That is some nice work Paul. I am not surprised that shorter periods did well, given the short term volatility of the markets.
I think the volatility has also been rough on short positions, except maybe those short on BP stock. : ) _____________ Rik Rasmussen On Sat, Jun 19, 2010 at 9:28 AM, tzsuj <[email protected]> wrote: > Dear Forum > > I'm a relatively new user of Best Charts – haven't use it for real yet, but > am trying to get a handle on it theoretically first. BC seems to be an > interesting and potentially powerful tool, but unfortunately it will take a > bit of testing to get it set-up before I can use it with confidence.... > > I completed my first test run and I thought I would publish some of the > results – to get some discussion going on here and also feedback from some > of the more advanced forum members. > > Some specifics of the test: > > Test Period: 19 April '10 to 17 May `10 > Test Stocks: Top 20 Australian stocks by market capitalisation (I used > these as they are large, well traded stocks – good volumes, and hopefully > the market is well enough informed such that true technical analysis > principles can operate) > Test Indicator: BCI (I only did the BCI indicator as based on previous > optimisation testing, it seemed to give the best overall gains) > Parameters: BCI was `optimised' each day (according to the series > description below). I realise that the last parameter of the BCI is user > defined and not automatically optimised – I just left this as the default. > Buy/Sell Triggers: Instruction from the optimisation output each day – > simply go long when `Bullish' and go short when `Bearish' (as per the intent > of the test series below) > Prices Used: Buy/sell at the opening price on the day following the signal > generation. > Stop Losses: No stop loss triggers were used – investment was held until > the signal changed. > Brokerage Costs: No brokerage costs were taken into account > > Test Series: #1 – Test Performance on Long Investment Only > Optimisation Period: 229 days > Optimise on Long Only > Invest Long Only > > Test Series: #2a – Test Performance on Long and Short Investment > Optimisation Period: 229 days > Optimise on Long & Short > Invest Long Only > > Test Series: #2b – Test Performance on Long and Short Investment > Optimisation Period: 229 days > Optimise on Long & Short > Invest Long & Short > > Test Series: #3a to 3h – Test Performance on Optimisation Period > Optimisation Period: 20, 60, 90, 120, 150, 180, 250, 320 days respectively > Optimise on Long & Short > Invest Long & Short > > Issues that may have affected the results/market: > > The overall ASX market during the test period – commenced at the start of a > downtrend, 3 weeks duration. Recovery in the last week. > The Greek sovereign debt crisis was rearing its head during the test period > and got decidedly worse during the latter half of the test period. > The Australian government announced the imposition of a higher rate of > taxation on mining companies during the last week of the test period – this > had a severe negative effect on resource stocks and resource service > industry type stocks. > > > Test results: > 1. Interestingly, the percentage of winning trades for each test series > (so # of winning trades for all 20 stocks in each test series compared to > the total # of trades for all 20 stocks in each test series) came in at > around 50% - the law of averages...... series #1 was low @ 38%, but the rest > ranged from high 40's to mid 50's. This would suggest to me that using BCI > in the way that I did is no better than flipping a coin – 50% of the time > you will get heads and 50% of the time you will get tails. This is a bit > disappointing as I would view the ability to pick a winning trade as one of > the most important metrics – you need to be on winning trades for something > like 70% of the time to have some sort of confidence that you are on the > right track. > > 2. In terms of the most number of winning trades, tests 3b (60 day), 3c > (90 day) and 3e (150 day) were the best performers with winning rates of > 57%, 54% and 59% respectively. Encouraging, but not stellar. > > 3. 2/20 stocks did extremely well in terms of the # of test series with > winning trades <70% - RIO (6/11 test series) and WOW (8/11 test series) – > one resource stock and a consumer staple stock. During the test period, RIO > was in a major down trend and WOW was in a range-bound pattern. As a > comparison other stocks in the test population of 20 came in at 2-3 (at > best) with series trades >70% winners. I don't know if there is anything to > be read from this observation...... > > 4. % winning LONG trades (41-67%) was decidedly greater than the % winning > SHORT trades (29-36%) for all test series. This is interesting, but not > sure what I can conclude from it. It seems to suggest that BCI's shorting > accuracy is less than that of long trigger accuracy. If you were to extend > this concept and say, only invest long (but optimise on long and short), you > would come up with a better outcome, but you would still only get in the > high 60%'s for # of winning trades – close but not quite at the comfort > level. WOW performed very well in terms of % of long winning trades – 7/11 > tests achieved >70% winners. > > 5. It is difficult to present statistically correct and meaningful data > for this item, but in general, the % gain/trade for winning shorts was > significantly greater compared to the gain/trade for winning long trades. % > Losses/trade for losing longs and losing shorts were about equal. > > 6. Performance against benchmarks – 4 benchmarks were used - #1 was the > `buy and hold' movement of the share price for each stock during the test > period, #2 was a theoretical 7% pa return, #3 was the movement of the ASX > 200 index (top 200 ASX stocks) over the test period, and #4 preservation of > invested capital. > 6a. Stock buy and hold - All test series performed considerably better > than the buy and hold scenario for each stock – the BCI series achieved > gains > the benchmark for between 70-90% of the 20 stock test set. > 6b. Nominal 7%pa interest – Mixed results. Series 1 and 2a were > decidedly worse than the benchmark (10-15% of stocks outperformed the > benchmark) – this is logical as these were series without shorting (so less > time in the market compared to a constant 7% earning rate). Other series > ranged from 40-70%, with best performers being 3b (70%), 3c (65%) and 3e > (65%). The remainder averaged out at the 50% mark......the law of averages > again ?? > 6c. ASX200 buy and hold – similar to 6a – not surprising given make-up > of ASX200 index. > 6d. Preservation of capital – initial investment capital was preserved > in most series (generally 60-70% of the 20 stocks preserved capital, for > each of the test series), with the exception of series 1 and 2a (only 20% of > the stocks preserved capital). The inability to short in these series is > the obvious difference to the other series, however this doesn't explain the > poor performance – if you couldn't short, then you just keep the money > uninvented – so no risk. The only reason I can think of here is that the > falling market did not correlate well with the 229 day test period data and > the long only optimisation condition (for test 1) and the mismatched > optimisation (long and short) vs investment practice (long only) (for test > 2a) resulted in BCI not predicting well. > > 7. Annualised % returns across the 20 stock spread – if you invested equal > initial amounts across the 20 stocks for each of the series, the following > annualised returns are realised: > > Series 1 -38% pa > Series 2a -41% pa > Series 2b -1% pa > Series 3a 22% pa > Series 3b 47% pa > Series 3c 44% pa > Series 3d -26% pa > Series 3e 20% pa > Series 3f 24% pa > Series 3g -13% pa > Series 3h 3% pa > Benchmark 1 -87% pa > Benchmark 2 7% pa > Benchmark 3 -94% pa > Benchmark 4 0% pa > > > So, in summary, the BCI testing showed OK results against a `buy and hold' > strategy in a falling market, but the specific process used did not deliver > consistently high probability results (refer point 1). Shorter optimisation > periods (60 and 90 day) seem to work the best in this instance. Long > trading was more successful than shorting (don't know why – this is counter > market trend) and shorting wins were bigger than long wins. No results came > close the optimised theoretical backtest results of ++100%pa (not sure if > this is realistic though). > > I will conduct more testing going forward. > > Any comments or suggestions. Analysis spreadsheet is available upon > request (it is a bit messy, but you will get the idea). > > > Paul > > > > > ------------------------------------ > > Yahoo! Groups Links > > > >
