The Friday Effect in European Securitized Real Estate Index Returns

This study extends research on the day-of-the-week effect towards European real estate indices. We examine this anomaly for several European securitized real estate index returns between 1990 and 2003. Although the countries under analysis have unique country-specific patterns, we find that eight out of eleven European countries exhibit abnormally high Friday returns. Moreover, two different Europe indices also exhibit the Friday anomaly. The anomaly is robust with respect to extreme observations, alternative specifications and several well-known calendar effects.     

American Parisian options

In this article, we describe the various sorts of American Parisian options and propose valuation formulae. Although there is no closed-form valuation for these products in the non-perpetual case, we have been able to reformulate their price as a function of the exercise frontier. In the perpetual case, closed-form solutions or approximations are obtained by relying on excursion theory. We derive the Laplace transform of the first instant Brownian motion reaches a positive level or, without interruption, spends a given amount of time below zero. We perform a detailed comparison of perpetual standard, barrier and Parisian options.     

Valuation of vulnerable American options with correlated credit risk

This article evaluates vulnerable American options based on the two-point Geske and Johnson method. In accordance with the Martingale approach, we provide analytical pricing formulas for European and multi-exercisable options under risk-neutral measures. Employing Richardson’s extrapolation gets the values of vulnerable American options. To demonstrate the accuracy of our proposed method, we use numerical examples to compare the values of vulnerable American options from our proposed method with the benchmark values from the least-square Monte Carlo simulation method. We also perform sensitivity analyses for vulnerable American options and show how the prices of vulnerable American options vary with the correlation between the underlying assets and the option writer’s assets.      

A semi-analytic method for valuing high-dimensional options on the maximum and minimum of multiple assets

Valuing high-dimensional options has many important applications in finance but when the true distributions are unknown or complex, numerical approximations must be used. Approximation methods based on Monte-Carlo simulation show a steep trade-off between estimation accuracy and computational efficiency. This article presents an alternative semi-analytic approximation method for pricing options on the maximum or minimum of multiple assets with unknown distributions. Computational efficiency is shown to improve significantly without sacrificing estimation accuracy. The method is illustrated with applications to options on underlying assets with mean-reverting prices, time-dependent correlations, and stochastic volatility The authors would like to thank the two anonymous referees, the associate editor, and Dr. Jess H. Chua at the University of Calgary for valuable comments and insights on this research. This research was partly supported by NUS grant R-146-000-059-112     

Assessing the Least Squares Monte-Carlo Approach to American Option Valuation

A detailed analysis of the Least Squares Monte-Carlo (LSM) approach to American option valuation suggested in Longstaff and Schwartz (2001) is performed. We compare the specification of the cross-sectional regressions with Laguerre polynomials used in Longstaff and Schwartz (2001) with alternative specifications and show that some of these have numerically better properties. Furthermore, each of these specifications leads to a trade-off between the time used to calculate a price and the precision of that price. Comparing the method-specific trade-offs reveals that a modified specification using ordinary monomials is preferred over the specification based on Laguerre polynomials. Next, we generalize the pricing problem by considering options on multiple assets and we show that the LSM method can be implemented easily for dimensions as high as ten or more. Furthermore, we show that the LSM method is computationally more efficient than existing numerical methods. In particular, when the number of assets is high, say five, Finite Difference methods are infeasible, and we show that our modified LSM method is superior to the Binomial Model.     

发电企业上市公司引用股票期权激励机制探讨

分析了股票期权激励制度给上市公司带来的效益以及在中国的应用模式,并按九个方面阐述了股票期权激励制度设计。     

Timing of earnings restatements: CEO equity compensation and market reaction

This study investigates the impact of chief executive officers’ (CEO) compensation on their choices regarding the timing of earnings restatements. The results indicate a negative relationship between options exercised and lags in disclosing the restated earnings, suggesting that managers who exercise options in a given year tend to release information quickly. This effect is more pronounced if the options are exercised after the dark period. We also find that the market penalises longer lags in the restatement disclosure. It seems that the CEO would try to optimise the timing of information release so as to balance the costs and benefits.     

金融投机、实需与国际大宗商品价格——信息摩擦视角下的大宗商品价格影响机制研究

本文实证考察了2005-2015年金融投机和实需对国际大宗商品现货价格的影响及其作用机理。首先对具有信息噪音属性的金融投机进行了明确识别。其次,从多个维度出发区分市场信息摩擦状态,定量分析不同信息摩擦环境中金融投机和实需的影响差异。研究发现:大宗商品价格在长期中由实需因素主导,短期中由金融投机主导;短期中,相对于低信息摩擦环境,在市场波动性较高、金融压力上升以及投资者情绪高涨的高信息摩擦环境中,以金融投机为主的信息噪音对大宗商品价格的影响更强。进一步分析证实,相比于低信息摩擦环境,高信息摩擦环境中金融交易者的市场份额反而降低。据此,本文提出稳定大宗商品市场的关键在于提高市场透明度,减少信息摩擦,从市场质量出发降低信息噪音的影响。     

“Success breeds success” or “Pride goes before a fall”?: Teams and individuals in multi-contest tournaments

We study the impact of progress feedback on players' performance in multi-contest team tournaments, in which team members' efforts are not directly substitutable. In particular, we employ a real-effort laboratory experiment to understand, in a best-of-three tournament, how players' strategic mindsets change when they compete on a team compared to when they compete individually. Our data corroborate the theoretical predictions for teams: Neither a lead nor a lag in the first component contest affects a team's performance in the subsequent contests. In individual tournaments, however, contrary to the theoretical prediction, we observe that leaders perform worse—but laggards perform better—after learning the outcome of the first contest. Our findings offer the first empirical evidence from a controlled laboratory of the impact of progress feedback between team and individual tournaments, and contribute new insights on team incentives.     

REAL OPTIONS AND THE CROSS‐SECTION OF EXPECTED STOCK RETURNS

This paper surveys the theoretical literature investigating the effect of firms’ investment flexibility on the cross‐section of expected stock returns. Real options analysis derives firms’ value‐maximizing investment policies as functions of exogenous fundamental drivers of profitability and calculates firms’ market values as functions of the same variables. These functions yield the relationship between expected stock returns and firm fundamentals. Several plausible explanations for the value premium – the high average stock returns earned by firms with high book‐to‐market ratios – emerge from this literature.