# Classification of Normal and Abnormal Regimes in Financial Markets
## 5 Results and Discussions
### Discussion  
In this section, we shall highlight some of the major points made in this paper. Firstly, we have demonstrated that the DC indicator space is useful for comparing different markets. By positioning the market regimes in the DC indicator space, the distance between different regimes can be measured. This allows us to quantitatively measure the distance between different regimes in different markets. We can determine whether regimes are different or similar to each other, in terms of their positions in the indicator space. Secondly, the position of the market regimes allows us to classify different types of the market regimes. We have found that all the Regime 1's are similar to each other across assets, markets and time. All of the Regime 2's are similar to each other. But Regime 1's and Regime 2's occupy different positions in the DC indicator space. As shown in Figure 8, the two regimes are clearly separable in each of the four markets studied. Even when we put the regimes found in different markets together, Regime 1s and Regime 2s are separable, with a little amount of overlap (see Figure 9). The overlap is mainly due to regimes found in the Oil Crash market (2014-2016). This could suggest that the commodity market is slightly different from the stock and foreign exchange market; this is a much bigger topic which will be left for future research. Thirdly, by observing the positions of the market regimes, it is possible to define the region of normal market and the abnormal market in the indicator space. We called them normal and abnormal because in all the periods that we chose, dramatic external events took place, for example the bank failures in the 2007-2008 global financial crisis or the shock result of the Brexit referendum in Britain in 2016, all of which affected financial markets. In all our observations, the market changed from Regime 1 (which experienced less volatility) to Regime 2 (higher volatility) around these events. It is reasonable  
Figure 9: Indicator Space of all data-sets with regards to different value of thresholds. to believe that the regime change was either an anticipation, or a reaction, to these unpredictable events. For convenience, we have described what has happened when the markets changed from a normal regime to an abnormal regime. Let us elaborate our findings by looking more closely into the results. We say that the market experienced less volatility in Regime 1, the normal market. This can be seen in Figure 5(a),b, where less time (indicator T) is required to complete similar amount of price movements (indicator TMV) in Regime 2 than that of in Regime 1, and in Figure 5(c),d, less price movements are achieved within a similar amount of time when the market was in Regime 1, compared to the market periods in Regime 2. This indicated that Regime 1 represented a less volatile market period. On the other hand, we say that the market experienced higher volatility in Regime 2, the abnormal market. This can be seen in Figure 5(a),b, where bigger price movements were observed within a shorter period of time in the region of Regime 2, than those in the region of Regime 1. In Figure 5(c),d, bigger price movements (TMV) were completed in Regime 2, than those completed in Regime 1, within a similar amount of time (T). These indicated that Regime 2 represented a higher level of market volatility. We note that the choice of threshold affected the positions of the markets on the indicator space in some markets but not others. But overall, independent of the thresholds used, the two regimes occupy different areas of the DC indicator space. The relative positions of the normal and abnormal regimes are insensitive to the thresholds used, which indicated that our research is correct, that thresholds do not influence the outcome of regime positions. Finally, it is worth clarifying that our aim is not about finding the \"optimal\" threshold for regimes clarification. The intention was to generalise DC characteristics of normal regimes.