Cyclically Adaptive Trading (CAT)

 

Cyclically Adaptive Trading (CAT)

The recent post highlighted the challenge of short-term trading returns over the past year and, indeed, since 2009.  In this post, I will sketch how I am addressing those challenges in my own trading.When traders refer to the difficult trading environment, they often make reference to “choppy” or “noisy” markets.  Usually their next sentences lament the “algos” and their impact upon markets.  I find these to be expressions of frustration, not constructive formulations of trading challenges.  Invariably, those lamenting choppy markets dominated by algos that “manipulate” markets engage in their venting–and then go back to trading as they’ve always traded…and continue to lose money.

A key to understanding the recent poor returns of short term traders is to appreciate that these traders don’t merely lack an edge; they have a negative edge.  What they are doing, which largely falls into the category of trend/momentum trading, is systematically not working over time.  Waiting for high Sharpe trends to return to markets has not been a sound business model.  But perhaps we can trade in a way that benefits from anti-trending/mean reversion as well as momentum.

In coming months, I will be rolling out an approach that I refer to as Cyclically Adaptive Trading (CAT).  The core idea behind the strategy is that all markets contain linear, directional elements (trends) and cyclical elements.  On a given time frame, a “noisy” or “choppy” environment is simply one in which the cyclical aspects of market behavior dominate the linear ones.  Note that any market cycle itself has linear (rising and falling) components and range bound ones (topping and bottoming).  Very often, what is a trend on one time scale is a portion of a longer-term cycle.  The interaction of cycles over multiple time frames creates challenging irregularities, as markets switch between mean-reverting and trending phases.

The idea of CAT is that you trade the market’s personality, not your own.  Instead of trading the time frame and style you happen to prefer, you trade the cycles setting up in markets.  Because there are multiple cycles at work at any one time and because the dynamics of the current cycles are influenced by the activity of prior cycles, we can identify dominant cycles in real time and adjust trading parameters to those.  This is the adaptive element in cyclically adaptive trading.  The reason so many traders are failing is that they lock themselves into preferred time frames and trading styles.  An adaptive approach is one that trades momentum/trend when we are in the rising and falling phases of cycles and one that trades in a value/mean-reverting manner when we are in the topping and bottoming phases.  We trade longer-term when longer-term cycles dominate and shorter-term when we see those “choppier” conditions.  Trading one time frame in one style systematically fails over time in markets possessing strong cyclical elements.

(A corollary is that, to the degree you identify yourself, say, as a directional trader or a short-term trader, you are probably losing money.  Someone who limits themselves to trading one facet of market cycles is like a baseball hitter who specializes in hitting fast balls.  If you get enough of those guys on a team, it doesn’t take the opposition long to put breaking ball and off-speed pitchers on the mound.)

A second major idea behind CAT is that cycles are self organizing:  recent cycles impact the creation of new cycles which interact to generate other, different cycles.  There is no single periodicity to cycles that can be traded mechanically and, indeed, I have doubts that cycles even exist in chronological time.  Markets move in event units of price movement and volume: as participants enter and exit markets, they impact cycles in ways that impact future price behavior.  In other words, cycles are a function of the behavior of market participants, not a function of the passage of time on a clock. Our job as traders is to adapt to the market’s clock and trade in market time, not our time.

The trading I am rolling out is based upon an advance I’ve made in tracking the self-organization of cycles over multiple event time horizons.

Some sources of insight into market cycles can be found in the early technical works of George Lindsay and Terry Laundry.  Important quantitative perspectives and tools have been offered by John Ehlers, who introduced the notion of adapting technical trading systems to dominant cycle periods.  Relevant TraderFeed posts appear below, and I will be posting more as I formally roll this out in my trading.

 

Further Reading:

Published at Sun, 16 Apr 2017 10:51:00 +0000

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