Pin-Huang Chou

Price limits, margin requirements, and default risk

This article investigates whether price limits can reduce the default risk and lower the effective margin requirement for a self‐enforcing futures contract by considering one more period beyond Brennan’s (1986) model to take into account the spillover of unrealized residual shocks due to price limits. The results show that, when traders receive no additional information, price limits can reduce the margin requirement and eliminate the default probability at the expense of a higher liquidity cost due to trading interruptions. Consequently, the total contract cost is higher than of that without price limits. When traders receive additional signals about the equilibrium price, we find that the optimal margin remains unchanged with or without the imposition of price limits, a result that is in conflict with Brennan’s assertion. Hence, we conclude that price limits may not be effective in improving the performance of a futures contract.

Modeling daily price limits

Abstract This paper characterizes the behavior of observed asset prices under price limits and proposes the use of two-limit truncated and Tobit regression models to analyze regression models whose dependent variable is subject to price limits. Through a proper arrangement of the sample, these two models, the estimation of which is easy to implement, are applied only to subsets of the sample under study, rather than the full sample. Using the estimation of simple linear regression model as an example, several Monte Carlo experiments are conducted to compare the performance of the maximum likelihood estimators (MLEs) based on these two models and a generalized method of moments (GMM) estimator developed by K. C. John Wei and R. Chiang. The results show that under different price limits and various distributional assumptions for the error terms, the MLEs based on the two-limit Tobit and truncated regression models and the GMM estimator perform reasonably well, while the naive OLS estimator is downward biased. Overall, the MLE based on the two-limit Tobit model outperforms the other estimators.

A Gibbs sampling approach to the estimation of linear regression models under daily price limits

Abstract In this paper, we propose a Bayesian approach using the Gibbs sampler to estimate linear regression models in which the dependent variable, the stock return, is subject to a price limit regulation. Assuming that the underlying ‘true’ stock price process is not affected by the price limits, we show that the observed stock returns are serially correlated when the sample contains limit stock prices. The linear model is shown to be a variant of the two-limit Tobit model subject to some form of censoring rule, and a Gibbs sampling approach is proposed to estimate the model. Examples based on real data as well as simulated data are presented.

Margins and Price Limits in Taiwan's Stock Index Futures Market

This study extends the framework of Brennan (1986) to find the cost-minimizing combination of spot limits, futures limits, and margins for stock and index futures in the Taiwan market. Our empirical results show that the cost-minimization combination of margins, spot price limits, and futures price limits is 7 percent, 6 percent, and 6 percent, respectively, when the index level is less than 7,000. When the index level ranges from 7,000 to 9,000, the efficient futures contract calls for a combination of 6.5 percent, 5 percent, and 6 percent. The optimal margin, reneging probability, and corresponding contract cost are less than those without price limits. Price limits may partially substitute for margin requirements in ensuring contract performance, with a default risk lower than the 0.3 percent rate that is accepted by the Taiwan Futures Exchange. On the other hand, though imposing equal price limits of 7 percent on both the spot and futures markets does not coincide with the efficient contract design, it does have a lower contract cost and margin requirement (7.75 percent) than that without imposing price limits (8.25 percent).

A Comparison of Hedge Effectiveness and Price Discovery between TAIFEX TAIEX Index Futures and SGX MSCI Taiwan Index Futures

This article uses daily data from July 21, 1998 to July 31, 2000 to examine the hedging effectiveness, price behavior, and lead-lag relationship of SGX MSCI Taiwan index futures and TAIFEX TAIEX futures. By applying the Bayesian approach using Gibbs sampler, we find that TAIFEX index futures has a better hedging performance. A variance ratio test reveals that mean reversion and negative correlation of returns exist in SGX index futures. Only TAIFEX TAIEX futures is cointegrated with TAIEX spot. The uni-directional Granger causality between the two futures markets and spot market are from SGX to TAIEX and from TAIEX to TAIFEX. In terms of price discovery, SGX MSCI Taiwan index futures play a more important role than TAIFEX TAIEX futures.

Do macroeconomic factors subsume market anomalies in long investment horizons

The main purpose of this study is to examine if macroeconomic variables could virtually subsume the size and BM anomalies for longer return intervals using Tokyo Stock Exchange-listed stocks. Most macroeconomic variables explain short-term returns within six months, with the industrial production as the only variable that persistently explains returns of all horizons ranging from one month to one year. Firm size does bear significant risk premium, but its significance diminishes for return intervals beyond three month when macroeconomic variables are included in the regression. BM is the only variable that significantly accounts for the cross-section of stock returns for all horizons, regardless of the inclusion of macroeconomic variables.

Factors, Characteristics and Endogenous Structural Breaks: Evidence from Japan

Using an updated Japanese sample covering the 1975-2006 period, we reexamine whether it is Fama and Frenchs (1993) three-factor model or Daniel and Titmans (1997) characteristic model that better explains stock returns in the Japanese market. In contrast to Daniel, Titman, and Wei (2001), we find that the three-factor model works well for this updated sample. Further analysis identifies a structural break date in October 1997, which coincides with the publication date of Daniel and Titmans article. In particular, the characteristic model is supported before 1997, but not after; the Japanese evidence is similar to the U.S. evidence, as documented by Davis, Fama, and French (2000).

Being good or being known: corporate governance, media coverage, and earnings announcements

Based on a sample of banking firms listed on the Taiwan Stock Exchange, we examine the impact of corporate governance and media coverage on the market reaction to unexpected earnings announcements. This study finds that positive media reports prior to bad earnings announcements have a positive short-term impact on the markets response to unexpected negative earnings, but the impact is reversed in the long term. In contrast, a better corporate governance quality has a persistent positive impact on markets reaction to unexpected negative earnings, especially when the quality of corporate governance is measured by pledge ratios. The study finding provides one central implication for managements: Yes, being good would pay off.

A test of relative efficiency between two sets of securities

Based on a Markov chain Monte Carlo method, namely the Gibbs sampler, a simple approach is proposed to compare the potential performances between two sets of securities. The maximum attainable Sharpe measure is used to measure the potential performance of a set of securities. The procedure is easy to implement and does not require large samples.

What Drives the Liquidity Premium: Factors or Characteristics?

We investigate whether the liquidity premium is better explained by the risk-based model or the characteristic-based model. Based on three widely-used liquidity measures that are supposed to reflect different aspects of liquidity, we find that liquidity as a characteristic carries a significant liquidity premium that is beyond the size and book-to-market effects. In addition, liquidity as a factor does not yield a significant risk premium beyond that provided by Fama and French’s (1993) three factors. Finally, in direct comparisons under a liquidity-augmented two-factor capital asset-pricing model, the liquidity premium is better characterized by a characteristic-based model rather than a risk-based model, especially for the Amihud (2002) liquidity measure and for the post-1964 period.