant risk measure but is losing ground.
[Artzner... |
Which is a more appropriate choice of risk measurement in a utility function, CVaR or VaR? |
Imagine that you have the fastest connection to the exchange (receive quotes 1 ms earlier than everyone else) for both stocks and derivatives.
How would you benefit from this?
Of course almost any strategy would work better on a faster connection, but I'm looking for strategies that:
- will only work on the f... |
What strategy would benefit most from having the fastest connection to the exchange? |
What is the consensus on which risk measure to use in measuring portfolio risk? I am researching what is the best risk measure to use in a portfolio construction process for a long/short equity portfolio.
Since the late '90s thru today, it seems that VaR is the dominant risk measure but is losing ground.
[Artzner... |
What is the consensus on which risk measure to use in measuring portfolio risk? I am researching what is the best risk measure to use in a portfolio construction process for a long/short equity portfolio.
Since the late '90s thru today, it seems that VaR is the dominant risk measure but is losing ground.
[Artzner... |
If your problem is an equity portfolio without options, then I would vote for variance. This uses all the information rather than just looking at the tail. In 1999 the semi-variance became popular because it showed very small risk for telecom, media and tech stocks. They were just going up -- how is that risky?
E... |
I have a correlation matrix $A$ for a equity market that is not positive definite. Higham (2002) proposes the Alternating Projections Method minimising the weighted frobenius norm $||A-X||_W$ where $X$ is the resulting positive definite matrix.
How should one choose the weight matrix $W$?
The easy alternative is ... |
What weights should be used when find a positive definite correlation matrix? |
What is the consensus on which risk measure to use in measuring portfolio risk? I am researching what is the best risk measure to use in a portfolio construction process for a long/short option-free equity portfolio.
Since the late '90s thru today, it seems that VaR is the dominant risk measure but is losing ground.... |
When does an Exchange Traded Fund (ETF) take out expenses (for example 0,3% on a yearly basis)? Does it happen daily, or once yearly or according to some other scheme? Where does it take them from? |
When does an ETF take out expenses? |
- Market making (*to collect a liquidity rebate)*?
- Flash trading *(when the order is displayed to internal market
participants prior to being distributed to the wider market)?* ***1**
I think more generally strategies that implement pure latency arbitrage are related to *transaction market making (providing... |
Both for private projects, and for clients, I've been working on code a lot this year to evaluate automated trading strategies. This often ends up turning into the task of how to fairly compare apples and oranges. E.g. to use an FX example, some of the strategies just buy/sell 1 lot, in a single currency. Others are tr... |
- Market making (*to collect a liquidity rebate)*?
- Flash trading *(when the order is displayed to internal market
participants prior to being distributed to the wider market)?* ***1**
I think more generally strategies that implement pure latency arbitrage are related to *transaction market making (providing... |
- Market making (*to collect a liquidity rebate)*?
- Flash trading *(when the order is displayed to internal market
participants prior to being distributed to the wider market)?* ***1**
I think more generally strategies that implement pure latency arbitrage are related to *transaction market making (providing... |
I know two applications of local time in option pricing theory.
First, it allows a derivation of Dupire's formula on local volatility in a neat way (i.e. without resorting to differential operator theory which I'm not really acquainted with).
Second, it can be used to show that you can't perfectly replicate (f... |
I have a basic question about annualized Sharpe Ratio Calculation, say if I know the daily return of my portfolio, the thing I need to do is multiply the Sharpe Ratio by sqrt(252) to have it annualized. I don't know why is that, can any body explain? |
I found this Python example http://scikit-learn.sourceforge.net/auto_examples/applications/stock_market.html for "clustering". The code uses correlations of the difference in open and close prices as values for the affinity matrix. I prefer using the average return and standard deviation of return. This can be visualis... |
I found this Python example http://scikit-learn.sourceforge.net/auto_examples/applications/stock_market.html for "clustering". The code uses correlations of the difference in open and close prices as values for the affinity matrix. I prefer using the average return and standard deviation of return. This can be visualis... |
For example I want to construct 2 time series, one for ES and the other for NQ and test for cointegration.
ES one point equal to 50$.
NQ one point equal to 20$.
If I have the following data:
ES[0]=1300;ES[1]=1307;ES[2]=1314...
NQ[0]=2700;NQ[1]=2692;NQ[2]=2715...
How do I normalize this data for cointe... |
How to normalize Futures data(different leverage) for cointegration test? |
My goal is to find clusters hence the term clustering. In this case clusters of stocks. Affinity matrix will define the "closeness" of points.
I found this Python example http://scikit-learn.sourceforge.net/auto_examples/applications/stock_market.html for "clustering". The code uses correlations of the difference in... |
You should consider an unsupervised learning algorithm such as K-nearest neighbor ('KNN').
KNN will measure the distance amongst the observations in your feature space. You can and probably should consider alternative distance functions (besides euclidean distance) particularly if you are clustering on features such... |
You should consider an unsupervised learning algorithm such as K-nearest neighbor ('KNN').
KNN will measure the distance amongst the observations in your feature space. You can and probably should consider alternative distance functions (besides euclidean distance) particularly if you are clustering on features such... |
You should consider an unsupervised learning algorithm such as K-nearest neighbor ('KNN').
KNN will measure the distance amongst the observations with respect to clusters of observations in your feature space. You can and probably should consider alternative distance functions (besides euclidean distance) particular... |
You should consider an unsupervised learning algorithm such as K-nearest neighbor ('KNN').
KNN will measure the distance amongst the observations in your space. You can and probably should consider alternative distance functions (besides euclidean) particularly if you are clustering on features such as returns which... |
I need to calculate the skewness and kurtosis of 2 asset portfolio, can someone please help me with the formulas and definition of terms? Thank you.
I have been using the matrices method and I am not sure if that is correct. |
My goal is to find clusters hence the term [clustering][1]. In this case clusters of stocks. Affinity matrix will define the "closeness" of points. This [article][2] gives a bit more background.
I found this Python example http://scikit-learn.sourceforge.net/auto_examples/applications/stock_market.html for "clusteri... |
Where can the definition of a creation unit for a specific ETF be found? This information is needed for calculating the arbitrage possible between the ETF instrument itself and the creation unit constituent instruments.
ETF marketing material usually specifies what index or stocks it tracks, but it seems harder to f... |
Where are creation units for ETFs published? |
"Skewness" quantifies how asymetric a distribution is about the mean. "Kurtosis" quantifies how peaked or flat the distribution is.
Skewness is defined as:
E[ (X - mean)^3 ] = (Sum over (x_i - x_mean)^3 ) / N
and Kurtosis as:
E[ (X - mean)^4 ] = (Sum over (x_i - x_mean)^4 ) / N
where X is your d... |
Large institutions can swap baskets of underlying securities for ETF shares that can then be traded on an exchange as part of arbitrage between the price of the basket and the ETF share price. These baskets are called /creation units/. How often does the creation unit basket for a given ETF typically change? Hourly, da... |
How often do ETF creation units baskets change? |
"Skewness" quantifies how asymetric a distribution is about the mean. "Kurtosis" quantifies how peaked or flat the distribution is.
Skewness is defined as:
E[ (X - mean)^3 ] = (Sum over (x_i - x_mean)^3 ) / N
and Kurtosis as:
E[ (X - mean)^4 ] = (Sum over (x_i - x_mean)^4 ) / N
where X is your d... |
Where can the specification of a creation unit basket for an ETF be found? This information is needed for calculating the arbitrage possible between the ETF instrument itself and the creation unit basket constituent instruments.
ETF marketing material usually specifies what index or stocks it tracks, but it seems ha... |
Where are creation units baskets for ETFs published? |
Large institutions can swap baskets of underlying securities for ETF shares that can then be traded on an exchange as part of arbitrage between the price of the basket and the ETF share price. These baskets are called *creation units*. How often does the creation unit basket for a given ETF typically change? Hourly, da... |
My goal is to find clusters hence the term [clustering][1]. In this case clusters of stocks. Affinity matrix will define the "closeness" of points. This [article][2] gives a bit more background.
I found this Python [example][3] for "clustering" with related d[ocs][4]. The code uses correlations of the difference in... |
What are the most popular probability distributions in quantitative finance and what are their applications? |
I'm sure there is a simple answer to this but I haven't had any luck with searches. I'm just wondering when someone places a market order which order(s) from the limit order book are selected to fill that? Let's say the order book has the highest bid at 100 and the lowest ask at 101 and I place a limit order to buy a... |
How are limit orders selected from the order book? |
"Skewness" quantifies how asymetric a distribution is about the mean. "Kurtosis" quantifies how peaked or flat the distribution is.
Skewness is defined as:
$E[ (X - mean)^3 ] = \frac{(\sum (x_i - x_{mean})^3 )}{N}$
and Kurtosis as:
$E[ (X - mean)^4 ] = \frac{(\sum (x_i - x_{mean})^4 )}{N}$
where X is y... |
Say I have 6 possible investment options with the following probability of success and the corresponding returns:
| Investment | Probability of Success | Return |
| I1 | 0.5 | 2x |
| I2 | 0.3 | 6x |
| I3 | 0.1 ... |
How can I simulate portfolio risk (diversification) with a 'Wheel of Fortune' like investment options/returns? |
Both for private projects, and for clients, I've been working on code a lot this year to evaluate automated trading strategies. This often ends up turning into the task of how to fairly compare apples and oranges. E.g. to use an FX example, some of the strategies just buy/sell 1 lot, in a single currency. Others are tr... |
Quant Guy's answer is quite informative for your question already.
Just to add few other things: instead of figuring out the choice of features by your own brain, you could also use machine learning techniques to help in extracting the 'features' for your specific purpose, e.g. risk modeling or returns forecasting o... |
My goal is to find clusters hence the term [clustering][1]. In this case clusters of stocks. Affinity matrix will define the "closeness" of points. This [article][2] gives a bit more background.
I found this Python [example][3] for "clustering" with related d[ocs][4]. The code uses correlations of the difference in... |
My goal is to find clusters hence the term [clustering][1]. In this case clusters of stocks. The affinity matrix will define the "closeness" of points. This [article][2] gives a bit more background. The secondary goal is to investigate the "cohesion" within ETFs and between similar ETFs for the purpose of the arbitrage... |
Certain bank loans pay a spread above a floating-rate interest rate (typically LIBOR) subject to a floor. I would like to find the value of this floor to the investor. Assume for this example that the loan does not have any default (credit) risk.
As a first pass, the value of the floor could be approximated using ... |
How to value a floor when a loan is callable? |
You should consider an unsupervised learning algorithm such as K-nearest neighbor ('KNN').
KNN will measure the distance amongst the observations in your space. You can and probably should consider alternative distance functions (besides euclidean) particularly if you are clustering on features such as returns which... |
If you need a primer covering various domains of math then [Dan Stefanica's text][1] will do the job. The text covers multivariable calculus, lagrange multipliers, black scholes PDF, greeks & hedging, newton's method, bootstrapping, taylor series, numerical integration, and risk neutral valuation. It also includes a ma... |
I'm a university student and I'm quite interested in High Frequency Trading Algorithms. What courses should I take and what skills should I acquire so that I can work in this field?
So far, I've been developing web applications and Android apps as a software engineer. |
What skills and education are required for HFT? |
I only have a mean and standard deviation, what technique can I use to determine how similar the distributions these describe are? Assume that they values are built from very similar samples. I'm looking for a mechanism to detect when then distributions deviate from one another by some threshold. Access to historica... |
I'm trying to improve my methods for calculating real-time US Equity option portfolio risk.
My main problem is volatility "stability" across all strikes in an option series.
The current implementation is similar to the OCC Haircut calculations, where I calculate volatility at current market prices and then calc... |
I only have means and standard deviations of samples of two random variables. What technique can I use to determine how similar the distributions these describe are? Assume that the values are built from very similar samples. I'm looking for a mechanism to detect when the distributions deviate from one another by so... |
How can I compare distributions using only mean and standard deviation? |
My goal is to find [clusters][1] of stocks. The "affinity" matrix will define the "closeness" of points. This [article][2] gives a bit more background. The ultimate purpose is to investigate the "cohesion" within ETFs and between similar ETFs for arbitrage possibilities. Eventually if everything goes well this could le... |
How to cluster stocks and construct an affinity matrix? |
If you are looking for "accepted practice," then in my opinion you must read [Grinold and Kahn][1]. That book strongly advocates use of the [information ratio][2], the successor to the closely-related [Sharpe ratio][3]. See the wiki pages for lists of alternative ratios and performance evaluation measures, but none a... |
This question might be dumb, but anyone could explain the difference between stoxx and stoxxe?
Which is the right index for benchmarking European stocks?
Thanks. |
I was wondering if someone has an implementation of the Tian third moment-matching tree (<http://papers.ssrn.com/sol3/papers.cfm?abstract_id=1030143>) with
smoothing in code (e.g. c++, vba, c#, etc.)?
It would help hugely if the implementation also shows how to handle discrete dividends and calculate greeks (delta, v... |
I was wondering if someone has an implementation of the Tian third moment-matching tree (<http://papers.ssrn.com/sol3/papers.cfm?abstract_id=1030143>) with
smoothing in code (e.g. c++, vba, c#, etc.)?
It would help hugely if the implementation also shows how to handle discrete dividends and calculate greeks (delta, v... |
I have read the CBOE's white paper on the VIX and a lot of other things, but I need to honestly say, I don't really get it, or I am missing something important
In semi-layman's terms is the VIX simply the a measurement of the volume of protective options bought?
ie. individual contract volatility increases when t... |
I have read the CBOE's white paper on the VIX and a lot of other things, but I need to honestly say, I don't really get it, or I am missing something important
In semi-layman's terms is the VIX simply the a measurement of the volume of protective options bought?
ie. individual contract volatility increases when t... |
VIX is a measure of **implied volatility**, specifically, **model-free implied volatility**, a concept originally developed by [Demeterfi et. al. at Goldman Sachs in the 1990s][1]. The VIX is the square root of the market-implied variance swap rate, calculated based on the exchange-traded options portfolio typically u... |
I have read the CBOE's white paper on the VIX and a lot of other things, but I need to honestly say, I don't really get it, or I am missing something important.
In semi-layman's terms, is the VIX simply the a measurement of the volume of protective options bought?
That is, individual contract volatility increases... |
What does the VIX formula measure and how does it work? |
VIX is a measure of **implied volatility**, specifically, **model-free implied volatility**, a concept originally developed by [Demeterfi et. al. at Goldman Sachs in the 1990s][1]. One of my recent questions, [How to extrapolate implied volatility for out of the money options?][2], addressed some aspects of MFIV, and ... |
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