PRICING ASIAN OPTIONS FOR JUMP DIFFUSION

We construct a sequence of functions that uniformly converge (on compact sets) to the price of an Asian option, which is written on a stock whose dynamics follow a jump diffusion. The convergence is exponentially fast. We show that each element in this sequence is the unique classical solution of a parabolic partial differential equation (not an integro‐differential equation). As a result we obtain a fast numerical approximation scheme whose accuracy versus speed characteristics can be controlled. We analyze the performance of our numerical algorithm on several examples.     

中国CO_2排放与经济增长联动性实证分析

笔者在测算我国1953年～2007年间CO2排放量的基础上,通过对数据的经济计量检验,建立联立方程组模型,研究CO2排放量与人均GDP间双向因果关系,并分析各种因素对CO2排放量的影响。实证结果显示,我国CO2排放量与人均GDP间变动关系并不是简单EKC模型中的倒U型,有着更为复杂的相互作用关联。人均GDP提高导致CO2排放量上升的同时,能源利用效率的提高、能源消费结构的改善,以及资本设备更新速度的加快,都将减少CO2排放。     

When do B2B brands influence the decision making of organizational buyers? An examination of the relationship between purchase risk and brand sensitivity

The dominant perspective on organizational buying behavior suggests that buyers tend to rely on objective criteria when making product choice decisions and that the potential influence of subjective cues, such as brands, on buyer decision making decreases with increasing risk. An alternative perspective, confirmed in this study by in-depth interviews with various managers, suggests that brands serve as a risk-reduction heuristic, whereby the influence of brands on decision making increases as a function of risk. Building on risk and information processing theories, this research builds on these complementary perspectives to propose that risk and brand sensitivity relate in a U-shaped manner, where brand sensitivity is highest in relatively low- or high-risk situations. The results of scenario- and survey-based field studies—involving 206 and 180 members of buying centers, respectively—suggest that both perspectives have merit and support the proposed nonlinear relationship. Moreover, the findings reveal that the risk-brand sensitivity relationship is moderated by competitive intensity, such that the linear (negative) and quadratic (positive) effects are stronger when competitive intensity is low.     

三种电离层射线追踪自导引算法比较

通过建立电离层模型和地磁场模型,采用龙格库塔法求解Haselgrove方程,得到相应的射线路径参数,实现了电离层三维射线追踪。针对射线追踪无法进行自导引计算,分别采用牛顿差分自导引算法、基于变分方程的牛顿法以及单纯形法实现了射线追踪的自导引,并给出了详细的算法分析。重点对变分方程及其二阶微分的求解进行了详细推导。最后对以上三种自导引算法进行性能比较,仿真结果表明:基于变分方程的自导引算法优于其他两种自导引算法。     

平面任意力系的平衡方程及应用——高职教学中一道典型的例题

平面任意力系的平衡方程及应用是教学的重点和难点,它是解决物体系统平衡问题的基础,学生应理解并熟练掌握。本文举一典型例题来说明平面任意力系的平衡方程的三种形式的具体运用。     

The (un)importance of geographical mobility in the Great Recession

Unemployment during and after the Great Recession has been persistently high. One concern is that the housing bust reduced geographical mobility and prevented workers from moving for jobs. We characterize flows out of unemployment that are related to geographical mobility to construct an upper bound on the effect of mobility on unemployment between 2007 and 2012. The effect of geographical mobility is always small: Using pre-recession mobility rates, decreased mobility can account for only an 11 basis points increase in the unemployment rate over the period. Using dynamics of renter geographical mobility in this period to calculate homeowner counterfactual mobility, delivers similar results. Using the highest mobility rate observed in the data, reduced mobility accounts for only a 33 basis points increase in the unemployment rate.     

EXPLICIT SOLUTIONS OF CONSUMPTION-INVESTMENT PROBLEMS IN FINANCIAL MARKETS WITH REGIME SWITCHING

We consider a consumption and investment problem where the market presents different regimes. An investor taking decisions continuously in time selects a consumption–investment policy to maximize his expected total discounted utility of consumption. The market coefficients and the investor's utility of consumption are dependent on the regime of the financial market, which is modeled by an observable finite-state continuous-time Markov chain. We obtain explicit optimal consumption and investment policies for specific HARA utility functions. We show that the optimal policy depends on the regime. We also make an economic analysis of the solutions, and show that for every investor the optimal proportion to allocate in the risky asset is greater in a "bull market" than in a "bear market." This behavior is not affected by the investor's risk preferences. On the other hand, the optimal consumption to wealth ratio depends not only on the regime, but also on the investor's risk tolerance: high risk-averse investors will consume relatively more in a "bull market" than in a "bear market," and the opposite is true for low risk-averse investors.     

How Do Investors' Expectations Drive Asset Prices?

Based on an extension of the process of investors' expectations to stochastic volatility we derive asset price processes in a general continuous time pricing kernel framework. Our analysis suggests that stochastic volatility of asset price processes results from the fact that investors do not know the risk of an asset and therefore the volatility of the process of their expectations is stochastic, too. Furthermore, our model is consistent with empirical studies reporting negative correlation between asset prices and their volatility as well as significant variations in the Sharpe ratio.     

Modeling Clustered Ordered Categorical Data: A Survey

This article surveys various strategies for modeling ordered categorical (ordinal) response variables when the data have some type of clustering, extending a similar survey for binary data by Pendergast, Gange, Newton, Lindstrom, Palta & Fisher (1996). An important special case is when repeated measurement occurs at various occasions for each subject, such as in longitudinal studies. A much greater variety of models and fitting methods are available than when a similar survey for repeated ordinal response data was prepared a decade ago (Agresti, 1989). The primary emphasis of the review is on two classes of models, marginal models for which effects are averaged over all clusters at particular levels of predictors, and cluster-specific models for which effects apply at the cluster level. We present the two types of models in the ordinal context, review the literature for each, and discuss connections between them. Then, we summarize some alternative modeling approaches and ways of estimating parameters, including a Bayesian approach. We also discuss applications and areas likely to be popular for future research, such as ways of handling missing data and ways of modeling agreement and evaluating the accuracy of diagnostic tests. Finally, we review the current availability of software for using the methods discussed in this article.     

A discrete and a continuous-time model based on a technical trading rule

In this article we propose a model in discrete and continuoustime that incorporates explicitly a technical trading rule inthe specification of the volatility. The proposed discrete-timemodel is an alternative to GARCH-type processes. We derive conditionsfor the covariance and strict stationarity of the discrete-timeprocess and we study the estimation and inference problems.We also analyze the conditions under which the discrete-timeprocess converges in distribution to a diffusion process. Toillustrate the proposed model and compare it with the GARCHspecification, we analyze the daily closing stock prices oftwo major U.S. companies (Microsoft and Oracle), two stock indices(DAX and NASDAQ) and two U.S. Dollar exchange rates (Euro andSterling)