Focusing on Environmental, Social and Governance (ESG) responsible investments, this study examines the historical and forecasted volatility and dynamic correlations between Emerging Markets in Europe, Asia and Latin America. By complementing the previous studies that provide evidence for how high ESG-ratings can reduce volatility in stock prices, regardless of which market, we seek to find if this is true in Emerging Markets. We additionally incorporate an analysis of dynamic correlations between Emerging Markets to see potential diversification benefits, which can be crucial in risk management. Data selection is based on daily closing prices of six different Emerging Markets indices. Three indices capturing the traditional Emerging Markets and three more only consisting of firms with a high ESG-rating, considered to be ESG Leaders. The sampled period is between January 2020 to January 2024. Data was processed through the DCC- GARCH(1,1) model to measure historical and forecasted volatility and dynamic correlations. The model uses past information to predict future values, meaning that past volatility and correlations influence forecasted volatility and correlations. This allows for a nuanced understanding of how the volatility and correlations have evolved and how they are forecast to change between these Emerging Markets. Key findings suggest that Asia can work as the diversification benefactor, as it is the least volatile Emerging Market and the ESG Leaders in Asia are showing a lower dynamic correlation with the ESG Leaders in the other Emerging Markets. Further results indicate that Europe is the most volatile Emerging Market, including the ESG Leaders. Furthermore, ESG Leaders in Europe and Latin America were seen to have the best DCC-GARCH filtered daily returns, while also having the highest dynamic correlation. This means that a portfolio with these two assets tends to be more volatile as shocks in daily returns move in tandem.
| Identifer | oai:union.ndltd.org:UPSALLA1/oai:DiVA.org:liu-204222 |
| Date | January 2024 |
| Creators | Valencia Söderberg, Dan, Truong, Martin |
| Publisher | Linköpings universitet, Nationalekonomi, Linköpings universitet, Filosofiska fakulteten |
| Source Sets | DiVA Archive at Upsalla University |
| Language | English |
| Detected Language | English |
| Type | Student thesis, info:eu-repo/semantics/bachelorThesis, text |
| Format | application/pdf |
| Rights | info:eu-repo/semantics/openAccess |
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