What cockroaches can teach traders: reading list

A well-defended cockroach. Source: Google images.

A well-defended cockroach. Source: Google images.

The latest on my reading list is A Demon of Our Own Design: Markets, Hedge Funds, and the Perils of Financial Innovation by Richard Bookstaber.  It’s a bit dated, but right on the mark for what was to come in 2008.

The author’s experiences with risk management in a world of increasing financial complexity is the main theme of the book.  Now that I’m nearing the end, I’ve found a tasty morsel of advice for systematic traders – or, indeed, just about anyone.  Seek simplicity and robustness in system design/management.  The author uses biological systems for his metaphors; in this case, the very simple defence mechanism of the cockroach results in lots of false positives (i.e. the roach is too conservative), but is therefore well equipped to handle the unknown unknowns of the world.  His counterexample is a fish in Lake Victoria: very specialised for its environment – but gets wiped out when a foreign species is introduced.  Though the fish was perfectly designed for its environment – optimal in a lot of ways – it was ill-prepared for external shocks.

This reminds me of several folks’ ideas of systematic trading: why can’t we just program the algorithm to take all the (in hindsight) obvious precautions to avoid losses?  Well, aside from the observation that many of the precautions actually cost us in the long-run, a hyper-specific trading system is basically useless going forward.  The markets continue to make fools of us all; therefore we need to choose systems which have more robust (read: simplistic) trading and risk management.  Not only will that probably keep us profitable as markets change, they will probably be better equipped to survive external shocks.

As an example (but not meant as a plug): trend-following strategies are beautiful to me.  They’re extremely simplistic trading rules, with built-in risk management.  The latter is usually pretty blunt (e.g. stop-losses, or just signal reversals), but means good risk control in a variety of cases.  That’s probably why trend-followers have been around for decades, quietly churning decent – though maybe not show-stopping – performance through crises and more normal times.

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Hail to the quants…

I’ve written before about the merits of systematic trading…indeed I do a bit myself, in addition to investing with some quant shops.  Anyway, looks like they had a better year in 2014 than most stock pickers.  Congrats to those who have been long-term patient with the momentum traders – as expected/hoped/implicit in momentum strategies, years of lacklustre performance (e.g. 2009-2013) were more than compensated by 2014’s returns for a great many funds.

This leads to both Q & A:

  • A: I distinct recall speaking with many existing/potential investors in managed futures/systematic trading, in which the question was asked: is momentum dead?  Are the systems broken?  Hopefully 2014 helps answer that.
  • Q: is the performance of 2014 sustainable?  For example, 2008 was a great year for the strategy, with a bad year in 2009.  So will 2015 be like 2009?  I wish I knew, but for the moment I’m staying invested.

Who to trust: the machine, or me?

Who's smarter - computer or user?  Source: Google Images.

Who’s smarter – computer or user? Source: Google Images.

I suppose it’s a common refrain among newer systematic traders (i.e. those who prefer to have a programmed computer trade on their behalf): when is it OK to override the system I created?

This is particularly on my mind this week, as the volatility of global markets in the first few trading days of 2015 has been a mix of good and bad for my trading system:

  • The good: higher volatility, combined with strong trends (I’m looking at you, oil and euro) has meant several winning positions for my relatively simple momentum system.
  • The bad: despite some decent trends, there have been pretty good reactions/whipsaws in other markets (including equities and bonds).

So here’s my thought process, in the heat of battle, as it were:

  • Rational side: I’ve created a robust system, without fiddling too much with parameters (learning lessons from others).  It works in backtest, and has worked since live trading.  Just keep away from it.
  • Emotional side: I was up $xx in my S&P position, but am now up 75% of $xx.  The trend *looks* like it’s reversing.  Better to get out now, rather than await the inevitable close by the system.
  • Result: A few good discretionary closes, saving a decent chunk of accumulated gains/avoiding loss.  Set against that, a few other discretionary closes led to a bad outcome – fear of missing out.
    • Say I closed a trade in oil, just to see the price continue its downward trajectory.
    • The system wanted to stay short, but I exited early.
    • I get mad at my decision, so get back short at a lower price.
    • The oil price finally does reverse, vindicating my earlier decision to close out early.  But now I’m stuck with a position (that the system still wants, btw) that I don’t want.
    • I close this second, losing trade, again mad at myself for the whole scenario.
    • Overall, these losses offset a decent chunk of the profits saved by discretionary exits.

What to do.  I guess it’s back to work on my system’s exit logic – hopefully my idea for closing out earlier doesn’t completely screw up the system’s profitability.  Regardless, I’ll learn more.

Let there be…vol?

Will there be calm, or more party time?  Source: Google images

Will there be calm, or more party time? Source: Google Images

So this is probably the last ‘serious’ week for financial markets of 2014.  Some thoughts:

  1. Is oil done?  The news seems more bent on $40/barrel oil, or at least $50, so another 10-15% down move from here.  I’m sure many recognise that the media is generally way late to the party, so perhaps today’s slight recovery to above $58 is putting in the near-term floor.  My momentum models don’t care about the debate, and are staying well-short.
  2. Which is right: VIX or S&P?  Last week’s rise in the VIX, from about $12 to about $19, was an outlier move – similar to what happened last October.  So are we due for an exciting, proper sell-off in the S&P?  Or is this morning’s resilience in the index (up about 1%), combined with VIX selling off (down about 3%), the more relevant fact?  On Friday I reloaded on my old favourite UVXY trade, so I’m clearly hoping the latter.
  3. I feel bad for being long grains.  My same momentum models have me long soybeans, which has been a pretty good trade so far.  However I can’t ignore the oversupply, which I hear from family in the Midwest.  Another example of how the biggest enemy to a systematic trading approach is probably manual intervention.

In sum: I’d like a quiet week.  My models would prefer a chaotic week – or at least a continuation of that lovely oil trend.  With the remaining economic news of 2014 released this week, combined with rolls/option expiry, I’m guessing there will still be plenty of action.

Autonomous agents and genetic algorithms…oh my!

Input = binary.  Output = $$.  Source: Google Images.

Input = binary. Output = $$. Source: Google Images.

The latest book I’m reading is Professional Automated Trading: Theory and Practice by Eugene Durenard.  I’m about a quarter through; in the words of my dad, it’s way cool.

The book has that certain exoticism which probably appeals to a wide range of financial geeks: lots of mentions of hard sciences; passionate disregard of prevailing ‘rule of thumb’ approaches to valuation and trading; and the creation of a robot-army, led by a robot general, to achieve trading success in a landscape filled with chaos and complexity.  If this gets your interest piqued, I suggest purchasing a copy.

OK, back to Earth for a second.  Having not read the full book yet (but the early summaries give a pretty comprehensive overview of what’s to come), I wonder how much of the theory can and does get put into practice.  From the veneered description above, I clearly want to believe the secret to endless trading profits is a fantastically-engineered army of automatons.  However, it’s been my experience from reading more practical trading literature, as well as working in various trading shops, that higher complexity = higher disappointment.  The development cycle I’m accustomed to runs a bit like:

  1. I test a basic hypothesis, such as ‘the oil price trends’.
  2. I come up with a trading rule, having verified #1.  Perhaps a basic breakout strategy.
  3. The basic strategy in #2 looks OK-ish, but I notice a few really bad apples among the backtested trades.  So I create a filter rule to ensure trades like them don’t happen.
  4. I test #3 with the same data.  Perfect.  So now I test out-of-sample data.  Guess what? #3 stinks compared with #2.
  5. Repeat #3 and #4 until I finally give up trying to find a filter rule, and stick with #2.

The idea of continuously-evolving trading robots, or a static robot army led by a continuously-evolving general, sounds a bit like an in-line version of the above sequence.  Maybe, after enough trials, the robot general will beat my logic and analysis – I’m open-minded.  Perhaps that’s why I’m keeping with the book.

In sum: the financial markets offer numerous ways to get very complicated and technical.  Sadly for yours truly, I haven’t yet found a complex ‘golden nugget’ strategy which consistently outperforms more simple trading implementations.  But I keep searching…

In praise of systematic trading

I spent part of my career with a large systematic hedge fund; another part with a key participant in US cash equity High Frequency Trading.  Among the many things I learned was a strong appreciation for systematic trading strategies.  Why?

Most financial management we do, and like, is discretionary.  We like to hear and believe stories of ‘why’: why the market is going up or down; why a company’s stock seems good or bad value; why interest rates can’t go any lower.  I’m sure there’s a bit in Thinking Fast and Slow which talks about the human draw towards narratives.  I believe this is one of the key reasons why:

  1. Financial news networks prefer talking heads (such great forecasters on these shows) to statisticians, and insist on a new reason why the market is up or down each day.
  2. Most people stick with underperforming active asset managers rather than passive index funds for long-equity and long-bond exposure, even though overwhelming evidence shows this is an exercise in futility.

When I began with the hedge fund, my role was to communicate to clients what the systematic strategy did, and how it performed against expectations.  The first roadblock, both for potential investors and for the salespeople selling the systematic fund, was getting over the ‘black box’ fears.  Because the strategy involved no person saying ‘Asset is a good buy’, investors and salespeople assumed there was no merit to the strategy, and it was completely impossible to understand.  Sigh.

Here’s where systematic trading really has the edge:

  1. No baggage.  Algorithms really don’t care if you believe is a good buy or not.  They have no preconceived notions as to what’s fair or not; only what their told to do.  This can really help in times such as since the GFC, where interest rates have been relentless in falling; most pundits believed they couldn’t go lower, but a simple momentum strategy stayed long.
  2. Discipline.  I recently blew a couple trades because of an itchy finger – I was to fearful to keep on a losing trade, even though the probability was definitely in my favour.  Once I code this and let the computer trade, these type of misses won’t be an issue.
  3. Diversification.  It turns out that systematic trading strategies can be designed to produce very diversifying returns to the usual stocks/bonds portfolio.  Although they’ve had a ton of heat in the press, systematic managed futures funds remain the best ‘bang for the buck’ diversifiers for a normal stock/bond program.

I encourage anyone to look at Anti Ilmanen’s Expected Returns, for the joys of using systematic strategies to obtain many different risk/return exposures.