An extract from my book, Quantitative Research and Trading, to be published in 2017.

Home Archive by Category "Statistical Arbitrage"

JonathanCointegration, Correlation, Dickey-Fuller, Pairs Trading, Phillips-Perron, Spread Trading, Statistical ArbitrageNo commentsCointegration, CVX, Dickey-Fuller, Oil Stocks, Pairs Trading, Phillips-Perron, Statistical Arbitrage, XOM

An extract from my book, Quantitative Research and Trading, to be published in 2017.

JonathanCopulas, Correlation, Mathematica, Mean Reversion, Pairs Trading, Statistical Arbitrage1 commentCopulas, Nasdaq, Pairs Trading, S&P 500, Statistical Arbitrage

Introduction In a previous post, Copulas in Risk Management, I covered in detail the theory and applications of copulas in the area of risk management, pointing out the potential benefits of the approach and how it could be used to improve estimates of Value-at-Risk by incorporating important empirical features of asset processes, such as asymmetric…

JonathanCointegration, ETFs, Johansen, Long/Short, Portfolio Management, Statistical ArbitrageCointegration, ETF, Long/Short, Portfolio Management, Statistical Arbitrage

Recently I have been working on the problem of how to construct large portfolios of cointegrated securities. My focus has been on ETFs rather that stocks, although in principle the methodology applies equally well to either, of course. My preference for ETFs is due primarily to the fact that it is easier to achieve a…

JonathanCointegration, Kalman Filter, Pairs Trading, Statistical ArbitrageCointegration, Kalman Filter, Statistical Arbitrage

I tend not to get involved in Q&A with readers of my blog, or with investors. I am at a point in my life where I spend my time mostly doing what I want to do, rather than what other people would like me to do. And since I enjoy doing research and trading,…

I was asked by a reader if I could illustrate the application of the Kalman Filter technique described in my previous post with an example. Let’s take the ETF pair AGG IEF, using daily data from Jan 2006 to Feb 2015 to estimate the model. As you can see from the chart in Fig. 1, the…

JonathanKalman Filter, Matlab, Pairs Trading, Statistical ArbitrageKalman Filter, Pairs Trading, Statistical Arbitrage

One of the challenges with the cointegration approach to statistical arbitrage which I discussed in my previous post, is that cointegration relationships are seldom static: they change quite frequently and often break down completely. Back in 2009 I began experimenting with a more dynamic approach to pairs trading, based on the Kalman Filter. In…

JonathanCointegration, Econometrics, Johansen, Matlab, Mean Reversion, Pairs Trading, Statistical Arbitrage, Strategy Development, Systematic StrategiesCointegration, Statistical Arbitrage, Stocks

In his latest book (Algorithmic Trading: Winning Strategies and their Rationale, Wiley, 2013) Ernie Chan does an excellent job of setting out the procedures for developing statistical arbitrage strategies using cointegration. In such mean-reverting strategies, long positions are taken in under-performing stocks and short positions in stocks that have recently outperformed. I will leave a…

JonathanCointegration, Correlation, Portfolio Management, Statistical ArbitrageCointegration, Correlation, Equity Portfolios

The use of correlations is widespread in investment management theory and practice, from the construction of portfolios to the design of hedge trades to statistical arbitrage strategies. A common difficulty encountered in all of these applications is the variation in correlation: assets that at one time appear to be suitably uncorrelated for hedging purposes, may…

JonathanForecasting, Fourier Transforms, High Frequency Finance, Pairs Trading, Principal Components Analysis, Signal Processing, Statistical ArbitrageFourier Transforms, High Frequency Trading, Pairs Trading, Principal Components Analysis, Signal Processing, Statistical Arbitrage

One of the questions of interest is the optimal sampling frequency to use for extracting the alpha signal from an alpha generation function. We can use Fourier transforms to help identify the cyclical behavior of the strategy alpha and hence determine the best time-frames for sampling and trading. Typically, these spectral analysis techniques will highlight…

JonathanARMA, Econometrics, ETFs, Markov Model, Mean Reversion, Pairs Trading, Regime Switching, Statistical ArbitrageETFs, Kalman Filter, Markov Model, Pairs Trading, Regime Switching, Statistical Arbitrage

In the previous post I outlined some of the available techniques used for modeling market states. The following is an illustration of how these techniques can be applied in practice. You can download this post in pdf format here. The chart below shows the daily compounded returns for a single pair in an ETF statistical arbitrage…

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