دانلود رایگان مقاله سرریز نوسانات بین قیمت نفت و بازار سهام نقض ساختاری

Abstract

This paper employs univariate and bivariate GARCH models to examine the volatility of oil prices and US stock market prices incorporating structural breaks using daily data from July 1, 1996 to June 30, 2013. We endogenously detect structural breaks using an iterated algorithm and incorporate this information in GARCH models to correctly estimate the volatility dynamics. We find no volatility spillover between oil prices and US stock market when structural breaks in variance are ignored in the model. However, after accounting for structural breaks in the model, we find strong volatility spillover between the two markets. We compute optimal portfolio weights and dynamic risk minimizing hedge ratios to highlight the significance of our empirical results which underscores the serious consequences of ignoring these structural breaks. Our findings are consistent with the notion of cross-market hedging and sharing of common information by financial market participants in these markets.

7. Summary and concluding remarks

This paper employs univariate and bivariate GARCH models to examine volatility dynamics of oil and the stock market return series using daily data from July 1, 1996 to June 30, 2013. We detect structural breaks in volatility of oil and stock market returns endogenously using an iterated algorithm. We find significant direct and indirect transmission of volatility between oil and the stock market if structural breaks are incorporated into the model. However, if we (erroneously) ignore structural breaks in variance, then we do not find any direct or indirect volatility spillover effects between these two important markets. This paper makes a timely and essential contribution by accurately estimating the volatility dynamics of oil and the stock market. Understanding the behavior of volatility in oil and stock prices is not only important for derivative valuation and hedging decisions but also has significant consequences for broader financial markets, the oil industry, and the overall economy. Since many different financial assets are traded based on these series, it is important for financial market participants to understand the volatility transmission mechanism across these series over time in order to make appropriate decisions. We compute optimal portfolio weights and dynamic risk minimizing hedge ratios to highlight the significance of our findings. Our results support the idea of cross-market hedging and sharing of common information by market participants.