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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 ...

5

You can view the price of an option as the cost to dynamically replicate it. The more volatility, the more costs you will have trading the underlying to keep your delta equal to 0 (I'm assuming you sold the option, hence a negative gamma position). So, if at any spot, any date your local vol is above 0.194, rebalancing the portfolio will be constantly more ...

3

It is unlikely with so few observations that you will get statistical significance. Also you should benchmark your model against a "naive" model. If your conjecture is that high VIX implies high expected returns and you want to use that for trading, I suggest that you run a Goyal and Welch (2008) type of model. They use regressions (you can easily use ...

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 ...

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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 ...

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There are different methodologies to detect a change in the market efficiency, both in the market and firm-specific cases. In the FIRM-SPECIFIC case, the most common procedure is the event study methodology; you can find how to construct an event-study case explained in Kothari & Warner (2006), who collected all the event study methodology implemented ...

1

We assume weak stationarity definition. Price level is non-stationary. Trend-stationarity is like following a trend, not working on this time scale. So need to use returns. Returns on interval <15min are dominated by bid-ask bounce. Useless, trap. So test should be using >15min returns on window interval W < (hold time / N), N = 2-4. Then Unit root ...

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Don't need to re-invent the wheel, I suggest you to isolate the time-consuming part of your algorithm in a c++ dll and to call it directly from Ninja trader or whatever platforms. Regarding the data here three advices: Identify exactly the data you need (ex: if your strategy is based on bar data, you may not need higher/lower prices...) Always keep a ...

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The rating downgrade/upgrade effect is definitely more extreme during financial crisis, because of several effects (among all, flight-to quality, flight-to-liquidity and news effects itself), as shown by: Arezki, Rabah, Bertrand Candelon, and Amadou Nicolas Racine Sy. "Sovereign rating news and financial markets spillovers: Evidence from the European debt ...

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So you are asking whether the function Box.test requires standardized or raw residuals as input? I do not know this function but as you mention that the results change based on your input it should be such that the function requires standardized values. In case a standardization is implemented directly the output should not differ because you either plug-in ...

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