Statistical inference and modelling of momentum in stock prices

The following results are obtained, (i) It is possible to obtain a time series of market data {y(t)} in which the fluctuations in fundamental value have been compensated for. An objective test of the efficient market hypothesis (EMH), which would predict random correlations about a constant value, is thereby possible, (ii) A time series procedure can be used to determine the extent to which the differences in the data and the moving averages are significant. This provides a model of the form y(t)-y(t-l)=0.5{y(t- l)-y(t-2)}+ε(t)+0.8ε(r-1) where ε(t) is the error at time t, and the coefficients 0.5 and 0.8 are determined from the data. One concludes that today's price is not a random perturbation from yesterday's; rather, yesterday's rate of change is a significant predictor of today's rate of change. This confirms the concept of momentum that is crucial to market participants. (iii) The model provides out-of-sample predictions that can be tested statistically. (iv) The model and coefficients obtained in this way can be used to make predictions on laboratory experiments to establish an objective and quantitative link between the experiments and the market data. These methods circumvent the central difficulty in testing market data, namely, that changes in fundamentals obscure intrinsic trends and autocorrelations. This procedure is implemented by considering the ratio of two similar funds (Germany and Future Germany) with the same manager and performing a set of statistical tests that have excluded fluctuations in fundamental factors. For the entire data of the first 1149 days beginning with the introduction of the latter fund, a standard runs test indicates that the data is 29 standard deviations away from that which would be expected under a hypothesis of random fluctuations about the fundamental value. This and other tests provide strong evidence against the efficient market hypothesis and in favour of autocorrelations in the data. An ARIMA time series finds strong evidence (9.6 and 21.6 standard deviations in the two coefficients) that the data is described by a model that involves the first difference, indicating that momentum is the significant factor. The first quarter's data is used to make out-of-sample predictions for the second quarter with results that are significant to 3 standard deviations. Finally, the ARIMA model and coefficients are used to make predictions on laboratory experiments of Porter and Smith in which the intrinsic value is clear. The model's forecasts are decidedly more accurate than that of the null hypothesis of random fluctuations about the fundamental value.     

中国股票市场收益率分布曲线的实证

股票价格行为的随机理论认为市场收益服从正态分布 ,但在现实中这一假设不一定成立 ,市场收益率更多地呈现出偏离正态分布的形式。本文检验中国市场的收益率分布形态。     

On the structure of the Wishart distribution

In this paper it is shown that every nonnegative definite symmetric random matrix with independent diagonal elements and at least one nondegenerate nondiagonal element has a noninfinitely divisible distribution. Using this result it is established that every Wishart distribution W_p(k, Σ, M) with both p and rank (Σ) ≥ 2 is noninfinitely divisible. The paper also establishes that any Wishart matrix having distribution W_p(k, Σ, 0) has the joint distribution of its elements in the rth row and rth column to be infinitely divisible for every r = 1,2,…,p.     

On the identifiability of multivariate survival distribution functions

Let (T₁, T₂) be a non-negative random vector which is subjected to censoring random intervals [X₁, Y₁] and [X₂, Y₂]. The censoring mechanism is such that the available informations on T₁ and T₂ are expressed by a pair of random vectors W=(W₁, W₂) and δ=(δ₁, δ₂), where W_i=max(min(Y_i, T_i), X_i) and In this paper we will show that under some mild conditions the joint survival function of T₁ and T₂ can be expressed uniquely as functional of observable joint survival functions. Our results extend recent works on the randomly right censored bivariate data case and on the univariate problem with double censoring to the bivariate data with double censoring.     

On risk processes with the Markov property and with independent increments

We study the influence on the underlying counting process of the Markov property and of the property of independent increments for a risk process.     

两参数分数Wiener过程增量的一般形式

§1Introductionandresults A2-parameterGaussianprocess{Z(t,s);t,s≥0}iacalleda2-parameterfractional Wienerprocesswithorderα(0<α<1),ifZ(0,0)=0a.s.EZ(s,t)=0anditscovariance EZ(t1,s1)Z(t2,s2)={|t1|2α+|t2|2α-|t2-t1|2α}{|s1|2α+|s2|2α-|s2-s1|2α}/4.LetR=[x1,x2]×[y1,y2],DT={(x,y)∶0≤x,y≤bT,xy≤T}.Let0相似文献   

中国股市短期波动的非线性ARCH效应显著性分析及参数估计

中国股票市场受政治或其它因素的影响有自己的波动特点。本文利用拉格朗日乘子,选择不同的频率检验中国股票市场短期的ARCH效应的显著性,并用FGLS四步法进行非线性估计。结果表明:中国股票市场在选择适当的频率下,短期的ARCH效应是显著的,对于研究中国股票市场的成熟度,预测股票短期投资风险,规范中国股票市场发展等具有重要的意义。     

欧式复合期权的定价公式

本文根据风险中性定价原理,用较简单的数学方法推导出了股票欧式复合期权的定价公式。该公式和求解B lack-Scho les微分方程所得结果一致。     

基于股票分布模型的平均建仓成本价分析

股票价格分布理论的基础上,对平均建仓成本价及其分散程度进行了分析,发现平均建仓成本价与其一期滞后的分散程度成显著的负相关关系.     

On the posterior distribution of a dirichlet process given randomly right censored observations

The purpose of this note is to show that the conditional distribution of a Dirichlet process P given n independent observations X₁… X_n from P and belonging to measurable sets A₁,… A_n with A₁ ? A₁₊₁ for i=1,… n=1 is a mixture of Dirichlet processes as introduced by Antoniak. It is also shown that this result is applicable in Bayesin decision problems concerning a random survival distribution under Dirichlet process priors.     

Quantum modeling of nonlinear dynamics of stock prices: Bohmian approach

We use quantum mechanical methods to model the price dynamics in the financial market mathematically. We propose describing behavioral financial factors using the pilot-wave (Bohmian) model of quantum mechanics. The real price trajectories are determined (via the financial analogue of the second Newton law) by two financial potentials: the classical-like potential V (q) (“hard” market conditions) and the quantumlike potential U(q) (behavioral market conditions). Translated from Teoreticheskaya i Matematicheskaya Fizika, Vol. 152, No. 2, pp. 405–415, August, 2007.     

On the Convergence of Successive Substitution Sampling

Abstract

The problem of finding marginal distributions of multidimensional random quantities has many applications in probability and statistics. Many of the solutions currently in use are very computationally intensive. For example, in a Bayesian inference problem with a hierarchical prior distribution, one is often driven to multidimensional numerical integration to obtain marginal posterior distributions of the model parameters of interest. Recently, however, a group of Monte Carlo integration techniques that fall under the general banner of successive substitution sampling (SSS) have proven to be powerful tools for obtaining approximate answers in a very wide variety of Bayesian modeling situations. Answers may also be obtained at low cost, both in terms of computer power and user sophistication. Important special cases of SSS include the “Gibbs sampler” described by Gelfand and Smith and the “IP algorithm” described by Tanner and Wong. The major problem plaguing users of SSS is the difficulty in ascertaining when “convergence” of the algorithm has been obtained. This problem is compounded by the fact that what is produced by the sampler is not the functional form of the desired marginal posterior distribution, but a random sample from this distribution. This article gives a general proof of the convergence of SSS and the sufficient conditions for both strong and weak convergence, as well as a convergence rate. We explore the connection between higher-order eigenfunctions of the transition operator and accelerated convergence via good initial distributions. We also provide asymptotic results for the sampling component of the error in estimating the distributions of interest. Finally, we give two detailed examples from familiar exponential family settings to illustrate the theory.     

An investigation of stock price dynamics in emerging markets

The emergence of stock markets in former centrally planned economies poses a significant problem to financial economists and policy makers in that price movements in these markets are not well explained by conventional capital theory. The opening of stock markets brings about a new equilibrium value P̂ for the firm. Shares are floated on an estimate of P̂, and buyers of these shares and individuals trading in the secondary market are also obliged to do so on the basis of their estimates of this magnitude. At any time, the market price of the firm's shares then reflects the market's best guess of what its value would be in the new equilibrium, and information on which to calculate estimates become more readily available as the stock market matures. This paper presents a stochastic price model which takes all of these factors into consideration. The model also provides a theoretical foundation underlying the pronounced trends of prices in emerging stock markets, and explains why they appear to be so volatile. © 1998 John Wiley & Sons, Ltd.     

机械抽样在林业伐区蓄积量调查中的应用

本文叙述了过去林业伐区木材蓄积量调查的一般概况。在学生生产实习中采用了机械抽样方法进行木材蓄积量调查，结果表明，该方法缩短调查时间，降低生产成本，效果较好     

ARIMA模型与ARCH模型在香港股指预测方面的应用比较

由于香港金融市场易受政治或投机等因素的影响而使股价波动呈现出不确定性 ,而ARCH模型又善于描述这种不确定性 ,因而本文试图将ARCH模型和ARIMA模型在香港股指预测方面的应用进行对比 ,以期为投资者选择模型进行预测时提供参考     

On a characterization of the exponential distribution by spacings

Summary LetX be a non-negative random variable with probability distribution functionF. SupposeX _i,n (i=1,…,n) is theith smallest order statistics in a random sample of sizen fromF. A necessary and sufficient condition forF to be exponential is given which involves the identical distribution of the random variables (n−i)(X _i+1,n−X_i,n) and (n−j)(X _j+1,n−X_j,n) for somei, j andn, (1≦i<j<n). The work was partly completed when the author was at the Dept. of Statistics, University of Brasilia, Brazil.     

利用皮尔逊分布族计算非正态分布工序能力指数

本文利用皮尔逊分布族设计了一种计算非正态分布工序能力的方法。它可用于工序分布形式完全未知的情况。     

On large increments of a two-parameter fractional Wiener process

In this paper, how big the increments are and some liminf behaviors are studied of a two-parameter fractional Wiener process. The results are based on some inequalities on the suprema of this process, which also are of independent interest     

On the Distribution Behaviour of Sequences

This paper presents results concerning those sets of finite Borel measures μ on a locally compact Hausdorff space X with countable topological base which can be represented as the set of limit distributions of some sequence. They arc characterized by being nonanpty, closed, connected and containing only measures μ with μ(X) = 1 (if X is compact) or 0 ≤ μ(X) ≤ 1 (if X is not compact). Any set with this properties can be obtained as the set of limit distributions of a sequence even by rearranging an arbitrarily given sequence which is dense in the sense that the set of accumulation points is the whole space X. The typical case (in the sense of Baire categories) is that a sequence takes as limit distributions all possible measures of this kind. This gives new aspects for the recent theory of maldistribukd sequences.     

Parameter estimation of an agent‐based stock price model

The influence of the behavior and strategies of traders on stock price formation has attracted much interest. It is assumed that there is a positive correlation between the total net demand and the price change. A buy order is expected to increase the price, whereas a sell order is assumed to decrease it. We perform data analysis based on a recently proposed stochastic model for stock prices. The model involves long‐range dependence, self‐similarity, and no arbitrage principle, as observed in real data. The arrival times of orders, their quantity, and their duration are created by a Poisson random measure. The aggregation of the effect of all orders based on these parameters yields the log‐price process. By scaling the parameters, a fractional Brownian motion or a stable Levy process can be obtained in the limit. In this paper, our aim is twofold; first, to devise statistical methodology to estimate the model parameters with an application on high‐frequency price data, and second, to validate the model by simulations with the estimated parameters. We find that the statistical properties of agent level behavior are reflected on the stock price, and can affect the entire process. Moreover, the price model is suitable for prediction through simulations when the parameters are estimated from real data. The methods developed in the present paper can be applied to frequently traded stocks in general. Copyright © 2013 John Wiley & Sons, Ltd.