Excess Returns in Hospitality Stocks

Performance of hospitality stocks and financial ratios are relatively well discussed topics in hospitality finance. The current study contributes to the body of knowledge by attempting to identify if certain groups of hospitality stocks continually outperform market and if selected financial ratios can predict excess returns. Hospitality stocks betas were computed and most recent five-year annual returns were utilized for analysis. Study used Jensen＇s alpha to determine excess returns for various hospitality segments studied. Six major ratios were operationalized to determine the predictability of excess returns in hospitality stocks. Overall, the excess returns in hospitality company stocks were positive but no significance was found with an exception of one year. Out of six selected ratios, cash flow per share was determined to have significant predictive power for excess returns. In conclusions, study provides important implications for the investors and industry decision makers.

Innovation and Firm Performance： Evidence From the Capital Market

This paper examines the role of innovation in firm performance by drawing empirical evidence from the capital market. The current study analyzes risk premiums and risk-adjusted excess returns of a portfolio of the most innovative firms in the US from 2006 to 2010. The results show that average risk premiums of an equal-weighted portfolio of the most innovative finns in the US are economically larger than the CRSP2 value-weighted index risk premiums four years in a row from 2006 to 2009 and are economically greater than the standard and poor （S＆P） 500 index risk premiums from 2006 to 2010. The portfolio exhibits average statistically significant and positive risk-adjusted excess returns for the 3-year and 5-year holding period intervals. The findings serve as evidence of the favorable role of innovation in firm performance.

Downside risk and defaultable bond returns

This paper analyzes the influence of downside risk on defaultable bond returns.By introducing a defaultable bond-trading model,we show that the decline in market risk tolerance and information accuracy leads to trading loss under downside conditions.Our empirical analysis indicates that downside risk can explain a large proportion of the variation in yield spreads and contains almost all valid information on liquidity risk.As the credit level decreases,the explanatory power of downside risk increases significantly.We also investigate the predictive power of downside risk in cross-sectional defaultable bond excess returns using a portfolio-level analysis and Fama-Mac Beth regressions.We find that downside risk is a strong and robust predictor for future bond returns.In addition,due to the higher proportion of abnormal transactions in the Chinese bond market,downside risk proxy semi-variance can better explain yield spreads and predict portfolio excess returns than the proxy value at risk.

Tail asymptotic expansions for L-statistics

We derive higher-order expansions of L-statistics of independent risks X1,..., Xn under conditions on the underlying distribution function F. The new results are applied to derive the asymptotic expansions of ratios of two kinds of risk measures, stop-loss premium and excess return on capital, respectively. Several examples and a Monte Carlo simulation study show the efficiency of our novel asymptotic expansions. Keywords smoothly varying condition, second-order regular variation, tail asymptotics, value-at-risk, con- ditional tail expectation, largest claims reinsurance, ratio of risk measure, excess return on capital