Hi ZMiniTrader, thanks for your question.
The processes of searching consistent profitability involves a lot of struggling which in time, may change completely the way one approaches trading and make realize that most of concept found on some websites (not ET! clearly ;-) or books, about trading, are often misleading, as they actually lead to systematic unprofitability. So during this process there is often a radical change of perspective and development of new perspectives.
Why i am saying that ? Well, simply because, as i see it, i do not have the concept of "risk per trade" because a single "trade" itself is not actually defined. I see a "strategy" as a continuous flow orders which are issued with an objective, which is the maximization of the overall ratio AvgProfit / Max drawdown. Anyway, i see where you are leading and the real question probably becomes: how does this particular algo (strategy) manages to hedge ? The idea, as anticipated, is that, at any time, it would try to "embrace" the price curve with (low) buys and (high) sells:
SELL.....................x x x
price curve
BUY......................x x x x
Now, it is evident that, especially at the beginning of the trading session, the price will "escape" several times those (dynamic) "bounds" breaking up or down. And, in the case of futures the break up / down can sometimes be sudden and deep. When there is "break up/down", clearly, while one side is "profiting", there is always one side (the opposite one) which is causing drawdown, either because there will be buys above the new current price (break down) or because there will be sells below the new current price (break up).
The algorithm discussed here manages to recover from this (temporary) drawdowns by "wrapping again" the price on the new "range". Clearly, the entity of drawdown is dependent on the nature and magnitude of the break outs. If they could always be of relatively small or moderate entity you might actually never see any negative P&L because usually the trades inside the buy/sell (sideways movement) often readily create a protective, hedging, profit "cushion". If, instead, several instruments break up or down all simultaneously and violently, as not uncommonly happen with correlated futures, then the drawdown can be more significant and last longer, while the algo manages to "take control" of the new price range.
To determine what is the capital necessary to manage these events, depending on the algorithms parameters, backtesting (and or experience) is very useful. The actual values could also be worked out theoretically as a function of the minimum distance between orders (what i have called improperly "trade size", just to simplify) and the rate of increase of order distance as a function of instrument volatility.
I'd like to point out that another way to look at this algorithm is like having 2 traders sharing one account. Assume that periodically - say when the price moves M ticks - they both make simultaneously an order:
TRADER L (always playing long) buys I contract
TRADER S (always playing short) sells I contract
They are both attempting to catch a so-called "trend" (TRADER L hopes the price goes up, while TRADER S has an opposite hope). On the other end, while both these trades will have a "position", an external observer looking at the shared account will see actually a 0 position on the account. If Trader L, for instance, gets lucky and he catches a trend and then, at a certain point, takes profit, our external observer will perceive that the account has now position -1. This just to say that, depending on how we like to look at it, the game of trying to "wrap" an expanding range could be seen, at the same time, as "trending", or "countertrending", depending on the perspective. Personally, i dont embrace any of these 2 points of view and prefer to look at it as dynamic process where orders at any time attempt to wrap the price, by expanding with volatility.
Using a folio, usually causes that while some instruments break out, several other ones will have the price wrapped inside buy/sell (a profitable situation) which, in time, provides a sort of "cushion" to hedge against the periodical break up/down, which are anyway necessary to continue profiting.
Clearly, very large, or simultaneous, break up/down (as currently happening) will take longer to recover (and, eventually, turn into profit).
The june 28 gold vertical plunge (27$ less in 1 our and a half) and simultaneous break down of several folio instruments (aud, cad, es, nq, ym) is providing a manual example of drawdown in a nasty scenario. Also CL (over 400 ticks) and EUR (almost 250) dropped down. Now, while someone can talk about market manipulation prior to option expiration:
[see for instance: http://www.marketoracle.co.uk/Article20677.html
<i>"The extreme concentration of paper short positions by 4 or fewer banks is certainly fishy ... As a trader, you can utilize the trend documented above in order to seek short-term trading opportunities. As a long-term investor, you should realize that the sharp sell-offs in precious metals just prior to expiration dates are likely manufactured and almost always short-lived. Therefore, donât be a panic seller and play into their game. If you believe in the fundamentals and long-term prospects for gold, clutch your precious metals with strong hands and donât let your emotions force you to sell at the wrong times. You will invariably have to buy back at higher prices, incur additional trading fees and create high levels of undue stress in the process"</i>]
whether manipulation theories are paranoid or actually accurate, the robot simply could not care less, and certainly does not get scared by these (speculative or not) movements. It simply sistematically adjusts to buy/sell at lower/higher levels, to "wrap" again the price according to its predefined logic.
This is not, clearly, a particularly favourable configuration just at the beginning of our forward test, but it will be a good occasion to see how the algorithm behaves versus very unfavourable situations and high volatility, and whether it is actually able to recover from such events and survive profitably in the market (and perhaps will suggest ideas to devise additional protection mechanisms at folio level). Also provides an order of magnitude for drawdowns.
Currently, most of drawdown is due to CL and ES (and aud, eur): later will show drawdown charts, also comparing the drawdown obtained with a larger "trade size" parameter.
Tom
)