Some highly ranked and widely followed systems are presently or recently experiencing very significant drawdowns in dollar terms and percentage wise. They may be open position or closed position drawdowns. The question is:
How many system followers are bailing out because of liquidity issues verses personal risk tolerance (psychological risk aversion)?
It may be impossible to get a quantitative answer to the above question.
Can I handle a big drawdown when it comes from a system that I have a lot of confidence or faith in?
A low starting capital requirement makes it possible to have a higher percent return rate. Is the C2 Monte Carlo analysis actually representative of the long-term system performance and potential risk?
Hello.
I think than Montecarlo could not be representative in too much cases. For example, a lot of strategies sell options (having huge risk / profit ratio) and track record can be god, because the black swan hasn´t become still, but it will come anytime.
Other example could be strategies shorting VXX. This ETF exist since 2009 I think. It means than there aren´t data to test this strategies in a bear market.
Of course over strategies with small track record isn´t applicable.
For having a better risk measure, I only would have in account TOS strategies, and also I would try to understand what´s the edge than developer exploit seeing strategy trades detail.
If an strategy works over a real edge with limited risk, then Montecarlo will be closer to reality.
Hello AndresPadrones,
Thanks for your well thought reply. I agree with you about black swan events and short track records causing problems with risk analysis and drawdown management.
A trading system with a 72% win rate can have 11 losing trades in a row. This is found using a Monte Carlo simulation on a long track record of trades (1000 trades in this case). If a trading system starts running live during favorable market conditions it might me operating near the beginning of a winning streak that could last up to 18 profitable trades in a row.
This does not imply anything about the accuracy of the Monte Carlo simulation on C2 except that the smaller the sample size the larger the error; conversely, the larger the sample size the smaller the error.
Thanks for your reply…
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