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Quantitative Trading Strategies. Statistical Arbitrage in the U.S. Equities Market. ETF approach: Using industries. A diverse set of ETFs can be used to explain the returns of a stock Multiple regression model will be of the form:. The PCA approach. - PowerPoint PPT Presentation
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Quantitative Trading Strategies
Statistical Arbitrage in the U.S. Equities Market
ETF approach: Using industriesA diverse set of ETFs can be used to explain
the returns of a stock Multiple regression model will be of the form:
The PCA approachPrinciple Component Analysis to extract
factors from the return dataEigenvectors are the principle components of
the data and its corresponding eigenvalues are its variance.
Each principle components are a linear combination of all the stocks in the data and can be regarded as an eigenportfolio
The returns of each eigenportfolio can be used in the multiple regression analysis
Differences between PCA and ETF approachesETF approach requires some prior
understanding of the economical situation to know the “appropriate” set of ETFs needed
PCA factor loadings is more intuitive than for ETF
ETF gives more weight to large capitalization companies, whereas PCA has no a priori capitalization bias
Trading SignalsUsing the OU parameters, we can obtain the mean and
variance of X and define the dimensionless variable:
Above equation is known as the s-score which measures the distance to equilibrium of the co-integrated residual in units of standard deviations. The signals are as follow:buy to open if si < −sbo
sell to open if si > +sso
close short position if si < +sbc
close long position si > −ssc
Results from using PCA approachThe stock MCK gives the best result. The
trading strategy performs well throughout the 3-year period with a profit of almost $754,000 at the end of the trading period.
The optimized trading levels sbo, sbo, sbc, ssc
obtained are 1, 0.25, 1, 0.25 respectively.
Results from using PCA approachSecond best performing stock is “IP” with an
Omega of 1.33. The P&L over the three year period is shown below.
A profit of almost $811,000 at the end of the trading period. The optimized trading levels are same as before.
Results from using ETF approachAmong the 100 stocks, NRG gives the best
results. The trading strategy performs well throughout the 3-year period with a profit of almost $1,730,000 at the end of the trading period.
The optimized trading levels sbo, sbo, sbc, ssc
obtained are 1, 0.25, 1, 0.25 respectively.
Results from using ETF approachSecond best performing stock is “ATI” with
an Omega of 1.47. The P&L over the three year period is shown below.
A profit of almost $1,590,000 at the end of the trading period. The optimized trading levels are same as before.Video of P&L using ETF Approach
Backtest: Bootstrapping
Backtest: Bootstrapping
Backtest: Outsample Test
New FindingsWe find that the optimized trading levels sbo,
sbo, sbc, ssc obtained are 1, 0.25, 1, 0.25 respectively as opposed to what is being proposed in the paper
For the optimized set of parameters we got very good profit in both the approaches (ranging above 80%)
Omega achieved from out-sample testing was not good enough to support the strategy
This is further cemented by the results from bootstrapping
Please run ‘main_ETF.m’ to see the results.
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