论文检索

从新闻流中提炼信息以分析股票反应AI 解读

The gargantuan plethora of opinions, facts, and tweets on financial business offers the opportunity to test and analyze the influence of such text sources on future directions of stocks. It also creates though the necessity to distill via statistical technology the informative elements of this prodigious and indeed colossal data source. Using mixed text sources from professional platforms, blog fora, and stock message boards, we distill via different lexica sentiment…

通过潜在共同因子建模多元波动率AI 解读

Volatility, represented in the form of conditional heteroscedasticity, plays an important role in controlling and forecasting risks in various financial operations including asset pricing, portfolio allocation, and hedging futures. However, modeling and forecasting multi-dimensional conditional heteroscedasticity are technically challenging. As the volatilities of many financial assets are often driven by a few common and latent factors, we propose in this article a…

计量经济模型中的混合分布：简要综述与新结果AI 解读

This paper is concerned with applications of mixture models in econometrics. Focused attention is given to semiparametric and nonparametric models that incorporate mixture distributions, where important issues about model specifications arise. For example, there is a significant difference between a finite mixture and a continuous mixture in terms of model identifiability. Likewise, the dimension of the latent mixing variables is a critical issue, in particular when a…

短时间维度下内生空间权重动态面板模型的工具变量估计AI 解读

The spatial dynamic panel data (SDPD) model is a standard tool for analysing data with both spatial correlation and dynamic dependences among economic units. Conventional estimation methods rely on the key assumption that the spatial weight matrix is exogenous, which would likely be violated in some empirical applications where spatial weights are determined by economic factors. In this paper, we propose an SDPD model with individual fixed effects in a short time dimension,…

用于分析金融极端共同变动的尾部依赖度量AI 解读

Modeling and forecasting extreme co-movements in financial market is important for conducting stress test in risk management. Asymptotic independence and asymptotic dependence behave drastically different in modeling such co-movements. For example, the impact of extreme events is usually overestimated whenever asymptotic dependence is wrongly assumed. On the other hand, the impact is seriously underestimated whenever the data is misspecified as asymptotic independent.…

Copula 结构的 M4 过程及其在高频金融数据中的应用AI 解读

Statistical applications of classical parametric max-stable processes are still sparse mostly due to lack of (1) efficiency of statistical estimation of many parameters in the processes, (2) flexibility of concurrently modeling asymptotic independence and asymptotic dependence among variables, and (3) capability of fitting real data directly. This paper studies a more flexible model, i.e. a class of copula structured M4 (multivariate maxima and moving maxima) processes, and…

大型投资组合风险的稳健推断AI 解读

We propose a bootstrap-based robust high-confidence level upper bound (Robust H-CLUB) for assessing the risks of large portfolios. The proposed approach exploits rank-based and quantile-based estimators, and can be viewed as a robust extension of the H-CLUB procedure (Fan et al., 2015). Such an extension allows us to handle possibly misspecified models and heavy-tailed data, which are stylized features in financial returns. Under mixing conditions, we analyze the proposed…

高维协方差矩阵超对角线结构的检验AI 解读

The covariance matrices are essential quantities in econometric and statistical applications including portfolio allocation, asset pricing and factor analysis. Testing the entire covariance under high dimensionality endures large variability and causes a dilution of the signal-to-noise ratio and hence a reduction in the power. We consider a more powerful test procedure that focuses on testing along the super-diagonals of the high dimensional covariance matrix, which can…

参数化 GARCH-in-Mean 模型的渐近理论AI 解读

In this paper we develop an asymptotic theory for the Quasi-Maximum Likelihood Estimator (QMLE) of the parametric GARCH-in-Mean model. The asymptotics is based on a study of the volatility as a process of the model parameters. The proof makes use of stochastic recurrence equations for this random function and uses exponential inequalities to localize the problem. Our results show why the asymptotics for this specification is quite complex although it is a rather standard…

数据清洗与推断之间：预平均及有效价格的稳健估计AI 解读

Pre-averaging is a popular strategy for mitigating microstructure in high frequency financial data. As the term suggests, transaction or quote data are averaged over short time periods ranging from 30 s to five min, and the resulting averages approximate the efficient price process much better than the raw data. Apart from reducing the size of the microstructure, the methodology also helps synchronise data from different securities. The procedure is robust to short term…

未知对角系数时空模型的广义 Yule–Walker 估计AI 解读

We consider a class of spatio-temporal models which extend popular econometric spatial autoregressive panel data models by allowing the scalar coefficients for each location (or panel) different from each other. To overcome the innate endogeneity, we propose a generalized Yule–Walker estimation method which applies the least squares estimation to a Yule–Walker equation. The asymptotic theory is developed under the setting that both the sample size and the number of locations…

资产类别间相关性上升：波动、跳跃还是二者共同作用？AI 解读

We develop estimators and asymptotic theory to decompose the quadratic covariation between two assets into its continuous and jump components, in a manner that is robust to the presence of market microstructure noise. Using high frequency data on different assets classes, we find that the recent financial crisis led to an increase in both the quadratic variations of the assets and their correlations. However, we find little evidence to suggest a change between the relative…

融合低频与高频金融数据的统一离散时间和连续时间模型AI 解读

This paper introduces a unified model, which can accommodate both continuous-time Itô processes used to model high-frequency stock prices and GARCH processes employed to model low-frequency stock prices, by embedding a discrete-time GARCH volatility in its continuous-time instantaneous volatility. This model is called a unified GARCH-Itô model. We adopt realized volatility estimators based on high-frequency financial data and the quasi-likelihood function for the…

小样本中的稳健标准误：一些实用建议AI 解读

We study the properties of heteroskedasticity-robust confidence intervals for regression parameters. We show that confidence intervals based on a degrees-of-freedom correction suggested by Bell and McCaffrey (2002) are a natural extension of a principled approach to the Behrens-Fisher problem. We suggest a further improvement for the case with clustering. We show that these standard errors can lead to substantial improvements in coverage rates even for samples with fifty or…

残障补助对家庭劳动收入与总收入的影响：儿童SSI项目证据AI 解读

I estimate the effect of removing children with disabilities from Supplemental Security Income (SSI) on parental earnings and household disability receipt. Using administrative data from the Social Security Administration (SSA), I implement regression discontinuity and differencein- differences designs based on changes in SSA's budget for child medical reviews. I find that parents fully offset the SSI loss with increased earnings, and the loss of the child's SSI payment…

断点回归的分布检验：理论与实证示例AI 解读

This paper proposes consistent testing methods for examining the effect of a policy treatment on the whole distribution of a response outcome within the setting of a regression discontinuity design. These methods are particularly useful when a policy is expected to produce treatment effects that are heterogeneous along some unobserved characteristics. The test statistics are Kolmogorov-Smirnov-type and are asymptotically distribution free when the data are i.i.d. The…

协整多项式回归的完全修正 OLS 估计与推断AI 解读

This paper develops a fully modified OLS (FM-OLS) estimator for cointegrating polynomial regressions, i.e., regressions that include as explanatory variables deterministic variables, integrated processes, and integer powers of integrated processes. The stationary errors are allowed to be serially correlated and the regressors are allowed to be endogenous. The paper extends the fully modified estimator of Phillips and Hansen (1990) from cointegrating regressions to…

含生成协变量的半参数估计AI 解读

We study a general class of semiparametric estimators when the infinite-dimensional nuisance parameters include a conditional expectation function that has been estimated nonparametrically using generated covariates. Such estimators are used frequently to e.g., estimate nonlinear models with endogenous covariates when identification is achieved using control variable techniques. We study the asymptotic properties of estimators in this class, which is a nonstandard problem…

正态分布的新刻画与正态性检验AI 解读

We study the asymptotic covariance function of the sample mean and quantile, and derive a new and surprising characterization of the normal distribution: the asymptotic covariance between the sample mean and quantile is constant across all quantiles, if and only if the underlying distribution is normal. This is a powerful result and facilitates statistical inference. Utilizing this result, we develop a new omnibus test for normality based on the quantile-mean covariance…

固定效应自回归模型中的似然推断AI 解读

We calculate the bias of the profile score for the regression coefficients in a multistratum autoregressive model with stratum-specific intercepts. The bias is free of incidental parameters. Centering the profile score delivers an unbiased estimating equation and, upon integration, an adjusted profile likelihood. A variety of other approaches to constructing modified profile likelihoods are shown to yield equivalent results. However, the global maximizer of the adjusted…

货币政策的信号效应AI 解读

We develop a dynamic general equilibrium model in which the policy rate signals the central bank’s view about macroeconomic developments to price setters. The model is estimated with likelihood methods on a U.S. data set that includes the Survey of Professional Forecasters as a measure of price setters’ inflation expectations. This model improves upon existing perfect information models in explaining why, in the data, inflation expectations respond with delays to monetary…

双成分混合模型的估计及其多重检验应用AI 解读

Summary We consider a two-component mixture model with one known component. We develop methods for estimating the mixing proportion and the unknown distribution non-parametrically, given independent and identically distributed data from the mixture model, using ideas from shape-restricted function estimation. We establish the consistency of our estimators. We find the rate of convergence and asymptotic limit of the estimator for the mixing proportion. Completely automated…

样本选择模型中的稳健推断AI 解读

Summary The problem of non-random sample selectivity often occurs in practice in many fields. The classical estimators introduced by Heckman are the backbone of the standard statistical analysis of these models. However, these estimators are very sensitive to small deviations from the distributional assumptions which are often not satisfied in practice. We develop a general framework to study the robustness properties of estimators and tests in sample selection models. We…

利用似然比扫描统计量推断时间序列的多个变点AI 解读

Summary We propose a likelihood ratio scan method for estimating multiple change points in piecewise stationary processes. Using scan statistics reduces the computationally infeasible global multiple-change-point estimation problem to a number of single-change-point detection problems in various local windows. The computation can be efficiently performed with order O{npt log (n)}. Consistency for the estimated numbers and locations of the change points are established.…