Here's one example of a terribly simple idea that guarantees great profits if implemented properly. We all know that trend following is profitable. We also know that by design you must return some of the profits when market becomes choppy. So why not implement a filter that detects when market is trending and only THEN run your TF strategy? Can you imagine anything simpler? Obviously, such a strategy would be a great winner and you could finally buy your island country. But, only when you actually attempt to detect market regime you find out that it's not nearly that simple. As soon as you detect that you're in the choppy market you already gave up some profits, and mysteriously market starts trending just when you've decided to stop trading so you miss some more profits.
I wanted to comment on this and just say -- in my vision of the legion, none of the active bots would be turned on and off, aside from strategy logic already programmed into the bot. For example filters or phantom trading -- but they would already be statistically measured in the backtesting phase, before they got inducted to the legion.
So it is not my position as the human to tinker with bots once they are in the legion - only to measure their ongoing performance stats. As a sidenote, I'm hoping that one day my skills would evolve to a point that I could actually program the bots to measure themselves and deactivate on their own. For example, after the testing/approval/induction phase, I as the human would set acceptable thresholds for each bot, perhaps in a .ini file. Then after each trade, the bot would calculate metrics and determine whether or not they had become "out-of-spec" for those thresholds and then act accordingly (note: I have not yet defined what "out-of-spec" means to me).
Why this example? Because I believe the algorithm (the bot manager) that will decide which of your strategies to trade will have all the same problem. You might say, I'll just replace the strategy that is losing money, but how much will you let it lose before you decide to replace it? What if it starts losing right away like Z's are doing in my demo? Should I replace them already or let them lose even more money? Some tough questions, right?
I think you just made that more complicated than it has to be. My plan was to simply design the bots and then establish acceptable performance boundaries. At some yet-to-be-defined interval, I would test the bots performance in-the-field, and if it showed that it was performing out-of-spec (also yet-to-be-defined), then it would simply be removed and the next contender bot added to the legion. "Losing money", in and of itself, is not a reason to remove a bot. But say for example, if the bot loses more than the statistically-measured historical Max-Avg-Excursion, then that could be a trigger to say it has fallen out-of-spec.
I believe the bots need some sort of infrastructure to be part of the legion, lets call it their credentials. Zorro already brings much of this infrastructure to the table (proper trading interface to the broker, error-free order execution, performance measures, etc) but there will always be other credentials that the trader may individually want in every bot. For example, I may want bots to always close trades before the weekend, or to restrict the number of trades that could be open at once, etc. Steve Hopwood used a similar philosophy that enabled him to churn out new bots at lightning speed because the only thing he needed to do was add the actual logic programming and then flip a few switches on/off in the infrastructure. So I'm borrowing from his design model in that.
some thoughts from a higher timeframe trader:
Do not confuse backtesting over long periods to establish positive expectancy and optimisation to tweak a little more profitability by keeping your parameters in tune with current conditions.
What do we mean when we say markets change over time? Markets trend, range or chop so are we saying that the % of time they spend in these states changes? I think that is what we mean, so we want to know how well the strategy copes not only when the mix suits our approach but more importantly how badly it does when the market mix doesn't suit. I'm leaning for more history.
I agree with you. My only bone of contention with that line of thinking is that "more history" is too vague. And it doesn't provide an apples-to-apples comparison when you change something like the BarPeriod of the logic. So while you may be right in the thinking that max history is best, it could still be misleading if you aren't aware of that relationship between BarPeriod and NumBars, for example. One example I can think of offhand is in the Z strategies... I believe it is the EURCHF one... it doesn't have nearly as much history on the backtest as the others. That fact should be taken into account when comparing those strategies, for example.
A completely different problem we have is defining our market mix, what mix of trend, range and chop gave periods of high profitability or low profitability. If we define this, we can look into mechanisms to switch on or off the bot appropriately, be they filters or equity curve trading. Only then would I look into optimising parameters, and I would be wary of where the breaks in my WFO cycles fall. 2008 is the type of year where I would want the bot switched on or off not contributing sample data for optimising parameters in 2011 for example. I'm still for more history, but cautious about optimisation.
I'm still trying to understand the best way to utilize optimization myself. One area I've struggled with recently is being able to identify which parameters are even appropriate to be optimized. I think perhaps only core-logic params should be... for example, only those parameters that would produce the "broad hill" the manual talks about in the optimization profile.
Finally, beware permanent changes over time when backtesting. A 0.1 change in the S&P in 2007 is a more significant percentage change than 0.1 in 2013, this can affect stops, targets, certain indicators, and equity. So I'm still with more history, but algos need to specifically allow for permanent changes.
Edit: was composing this when acid posted, apologies for making similar points. Also I wouldn't expect my comments to be valid on shorter time frames, but I have little experience of this.
Agreed, the market changes in permanent ways over time. This is partly why I'm exploring the idea of "less history" rather than "max history". If, over the course of several years, the market personality changes in a significant way (take the evolution to decimalization as an example in equity markets), then perhaps it doesn't make sense to fit the bot logic to those periods. You could force-fit the bot, but then you have just watered down its potential in current markets. That's my theory anyway. I'd rather have a more dynamic way to deal with the permanent market changes.
Btw I'm also a longer-term trader. I've tried the complete range, from 1440 down to 1 minute over the years. I always come back to 240, so that is my preferred (discretionary) timeframe. However, I don't believe it's wise to set limits on automated trading. I intend to test a wide gamut of BarPeriods and see what I can learn from them. It may be that in my legion I trade with both short-term and long-term bots; that seems like a good idea even for diversification purposes.
