Hedging,Financing and Investment Decisions: A Simultaneous Equations Framework

We empirically investigate the interactions among hedging, financing, and investment decisions. We argue that the way in which hedging affects a firm's financing and investing decisions differs for firms with different growth opportunities. We find that high growth firms increase their investment, but not leverage, by hedging. However, we also find that firms with few investment opportunities use derivatives to increase their leverage.     

A theoretical framework to evaluate different margin‐setting methodologies

The margin system is the first line of defense against the default risk of a clearinghouse. From the perspectives of a clearinghouse, the utmost concern is to have a prudential system to control the default exposure. Once the level of prudentiality is set, the next concern will be the opportunity cost of the investors, because high opportunity cost discourages people from hedging futures, and thus defeats the function of a futures market. In this article, we first develop different measures of prudentiality and opportunity cost. We then formulate a statistical framework to evaluate different margin‐setting methodologies, all of which strike a balance between prudentiality and opportunity cost. Three margin‐setting methodologies, namely, (1) using simple moving averages; (2) using exponentially weighted moving averages; (3) using a GARCH approach, are applied to the Hang Seng Index futures. Keeping the same prudentiality level, it is shown that the one using a GARCH approach by and large gives the lowest average overcharge. © 2004 Wiley Periodicals, Inc. Jrl Fut Mark 24:117–145, 2004     

The index futures markets: Is screen trading more efficient?

This article uses a nonparametric test based on the arc‐sine law (see, e.g., Feller, 1965 ), which involves comparing the theoretical distribution implied by an intraday random walk with the empirical frequency distribution of the daily high/low times, in order to address the question of whether the abandonment of pit trading has been associated with greater market efficiency. If market inefficiencies result from flaws in the market microstructure of pit trading, they ought to have been eliminated by the introduction of screen trading. If, on the other hand, the inefficiencies are a reflection of investor psychology, they are likely to have survived, unaffected by the changeover. We focus here on four cases. Both the FTSE‐100 and CAC‐40 index futures contracts were originally traded by open outcry and have moved over to electronic trading in recent years, so that we are able to compare pricing behavior before and after the changeover. The equivalent contracts in Germany and Korea, on the other hand, have been traded electronically ever since their inception. Our results overwhelmingly reject the random‐walk hypothesis both for open‐outcry and electronic‐trading data sets, suggesting there has been no increase in efficiency as a result of the introduction of screen trading. One possible explanation consistent with our results would be that the index futures market is characterized by intraday overreaction. © 2004 Wiley Periodicals, Inc. Jrl Fut Mark 24:337–357, 2004     

An empirical analysis of the relationship between the hedge ratio and hedging horizon: A simultaneous estimation of the short‐ and long‐run hedge ratios

This article analyzes the effects of the length of hedging horizon on the optimal hedge ratio and hedging effectiveness using 9 different hedging horizons and 25 different commodities. We discuss the concept of short‐ and long‐run hedge ratios and propose a technique to simultaneously estimate them. The empirical results indicate that the short‐run hedge ratios are significantly less than 1 and increase with the length of hedging horizon. We also find that hedging effectiveness increases with the length of hedging horizon. However, the long‐run hedge ratio is found to be close to the naïve hedge ratio of unity. This implies that, if the hedging horizon is long, then the naïve hedge ratio is close to the optimum hedge ratio. © 2004 Wiley Periodicals, Inc. Jrl Fut Mark 24:359–386, 2004     

General‐to‐Specific Model Selection Procedures for Structural Vector Autoregressions*

Structural vector autoregressive (SVAR) models have emerged as a dominant research strategy in empirical macroeconomics, but suffer from the large number of parameters employed and the resulting estimation uncertainty associated with their impulse responses. In this paper, we propose general‐to‐specific (Gets) model selection procedures to overcome these limitations. It is shown that single‐equation procedures are generally efficient for the reduction of recursive SVAR models. The small‐sample properties of the proposed reduction procedure (as implemented using PcGets) are evaluated in a realistic Monte Carlo experiment. The impulse responses generated by the selected SVAR are found to be more precise and accurate than those of the unrestricted VAR. The proposed reduction strategy is then applied to the US monetary system considered by Christiano, Eichenbaum and Evans (Review of Economics and Statistics, Vol. 78, pp. 16–34, 1996) . The results are consistent with the Monte Carlo and question the validity of the impulse responses generated by the full system.     

Syndicated Loan Announcements and Borrower Value

Announcements of syndication loans increase borrowers' shareholder wealth if they are revolving credit agreements but not if they are term loans. Share price responses to revolving credit announcements are positive and significant, whereas the wealth effect for term loans is negative and significant. The results show that announcements from both the financial press and commercial information providers can affect borrower share price reaction. Overall, single syndication announcements appear to be more newsworthy than multiple announcements reported in the financial press, and we find evidence of information leakage, post‐announcement drift, or both.     

Improved estimation of portfolio value‐at‐risk under copula models with mixed marginals

Portfolio value‐at‐risk (PVAR) is widely used in practice, but recent criticisms have focused on risks arising from biased PVAR estimates due to model specification errors and other problems. The PVAR estimation method proposed in this article combines generalized Pareto distribution tails with the empirical density function to model the marginal distributions for each asset in the portfolio, and a copula model is used to form a joint distribution from the fitted marginals. The copula–mixed distribution (CMX) approach converges in probability to the true marginal return distribution but is based on weaker assumptions that may be appropriate for the returns data found in practice. CMX is used to estimate the joint distribution of log returns for the Taiwan Stock Exchange (TSE) index and the associated futures contracts on SGX and TAIFEX. The PVAR estimates for various hedge portfolios are computed from the fitted CMX model, and backtesting diagnostics indicate that CMX outperforms the alternative PVAR estimators. © 2006 Wiley Periodicals, Inc. Jrl Fut Mark 26:997–1018, 2006     

构建旅游院校教师培训体系的思考--以北京联合大学旅游学院为例

旅游院校教师培训体系的建构问题是旅游院校教师培训建设中的空白领域,通过对北京联合大学旅游学院教师培训的现状及存在的问题分析,试图从旅游院校教师培训体系构建的维度指标选择原则及教师培训体系构建中需要注意的几个侧重点出发,来探讨旅游高等院校的教师培训体系的构建问题.     

Looking for contagion in currency futures markets

This article tests whether there are pure contagion effects in both conditional means and volatilities among British pound, Canadian dollar, Deutsche mark, and Swiss franc futures markets during the 1992 ERM crisis. A conditional version of international capital asset pricing model (ICAPM) in the absence of purchasing power parity (PPP) is used to control for economic fundamentals. The empirical results indicate that overall there are no mean spillovers among those futures markets, but they are detected during the crisis period. That is, past return shocks originating in any one of the four markets have no impact on the other three markets during the entire sample period, suggesting that these markets are weak‐form efficient. However, this weak‐form market efficiency fails to hold during the market turmoil, especially for British pound and Swiss franc, and the sources of contagion‐in‐mean effects are mainly due to the return shocks originating in three European currency futures markets. As for the contagion‐in‐volatility, it is detected for British pound only because its conditional volatility is influenced by the negative volatility shocks from Canadian dollar, Deutsche mark, and Swiss franc, with Deutsche mark playing the dominant role in generating these shocks. JEL Classifications: C32; F31; G12. © 2003 Wiley Periodicals, Inc. Jrl Fut Mark 23:957–988, 2003