技术分析、主体异质性与资产定价

通过构建异质主体经济跨期模型, 从技术分析的角度研究了主体异质性对市场理性预期均衡的影响,进而发现了异质主体经济下的市场价格稳定条件由技术分析者对历史价格的敏感程度、技术分析者所占市场份额以及无风险利率三者共同所决定.研究表明, 若分析策略不能严格地满足所给出的特定条件, 则技术分析会长期影响价格水平及波动性.此外, 价格序列的发散表征了市场泡沫的产生, 而造成价格发散的部分原因是由于理性投资者与技术分析者异质性较高, 技术分析者对历史信息过度敏感.针对此类泡沫,小幅度提升无风险利率并不能起到有效的抑制作用.     

Mitigating Inventory Overstocking: Optimal Order‐up‐to Level to Achieve a Target Fill Rate over a Finite Horizon

Service level agreements (SLAs) are widely adopted performance‐based contracts in operations management practice, and fill rate is the most common performance metric among all the measurements in SLAs. Traditional procedures characterizing the order‐up‐to level satisfying a specified fill rate implicitly assume an infinite performance review horizon. However, in practice, inventory managers are liable to maintain and report fill rates over a finite performance review horizon. This horizon discrepancy leads to deviation between the target fill rate and actual achieved fill rate. In this study, we first examine the behavior of the fill rate distribution over a finite horizon with positive lead time. We analytically prove that the expected fill rate assuming an infinite performance review horizon exceeds the expected fill rate assuming a finite performance review horizon, implying that there exists some inventory “waste” (i.e., overstocking) when the traditional procedure is used. Based on this observation and the complexity of the problem, we propose a simulation‐based algorithm to reduce excess inventory while maintaining the contractual target fill rate. When the lead time is significant relative to the length of the contract horizon, we show that the improvement in the inventory system can be over 5%. Further, we extend our basic setting to incorporate the penalty for failing to meet a target, and show how one can solve large‐scale problems via stochastic approximation. The primary managerial implication of our study is that ignoring the performance review horizon in an SLA will cause overstocking, especially when the lead time is large.     

Enhancing Estimation for Interest Rate Diffusion Models With Bond Prices

We consider improving estimating parameters of diffusion processes for interest rates by incorporating information in bond prices. This is designed to improve the estimation of the drift parameters, which are known to be subject to large estimation errors. It is shown that having the bond prices together with the short rates leads to more efficient estimation of all parameters for the interest rate models. It enhances the estimation efficiency of the maximum likelihood estimation based on the interest rate dynamics alone. The combined estimation based on the bond prices and the interest rate dynamics can also provide inference to the risk premium parameter. Simulation experiments were conducted to confirm the theoretical properties of the estimators concerned. We analyze the overnight Fed fund rates together with the U.S. Treasury bond prices. Supplementary materials for this article are available online.     

Wavelet estimators for the derivatives of the density function from data contaminated with heteroscedastic measurement errors

Measurement errors occur in many real data applications. In this paper, the linear and the non linear wavelet estimators of the derivatives of the density function are constructed in the case of data contaminated with heteroscedastic measurement errors. We establish L_p risk performance of the estimators and show that they achieve fast convergence rates under quite general conditions.     

Levels and patterns of internal migration in Europe: A cohort perspective

Europe displays important variations in the level of internal migration, with a clear spatial gradient of high mobility in northern and western Europe but lower mobility in the south and east. However, cross-national variation in levels of internal migration remains poorly understood, because it is analysed almost exclusively using cross-sectional data and period measures. This paper seeks to advance understanding of cross-national variation in migration levels in 14 European countries by drawing on a recently proposed suite of migration cohort measures, coupled with internationally comparable retrospective residential histories. It shows that differences in migration levels are mainly attributable to variation in the extent of repeat movement, which is underpinned by the differences in mean ages at first and last move that together delineate the average length of migration careers. Cohort analysis provides a robust foundation for exploring the demographic mechanisms underpinning variation in migration levels across countries and over time.     

A new large sample goodness of fit test for multivariate normality based on chi squared probability plots

Based on a chi square transform of the multivariate normal data set, we proposed a technique for testing multinormality which is the sum of interpoint squared distances between an ordered set of the transformed observations and the set of the population pth quantiles of the chi squared distribution. The critical values of the test were evaluated for different sample sizes and random vector dimensions through extensive simulations. The empirical type-I-error rates and powers of the proposed test were compared with those of some other well known tests for MVN with the proposed test showing excellent results at large sample sizes.     

Bayesian inverse problems with heterogeneous variance

We consider inverse problems in Hilbert spaces under correlated Gaussian noise, and use a Bayesian approach to find their regularized solution. We focus on mildly ill-posed inverse problems with fractional noise, using a novel wavelet-based vaguelette–vaguelette approach. It allows us to apply sequence space methods without assuming that all operators are simultaneously diagonalizable. The results are proved for more general bases and covariance operators. Our primary aim is to study posterior contraction rate in such inverse problems over Sobolev classes and compare it to the derived minimax rate. Secondly, we study effect of plugging in a consistent estimator of variances in sequence space on the posterior contraction rate. This result is applied to the problem with error in forward operator. Thirdly, we show that empirical Bayes posterior distribution with a plugged-in maximum marginal likelihood estimator of the prior scale contracts at the optimal rate, adaptively, in the minimax sense.     

Adaptive Local Polynomial Whittle Estimation of Long‐range Dependence

The local Whittle (or Gaussian semiparametric) estimator of long range dependence, proposed by Künsch (1987) and analyzed by Robinson (1995a), has a relatively slow rate of convergence and a finite sample bias that can be large. In this paper, we generalize the local Whittle estimator to circumvent these problems. Instead of approximating the short‐run component of the spectrum, ϕ(λ) , by a constant in a shrinking neighborhood of frequency zero, we approximate its logarithm by a polynomial. This leads to a “local polynomial Whittle” (LPW) estimator. We specify a data‐dependent adaptive procedure that adjusts the degree of the polynomial to the smoothness of ϕ(λ) at zero and selects the bandwidth. The resulting “adaptive LPW” estimator is shown to achieve the optimal rate of convergence, which depends on the smoothness of ϕ(λ) at zero, up to a logarithmic factor.     

Identifying key factors in momentum in basketball games

Momentum as elaborated under a recent novel definition has been shown quantitatively to have a significant impact on basketball game outcomes. This paper makes two contributions to the analytical literature on sports momentum: (1) two aspects of the new definition are operationalized so that its practicality becomes evident; and (2) through a dimension-reduction technique (elastic net), key factors associated with momentum are identified. Both technical variables such as field goals, assists, rebounds, etc. and environmental variables such as the spectator attendance rate and player salary dispersion are considered, and the potential for useful real-time analyzes is illustrated.