سقوط بازار سهام، ویژگی های شرکت و بازده سهام

A number of studies have investigated the causes and effects of stock market crashes. These studies mainly focus on the factors leading to a crash and on the volatility and co-movements of stock market indexes during and after the crash. However, how a stock market crash affects individual stocks and if stocks with different financial characteristics are affected differently in a stock market crash is an issue that has not received sufficient attention. In this paper, we study this issue by using data for eight major stock market crashes that have taken place during the December 31, 1962–December 31, 2007 period with a large sample of US firms. We use the event-study methodology and multivariate regression analysis to study the determinants of stock returns in stock market crashes.

Studying stock market crashes has long been a popular research topic in finance. Arshanapalli and Doukas (1993) and others study the effects of the 1987 global stock market crash on the co-movements of national stock markets. Pan et al. (2001) and others examine the role of emerging markets on the 1997 global stock market crash. Hon et al. (2004) and others investigate the effect of the September 11, 2001 terrorist attacks on the world’s stock markets. Previous studies mainly focus on the factors causing stock market crashes and on the volatility and co-movements of stock markets during and after the crashes. However, the impact of company financial characteristics on stock returns during stock market crashes has not received sufficient attention. In the traditional capital asset pricing model (CAPM), a stock’s returns are explained by its market risk (beta). There are many empirical tests of the CAPM conducted during normal periods. However, there are no studies that investigate if beta has a significant influence on stock returns in stock market crashes. Fama and French, 1992 and Fama and French, 1993 present a three-factor capital asset pricing model. They demonstrate that size and market-to-book ratio are two significant proxies for risk that can help explain asset returns better than using beta alone. There are many empirical studies that test the Fama–French model during normal periods. However, there are no studies that investigate if size and market-to-book ratio can affect stock returns significantly in stock market crashes. The traditional CAPM relies on market risk and it assumes that company-specific idiosyncratic risk can be diversified away. However, Xu and Malkiel (2003) and others show that company-specific idiosyncratic risk and expected earnings growth are positively related. Amihud et al. (1990) observe that the decline in liquidity contributed significantly to the decline in stock prices in the 1987 stock market crash. Amihud (2002) finds a positive relationship between illiquidity and stock returns. The findings of these studies suggest that company-specific idiosyncratic risk factors and stock-specific illiquidity characteristics can be significant determinants of stock returns in stock market crashes. In this paper, we study the effects of several company-specific, stock-specific, and industry-related characteristics on stock returns in eight major stock market crashes with data for a large sample of US firms using the event-study methodology and multivariate regression analysis. We find that stocks with higher betas, larger capitalization, lower levels of illiquidity, and more return volatility prior to the crash date have significantly lower returns in stock market crashes. We also find that the stocks of companies with higher debt ratios, higher levels of liquid assets, lower cash flow per share, and lower profitability tend to have lower returns in crashes. We observe a significant positive momentum effect for the cumulative stock returns earned one-week prior to the crash date in most crashes. Stocks with higher returns one-week prior to the crash date tend to have higher returns on the crash day. We observe a significant negative reversal effect for the cumulative stock returns earned three months and three years prior to the crash date in most crashes. Stocks with higher returns for three months and three years prior to the crash date tend to have more losses on the crash day. We also find that high tech firms lose more value in most crashes compared with firms in other industries. The paper is organized as follows: In Section 2, we describe our sample. In Section 3, we explain our methodology. We present our regression results in Section 4. We present some robustness tests in Section 5. In Section 6, we study the cumulative returns of high-cap firms during the three-day period after each crash. Section 7 summarizes the paper and presents our conclusions.

Studying stock market crashes has long been a popular research topic in finance. However, previous studies generally focus on the causes of crashes and the co-movements and volatility of stock markets during and after crashes. The role of stock, firm, and industry characteristics in explaining the impact of crashes on individual stock returns has not received sufficient attention. In this paper, we use the event-study methodology and multivariate regression analysis to study this issue with a large sample of US firms in eight major stock market crashes that have taken place during the December 31, 1962–December 31, 2007 period. We find that stocks with higher betas, larger capitalization, lower levels of illiquidity, and more return volatility one-year prior to the event date lose more value on crash days. We also find that the stocks of companies with higher debt ratios, higher levels of liquid assets, lower cash flow per share, and lower asset profitability tend to lose more value on the crash day. We find a positive momentum effect for the cumulative stock returns earned one-week prior to the crash date and a negative reversal effect for the cumulative stock returns earned three months and three years prior to the crash date in most stock market crashes. We find that high-cap firms react faster to stock market crashes and high-cap firm returns lead low-cap firm returns in the downward direction on the crash day. We also find that high-cap firm returns lead low-cap firm returns and they earn significantly higher returns during the three-day recovery period after the crash day in most crashes. Our findings with crash data in this study provide support for the previous findings by Lo and MacKinlay, 1990 and Richardson and Peterson, 1999, and others that large firm returns lead small firm returns and large firms respond faster to new information compared with small firms.