General closed-form basket option pricing bounds

This article presents lower and upper bounds on the prices of basket options for a general class of continuous-time financial models. The techniques we propose are applicable whenever the joint characteristic function of the vector of log-returns is known. Moreover, the basket value is not required to be positive. We test our new price approximations on different multivariate models, allowing for jumps and stochastic volatility. Numerical examples are discussed and benchmarked against Monte Carlo simulations. All bounds are general and do not require any additional assumption on the characteristic function, so our methods may be employed also to non-affine models. All bounds involve the computation of one-dimensional Fourier transforms; hence, they do not suffer from the curse of dimensionality and can be applied also to high-dimensional problems where most existing methods fail. In particular, we study two kinds of price approximations: an accurate lower bound based on an approximating set and a fast bounded approximation based on the arithmetic-geometric mean inequality. We also show how to improve Monte Carlo accuracy by using one of our bounds as a control variate.     

大学生课外体育锻炼的影响因素分析

课外体育锻炼也是学校体育教学的一部分,本文分析我国高校大学生课外体育锻炼的影响因素,并提出大学生开展课外体育健身活动的建议,促进大学生的健康成长。     

TRUE UPPER BOUNDS FOR BERMUDAN PRODUCTS VIA NON-NESTED MONTE CARLO

We present a generic non-nested Monte Carlo procedure for computing true upper bounds for Bermudan products, given an approximation of the Snell envelope. The pleonastic "true" stresses that, by construction, the estimator is biased above the Snell envelope. The key idea is a regression estimator for the Doob martingale part of the approximative Snell envelope, which preserves the martingale property. The so constructed martingale can be employed for computing tight dual upper bounds without nested simulation. In general, this martingale can also be used as a control variate for simulation of conditional expectations. In this context, we develop a variance reduced version of the nested primal-dual estimator. Numerical experiments indicate the efficiency of the proposed algorithms.     

A real options perspective on the future of the Euro

A break-up of the Eurozone is no longer regarded as implausible. This will be a costly and irreversible decision in conditions of continuing uncertainty; therefore it is amenable to analysis in the real options framework. We do so by solving as an n-dimensional optimal stopping problem with country-specific shocks and “convergence” of member economies. We compare a complete break-up with individual country departures. In calibrated solutions for a symmetric case we find a non-negligible but small option value. Furthermore, we find a new theoretical result on the non-monotonicity of abandonment threshold with respect to volatility.     

The effects of employee stock option plans on operating performance in Chinese firms

As a part of the ongoing liberalization of the marketplace, Chinese regulators adopted the guideline called “Regulation of Equity Incentive Plans (trial)” to allow firms to provide employee incentives through employee stock option plans. Firms began initiating the plans in 2006. We investigate the impact of these plans on firm performance by comparing option-award firms with similar non-award matching firms. The change in ROE for the option-award firms is significantly higher than the matching firms. This is primarily due to their performance holding up better during the global financial crisis while the matching firms’ performance deteriorates. The stock price of these firms shows a positive reaction to the announcement, but no long-term abnormal returns. The better ROE performance for option-award firms is strong for subsets of the sample that are likely to benefit more from incentivized employees; specifically, privately owned firms, firms with higher board independence, and smaller firms. After various robustness tests, we conclude that the higher performance comes from the employee incentives, rather than earnings manipulation, a replacement of cash compensation, a binding of employees to executives, or gaming vesting periods.     

Balance and agility training does not always decrease lower limb injury risks: a cluster-randomised controlled trial

The objective of this study was to examine the effects on lower limb injury rates of adding structured balance and agility exercises to the 80-day basic training programme of army recruits. A blocked (stratified), cluster-randomised controlled trial was employed, with one intervention group (IG) and one control group (CG), in which 732 male and 47 female army recruits from the Australian Army Recruit Training Centre participated through to analysis. The IG performed specified balance and agility exercises in addition to normal physical training. The incidence of lower limb injury during basic training was used to measure effect. Analysis, which adhered to recommendations for this type of trial, used a weighted paired t-test based on the empirical logistic transform of the crude event rates. The intervention had no statistically significant effect on lower limb injury incidence (RR = 1.25, 95% CI 0.97–1.53, 90% CI 1.04–1.47), on knee and ankle injury incidence (RR = 1.08, 95% CI 0.83–1.38), and on knee and ankle ligament injury incidence (RR = 0.98, 95% CI 0.64–1.47). We conclude that the intervention, implemented in this fashion, is possibly harmful, with our best estimate of effect being a 25% increase in lower limb injury incidence rates. This type of structured balance and agility training added to normal military recruit physical training did not significantly reduce lower limb, knee and ankle, or knee and ankle ligament injury rates. Caution needs to be used when adding elements to training programmes with the aim of reducing injury, as fatigue associated with the addition may actually raise injury risk.     

加强安全技能培训 提高高校实验室安全管理

本文对高校实验室造成人员、财产损失的安全事故原因进行分析,主要从安全知识和技能培训、紧急预案制定和演练等方面阐述加强实验室安全培训对提高实验室安全管理工作的作用。     

Are classical option pricing models consistent with observed option second-order moments? Evidence from high-frequency data

As a means of validating an option pricing model, we compare the ex-post intra-day realized variance of options with the realized variance of the associated underlying asset that would be implied using assumptions as in the Black and Scholes (BS) model, the Heston, and the Bates model. Based on data for the S&P 500 index, we find that the BS model is strongly directionally biased due to the presence of stochastic volatility. The Heston model reduces the mismatch in realized variance between the two markets, but deviations are still significant. With the exception of short-dated options, we achieve best approximations after controlling for the presence of jumps in the underlying dynamics. Finally, we provide evidence that, although heavily biased, the realized variance based on the BS model contains relevant predictive information that can be exploited when option high-frequency data is not available.     

Financial applications of semidefinite programming: a review and call for interdisciplinary research

Optimisation problems in finance commonly have non-linear constraints for which previous solutions have required unrealistic assumptions. However, many of these can be efficiently solved as semidefinite programming (SDP) problems, which have less restrictive assumptions. Through review of the literature that uses SDP in finance, two major research streams are identified: portfolio optimisation and option pricing. Nevertheless, many finance researchers are unaware of SDP. One possible reason is that this research is often published in non-finance journals. This paper aims to better integrate the SDP research to promote wider use of current findings and further interdisciplinary research, particularly in environmental finance.     

A novel option contract integrated with supplier selection and inventory prepositioning for humanitarian relief supply chains

This paper proposes a novel two-period option contract integrated with supplier selection and inventory prepositioning. A two-stage scenario-based mixed possibilistic-stochastic programming model is developed to cope with various uncertainties. The first stage's decisions include supplier selection and capacity reservation level at each supplier/period and the level of inventory prepositioning. Furthermore, decisions regarding the time and exercised amount are made in the second stage. Applicability of the model is validated through a real case study. Finally, several sensitivity analyses are conducted to examine the effect of important parameters on the solutions to gain useful managerial insights.