We analyze a general equilibrium exchange economy with a continuum of agents who have ``catching up with the Joneses'' preferences and differ only with respect to the curvature of their utility functions. While individual risk aversion does not change over time, dynamic re-distribution of wealth among the agents leads to countercyclical time variation in the Sharpe ratio of stock returns. We show that the level of stock prices is negatively related to both the conditional return volatility and the risk premium, as observed empirically. Therefore, our model also produces the correct sign for the slope coefficients in long-horizon predictive regressions. For comparison, otherwise similar representative agent economies with the same type of preferences exhibit counter-factual behavior of conditional moments of returns, i.e., a constant Sharpe ratio and procyclical risk premium and return volatility.

本文通过分析德国法兰克福证券交易所(Deutsche Boerse)电子证券交易平台Xetra的拍卖市场定价和交易数量分配准则，第一次规范地提出了这一拍卖市场定价和交易数量分配的理论模型，并对其相应的经济特性作出分析。我们发现，Xetra拍卖市场价格并非传统经济学意义上的市场均衡价格(market equilibrium price)；根据其市场定价模型，在市场非均衡(market disequilibrium)情况下仍存在市场交易价格。同时我们发现，从市场均衡(market equilibrium)的角度看，现有的拍卖市场定价模式仍存在可以进一步改良的空间。另外，我们发现Xetra拍卖市场的交易数量分配模型亦非传统经济学中的均衡市场分配机制，而应归属于市场定量配给模型(rationing theory)。这一发现是对传统经济学中均衡市场分配机制的一个相互补充，同时也指出了证券交易市场微观结构的进一步研究方向。 从实际应用的角度来看，本文通过对德国电子证券交易系统进行的实证和规范化分析，为我国设计切合本国实际情况的电子证券市场交易机制提供有价值的参考。

Optimal Timing and Optimal Intensity of Real Estate Development Abstract The traditional real option approach treat firms as price taker and at the same time the firm is assumed to have monopoly power because no competition or future competitive entry is not considered in most of the real option literature. In this article we assume the real estate developer has monopoly power in a real estate submarket, given the nature of real estate market. The developer makes the timing decision as well as the intensity decision at the same time. We model the developer decision in the framework of the real option and derived the optimal timing and optimal intensity of real estate development of a certain real estate project. Our Result shows that not only the uncertainty but also the low rent sensitivity of housing demand will lead to defer of real estate development. And both the timing decision and intensity decision are sensitive to the demand factors besides the uncertainty effect.

Firms, which trade in today’s open economy often involved multi-currency transactions, will have their stock returns influenced by traded transaction currencies variations. Frequently, these firms also use derivatives for either active (hedging and speculative) or passive (hedging) currency risk management. It is therefore nontrivial to analyse empirically for these firms the relationship between stock return, currency risk exposure, and the motive of their derivatives use. This paper aims to test the relationships, via a two-factor market return model, which is based on the Arbitrage Pricing Theory (Ross, 1976). Descriptive and Inferential statistical tests are implemented on published accounting data (cross sectional and time series) for 69 Australian listed firms excluding non-financial institutions. Statistical test results reveal that there is a weak positive relationship between stock return and currency risk exposure level. The test results also suggest a negative relationship between the currency risk level and the motive (either hedging, speculative or both) of derivatives use. These findings are consistent with the modern finance theory.

We develop a nonparametric specification test for continuous-time models using the transition density. Using a data transform and correcting for boundary bias of kernel estimators, our test is robust to serial dependence in data and provides excellent finite sample performance. Besides univariate diffusion models, our test is applicable to a wide variety of continuous-time and discretetime dynamic models, including time-inhomogeneous diffusion, GARCH, stochastic volatility, regimeswitching,jump-diffusion, and multivariate diffusion models. A class of separate inference procedures is also proposed to help gauge possible sources of model misspecification. We strongly reject a variety of univariate diffusion models for daily Eurodollar spot rates and some popular multivariate affine term structure models for monthly U.S. Treasury yields.

Price and quantity are the two fundamental variables in the analysis of market interactions. Yet the study of financial markets has focused primarily on the behavior of asset prices and their relation to economic fundamentals. Much less attention has been devoted to the understanding of quantities such as trading volume. Only recently, there has been a growing body of work to link price {\it and} volume to economic fundamentals. In this paper, I review some of these work within a unified framework. I start by describing an intertemporal asset pricing model that explicitly models investors' trading motives, their optimal portfolio choices and the resulting equilibrium asset prices. I then examine the price-volume implications within the framework of the model. Finally, I discuss the results from the empirical analysis of volume and stock returns based on the data of the U.S. stock market. The theoretical analysis together with its empirical support clearly demonstrate that volume and prices are jointly linked to the economic fundamentals, e.g., the risks of the assets and the investors' attitude toward them. Moreover, the behavior of volume is closely related to the behavior of prices and from which we can learn a great deal about the prices as well as the economic fundamentals.

Based on prospect theory and individual investors’ biases such as representativeness heuristic and conservatism, we establish a behavioral model to explain the contrarian effect in China’s financial market. We find that contrarian effect is mainly attributed to trend chasing instead of disposition effect. Our model also suggests that small-cap stocks show stronger contrarian effect, phenomena confirmed by empirical research.

本文采用连续时间的多重复合期权Geske及其扩展模型来解决多阶段投资决策问题，在基本Geske公式基础上，给出了具有时变参数的连续时间N重复合期权的扩展Geske公式，并对采用Geske公式和离散期权模型得出的数值结果进行了比较。实例结果分析比较表明，利用已发表的算法和目前的普通PC计算机和数学工具软件，如DATAPLOT、MATHEMATICA等，对连续时间的N重复合期权模型(N ≤ 10)的数值解求解不再具有困难，并且可以得到较其他方法更高精度的计算结果。 Abstract: This paper make uses of N-fold continuous compound option formula to resolve multi-stages investment decision problem, and give an expansion of basic Geske formula to N-fold continuous time option with variable parameters, and then make a comparison of the results of adoption expanded Geske formula with other discrete option formulas such as binomial and trinomial formula. The results show, by means of the popular home PC with mathematic software, such as DATAPLOT, MATHEMATICA etc., the solution procedure if n ≤ 10 is quite easy with a no difficult, and can get the results with higher accuracy than other solution method.

The current paper is concerned with exploring information contained in a series of undisclosed orders that are submitted by the same broker, using this information to estimate the volume contained in the current undisclosed order, and further investigating the trading patterns followed by stockbrokers in the use of undisclosed orders. In an ARMA framework, the estimation results suggest that the information revealed in past-executed undisclosed orders of a stockbroker is explanatory to the volume of the current undisclosed order submitted by the same broker. As a supplement to the current literature relating to the package-trading patterns detected in large disclosed orders, the current study finds that stockbrokers follow the same pattern in the use of undisclosed orders. A practical application of this method is to use it for the prediction of the volume enclosed in a given undisclosed order.

In August 2000 the Singapore Stock Exchange introduced a pre-trading routine that allowed brokers to place orders into the Exchange’s computerized order matching system for a period of 30 minutes prior to market opening. A post-market trading routine was also introduced allowing for a final order matching and trade execution to occur five minutes after market close. This study investigates the impact of these changes on volatility and the price discovery process. The pre-trading session significantly reduced opening stock market volatility while the post-trading session increased volatility prior to close. A GARCH (1,1) model remains the most appropriate model for capturing the characteristics of the intra-day stock price movements in both before and after periods.