It’s been four months since the last book review. I wanted to make book reviews a more frequent feature of the blog. Problem is I often start few books at once but struggle to finish them.
The book for today’s review is A Practical Guide to ETF Trading Systems by Anthony Garner, who is a Trend Follower and fund manager (and user of Trading Blox). The book is aimed at investors wanting to investigate rule-based trading and explains, with numerous examples, the path to designing, building and testing mechanical trading systems, with an emphasis on how this can be applied to the ETF instruments.
The book is a quick read (170 pages) with lots of charts to illustrate the testing.
The author starts by presenting systematic/mechanical trading by the way of a very simple system example and the track records of systematic funds such as Renaissance and many of the Trend Following Wizards.
The next chapter deals with Data. Stressing the importance of good quality data, the author lists a few sources to get historical data to be used as a proxy for the (fairly recent) ETFs. An example of investing with/without dividends makes a compelling case for trying to source that data as well (over slightly more than one century, including and reinvesting dividends nearly double the annual return – and with compounding, that means multiplying your end balance by a factor of over 150!). Finally, Garner touches on commodities and the need to construct indices including less obvious factors such as roll return.
A quick chapter on Backtesting software follows on (Garner uses Trading Blox throughout the book) leads to the final chapter of Part 1 on Strategy and System design.
Aspects such as optimisation and curve-fitting are discussed as well as the need for realistic testing assumptions, in simulating slippage and transaction costs – which can also have a dramatic impact on the simulation results.
Part 2: The meat of the book
The second and final part introduces several investing strategies including systematic (or rule-based) trading. As highlighted by the author, asset allocations is a one of the most important source of return. The good news is that most major asset classes (and more) are available in the form of an ETF. Various asset allocations are tested using the different systems throughout this part.
As a base for comparison, various statistics (CAGR, drawdown, etc.) are calculated for different Buy and Hold portfolios (Equities-only, Equities with Bonds and Commodities, Commodities-only, etc.). One conclusion is that a diversified portfolio helps generate smoother and higher returns. Another point is how regular rebalancing is important to keep an appropriate level of diversification in the portfolio.
Garner uses the ill-named risk-adjusted return metric to compare strategies. Let’s just call this a semantic error (it is widly used throughout the industry), the astute reader should be able to mentally translate this to volatility-adjusted return. (sorry… a bug bear of mine: Variance != Risk)
Finally, an interesting side note specific to commodities and their equivalent ETCs for long-term holdings. The author demonstrates that because of negative roll yields (for markets in contango) and additional ETC sponsor fees eroding much of the returns, these instruments are not an ideal option for long-term holding.
The first rule-based system that Garner introduces is a Bollinger Band BreakOut. He describes the full system using rules, not only for entry and exit, but also for risk and position sizing, rebalancing, money management, etc. (as any good system should). The nice extra for Trading Blox users is that the system is made available on the forums over there.
The author runs comparisons with the various asset allocation benchmarks discussed in the prior chapter, which fairly conclusively demonstrate the superiority of this Trend Following system over any
Buy and Hope Buy and Hold strategies. Playing with the system parameters also shows some form of robustness, with the performance staying fairly constant.
One point is made about trading short. It is recommended not to.
This is mainly in the light of bad performance of short-only strategies tested in the book. But the problem with this reasoning is that most backtests go back only to 1982! I believe the author might have fallen prey to a biased view of the markets, making macro predictions on the continuity of market conditions (suggesting that despite very good performance in 2007-2008 short-positioned systems will “go back to negative performance when stock markets recover”).
I have several problems with this:
- Who knows if markets will recover any time soon? Without getting into macro-economics discussions in much detail here: since the 80′s, the world markets have been subjected to the greatest inflationary expansion in the last 100 years (ever?), helping support (create?) the major macro bull run (bubble?) in most asset classes, globally. I do not want to be making any prediction about where we are heading next, but who knows if the next 25 years will not rhyme with 1931-1955 (ie and/or give us a long “Japan-style” deflationary decline spiral).
- The assumption has not been tested on earlier markets (mostly because of lack of data prior to 1982).
As a side note to the above: it would be interesting to measure and test the impact of a macro filter on a Trend Following system (ie something in the vein of: “favour long trades in the system when the macro indicators indicate a period of expansion and short trades during declines”). Maybe exploring a mechanized version of Schumpeter Business Cycles or Kondratiev Waves as a very long-term filter would be a worthy approach.
This is an interesting chapter addressing one of the shortfalls of ETFs versus futures as systematic trading instruments: leverage (or rather lack of). The new altered Money Management algorithm dictates to the system to concentrate the equity on the available signals, rather than separating the equity equally by instrument (and sitting in Cash where there are no signals). This is an interesting concept that deserves further investigation.
The performance improvement that this Money Management rule change generates is quite interesting. The conclusion is that it is possible to increase returns without increasing leverage.
The last chapter gives the same comparison treatment to a momentum system (buy strongest performing markets), which seems to over-perform the BBBO system (and obviously Buy and Hold as well).
Again, this system code is available on the Trading Blox forums.
A fairly short and pleasant read from a seasoned and real-life Trend Follower and Trading System Developer. There are a few ideas to take away, which is always appreciable. A bit on the expensive side (but I somehow managed to get it at nearly -50% on amazon…).