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I'm not sure I'm understanding exactly what you mean. When you mention the 'allocation % in your factors', are you speaking of the entries of the cointegration vector, which act as the weights of each underlying stock in the basket? If so, as of now, they would indeed be fixed. If they were...

I've considered using a rolling window, but it seems that one must be careful about recalibrating the cointegration vector too often or else the transaction costs become prohibitive. I figured I'd first try to see if there were any other techniques available to stabilize the spread aside from...

the latter - I have, for example, a strategy that was profitable in-sample, but fails out-of-sample. by 'fails', I mean that the amplitude of the spread changes drastically out-of-sample, the spread begins trending out-of-sample, or a combination of both. these changes to the spread result from...

hypothetically, the model trades 'at the close' because I'm only using daily close prices in my backtesting. in the future, my aim is focus on intraday price data. for example, 1-minute bars. the model would then be set up to look for trades 'at the close' of each minute. the spread of each...

anyone else struggling with cointegration vectors that break down quickly in out-of-sample backtests? I'm currently backtesting a stat arb strategy - basket trading ETF's and some of their underlyings. it's based on a model that only trades at the close of each trading day. in every one of...

anyone else struggling with cointegration vectors that break down quickly in out-of-sample backtests? I'm currently backtesting a stat arb strategy - basket trading ETF's and some of their underlyings. it's based on a model that only trades at the close of each trading day. in every one of...