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Aug 16, 2016 at 16:20 answer added Peter Cotton timeline score: 0
Aug 17, 2011 at 18:53 answer added G__ timeline score: 0
Aug 16, 2011 at 13:30 history edited Tal Fishman CC BY-SA 3.0
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Aug 15, 2011 at 22:24 history tweeted twitter.com/#!/StackQuant/status/103230698718105600
Aug 15, 2011 at 16:16 answer added babelproofreader timeline score: 1
Aug 15, 2011 at 14:37 answer added Tal Fishman timeline score: 7
Aug 15, 2011 at 4:31 comment added JeremyKun So yes, maybe I want the data to be so simplistic that any reasonable strategy should beat it, but even so I want to model a real market as closely as possible...
Aug 15, 2011 at 4:30 comment added JeremyKun Beating a fake market is a problem, hence my interest in existing research. You're right, I should and do test on live data from a broker as well. The problem is that live data takes time, and I can't control it. In addition to live testing, I want to have a suite of unit tests to run my strategy against, to serve as a sanity check that even in the ideal cases my strategy makes profit. Ideally, I would check a large number of cases with varying parameters. I can't guarantee that all such movements show up in live data, and historical data is unclean in addition to having the same problem.
Aug 15, 2011 at 1:46 comment added strimp099 You could use a stochastic process with a drift and volatility term. Perhaps an interest rate model such as Vasicek that has mean reversion, ES-VJ++ which is Vasicek with jumps, Hull-White, Black-Derman-Toy, etc. etc. The problem of course is that your trading algorithms (should) quickly identify the Guassian (or otherwise) assumptions from the model and beat the "market". Why not try sim trading with a broker that will give you live data? I have not seen writings on synthetic trading data.
Aug 15, 2011 at 0:12 history asked JeremyKun CC BY-SA 3.0