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This is the whole problem with the FF3 model, and indeed the very reason it was ever concocted in the first place! CAPM 101 argues that the cost of equity is constant riskless plus market beta. Except this doesn't work, because there are clear value and size; or value, size, and momentum effects also in operation. In statistical parlance, the null ...


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Yes, matching by strike, expiry and valuation date makes total sense. My guess is that you're only getting valuations for options that have valuations, ie options that have been written. Or at least against which the dealers have bothered to offer quotes. In which case, I suspect the mismatch you're getting is lots of calls with high strikes that have no ...


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I don't know the R-code; but I can maybe cut through a lot of the academic bull=plop in the paper referenced. A decade ago, I used to work on the sell-side, and used to produce a "Correlation of Everything to Everything Else" series (of cross-asset-class correlations) that was a pretty good proxy for PCA-domination and risk-on, risk-off mono-risk as was. ...


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You can find a python implementation here https://github.com/tzhangwps/Turbulence-Suite The author refers to the absorption ratio as "systemic risk indicator" but the calculation is the same.


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Please take a look at the TA-lib documentation on momentum indicators. While the example for MACD contains 12 and 26: macd, macdsignal, macdhist = MACD(close, fastperiod=12, slowperiod=26, signalperiod=9) you are free to set them to other numbers. There are also examples for MACD that use a context at this source code browser. One function uses talib....


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The two types of backtesters have slightly different purposes. The vectorised backtest is a rather crude way to quickly test a strategy. You do it by multiplying the signal vector with the returns vector and the result is the equity curve. The event-driven backtester is a more well thought out simulation. By making use of an event driven backtester we can ...


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You don't need an event-driven backtester. To establish some convention, a function or method that takes a vector as an argument (e.g. a MATLAB function, statsmodels API methods) is sometimes interchangeably and confusingly referred to as a vectorized function. This doesn't necessarily mean that it uses SIMD vectorization, although quite often it is ...


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Assuming we are talking about Pearson correlation, then we may apply the triangle inequality. Let $\rho(X,Y)$ denote the correlation between $X$ and $Y$. Then, $(1-\rho(X,Z))^{1/2}\le (1-\rho(X,Y))^{1/2} + (1-\rho(Y,Z))^{1/2}$


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