Here’s the system: At the end of every month,
* if the index is above its 10-month simple moving average: the portfolio is 100% in the market
* if the index is below its 10-month simple moving average: the portfolio is 100% in cash
And that’s it. So, if we take the FTSE 100 Index as an example, if at the end of a month the FTSE 100 is above its 10-month simple moving average then either,
* the portfolio moves into the market by buying, say FTSE 100 ETFs, (these will be the easiest instrument for most investors, but equally futures, CFDs or spread bets could be used), or
* nothing needs to be done if the portfolio is ready in the market. Conversely, if at the end of a month the FTSE 100 is below its 10-month simple moving average then the portfolio sells the ETFs and moves 100% to cash; if it is already in cash then nothing is done. [NB. OK, it’s possible that this isn’t absolutely the simplest trading system imaginable, but apart from buy and hold it is unlikely there are many systems much simpler than this one!] The following chart illustrates such a portfolio for the FTSE 100 Index since 1995. The diamond markers indicate the decisions made at the end of each month whether to be in the market (green diamond) or in cash (red diamond).
Roughly, one can see that the system kept the portfolio in the market in uptrends and out of the market (in cash) when the market fell. This trading system is well-known in the US, what we will look at here is:
1. If the trading system can be profitably applied to the FTSE 100 Index.
2. Whether 10 months is the optimum parameter for the moving average (or would a 5-month, or 15-month, moving average produce superior results)?
Terminology: we will use SMATS(10) to refer to the 10-month simple moving average trading system. And SMATS(5) for the trading system using the 5-month simple moving average etc. Below we will analyse the trading system for 14 different parameters of the simple moving average, i.e. from SMATS(4) to SMATS(16).
1. By the end of the 20-year period all the SMATS portfolios had out-performed the FTSE 100 – except SMATS(5).
2. By the end of the period, SMATS(10) had the highest value; although it can be seen that it wasn’t consistently the most profitable throughout the whole period.
3. For the first six years (up to August 2001) all SMATS under-performed the FTSE 100. This was caused by the market volatility in 1998 and 2001, which caused the portfolios to be whipsawed in and out of the market. The following chart summarizes the final portfolio values in 2016 after running the trading system from 1995.
Not surprisingly the FTSE 100 had the highest volatility. The volatility of the SMATS portfolios was less due to the fact they were in cash for part of the time; broadly their volatility increased as the moving average month parameter increased. The Sharpe Ratio combines returns with volatility to provide a comparative measure of profitability per unit of risk incurred. The ratio’s purpose is to answer questions of the form: is the profitability of a strategy justified by the risk incurred, compared to another strategy? The following chart plots the Sharpe Ratio for the 14 portfolios. (The benchmark for the Sharpe Ratio calculation was the FTSE 100 Index.) SMATS(10) had the highest (i.e. the best) Sharpe Ratio, although close behind were SMATS(14) and SMATS(15).
realised losses as margins have to be paid. By contrast in the case of unleveraged equities or ETFs, drawdowns incur unrealised losses. Having said that, unrealised losses can still be uncomfortable and can have a major adverse psychological impact on the investor or trader. The following chart shows the max drawdown values for the 14 SMATS portfolios and the FTSE 100 Index. Here the SMATS(10) portfolio only had a middling relative score. The best portfolios (i.e. those with the lowest max drawdowns) were: SMATS(7), SMATS(14), SMATS(15), and SMATS(16).
As would be expected the number of trades decreases as the length of the moving average month parameter increases. In other words, systems get whipsawed less with longer moving averages. The profitability figures above did not include transaction costs, but with the systems averaging under 2 trades per year the transaction costs would not be significant.
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