Improved Pricing on the Stock Market with Trading Agents

More documents

Recommendations

Info

subagents performed according to a certain scheme. If the plateaux and the valleyscould be anticipated then, and not until then, the results of the tests of the tradingagent could be of practical use. In Table 5 the resulting values are shown.Table 5. Performance of four variations of the trading agent compared to theaverage of their four constituent subagents. The results are given in bold type.All values are relative to the ‘Buy and Hold’ strategy. The trading agents,corresponding to the four columns, were run 10,000 times on every sample toobtain a mean. Transaction fee was set at 0.05 per cent. The resultingimprovements of the trading agents compared to their constituent subagents arehighlighted with a shaded background. The values in column 2 pertain to thetrading agent that adheres to the scheme of Table 4.Column 1 Column 2 Column 3 Column 4Rates Rising Falling Rising FallingPeriod, Samples 3 to5826 Feb 99 –24 Feb 0025 Feb 00 –23 Feb 0126 Feb 99 –24 Feb 0025Feb00–23 Feb 01Subagent S1 In the valley On the plateau On the plateau In the valleyThreshold of sale 0.01 0.01 0.02 0.02Threshold of 0.06 0.06 0.03 0.03purchaseSubagent S2 On the plateau In the valley In the valley On the plateauThreshold of sale 0.0 0.0 0.0 0.0Threshold of 0.0 0.0 0.07 0.07purchaseSubagent S3 On the plateau In the valley In the valley On the plateauThreshold of sale 0.02 0.02 0.01 0.01Threshold of 0.03 0.03 0.06 0.06purchaseSubagent S4 In the valley On the plateau On the plateau In the valleyThreshold of sale 0.0 0.0 0.0 0.0Threshold of 0.07 0.07 0.0 0.0purchaseAverage of agent 0.955 1.082 0.970 1.073Average of 0.998 1.037 0.998 1.037constituentsubagentsMean value of - 0.043 0.045 - 0.028 0.036improvementStandard deviationof mean value ofimprovement0.021 0.019 0.017 0.018As can be seen in this table, the trading agent does on average 4.5 per cent betteron a 3 month period than the average of its constituent subagents do, on a market offalling rates (column 2). The result seems quite remarkable as the performance of thecombined agent reaches the same level as those of the two winning subagents do15
separately (compare with results of Chart 5 and Table 2). Letting the subagents S2and S3 be the winning type of subagent, with rates falling, and with S1 and S4 goingbelow the ‘Buy and Hold’ strategy, the good results persist (column 4). Looking at theperiod of rising rates (column 1), it seems the good performance during the period offalling rates has been traded for bad performance during the period of rising rates. Thepattern is the same as the analytical results of [Parrondo et al, 2000].To give an idea of how volatile the performance of a single trading agent couldbe, I tested one on two separate periods, one period of rising rates and one period offalling rates. The results are shown in Table 6.Table 6. Standard deviation of a 1000 runs over 63 days of trading in 2 sampleswith the trading agent. Initial amount 10,000 (SEK). Transaction fees set at 0.05per cent. Results in bold type.Rates Rising Falling30 Aug 99 – 24 Nov 99 29 May 00 – 28 Aug 00Subagent S1 In the valley On the plateauThreshold of sale 0.01 0.01Threshold of purchase 0.06 0.06Subagent S2 On the plateau In the valleyThreshold of sale 0.0 0.0Threshold of purchase 0.0 0.0Subagent S3 On the plateau In the valleyThreshold of sale 0.02 0.02Threshold of purchase 0.03 0.03Subagent S4 In the valley On the plateauThreshold of sale 0.0 0.0Threshold of purchase 0.07 0.07Mean value (SEK) 9895 9685Mean value of ‘Buy and 11135 9414Hold’ strategy (SEK)Corrected Standard 156 275Deviation (SEK)Standard deviation ofmean value (SEK)4.9 8.7For the sample of the falling exchange the corrected standard deviation is 275SEK. If the distribution of the results of the 1000 runs would be Gaussian, it wouldmean that the confidence of a value to lie within the range 9685 - 275 SEK to 9685 +275 SEK would be 68 per cent. This means that an agent, on a single run, might verywell get results below the level of the ‘Buy and Hold’ strategy. It should also be notedthat the standard deviation of the mean value is as low as 8.70 SEK. This margin oferror is independent of the type of distribution at hand, i.e., it does not have to beGaussian. Thus, the mean value should be quite accurate. This should not be toosurprising. As the volatility of the results is due to the random function of the agent,the combined results of several agents should be less volatile. This is similar to theconcept behind the use of the Sharpe ratio (a ratio that is used to find the best possibleproportions of different securities in a portfolio, that also can contain cash, for optimal16
Page 1 and 2: Improved P
Page 3 and 4: mathematical sign that all is not a
Page 5 and 6: If the model corresponds well with
Page 7 and 8: this purpose I designed a subagent
Page 9 and 10: exceeded a threshold value, set bef
Page 11 and 12: Chart 2, 26 Feb 99 - 25 Feb 00, sam
Page 13 and 14: Chart 4, Average of 28 samples, 26
Page 15: Table 4. The choice of subagent.The
Page 19 and 20: interesting to see how much time th
Page 21 and 22: As I have already indicated in a pr
Page 23 and 24: [Blume and Easley, 1990] L. Blume,
Page 25 and 26: B, SHB-ATEL2-B,VOLV-B,WM-B, STE-R,A

Improved Pricing on the Stock Market with Trading Agents

You also want an ePaper? Increase the reach of your titles

Delete template?

Save as template?