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Governance with multiple objectives: Evidence from top executive turnover in China

Journal of Corporate Finance 2009 15(2), 230-244
We examine the relationship between Chief Executive Officer (CEO) turnover and the performance of listed Chinese firms and obtain two results. First, we find a negative relationship between the level of pre-turnover profitability and CEO turnover when firms are incurring financial losses, but no such relationship when they are making profits. Second, there is an improvement in post-turnover profitability in loss-making firms, but no such improvement in profit-making firms. These results indicate the existence of a time-varying objective function, whereby shareholders have a greater incentive to discipline their CEOs on the basis of financial performance when their firms are incurring financial losses rather than profits.

Effects of the volatility smile on exchange settlement practices: The Hong Kong case

Journal of Banking & Finance 2009 33(1), 98-112
The well-documented volatility smile phenomenon in the US options market has affected the option settlement practices of other markets. To settle Hang Seng Index (HSI) options, the Hong Kong Stock Exchange artificially builds in a piecewise linear “smile” or “sneer” volatility function, which is determined daily by market makers rather than directly by market forces. In this study, we investigate the time-varying settlement function and find the following economic determinants of the volatility function: lag parameters, current-day HSI returns, the distribution of HSI returns, transaction costs as proxied by the bid-ask spread, and the “Monday effect”. For evaluation purposes, we use as a benchmark the estimated piecewise linear volatility function as directly driven by market forces. The comparison analyses show that base volatilities set by market makers run somewhat high, while downside slopes are not steep enough. This results in the overpricing of the lion’s share of traded options. An economic determinants analysis of market-force-driven parameters reveals that market makers can better align artificial volatility parameters both by reducing reliance on the function parameters of prior days and by more precisely accounting for current-day HSI returns, option time-to-maturity, bid-ask spreads and buying pressure.