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Quantitative trading strategies lars kestner pdf


quantitative trading strategies lars kestner pdf

I are very much aligned here. Now, assuming that Q actually wants algos that are durable and robust under different market conditions in future, is there anything that Q can do to improve the chances of success in future, rather than just simply running a live test for 6 months? The astute reader has no doubt already figured out where this is leading. Either it can be done as some sort of conventional volatility-related measure, of which there are many, such as for example Standard Deviations. Of course this is a Monte Carlo (MC) simulation technique, and it only takes a matter of seconds or maybe a minute or so on. 1 rebalancing : Some algos are reasonably sensitive to whether rebalancing is done daily, weekly, monthly, or at some other interval(s). However 6 months probably represents about the best workable compromise between the two sets of conflicting perspectives a) b). After all, if people can wait for 6 months to see their "final results then a few more minutes of calculation time after that should be easy for everyone. The latter choice makes more sense to me, as it highlights the combination of reward AND risk together. It can be assumed that this (generally quite large) set of actual trade results are reasonably representative of the algo in general and are in some sense "typical" of what the algo will probably do in future. 3 application of Algos in Q : This one is especially for @Dan others in Q, as well as the general Forum readers. For anyone to whom this is not intuitively obvious, it is easy to prove.

quantitative trading strategies lars kestner pdf

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I ask Q please to give this part very careful thought. Assumptions i) ii) may turn out to be wrong, but they are about as good as anyone can do in advance and are consistent with statistical theory as well as common sense. However if Q is going to have a "ranking of winners" (which some participants like then how will the 1) Return and 2) Volatility (or ratio) parts be combined into a single final score number? Now, when Q tests an algo for 6 months, a lot of trades are generated. The big advantage of running a MC simulation using the results from an actual 6 month period of trading is not just that it gives a "best estimate" of the likely results from the next (i.e. However even if the trade distribution remains the same, the specific order of the trade results will not be, as market history is unlikely to repeat itself. In my opinion, 6 months is actually WAY too short unless some other measures are taken. I have to wonder why not, when it is so easy to implement?

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