- Joined
- May 21, 2008

- Posts
- 20

- Reactions
- 0

I've recently read the book by Van Tharp - Definitive_Guide_to_Position_Sizing

and i think it's a great read on the topic of determining how to best select position sizes for your trades.

I have a question however regarding the system quality number Van Tharp uses to determine if a strategy is good or not. Basically it is a creative way of working out whether a strategy will perform well long term, based on x amounts of trades. The premise behind it is that it relates everything back to how much you are risking on each trade, in terms of "R" multiples (where "R" is the amount risked). You determine your average R profit over all trades, and also the std deviation of these trades. This is then used along with the number of trades to work out your SQN :

SQN = average of trades in terms of R multiples / stddev of r multiple trades * sqrt(number of trades).

From Van Tharp, if your SQN > 1.7 you have a system that "statistically" should generate profits.

I have thought about this topic for quite some time, and really like how he ties in the statistics into this, as I have tried to do in the past.

In his book he infers a problem with the SQN though, for when you have samples over 100. The problem is that it inflates the SQN result, so one way he suggests to cope with the problem is to just set the trades = 100 when it's greater than 100.

My problem, is that I have a strategy, tested over a number of different FOREX pairs and over 3 years of data, and I think the equity curve is excellent.

There's about 3000 trades which is an excellent sample size.

When I plug the numbers into the SQN formula though (limiting to 100 trades) the result is no good. If I use the 3000 trades, the result is TOO good.

My question overall is, what do I do in this situation when I have 3000 trades and want to work out what the SQN is.

My numbers work out to be :

avg std dev #trades sqn

0.26 2.57 100 1.01

0.26 2.57 3149 5.69

I've attached the equity curve also.

any ideas appreciated.

thanks.