5 ANALYSIS AND RESULTS
5.1 Data analysis
The data used in the analysis is shown in the following graphs. Figures from 4 to 19. For each graph the solid blue line describes the values before Brexit, the blue dashed line describes values during Brexit and the black solid line describes the historic average for Figures 4 and 5 and means for figures from 6 to 17. The placements of the standard deviations for both volatility calculations can be seen from Figures 4 and 5.
Figure 4.The exchange rate volatility of the GBP towards the EUR and the historic average.
Figure 5.The exchange rate volatility of the GBP towards the USD and the historic average.
The prominent spikes in Figures 4 and 5 are placed between May 2016 and July 2016, what occur simultaneously with the Brexit referendum. However, after this event the curves in the GBP/EUR and the GBP/USD models return to level of the historic average in both graphs.
The maximum value of the spike in Figure 4 is 1.6880, which is the standard deviation of June 2016. There was a 0.5754 or in other words 57.54 % increase in the volatility of the exchange rate of the GBP towards the EUR from the last month during June 2016. Likewise, the maximum value of the volatility of the exchange rate of the GBP towards the USD is 2.3075 making the increase 0.7271 or 72.71 % in percentages. More variation in the standard deviation can be seen in Figure 4 before June 2016 and after compared to the same time of Figure 5. The historical average of the exchange rate volatility of the GBP towards the EUR is 0.3977 and for the GBP towards the USD is 0.5161.
The monthly percentage change for the inflation for the UK, the EU and the US can be seen from Figures 6, 7 and 8. The inflation rates increased for both the UK and the EU during the month of the Brexit referendum on June 2016. The inflation rates increased 66.67 % in the UK and 200 % in the EU. However, none of these where the peak values of the percentage changes, unlike in the graphs for the exchange rate volatilities where the peaks were on June 2016. The inflation rates of the US decreased 1.96 % on June 2016. The mean of the inflation rate’s percentage change in the calculated time period for the UK is 2.59 %, for the EU the mean is 6.63 % and for the US it is 9.47 %.
Figure 6.Percentage changes of inflation of the UK.
Figure 7.Percentage changes of inflation of the EU.
Figure 8.Percentage changes of inflation of the US.
Figures 9, 10 and 11 represent the monthly percentage changes of the interest rates for the UK, the EU and the US. During June 2016 the interest rates increased 4.08 % in the UK, while the interest rates decreased 100 % in the EU and 2.94 % in the US. The monthly percentage change means are 0.40 % for the UK, -7.00 % for the EU and 1.40 % for the US.
Figure 9.Percentage changes of the interest rates of the UK.
Figure 10.Percentage changes of the interest rates of the EU.
Figure 11.Percentage changes of the interest rates of the US.
The monthly percentage changes of the M1 money supply are represented in Figures 12, 13 and 14. The highest peak in the monthly percentage change graph for the UK is on June 2016 with an increase of 4.04 %. The percentage change on June 2016 in the EU increased 1.59 % and in the US it increased 0.25 %. The percentage variation of the M1 money supply of the EU is uncertain for 2019 due to the missing data. Therefore, there is no percentage change in the graph during the year. The monthly percentage change means are 0.48 % for the UK, 0.76 % for the EU and 0.72 % for the US. The missing data can affect on the actual mean of the EU.
Figure 12.Percentage changes of the M1 money supply of the UK.
Figure 13.Percentage changes of the M1 money supply of the EU.
Figure 14.Percentage changes of the M1 money supply of the US.
Figures 15, 16 and 17 show the monthly percentage changes of the M3 money supply for each the UK, the EU and the US. As for M1 money supply of the EU, the percentage change of the Euro M3 money supply is uncertain for the year 2019 due to missing data, affecting the actual mean of the monthly percentage change of the EU as well. The Brexit referendum month June 2016 includes percentage changes of 3.45 % for the UK, 1.24 % for the EU and 0.53 % for the US. The monthly percentage change means are 0.20 % for the UK, 0.51 % for the EU and 0.52 % for the US.
Figure 15.Percentage changes of the M3 money supply of the UK.
Figure 16.Percentage changes of the M3 money supply of the EU.
Figure 17.Percentage changes of the M3 money supply of the US.
Figures 18 and 19 show the monthly changes of the exchange rate for the GBP to the EUR and the USD. On June 2016 the value of the EUR increased against the GBP from 0.7884 to 0.85035 weakening the purchase power and value of the GBP. The increase in percentage during the month is 7.86 from the last month. The exchange rate value of the GBP to the EUR has stayed above the mean after the referendum, where the value of the mean is 0.8360.
The value of the exchange rate of the GBP to the USD increased from 0.69767 to 0.76953 and has stayed above the mean after June 2016, where the mean is 0.6913. The percentage increase to June 2016 from its previous month is 10.3, meaning that the value of the GBP against the USD weakened.
Figure 18.Monthly exchange rates of the GBP to the EUR.
Figure 19.Monthly exchange rates of the GBP to the USD.
5.1.1 Results of the pound sterling towards the Euro
Figure 20 shows the fitted classification tree used for prediction. The importance of the variables used for prediction are presented in Figure 21. The reliability is tested with the confusion matrix, which results are shown in Figure 22.
The predictor importance graph indicates that the most important variable in predicting the model is the exchange rate of the previous month (Prev mon XR) with an estimate value of 0.0058, followed by the interest rate of the EU with an estimate value of 0.0041. Inflation of the UK has an estimate value of 0.0032, M1 money supply of the UK has 0.0028, M1 money supply of the EU has 0.0046, M3 money supply of the UK has 0.0045 and M3 money supply of the EU has the value of 0.0034. Indicated by the results, the inflation of the EU and the interest rate of the UK, Brexit and Brexit related events has no importance in predicting the model with the values of 0.
Figure 20.The decision tree classifier of the GBP towards the EUR.
According to the confusion matrix, the classification model predicted correctly 33 times the class label as1, which designates as below the historic average of exchange rate volatility, while it got 8 labels wrong predicting them as2, which signifies equal or above the historic average of the exchange rate volatility. The model correctly predicted 58 times the class label as2, while 9 of the labels were falsely predicted.
Figure 21.Importance of the predictors in the classifier tree model of the GBP towards the EUR.
Figure 22.Confusion matrix of the label prediction for the GBP towards the EUR.
Lastly, the accuracy is measured after forming the confusion matrix. The values needed in the calculation can be obtained from the confusion matrix in Figure 22. The value ofTPis 33, FPis 8,FN is 9 and TN is 58. After obtaining the values, the value of accuracy of the prediction can be calculated giving it the value of 0.8426, for the precision 0.8657 and for the recall 0.8788.
5.1.2 Results of the pound sterling towards the U.S. dollar
Figure 23 shows the fitted classification tree used for prediction. The importance of the variables used for prediction are presented in Figure 24. The reliability is tested with the confusion matrix, which results are shown in Figure 25.
The predictor importance graph indicates that the most important variable in predicting the model is the exchange rate of the previous month (Prev mon XR) with an estimate value of 0.0064, closely followed by the M1 money supply of the UK with an estimate value of 0.0063. Inflation of the UK has an estimate value of 0.0019, inflation of the US has 0.0038, interest rate of the UK has 0.0019, M1 money supply of the US has 0.0036 and M3 money supply of the US has the value of 0.0042. Indicated by the results, the interest rate and the M3 money supply of the UK, Brexit and Brexit related events has no importance in predicting the model with the values of 0.
Figure 23.The decision tree classifier of the GBP towards the USD.
According to the confusion matrix, the classification model predicted correctly 64 times the class label as1, which designates as below the historic average of exchange rate volatility, while it got one label wrong predicting it as 2, which signifies equal or above the historic average of the exchange rate volatility. The model correctly predicted 37 times the class label as2, while 6 of the labels were falsely predicted.
Figure 24.Importance of the predictors in the classifier tree model of the GBP towards the USD.
Figure 25.Confusion matrix of the label prediction for the GBP towards the USD.
Lastly, the accuracy is measured after forming the confusion matrix. The values needed in the calculation can be obtained from the confusion matrix in Figure 25. The value ofTPis 64, FPis 1,FN is 6 and TN is 37. After obtaining the values, the value of accuracy of the prediction can be calculated giving it the value of 0.9352, for the precision 0.8605 and for the recall 0.9737.
6 DISCUSSION
According to the results, the most important explanatory variables for the prediction of the exchange rate volatility of the GBP/EUR are the exchange rate of the previous month and the M1 money supply of the Euro and slightly below this the M3 money supply of the pound sterling. For the prediction of the exchange rate volatility of the GBP/USD the most impor-tant variables are the exchange rate of the previous month and the M1 money supply of the pound sterling. The accuracy of the prediction for the models determined by the confusion matrix are quite good, especially for the model of the GBP/USD.
The Brexit related variables do not have any importance in predicting the exchange rate volatility for both of the models. However, as the research by Driffield and Karoglou (2019) indicated that Brexit affects the exchange rate of the UK, while the exchange rate was the most important predictor of the model in this report. This would support the perspective of interpreting that Brexit affects the exchange rate volatility indirectly by affecting it through the exchange rate. The graphs of the exchange rates of GBP/EUR and GBP/USD indicate that the time during Brexit affected the exchange rates in a way that the value of the GBP against the EUR and the USD weakened.
The results of the research by Korus and Celebi (2019) showed that the referendum and Brexit related events had an influence on the exchange rate volatility of the GBP to the EUR, conflicting with the results of this thesis. Even if the Brexit related events have no importance predicting the both models of the exchange rate volatility, the results of the research by Korus and Celebi (2019) and this thesis do support each other by analysing the graphs of the exchange rate volatility, as shown in Figures 4 and 5. For example, the month of the referendum of Brexit and its results on June 2016 the exchange rate volatility peaks for both the GBP to the EUR and the USD, returning back to its original level on the next month.
Therefore, this can be interpreted that the referendum had importance for a short-term.
Other observation where Brexit itself or the referendum had influence are that the variation monthly percentage change of the interest rate of the UK became unstable during Brexit, the inflation rate of both the EU and the UK and the M1 money supply of the UK have a upward spike in the monthly percentage change during the month of the referendum, where the spike of the M1 of the UK is the peak. The monthly percentage changes of the US for the inflation rate, interest rate, M1 and M3 money supply, all stabilised to a level close to their mean values, while the changes were more unstable before Brexit or right before the referendum.
As observed in the literature review, the prediction of the exchange rate volatility is uncer-tain since the macroeconomic variables may have various behaviours in different situations.
Furthermore, several researches state various research methods that conflict each other. In addition, the missing data of the M1 money supply of the Euro may have negative influ-ence in the prediction of the exchange rate volatility of the GBP/EUR model. Therefore, the results of this research may indicate accurate or inaccurate outcomes depending on the context.
This research can be improved further by applying more Brexit related data, and more macroeconomic variables. Additionally, the research can be improved by investigating the effect of Brexit related variables on the macroeconomic variables which predict the exchange rate volatility. This way the possible indirect influence of Brexit on the exchange rate volatil-ity can be observed. For the future research, the data until the end of Brexit and after it should be investigated to potentially achieve more accurate results.
7 CONCLUSION
The main objective of this research was to investigate whether Brexit had any influence in the exchange rate volatility of the pound sterling towards the Euro and the pound sterling towards the U.S. dollar. The sub-objectives were derived from the main objective, investigating which variables were the most important in predicting the exchange rate volatility and were the Brexit related variables more important for the classification rather than the macroeconomic variables.
The investigation was done modelling a decision tree classifier which predicted whether the exchange rate volatility of the GBP to the EUR or the GBP to the USD was above or below its historic average. The explanatory variables used for the prediction included monthly percentage changes of the inflation rates, interest rates, exchange rates of the previous month, M1 and M3 money supply values and Brexit and Brexit related events. The data used in this research was obtained fromThompson Reuters Datastreamand the Brexit related data was collected from the Council of the European Union’s website. Lastly the accuracy of the predictions for both of the models were calculated using a confusion matrix.
The results showed that the Brexit and Brexit related variables had no importance in predict-ing the exchange rate volatility, however it appeared to have an effect on the variables that predict the volatility based on the curves in the graphs that describe the monthly percentage changes. The referendum of Brexit did have a short-term influence on the exchange rate volatility during the month it was held, on June 2016. In addition, Brexit had an effect on the exchange rate values of GBP/EUR and GBP/USD during and after the month when the referendum was held.
The results of this research where Brexit related events had no effect on the exchange rate volatility conflict with earlier research. However, the effect of the referendum to the ex-change rate volatility was indirect mainly through the monthly percentage ex-change of the previous month’s exchange rate. The concise amount of the Brexit related data and the miss-ing values of the M1 money supply of the EU, may have negative affect on the accuracy of the results in this research.
For the future, it would be interesting to investigate the effects of Brexit on the exchange rate volatility of the GBP to the EUR and GBP to the USD including the data until the end of Brexit and after it. In addition, the effect of Brexit could be investigated on the EU for example how Brexit affected the exchange rate volatility of the EUR towards the USD or the Japanese yen.
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