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The IUP Journal of Financial Risk Management
Did BREXIT Lead to a Structural Break in Stock Returns of Select EU Countries? – A Time Series Econometric Investigation
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The present study is an attempt to investigate the impact of an important event ‘Britain’s exit from the EU, BREXIT, i.e., whether or not this even, whose referendum took place on June 23, 2016 with the result being reported in the early morning of June 24, 2016, resulted in causing any structural break in the stock index movement in the select five EU member countries, namely, UK, France, Germany, Finland and Spain. The period of study was 45 days (June 2, 2016-July 15, 2016) with a 30-day event cycle; 15 days before the event and 14 days after the event (–15 to +14). The analysis is carried out on the closing prices of the major indices of these five EU nations. The tools used to analyze the impact of the event, BREXIT, are CUSUM and CUSUMSQ plots and Chow dummy variable test. The results of CUSUMSQ plots give an indication of a break in four out of five markets: UK, Germany, Finland and Spain in the time period 16-18 (between June 23 and 25, 2016). However for France, the plot reveals a break somewhere in between the time periods 14-16 (between June 21 and 23, 2016). The Chow Breakeven test however could not confirm any structural break for time series of UK, Spain and Finland, as the null hypothesis of no structural break is accepted. On the other hand, for two countries, France and Germany, there is some evidence of break at 5% and 10% confidence levels, respectively, and the date of break identified is June 23, 2016; this was the same date when the referendum on UK’s withdrawing from the EU took place.

 
 
 

A shift in the time series that is not according to one’s expectations is usually referred to as a ‘structural change’. If we ignore this shift and continue with our time series analysis, it might lead to huge errors. Moreover, the coefficients obtained from such a time series would also be unstable. In simple words, the regression line has a break and one must account for this break in estimating a time series model. We can give a number of examples when a structural break could have occurred, e.g., a break due to Great Depression, IT Boom, Subprime Crisis, Asian Financial Crisis, etc. Back home, structural break in time series could be associated with the beginning of economic reforms in 1991 or allowing entry of FII to invest in Indian capital markets. As a solution to this structural break problem, one can easily fit a piecewise linear model consisting of two or more straight lines (called segments) instead of usual one straight line OLS regression. This would also mean there would be two regressions, one for each of the sub samples with separate intercept and slope coefficients.

 
 
 

Financial Risk Management Journal, BREXIT Lead to a Structural Break, A Time Series Econometric Investigation, Stock Returns of Select EU Countries.