On Trading Strategies, THeir Dynamics and How That May Change

Sorry I haven't been able to write too much. Finally on break so I think I'll jot some thoughts down which I thought were interesting. First I'll start with a couple claims regarding autocorrelation. "Autocorrelation" is nothing more than a fancy term to describe a particular dynamic that some processes follow, be they stock or bond prices, the ebb and flow of a government regime, or the performance of a class of trading strategies-- autocorrelation answers the question "when a stock goes up today, does it tend to follow that trend and go up tomorrow (positive autocorrelation), and does it revert to the mean and go back down tomorrow (negative autocorrelation)?" I posit the following: (1) autocorrelation exists when people aren't entirely able to detect and/or trade on it effectively or economically, for whatever reason, and (2) autocorrelation, once detected, tends to decline in absolute terms over time to a steady-state (and negative) level. There are some interesting consequences for where we are right now.First of all it's pretty much a moot point that detected autocorrelation tends to dissappear rather quickly. Our own Professor Mackinlay with Andy Lo detected positive autocorrelation within the S&P with a coefficient of around .3, which is huge, back around 20 or 25 years ago I believe. .3 means each move one day in percentage terms implied a move 30% as strong on average in the same direction the next day. However since then it's all but evaporated. A similar form of autocorrelation was later detected in certain industries... then it was detected in certain industries on intraday data. Arguably there is still some autocorrelation to be found intraday in semiconductor stocks (at least as of say 9 months ago). All getting arbed away.I bet that at this moment, the highest degree of autocorrelation exists broadly in 'trading strategies.' The performance of trading strategies themselves are at times very positively autocorrelated. It's something that we've all seen or at least felt to some degree, and it's been statistically detected for generic pairs trading portfolios. It makes intuitive sense, and up until recently, I'm not terribly convinced that the investment community has been able to take advantage of anything of this sort-- due to personnel risk, complications due to having multiple managers, inflexibility transitioning from one strategy to another, and personal bias towards certain skillsets relative to others by the person in charge. After building up a competitive advantage with a particular trading strategy, autocorrelation of trading strategies is the one killer which becomes almost impossible to avoid. All of these frictions in conjunction with one another make it very difficult to effectively "trade" trading strategies.My bet is that some of that may be changing now, or at least that it should, especially with the rise of fund of fund managers. Trading strategies themselves in a fund of funds context are becoming more tangible-- more like real assets-- because they have become so well defined. While diversification across strategies is great, I bet more aggressive effective flexible tactical allocation among strategies by a person very well versed with multiple unrelated strategies would have some pretty good juice to it. Multiple layers of performance fees can be a big problem, but I'm not sure anyone has as of yet been able to actually execute on this idea terribly effectively.Examples of positively autocorrelated strategies are numerous. Take for example convertible arbitrage. It isn't like their current problems just came out of nowhere... they've been around for a while, and they just got worse. More than that, their weakness then feeds on itself, as fund redemptions force funds to unwind their positions-- but of course their positions are probably more or less highly correlated to all the other funds out there in the convert arb space, so the unwinding of one portfolio naturally inflicts mark to market pain on most others. Another example is statistical arbitrage. I have a hunch that a class of traders may be next on the list... more on that later perhaps.I'll try to go one layer deeper. Note that there is a distinct difference between stating that trading strategies are cyclical and stating that trading strategies are trend following or positively autocorrelated. A cyclical industry is an industry which is in some sense both trend following and mean reverting at the same time. Cyclicality implies mean reversion over longer time horizons because no industry stays hot or dead forever. At the same time it implies trend following over shorter time horizons because success and failure tend to feed on themselves. In that framework then, I'm implying only one leg of the cyclical dynamic. I guess the reason is I'm not terribly optimistic that trading strategies in general will survive in the long haul. On a fundamental, some will live and others will die. Now I guess I'll bring up my example of a class of trading which I believe may diminish in importance to a large extent.I'm hesitant to believe that some forms of cash trading will remain around for much longer as well from what i've seen at my own desk and some of the others that i've seen/the people i've talked to. Hedge funds have the ability to lock up capital for 2 to 3 or more years and maintain that longer time horizon without having to worry about marking to market all the time. At banks though a ton of their trading simply doesn't have that flexibility. Very few traders are allowed to have that longer term outlook from what i've seen when things start to turn south. It raises an interesting question: when the primary activity of a desk, be it prop trading or market making, is to create really short term profits on a wide range of credits, is that a job that a large flock of cash traders should be doing in steady state? Or should it be a small handful of traders supported by computers and computer scientists? Some short term traders call it a battle of man vs machine on their desks, and some are saying the machines are making things a hell of a lot more difficult. Machines have that level of efficiency over short time horizons that is difficult to match both in speed and in scale by humans. Which brings back that old topic of quantitative methodologies vs qualitative-- quant shines with really high frequency data and with a large universe of liquidstocks on which to operate for obvious reasons. humans can't possibly absorb really high frequency data, let alone for 1000 stocks at the same time. high frequency data tends to work best over shorter time horizons, which implies that if we are to employ primarily qualitative methodologies, we may not want to be cash trading. haha. So yeah, trend following a agree with a lot when it comes to trading strategies. mean reversion i'll agree with sometimes (high yield being one of them... as well as deep value), but there seem to be a lot more exceptions. lemme kno what you think! -danny