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Per Trade P&L vs Daily Returns for Risk assessment and Monte Carlo


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Per Trade P&L vs Daily Returns for Risk assessment and Monte Carlo

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seoul, Korea
 
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To use per Trade P/L or daily returns data for portfolio / risk assessment and Monte Carlo analysis, that is the question. Monte Carlo and other analysis for Risk of Ruin, profitability, max DD and other confidence intervals are a critical factor in trading strategy analysis albeit for algorithmic or manual traders. I think at futures.io (formerly BMT) we can take this as a given. However if you consider most of the monte carlo analysis , and risk assessments done here on futures.io (formerly BMT) takes in per trade P/L. A majority of financial literature as well as practice use daily returns instead of individual trade P/Ls.

My question is, which one is better? Also what are the pro's and cons. Especially as retail vs professional level risk analysis and portfolio simulations go.

I am personally building my own risk assessment and monte carlo simulator in R and I need feedback. A majority of the consensus in the R community, as well as talking with risk managers at institutions, and academic literature is that percent daily returns is the defacto standard of reporting for usage to quantify strategy performance and risk. But even if you consider a "commercial product" like adaptrade market analyzer which I have used, it also takes per trade stats. I put quotes because most institutions have custom in house software for risk management and assessment.

My thoughts with specific focus on monte carlo for risk analysis. For Closed Trade P/L, its very simple to calculate, every trade is independent and identifiable, and most of the retail platforms spit out trade reports with this information. However because of this closed end trade to PL relationship, we are assuming that hypothetically that trade would have the same duration and P/L given any market condition/hypothetical scrambling.

For daily % returns, a strategy equity curve can be treated as any other asset and analyzed as such, its much more granular as any specific daily return is not associated with any specific trade, more data points (assuming you trade less than once per day, which I usually do), and the results can easily be scaled to any dollar amount (which probably will not matter to us since most of us do not have billions). However because the daily returns are independent of any particular trade, we have no way of knowing if we would be in a position on that day or not. Or we could have random days were we receive returns (are in a trade) but is shorter than our actual average holding period. For example: our holding period is 10 days. We randomly receive returns for 2 random days, which technically would not be possible with our system.


Anyone have any thoughts? Would you consider using daily returns instead of Closed P/L? or vice versa?

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