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Infantino’s PCA Model, 2010

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Infantino’s PCA Model, 2010

This model, from a large group of stocks e.g., S&P 500, computes, using ​Principal Component Analysis, the common factors that drive stock returns and filters out noises. We can then estimate the short term expected returns for each individual stock, hence a trading decision.

Moreover, the model proposes a way to use intraday volatility to estimate which of the two regimes we are in: mean-reversion or momentum.

Combining the estimated expected returns with the regime indicator, we do mean-reversion when the intraday volatility is small, and trend following when the intraday volatility is big.

References

​Developing high-frequency equities trading models

Code

http://redmine.numericalmethod.com/projects/public/repository/svn-algoquant/show/core/src/main/java/com/numericalmethod/algoquant/model/infantino2010

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