The problem is: how do you write a system that can identify the prevailing market tone/sentiment? This is a fairly subjective assessment that must take into account a wide variety of data (i.e., volume, volatility, VIX, TICK/TRIN, stochastics, global indicators, economic news, world events, etc. ad nauseum). For example, right now we're in a bear market so previous bull market strategies won't necessarily work. Stocks reaching all new highs won't take off, instead they'll retrace and get choppy. So how will your system determine if the market is oversold, overbought, choppy, frothy, etc.? Veteran traders develop a "feel" for what the market is like based on years of experience. Your system will only be as good as your inputs and there are far too many variables to consider. Right now the overall market tone is bearish and trading conditions are choppy and volatile. A good system should know to stay away from swing and trend following systems and instead rely on short-term intraday microtrends (i.e., momentum scalping) for stocks with good volume and intraday ranges (i.e. AAPL). This type of trading will provide consistent (albeit smaller) profits regardless of the type of market you're in. Momentum scalping can then be supplemented by trend following systems once we find ourselves in a good trending environment (which probably won't occur for awhile). If there is truly a holy grail system that has the highest success rate, it would be based on very short-term momentum scalping for stocks with a high beta or relative strength. The key to success in today's market is to be super selective and double down on your strongest hands. Let the newbies try and play every hand they're dealt. Be smart and wait for your good opportunities and then pounce!
You don't. You're looking for the wrong thing. You're trying to create a system to measure and map out market elements that aren't even present yet to decipher. That is exceedingly difficult. What you should be doing is writing systems to measure and map out market elements from the past, one per tone and sentiment. Advantages to this are 1) If one system breaks or is flawed, they don't all come crashing down, and 2) no time is wasted designing on-the-fly to adapt to any given market condition. Your task will be to fit the given market tone and sentiment into the system that has profitably measured and mapped out that set of variables before, to the end of trading it with some level of predictability. That way, you are waiting for the market to show its colors, so you can fit it into the round or square box, and then you know how to play it. The alternative is on-the-fly market adaptation, which is passive vs. active and operates largely in panic mode. The "feel" you refer to is no more than familiarity of a market pattern that a trader has exploited in the past with a system geared to spot that market.
Corey, I think what you're talking about is possible. Perhaps in the direction of what goldenarm is talking about. I'm talking my own book here since I'm trying to do the same thing that you are. I've only been at it a few months. guauld's point is a fair one. If your indicators aren't fast and w/reasonable accuracy then you'll get killed on retracements while you're trying to figure out the market state. I only trade intra-day in the direction of a trend on a daily chart. My signals mostly die off b/f the daily mkt trend is visible which minimizes the retracement costs. FWIW, I've attached a pic of part of my strategy. Following the pic, basically, if red > 0.50 and yellow < 0.20 then bet on blue. Red is a slightly modified version of the Hurst exp. Yellow and blue are proprietary algorithms. Yellow is a "vol" indicator and blue is the direction and force of vol. If I'm posting here next year then you'll know that the idea worked. Best of luck, Lou
Exponential movements and large deviations from long term trends (estimated by moving averages) immediately come to mind as foreboding signals of euphoria. Note that it works much better on the shorting side -- fear is much more powerful than confidence (and its strange cousin, greed). People are more likely to rush into a waterfall sell-off at the top than they are to pig-pile at the bottom ... in my experience at least.
Well, I think the real question becomes, how parsimonious can you make your model while still retaining its statistical significance? Yes, I can find plenty of measurements for volatility, but I might only need one to get me 90% of the way there. If we can identify a vector of market characteristics, and identify simple metrics to determine each characteristic, we could explain the market condition. Here you describe the market condition. All of which can be quantitatively identified, too, if you ask me. Downward sloping moving averages, VIX readings, trend to noise ratios ... all descriptors. And all pretty standard for a bear market -- fear is more volatile (and powerful) than confidence. It makes fundamental sense, then, to trade in a manner that suits this condition. And here you describe the niche system that can trade this environment... And finally, you describe yet another niche system that will work in another environment. That is exactly my point. If we can quantitatively describe the environment, we can better identify which strategy to use! But, I am coming around to the idea that we don't have to identify the market condition through any external program. Imagine 10 trading systems, each designed to trade a specific niche market. When I turn them all on for the first time, they begin paper trading. Some will win, some will lose. The ones that win consistently turn themselves on, and trade live. Eventually, when the condition of the market changes and their bias no longer aligns, they will start to lose. Eventually, in a statistically significant manner (not within normal win/loss variance, perhaps?) At which point, the system goes back to paper trading. In this way, you don't need a separate identifier of market condition ... you let the systems self regulate. The downside of a system like this is the potential draw-downs you take before a system recognizes that it is out of its normal variance. To avoid this, you would need a separate system whose sole purpose is to identify which niche strategy to employ...
If you wish to explore this direction, where you use auxiliary paper trading accounts to identify favourable conditions... i think that you can probably avoid the complication of switching between systems. Talking about implementation, you could use always the same system. You could simulate the consequences of a strategy without actually trading (simulated orders). Then you could activate the subsystems you have selected for real trading. This is probably more confortable to implement, and probably safer, due to the fact often paper trading does not behave exactly equal to real trading (eg, occasional strange behavior of bid/ask in ib paper trading). Tommaso