# Intelligent Dynamic Backlash Agent: A Trading Strategy Based on the Directional Change Framework
## 8 Experiments: Results and Discussion
### Experiment 3: Comparing IDBA with TSFDC  
The objective of this experiment was to compare the performance of IDBA with that of the trading strategy named TSFDC [13]. The details of TSFDC is reported in Section 3.5. We first highlight the difference between the functionalities of these two DC-based trading strategies as follows:  
* TSFDC relies on the forecasting model developed by [PERSON] et al. [6] to decide when to initiate a trade, whereas, IDBA uses a different forecasting model to control order's size.
* TSFDC consists of tracking price changes using two DC thresholds, _STTheta_ and _BTTheta_, whereas IDBA uses only one DC threshold.
* The traders must decide the values of the parameters _STTheta_ and _BTTheta_, whereas IDBA has an embedded learning module to find the values of the trading partners _best_theta_ and _best_down_ind_ (Section 5.1).  
We can also highlight some common proprieties of TSFDC and DBA as follow:  
* Both trading strategies open contrarian position.
* They both close these positions at the next DC confirmation point for the succeeding DC trend.  
We then compare the performance of TSFDC to IDBA. For this purpose, we apply TSFDC to the same considered six currency pairs previously introduced in Section 6.2. We compare the rate of return and maximum drawdown of IDBA (Experiment 1) to that obtained by TSFDC. We employ the Wilcoxon test to validate this comparison statistically. Table 12 summarizes the \(RR\) and \(MDD\) of IDBA and TSFDC. To validate our comparison statistically, we consider the Wilcoxon rank sum test twice. Firstly, we apply the Wilcoxon test with the null hypothesis being that \"the median difference between the rate of return produced by IDBA and TSFDC, shown in column \(RR\), is zero\". Secondly, we apply the Wilcoxon test with the null hypothesis being that \"the median difference between the maximum drawdown produced by IDBA and TSFDC, shown in column \(MDD\), is zero\".  
\begin{table}
\begin{tabular}{c c c c c} \hline \hline \multirow{2}{*}{**Currency Pairs**} & \multicolumn{2}{c}{\(RR\)} & \multicolumn{2}{c}{\(MDD\)} \\ \cline{2-5}  & **IDBA** & **DBA** & **IDBA** & **DBA** \\ \hline
**AUD/USD** & 23.5 & 11.2 & 1.5 & 6.7 \\
**AUD/CAD** & 26.2 & 10.7 & 1.7 & 4.9 \\
**GBP/CAD** & 4.3 & 3.4 & 2.6 & 5.8 \\
**GBP/NZD** & 29.8 & 15.5 & 1.7 & 6.5 \\
**NZD/USD** & 18.8 & \(-\)0.7 & 3.4 & 6.2 \\
**EUR/NZD** & 16.1 & 6.9 & 2.2 & 7.5 \\ \hline \hline \end{tabular}
\end{table}
Table 10: Summary of \(RR\) and \(MDD\) of IDBA and DBA.  
\begin{table}
\begin{tabular}{c c c} \hline \hline  & \(RR\) & \(MDD\) \\ \hline \(p\)**-value** & 0.026 & 0.005 \\ \hline \hline \end{tabular}
\end{table}
Table 11: The \(p\)-value of the conducted Wilcoxon tests of comparing the \(RR\) and \(MDD\) of IDBA and DBA.  
In Table 12, IDBA provides lower _MDD_ than TSFDC in all cases. This observation is supported by the \(p\)-value of the Wilcoxon test shown in Table 13; the value of which 0.002 (shown in column _MDD_). Thus, we can reject the null hypothesis at the 5% level of significance in favor of the alternative hypothesis. In other words, the Wilcoxon test suggests that the median of the _MDD_ of TSFDC are greater than provided by IDBA. On the other hand, the \(p\)-value of the Wilcoxon test, in column \(RR\) in Table 13, is 0.932, suggesting that the difference of \(RR\) between TSFDC and IDBA are not statistically significant, at the level of 5%. In other words, the Wilcoxon test could not reject the hypothesis that the \(RR\) medians of TSFDC and IDBA are equal. To conclude, the Wilcoxon test suggests that IDBA outperforms TSFDC in term of _MDD_ but not in term of \(RR\).