Volatility and Predictability – Excess Returns in Emerging Markets
Emerging markets is a whole different game when compared to fully developed markets such as the United States and Great Britain. With ever ongoing uncertainties in the emerging markets, we are bound to face difficulties, be it political instability or crazy monetary policies. Exchange rates of various emerging market countries is key to the respective countries’ growth. In our analysis, we calculate the excess returns in emerging market currencies compared over the US market returns. We also try to find the interdependence of different exchange rates by applying the correlation on Microsoft Excel Analysis package. We have the arithmetic means of 3-month and 6-month excess returns for Philippines, Korea and India. Finally, we would be performing a Granger-Causality test using MATLAB to see the linkage of excess returns on different exchange rates and conclude on this contagion effect.
We have the arithmetic mean for India, Korea, and Philippines in the table. For the data from January 2001 to October 2016, we observe that only Korea has had a positive mean for 3-month excess returns, while all other countries under observation have returned a negative average over the period. Table-1 gives us the correlation matrix for the countries for 3 month excess returns. We notice that there is no evidence of any perfect multicollinearity. Though the correlation values are insignificantly low for the 3-month excess returns between the three countries, they are still positively correlated amongst each other. The correlation between India and Philippines for 3-month excess returns is the highest at 0.2411 amongst the comparable. Table-2 gives us the correlation matrix for the countries for 6 month excess returns. We note that Korea and India have the highest correlation for 6month excess returns at 0.1622. Philippines and Korea’s 6 month excess returns for 6 months is the most negatively correlated at -0.2734. India and Philippines are slightly negatively correlated.
Granger