Taken from http://processdriventrading.wordpress.com/page/2/
Here’s some lighter PDT reading for you this rainy Friday. A lot of people, certainly the vast majority of the Singapore Investoblogosphere, use copious amounts of technical analysis. The way I approach technical analysis is in skeptical but openminded fashion – the burden of proof is on TA to show that it works, instead of the burden of proof being on me to show how it does not work (this is the true scientific method in investing – nothing can ever be shown to be true, but it can be shown to not have been proven false yet). In other words, my uninformed expectation of the value of much of the technical analysis being done out there is so close to zero it can be safely ignored^, thus I see no need to put in the effort to rigorously check if it has negative value.
However when the opportunity comes to quickly and authoritatively test TA, I welcome it with open arms. I ran the Bloomberg BTST screen from 2006-2011* on daily and monthly intervals, using long-only and long-and-short trades. The results are below:
Using the data:
I began this study looking to disconfirm technical analysis (anything that isn’t moving averages, see footnote ^), and confirmed my suspicions in the daily timeframe, but was pleasantly surprised by the monthly result. It may be a good idea, going forward to calibrate monthly expectations using Rex, TE, ROC, and MAO, and then trade on a daily basis using moving averages.
Footnotes
^Please note that I do not personally consider moving averages as technical analysis as the momentum effect is well examined in academia and has achieved the status of scientific validation. However I include them here as most authors would list them as part of TA. I also include sentiment indicators, insider transactions, investor holdings information and so on under my mental category of technical analysis, but most authors do not classify them this way.
*For some unknown but surely annoying reason Bbg does not allow daily backtests further than 5 years. However, this is an improvement over no backtesting at all.
** Short of sitting down a few hundred technical analysts to look at charts as they move through time without telling them what stock and what time period they are looking at… Now THERE’s a great idea for a lab experiment!
*** It is quite accurate to say that all forms of moving averages are just linear combinations of the simple moving average at different speeds. I can state this in terms of pseudomathematical proof. For example, the 5 day EMA is simply x1 times the 5 day SMA + x2 times the 4 day SMA + … + x5 times the 1 day SMA where x1 + x2 + … + x5 = 1 and xi is determined by your choice of exponential parameter. Thus if fast SMAs work better than slow SMAs, then any given X-day EMA will work better than its corresponding X-day SMA. If fast works poorer than slow, then EMA will underperform SMA. (Upon inspection, the DMI indcator that does so well in the HSI appears mathematically similar to the moving averages, but I won’t bother proving this.)
Here’s some lighter PDT reading for you this rainy Friday. A lot of people, certainly the vast majority of the Singapore Investoblogosphere, use copious amounts of technical analysis. The way I approach technical analysis is in skeptical but openminded fashion – the burden of proof is on TA to show that it works, instead of the burden of proof being on me to show how it does not work (this is the true scientific method in investing – nothing can ever be shown to be true, but it can be shown to not have been proven false yet). In other words, my uninformed expectation of the value of much of the technical analysis being done out there is so close to zero it can be safely ignored^, thus I see no need to put in the effort to rigorously check if it has negative value.
However when the opportunity comes to quickly and authoritatively test TA, I welcome it with open arms. I ran the Bloomberg BTST screen from 2006-2011* on daily and monthly intervals, using long-only and long-and-short trades. The results are below:
- btst guide is the official guide to what each of the fields mean as well as how each indicator was calculated.
- For Bloomberg newbies, each chart has been sorted according to final profit/loss figures (the number in green and red). This shows the final amount you would have gained or lost after starting off with $100k of capital in 2006. However, as this final figure could have come with a lot of downside variability, I will make reference to the corresponding Sharpe ratios as well.
- You will notice the glaring omission of some very popular technicals – head and shoulders, elliot wave, etc. This is because they are NOT objectively codifiable in any conceivable way and thus impossible to backtest**.
- You will also notice the omission of volume-based technical indicators, which is unforgivable.
- Bloomberg tries to make up for this by introducing some you have never heard of – “Fear and Greed” indicator anyone?
- First look at the STI and HSI “long daily” charts.
- I believe these two charts are the most relevant to so-called “punters” who trade on technical analysis as they are generally unable to go short. We see that moving average-based strategies perform well, improving the index Sharpe ratios from 0.5 to about 1.9 and 0.68 to about 1.93 respectively.***
- We also see what doesn’t work, and the list is stunning: Bollinger Bands, RSI, MAO, ROC.. a veritable who’s who of popular technical analysis indicators. What is going on here? Maybe, TA believers say, it is the ability to predict movements both up and down that is important.
- To check this, use the STI and HSI “longshort daily” charts.
- Here, shorting is enabled, and the results are even more stunning in Singapore. The rewards for following moving-average-based strategies INCREASE from 1.9 to 2.5 Sharpe. Moving average rules make money on BOTH the long and short legs, whereas all other technical indicators lose money on BOTH the long and short legs. Again, moving averages are better predictors of upward AND downward movement than Bollinger Bands, RSI, MAO, etc.
- The story is a little different in Hong Kong: SMA Sharpe DECREASES from 1.93 to 0.97 (though EMA remains at 1.90) and generally the moving average indicators do not make money on the short legs. However they all still outperform all the other indicators, which lose most of their money on the short legs of their trading.
- STI and HSI “long monthly” charts.
- Stunningly, we see a brilliant reversal. Moving Averages UNDERPERFORM other indicators and UNDERPERFORM Buy and Hold!!!
- STI and HSI “longshort monthly” charts.
- SAME RESULTS!!! In particular, Rex (The Rex Indicator), TE (Trading Envelopes), ROC (Rate of Change) and MAO (Moving Average Oscillator) do well in both HK and SG.
- Surprisingly too, RSI and Bollinger bands are missing from the list of indicators that have performed well in both markets.
- Sadly…
- This would be an interesting result if not for the fact that Bloomberg’s BTST is a laughably neanderthal product for proper backtesting. The source of the problems is that the BTST strategy parameters do not adjust with the periodicity of the data. So my backtest of “SMAvg”, which was based on 50 days as a parameter, is now 50 months, or 4 years. However the other strategies’ parameters are less affected for some as yet unknown reason.
- It is also worth noting that none of the strategies gain substantially much from being able to short, so they do not predict downturns well enough for us to use them for that purpose.
I began this study looking to disconfirm technical analysis (anything that isn’t moving averages, see footnote ^), and confirmed my suspicions in the daily timeframe, but was pleasantly surprised by the monthly result. It may be a good idea, going forward to calibrate monthly expectations using Rex, TE, ROC, and MAO, and then trade on a daily basis using moving averages.
Footnotes
^Please note that I do not personally consider moving averages as technical analysis as the momentum effect is well examined in academia and has achieved the status of scientific validation. However I include them here as most authors would list them as part of TA. I also include sentiment indicators, insider transactions, investor holdings information and so on under my mental category of technical analysis, but most authors do not classify them this way.
*For some unknown but surely annoying reason Bbg does not allow daily backtests further than 5 years. However, this is an improvement over no backtesting at all.
** Short of sitting down a few hundred technical analysts to look at charts as they move through time without telling them what stock and what time period they are looking at… Now THERE’s a great idea for a lab experiment!
*** It is quite accurate to say that all forms of moving averages are just linear combinations of the simple moving average at different speeds. I can state this in terms of pseudomathematical proof. For example, the 5 day EMA is simply x1 times the 5 day SMA + x2 times the 4 day SMA + … + x5 times the 1 day SMA where x1 + x2 + … + x5 = 1 and xi is determined by your choice of exponential parameter. Thus if fast SMAs work better than slow SMAs, then any given X-day EMA will work better than its corresponding X-day SMA. If fast works poorer than slow, then EMA will underperform SMA. (Upon inspection, the DMI indcator that does so well in the HSI appears mathematically similar to the moving averages, but I won’t bother proving this.)
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