Automation of Trading Machine for Traders by Jacinta Chan

Author:Jacinta Chan
Language: eng
Format: epub
ISBN: 9789811399459
Publisher: Springer Singapore

Average cumulative return per year

8.5

3.1

1.6

4.5

−0.5

24.2

32.1

Source Author’s creation based on tests

The benchmark for any model is that the returns must surpass those of the passive strategy of buy-and-hold (Fama, 1965). The excess return is termed as abnormal return. If the strategy can outperform the benchmark buy-and-hold for different periods of time, then the market prices are not random (Fama, 1965).

Abnormal Returns

The results of these tests are recorded and compared. All the profit results are reported net of transaction costs. AMA’s results which are more profitable as it can automatically adjust to shifts in parameter. The following notes summarize the six technical trading rules, including AMA′ and OptMA which is obtained after a series of backtesting exercise to be used as a benchmark of what an ideal trading result can be.

The trading performance results show that although in certain years, like 2000, 2002, 2005, 2007, 2010, Buy and Hold is the best strategy to behold as advocated by Fama (1965); the cumulative returns for all the 15 years from 2000 to 2014 show that Opt50MA (cumulative return of 393%) and AMA′ (cumulative return of 523%) outperform the passive threshold Buy and Hold (cumulative return of 127%). The rational investor would have earned 6.7% average return per year if he had bought and held on for 15 years from 2000 to 2014, while in the same period, the fortune teller would foretell an abnormal average return of 20% average per year while the technical analyst market practitioner earned an abnormal average of 27% after transaction costs and slippage. The net results (after taking into account transaction costs and slippage) show AMA′ outperforms all the previous trading models for the period 2000–2014. Table 4.1 shows AMA′ produces the highest profit for the in-sample period from 2 January 2000 to 31 December 2014.

Figure 4.1 shows the adaptiveness of AMA′ to CLOF prices over the last ten years. This indicates that AMA′ is a robust trading model and can be used for CLOF market. AMA′ can be taken into consideration as a viable trading model for the professional model trading desk of financial institutions. The results from this study are consistent with earlier studies like Lukac et al. (1988), Brock et al. (1992), and Balsara, Carlson, and Rao (1996), which show that simple moving averages and moving average oscillators have predictive power for the stocks in Dow Jones Industrial Average (DJIA) index.

Fig. 4.1CLOF closing prices and adjustable moving average′ (AMA′)

(Source Author’s creation based on CLOF closing prices and adjustable moving average′ [AMA′])

Download

Copyright Disclaimer:
This site does not store any files on its server. We only index and link to content provided by other sites. Please contact the content providers to delete copyright contents if any and email us, we'll remove relevant links or contents immediately.