Stock market networks: The dynamic conditional correlation approach

We demonstrate the economic relevance of minimum spanning trees (MSTs) constructed from dynamic conditional correlations (DCC) for a sample of S&P 100 constituents. An empirical comparison of MST properties shows that using the standard approach of rolling (or sliding-window) correlations yields trees that are more robust, have higher densities and exhibit higher industry clustering than MSTs based on DCC. Our results suggest that these properties are achieved at the expense of the smoothing of market dynamics, which is better preserved by DCC. The DCC approach offers a new perspective for the analysis of complex systems such as stock markets.     

The relationships between Shanghai stock market and CNY/USD exchange rate: New evidence based on cross-correlation analysis,structural cointegration and nonlinear causality test

This paper explores the co-movement of Shanghai stock market and China Yuan (CNY) exchange rates. First, we find that stock price and exchange rate are significantly cross-correlated. Second, employing a cointegration test allowing for a structural break, we find that the Shanghai Composite Index (SCI) is not cointegrated with the exchange rate of CNY/USD. The so-called “cointegration” found in previous studies is just caused by the shock of the recent financial crisis. Third, using linear and nonlinear Granger causality tests, we find no causality between stock prices and exchange rates during the period before the recent financial crisis. After the financial crisis, a unidirectional causality behavior running from exchange rates to stock index is present.     

Black-Scholes期权定价模型的简化推导

本文讨论了 Black-Scholes期权定价模型的一种简化推导方法     

A geometric study of duality gaps, with applications

Lagrangian relaxation is often an efficient tool to solve (large-scale) optimization problems, even nonconvex. However it introduces a duality gap, which should be small for the method to be really efficient. Here we make a geometric study of the duality gap. Given a nonconvex problem, we formulate in a first part a convex problem having the same dual. This formulation involves a convexification in the product of the three spaces containing respectively the variables, the objective and the constraints. We apply our results to several relaxation schemes, especially one called “Lagrangean decomposition” in the combinatorial-optimization community, or “operator splitting” elsewhere. We also study a specific application, highly nonlinear: the unit-commitment problem. Received: June 1997 / Accepted: December 2000?Published online April 12, 2001     

非均衡市场价格调节的纯增益反馈控制问题研究

本文在弱化现有文献对非均衡微观市场所受到外干扰的限制条件下 ,具体讨论了两种非均衡微观市场价格调节的纯增益反馈控制问题 ,得出了符合经济现实的结果并给出了实例 .     

土地统一收购价格内涵界定研究

本文以土地统一收购是一种“强制性的买卖关系”为假设前题,通过对需要收购土地类型的产权界定和增值收益形成原因分析,认为收购价格内涵构成是与被收购土地原使用者对土地拥有的权利和利益保持一致的土寺现实用途价格,收购价格内涵构成中不包括各种安置补偿费,也不包括土地的发展权价格。     

商住综合用地评估的加价模型

从商业路线价、住宅用地级别价和商住综合用地路线价之间的相互关系出发,建立商住综合用地评估的每米加价模型,给出利用“每米加价”评估商住综合用地的步骤,并结合实例,用剩余估价法对模型的应用结果进行了验证。     

有政府干预的市场经济条件下收入及价格的变化对公共物品使用率的影响

本文根据有政府干预的市场经济的特点,假想公共物品在市场上达到了均衡,消费者在使用公共物品时,按其使用率支付相应的费用.建立了相应的数学模型,分析了当收入及价格发生变化时,对公共物品使用率的影响,具有一定的理论及应用价值.     

Time-Varying Parameters Prediction

This paper develops a method of adaptive modeling that may be applied to forecast non-stationary time series. The starting point are time-varying coefficients models introduced in statistics, econometrics and engineering. The basic step of modeling is represented by the implementation of adaptive recursive estimators for tracking parameters. This is achieved by unifying basic algorithms—such as recursive least squares (RLS) and extended Kalman filter (EKF)—into a general scheme and next by selecting its coefficients with the minimization of the sum of squared prediction errors. This defines a non-linear estimation problem that may be analyzed in the context of the conditional least squares (CLS) theory. A numerical application on the IBM stock price series of Box-Jenkins illustrates the method and shows its good forecasting ability.     

Semiparametric Bootstrap Approach to Hypothesis Tests and Confidence Intervals for the Hurst Coefficient

A major application of rescaled adjusted range analysis (R–S analysis) is to the study of price fluctuations in financial markets. There, the value of the Hurst constant, H, in a time series may be interpreted as an indicator of the irregularity of the price of a commodity, currency or similar quantity. Interval estimation and hypothesis testing for H are central to comparative quantitative analysis. In this paper we propose a new bootstrap, or Monte Carlo, approach to such problems. Traditional bootstrap methods in this context are based on fitting a process chosen from a wide but relatively conventional range of discrete time series models, including autoregressions, moving averages, autoregressive moving averages and many more. By way of contrast we suggest simulation using a single type of continuous-time process, with its fractal dimension. We provide theoretical justification for this method, and explore its numerical properties and statistical performance by application to real data on commodity prices and exchange rates. This revised version was published online in June 2006 with corrections to the Cover Date.