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Technically, there is a sweet spot between smaller timeframe trading (scalping) and larger timeframe trading (investing). The exact location of that sweet spot depends on variable costs such as slippage and commissions. We have already discussed this subject in the thread on "Risk of Ruin".
- System with 2,000 trades, and net expectancy after commission and slippage of $5 per trade.
- System with 200 trades, and net expectancy after commission and slippage of $50 per trade.
The question is not obvious to answer, I need to make a lot of assumptions first.
(1) First of all the model relies on fixed-fractional betting. If you say I have a system doing 2,000 trades with an expectancy of $5, you assume that all those trades …
The main idea was to compare risk-adjusted returns. Usually the shorter timeframe system (intraday trading) comes out winner compared to the longer timeframe system (swing trading), so I am not entirely with you.
The reason is that if you trade a longer timeframe the variance of returns is much larger compared to the variance of returns of the system that trades faster. In the example discussed in the thread on "Risk of Ruin", the higher timeframe system has a risk of ruin about 1,350 times higher than the smaller timeframe system.
As the fast trading system has a lower variance of returns and thus a lower risk of ruin, you may increase leverage and trade a larger number of contracts.
However, intraday trading also has its downsides. Commissions and slippage are much higher in relation to the average return per trade. Also intraday trading takes a higher toll on the health of the trader, unless the trades are fully automated.
When you develop a portfolio strategy for a basket of futures, are you using the exact same strategy for each futures instrument? If so, are you using the same parameters for each instrument, or do you "tune" for each?
What do you think makes it the Holy Grail? The diversification aspect?
Presently spending my time on a single strategy with two parameters, a moving average length and an oscillator length. These same parameters have been tested against dozens and dozens of uncorrelated instruments and have produced good results in the portfolio so far.
In this case, I do use NT to optimize the entire basket/group at one time, for the best parameter across say 20 stocks over say 10 years of data.
Thanks for sharing. I wonder how much of your performance is attributable to entries and exits being of high quality, as opposed to so-so entries and exits, but with superior diversification. I personally have found that diversification plays a major role in overall success.
It's all about diversification. Any one strategy on one instrument is nothing special, but put a dozen of them in a basket and the equity curve and drawdowns can become magical.
I've heard FT71, on multiple occasion, talk about how it's almost totally about the exit, and that one can make money with a random entry method; and that he can prove it.
What would you say about that statement?
I think THAT would be an excellent webinar..... and thusly, shatter the academic world, and have Eugene Fama running for the hills.
I would agree in principle with that assertion. Van Tharp and hedge fund manager Tom Basso did the same thing a bunch of years ago. I wrote a few articles for Active Trader Magazine a few years back looking into that - random entries, and random exits.
I think it is timeframe dependent though. A scalping strategy will probably never work with random entries. A long term swing strategy very well might.
I read an academic study once in college that showed how there was more skew and kurtosis in longer timeframes than shorter ones (in forex). This could also be another reason to add to the thorough ones you listed previously.