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6

Validating tops against the consolidated is a good method. Obviously the time stamps won't match up, but the event stream should. Bear in mind that this won't tell you much about whether you're getting the inner dynamics of the book correct (for example, did the newly inserted order go into the right spot within a given price level). You should build ...


5

I would add the Monte Carlo position permutation test to your list (see here for more details and book). The null in White's RC is that the system's returns are zero, but in the position permutation test the null is that the system's positioning (long, short or out of the market) is no better than random. Incidentally, there is an R package, ttrTests, which ...


3

Here is a possible explanation. Consider $X_t \sim N(0,1)$ and $Y_t \sim N(1,1)$. Then $(X_t)_0^n$ and $(Y_t)_0^n$ are realizations from stationary time series and I would expect the null hypothesis of stationarity not to be rejected (compatibly with the size of your test). Instead, the sample $(Z_t)_1^{2n} = (X_1, \dots, X_n, Y_1, \dots, Y_n)$ is drawn from ...


3

To put your above mentioned points into perspective you should definitely consider this seminal paper from Attilio Meucci which develops a general framework for trading systems: ‘The Prayer’ Ten-Step Checklist for Advanced Risk and Portfolio Management From the abstract: "We present “The Prayer”, a recipe of ten sequential steps for all portfolio ...


2

In terms of technology, I would suggest R. In terms of specific actions, you need to decide what to do when the trigger event occurs and you need to decide how to close the positions. Given that, you can then determine your profit and loss on the strategy over the data period. You can use the random portfolio idea by running your strategy a number of ...



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