Dynamic interactions among selected world stock indices: a VAR approach

Abstract

The present study focused on examining the dynamic and causal relationships among selected world stock market indices. The growing importance of dynamic interactions among the stock indices have emerged as a focal point of research, driven by the recognition that financial markets are interconnected and interdependent. To achieve the above stated objective, multivariate vector autoregressive (VAR) approach is applied. For which the monthly time series data on the selected indices are obtained for the period 2010-2024. The required data was sourced from yahoofinance.com and the analysis was conducted using RStudio software version 2022.12.0+353 and MS Excel. We found that almost all the indices exhibit a positive and significant impact from their own past values on their future values and they are expected to increase over the next eight months. The impulse response function analysis reveals that only shocks in NSE are positively influenced by their own past values, along with the past values of other indices. Additionally, the FEVD test results indicate that most of the variance in each index is attributable to their own shocks, with the exception of TSX and DAX.

Keywords

• causality
• forecasts
• indices
• shocks
• stationarity