Profitably And Navigating The Fluid Financial Market Dynamic

I am delighted to have guest blogger James Brodie posting an article on today’s group. James is a Hedge Fund manager at 'The Sherpa Funds' based in Singapore. James has been working as a trader for over 16 years, most of that time for Credit Suisse. At Sherpa Funds, James originates algorithmic trading ideas and approaches, as well as managing the trading systems. Mine and James’s paths crossed some years ago in the 90s when we both worked at Credit Suisse in London, I am sure you will find his article extremely interesting.

Profitably and consistently navigating the fluid financial market dynamics - A hedge fund perspective.

To the naked eye it’s virtually impossible to see financial market dynamics as they change before us. In fact, many traders miss these events completely and are therefore unable to react at all. At best, they tend to adapt their styles after the event.

But how can we really trade more consistently and profitably through these evolving markets?  

Let’s look at 3 examples of current changing market dynamics: Firstly let’s take long term portfolio management and the classic diversification across the 5 main investable asset classes: stocks, real-estate, bonds, commodities and alternative investments (hedge funds). There are many theories on the correct allocation between these assets during different stages of economic cycles, and depending upon one’s preferred risk tolerance. However unnoticed by many, in recent years there has been a significant change in the relationship between these 5 classes. The table below (data source: Bloomberg) shows the increasing correlation between these asset classes from the beginning of 2005 to the present day.

Secondly, let’s look at the markets in February and March 2012. At first glance the S+P for instance wouldn’t look noticeably different to any other trending period. But a deeper analysis shows volume at 14 year lows, volatility near 5 year lows, and the height of the short term price waves declining throughout the period. JPMorgan classified this as a 1 in 70 year event (it always is !!), but it meant for instance, that the short and medium term mean reverting strategies that were so profitable in October and November 2011 suddenly became consistently painful.

So how can we navigate consistently through these changing cycles?

Thirdly, let’s look at very short term market dynamics. At The Sherpa Funds we have a fully automated FX fund, with our rules based on technical analysis and mathematical pattern recognition, with trades lasting from 2 hours to 2 months. One shorter term retracement rule appeared to be consistently profitable until we further analysed the actual, and back tested returns. We looked at profitability against the time of day the trade was entered (Singapore time), and found that it was consistently profitable during the London and New York time zones. But between the NYSE close (05:00 SGP) and the European open (14:00 SGP) profitability was random at best, and over Asian data (especially Japan and Australia) it behaved particularly badly.

The table shows the breakdown of results, and highlights the randomness of markets in the Asian time zone where (we believe) lack of volume causes the markets to behave much more nervously and unpredictably.

So what can we focus on the help us profit more consistently in these changing markets?

This is by no means a definitive answer but here are some of our initial thoughts and findings:

The corner stone of any trading philosophy should always be discipline and consistency. This sounds obvious but human emotion has a dreadful way of forcing itself into a trading plan and over-riding, even destroying, some of the best strategies, especially with the inexperienced trader. There really is no room for inconsistent (and irrational) decision making; a disciplined trading strategy must be consistently applied at all times.

Flexibility is also crucial. Some great traders can suddenly swing a losing position into profit by turning their position on a dime, but in reality this is an incredibly difficult skill. What we’ve found is having a diversified set of “rules” that allow the trader to seek profit from different trading strategies, even at the same time (trend following, mean reverting, range trading, pattern recognition etc) with disciplined risk management, allows consistent profits to be made. All losses must be consistently cut early, whilst profits can be run to more optimal levels (RSI, DeMark, Bollinger Bands, price targets etc). [Ed – Interestingly this is the same point made by Jack Schwager in the interview last week – see link here]

It is also vital to have a trading diary to log a complete trading history (why each trade was initiated as well as how it performed). Running purely a mean reverting strategy which would have reaped great rewards late in 2011, as we saw in example 2, would have dealt a seriously blow to the morale of a trader in early 2012. Having a log of past performance would give the trader confidence in their long term strategy, rather than a psychological blow, possibly forcing unnecessary changes to their style. As Vince Lombardi said, “It’s easy to have faith in yourself and have discipline when you’re a winner, when you’re number one. What you’ve got to have is faith and discipline when you’re not a winner”. Another way to create a trading history is to back test trading ideas, but here care must be taken not to “data mine” or “curve fit” the data. [Ed – Vince Lombardi provides many interesting perspectives from sport which have application in trading, – see link here and here.]

What surprised us the most though in our research was the critical importance of position sizing, and being able to adapt that to current market volatility. It surprised us that this was probably the most important factor in our proprietary algorithms and something so often overlooked by both fundamental and technical traders.

At The Sherpa Funds, with our 52 years of trading experience, we set out to create the “perfect” trader by automating the trade identification, execution and risk management processes. We wanted to eliminate all human emotion (and any irrational behaviour!!), and totally ignore any fundamental views. Again, shorting EUR/USD, a favoured fundamental trade since the Greek crisis began in early 2009 brought stellar returns of 6% during May 2012, but the currency actually started the month at the same level it was at in: May 2009, May 2010, Jan 2011, October 2011 and December 2011. On the flip side a purely trend following strategy on its own would have made fantastic short term returns in May, but would have struggled so badly mid 2011.

By combining a portfolio of trading rules, and fully automating the whole trading process we hope to maximize the funds trading flexibility, discipline, consistency, and risk management, and at the same time eliminate any human input what so ever. Our algo’s scan over 390,000 trading opportunities per week looking at just 25 fx crosses, over 8 different time frames, and with the ability to trade “risk off” as easily as “risk on” we can generate pure alpha in a non-correlated way versus the main investable asset classes.