2\ We analyze these effects by considering both aggregate and individual stock indices. We first consider a global equity index, the BSE SENSEX quoted in the Bombay stock market. We further consider 12 individual stocks. To account for financial stress in the Indian stock markets, we define several variables. First, the variance of returns serves as a proxy of market volatility. It is measured by either the squared returns or the in‐sample forecasts obtained from a GARCH(1,1) model. Secondly, we consider indicators of liquidity risk in the stock markets to reflect a situation in which investors may not be able to sell or buy an asset at a price close to the preceding traded prices. The two proxies we consider for capturing this are the spread between the bid and ask prices, and, a illiquidity ratio proposed by Amihud (2002). As measures of financial stress in the US stock markets, we consider the following variables. Firstly, as a measure of funding liquidity in the US interbank market, we consider the daily 3‐month US dollar Libor overnight index swap (LIBOR‐OIS). A second variable captures the default risk of large US financial institutions (we compute the average of their credit default swap spread (CDS spreads). Thirdly, to account for the high uncertainty that has characterized the stock market during the 2008 financial turmoil, we consider the volatility of the S&P 500 index. Finally, we consider the exchange rate of the Indian Rupee against the dollar. Indeed, because. The data sample ranges from January 2000 until March 2009 and consists of daily observations.
3\ The empirical models are based on the interpretation of the impulse response functions of VAR models in which we examine how different stress indicators in the Indian stock markets react to changes in the US financial variables. We further consider the time‐varying influence of the latter by estimating simple linear regressions based on Kalman‐filter models.
4\ Our results points to a signification contagion effect after the period following the Lehman Brothers collapse. This is shown by both the stylized fact on the volatility and illiquidity indicators and by the Kalman filter analysis. The VAR analysis suggest that the impact was “structural” and not just temporary (due to the high persistence of shocks), which means that the observed drop in the Indian equities was not only the result of contagion behaviors but more generally of financial channels reflecting the important interconnectedness between the US and Indian Markets.