Purpose – This paper aims to assess the impact of the global financial crisis of 2007-09 on the risk structure of S&P 500 firms by examining their market, active, and residual risks before and during the crisis. Design/methodology/approach – The classic one-factor model is estimated for each firm in the S&P 500 to decompose risk into market, active, and residual components. Five sets of regression estimates based on monthly return data are used: 2002-06, 2003-07, 2004-08, 2005-09, and 2006-10. The estimates provide insight into the risk structure of S&P 500 firms before and during the crisis. Findings – The average correlation coefficient between S&P 500 firms rose during the crisis from 0.20 to 0.35, an increase of 75 percent. Although the results indicate that active and residual risks are significant across the firms and across the periods, the impact of the financial crisis was mostly on market risk. The increase in risks was pronounced for financial firms, especially insurance companies, and industrial firms, especially “hard” manufacturing. Research limitations/implications – Because the study focuses on the global financial crisis of 2007-09, researchers should be careful about generalizing the results to the post-crisis period. Practical implications – Investors should be aware that equity portfolio risk reduction during major crises can be hard to achieve because the average correlation coefficient between stock returns may rise significantly, crimping the efficacy of diversification. Originality/value – It was very difficult for equity investors to shield themselves from the risk associated with the global financial crisis of 2007-09.
The relationship between stock prices and exchange rates has preoccupied the minds of economists since both play important roles in influencing the development of a country’s economy. Many factors, such as enterprise performance, dividends, stock prices of other countries, gross domestic product, exchange rates, interest rates, current account, money supply, employment, their information etc. have an impact on daily stock prices (Kurihara, 2006: p.376). This paper investigates the nature of relationship between stock prices and exchange rates in India. For the purpose of determining relationship between the S & P CNX Nifty and Exchange Rate (USD/INR) the techniques of correlation and regression analysis has been applied. For using the above techniques SPSS tool has been used. The results suggest that there is causal relationship between stock prices and the exchange rate and fluctuations in exchange rate affect the movement of S&P CNX Nifty.
We document that the implied volatility skew of S&P 500 index puts is non-decreasing in the disaster index and risk-neutral variance, contrary to the implications of a broad class of no-arbitrage models. The key to the puzzle lies in recognizing that, as the disaster risk increases, customers demand more puts as insurance while market makers become more credit-constrained in writing puts. The resulting increase in the equilibrium price is more pronounced in out-of-the-money than in-the-money puts, thereby steepening the implied volatility skew and resolving the puzzle. Consistent with the data, the model also implies that the equilibrium net buy of puts is decreasing in the disaster index, variance, and their price. The data shows a significant decreasing relationship between the IV skew and the net buy and no relationship in other periods, also explained by the model.
We examine the possible determinants of the observed implied volatility skew of S&P 500 index options. We document that order flow toxicity measured by Volume- Synchronized Probability of Informed Trading (VPIN, Easley et al., 2012) is an important determinant of the slope of the volatility skew besides transactions costs and net buying pressure. We further analyze the relation at macroeconomic announcements and find that the effect of uncertainty resolution dominates when there is an announcement and when the surprise component of the announcement is higher. Model-free risk-neutral skewness measure which is highly correlated with slope is also significantly associated with VPIN.
We document that the implied volatility skew of S&P 500 index puts is non-decreasing in the disaster index and risk-neutral variance, contrary to the implications of a broad class of no-arbitrage models. The key to the puzzle lies in recognizing that, as the disaster risk increases, customers demand more puts as insurance while market makers become more credit-constrained in writing puts. The resulting increase in the equilibrium price is more pronounced in out-of-the-money than in-the-money puts, thereby steepening the implied volatility skew and resolving the puzzle. Consistent with the data, the model also implies that the equilibrium net buy of puts is decreasing in the disaster index, variance, and their price. The data shows a significant decreasing relationship between the IV skew and the net buy and no relationship in other periods, also explained by the model.
Roll, Schwartz, and Subrahmanyam (2007) investigate the linear relationship between stock market liquidity and index futures-cash basis. We extend their work and examine nonlinear relationship between the two variables of interests, in particular, tail dependence. We find that the tail dependence is asymmetric and varies significantly over times. The lower tail dependence between changes in (il) liquidity measured by bid–ask spread of S&P 500 index and changes in absolute value of S&P 500 index futures-cash basis is almost zero and the upper tail dependence is positive and significantly different from zero. The results suggest that an increase in liquidity is not always associated with a decrease in basis. However, a reduction in liquidity is significantly associated with an increase in basis. At the extreme situation, the link between changes in basis and changes in liquidity can break down. Arbitrage profits cannot be realized and hedging becomes less effective.
We ask whether directors on corporate boards contribute to firm performance as individuals. From the universe of the S&P 1,500 firms since 1996 we track 2,062 directors who serve on multiple boards over extended periods of time. Our initial findings suggest that the presence of these directors is associated with substantial performance shifts (director fixed effects). Closer examination shows that these effects are statistical artifacts and we conclude that directors are largely fungible. Moreover, we contribute to the discussion of the fixed effects method. In particular, we highlight that the selection of the randomization method is pivotal when generating placebo benchmarks.
Using weekly returns of S&P 500 constituents, we study the time- varying correlation structure during the period of 2006 to mid- 2011. Contrary to most of the previous correlation studies of many assets, we do not use rolling correlations but the DCC MV-GARCH model with the MacGyver strategy proposed by Engle (2009). We find empirical evidence that the correlation structure tends to change significantly during the periods of high volatility and market downturns.