论文检索

内生误报下的处理效应估计AI 解读

Participation in social programs is often misreported in survey data, complicating the estimation of treatment effects. We propose a model to estimate treatment effects under endogenous participation and endogenous misreporting. We present an expression for the asymptotic bias of both OLS and IV estimators and discuss the conditions under which sign reversal may occur. We provide a method for eliminating this bias when researchers have access to information regarding…

断点回归设计中的处理效应异质性检验AI 解读

Treatment effect heterogeneity is frequently studied in regression discontinuity (RD) applications. This paper proposes, under the RD setup, formal tests for treatment effect heterogeneity among individuals with different observed pre-treatment characteristics. The proposed tests study whether a policy treatment (1) is beneficial for at least some subpopulations defined by pre-treatment covariate values, (2) has any impact on at least some subpopulations, and (3) has a…

大样本相关矩阵正则化的多重检验方法AI 解读

This paper proposes a regularisation method for the estimation of large covariance matrices that uses insights from the multiple testing (MT) literature. The approach tests the statistical significance of individual pair-wise correlations and sets to zero those elements that are not statistically significant, taking account of the multiple testing nature of the problem. The effective p-values of the tests are set as a decreasing function of N (the cross section dimension),…

区制转换计量模型中极大似然估计量的渐近性质AI 解读

Markov regime switching models have been widely used in numerous empirical applications in economics and finance. However, the asymptotic distribution of the maximum likelihood estimator (MLE) has not been proven for some empirically popular Markov regime switching models. In particular, the asymptotic distribution of the MLE has been unknown for models in which some elements of the transition probability matrix have the value of zero, as is commonly assumed in empirical…

高频数据的因子GARCH–Itô模型与大型波动率矩阵预测AI 解读

Several novel large volatility matrix estimation methods have been developed based on the high-frequency financial data. They often employ the approximate factor model that leads to a low-rank plus sparse structure for the integrated volatility matrix and facilitates estimation of large volatility matrices. However, for predicting future volatility matrices, these nonparametric estimators do not have a dynamic structure to implement. In this paper, we introduce a novel Itô…

多回归变量线性模型中的残差自助检验AI 解读

This paper is concerned with bootstrap hypothesis testing in linear regression models with many regressors. I show that bootstrap F, LR and LM tests are asymptotically valid even when the numbers of estimated parameters and tested restrictions are not asymptotically negligible fractions of the sample size. One of the conditions for these results is that the regressors come from an asymptotically balanced design. Depending on the number of restrictions tested and on the…

因子Copula模型的结构突变检验AI 解读

We propose new fluctuation tests for detecting structural breaks in factor copula models and analyse the behaviour under the null hypothesis of no change. In the model, the joint copula is given by the copula of random variables which arise from a factor model. This is particularly useful for analysing data with high dimensions. Parameters are estimated with the simulated method of moments (SMM). The discontinuity of the SMM objective function complicates the derivation of a…

双尺度估计的代数性质与S-TSRV：对采样时点稳健的高频估计AI 解读

In this paper, we derive a new algebraic property of two scales estimation in high frequency data, under which the effect of sampling times is canceled to high order. This is a particular robustness property of the two scales construction. In general, irregular, asynchronous, or endogenous times can cause problems in estimators based on equidistant observation of (trade or quote) times.

扩展Roll模型中买卖价差的半参数估计AI 解读

We propose new methods for estimating the bid–ask spread from observed transaction prices alone. Our methods are based on the empirical characteristic function. We compare our methods theoretically and numerically with the Roll (1984) method as well as with its best known competitor, the Hasbrouck (2004) method, and find that our estimators perform much better when this distribution is far from Gaussian. Our methods are applied to the E-mini futures contract on the S&P 500…

气候风险与市场效率AI 解读

Climate science finds that the trend towards higher global temperatures exacerbates the risks of droughts. We investigate whether the prices of food stocks efficiently discount these risks. Using data from thirty-one countries with publicly-traded food companies, we rank these countries each year based on their long-term trends toward droughts using the Palmer Drought Severity Index. A poor trend ranking for a country forecasts relatively poor profit growth for food…

矩阵值高维时间序列的因子模型AI 解读

In finance, economics and many other fields, observations in a matrix form are often observed over time. For example, many economic indicators are obtained in different countries over time. Various financial characteristics of many companies are reported over time. Although it is natural to turn a matrix observation into a long vector then use standard vector time series models or factor analysis, it is often the case that the columns and rows of a matrix represent different…

系统重要性金融机构的尾部事件驱动网络AI 解读

The interdependence, dynamics and riskiness of financial institutions are the key features frequently tackled in financial econometrics. We propose a Tail Event driven Network Quantile Regression (TENQR) model which addresses these three aspects. More precisely, our framework captures the risk propagation and dynamics in terms of a panel quantile autoregression involving network effects that are quantified through a time-varying adjacency matrix. To reflect the risk content…

带状时空自回归模型AI 解读

We propose a new class of spatio-temporal models with unknown and banded autoregressive coefficient matrices. The setting represents a sparse structure for high-dimensional spatial panel dynamic models when panel members represent economic (or other type) individuals at many different locations. The structure is practically meaningful when the order of panel members is arranged appropriately. Note that the implied autocovariance matrices are unlikely to be banded, and…

已知因子、已知载荷或均未知：含噪异步数据下大型协方差估计量的比较AI 解读

We investigate estimators of factor-model-based large covariance (and precision) matrices using high-frequency data, which are asynchronous and potentially contaminated by the market microstructure noise. Our estimation strategies rely on the pre-averaging method with refresh time to solve the microstructure problems, while using three different specifications of factor models with a variety of thresholding methods, respectively, to battle the curse of dimensionality. To…

基于高频观测的高维因子建模AI 解读

This paper develops a statistical theory to estimate an unknown factor structure based on financial high-frequency data. We derive an estimator for the number of factors and consistent and asymptotically mixed-normal estimators of the loadings and factors under the assumption of a large number of cross-sectional and high-frequency observations. The estimation approach can separate factors for continuous and rare jump risk. The estimators for the loadings and factors are…

可预测性的尺度AI 解读

We introduce a new stylized fact: the hump-shaped behavior of slopesand coefficients of determination as a function of the aggregation horizon when running (forward/backward) predictive regressions of future excess market returns onto past economic uncertainty (as proxied by market variance, consumption variance, or economic policy uncertainty). To justify this finding formally, we propose a novel modeling framework in which predictability is specified as a property of…

适应预测变量不同性质的资产收益可预测性统一检验AI 解读

Some unified tests have been proposed recently in the literature for testing predictability of asset returns based on a simple linear predictive regression model, which has a drawback that predicted variable cannot be stationary if the predicting variable is nonstationary. To solve this issue, this paper includes the difference of the predicting variable into the simple linear predictive regression. Furthermore, a unified empirical likelihood inference is developed to test…

近似因子模型的稳健协方差估计AI 解读

In this paper, we study robust covariance estimation under the approximate factor model with observed factors. We propose a novel framework to first estimate the initial joint covariance matrix of the observed data and the factors, and then use it to recover the covariance matrix of the observed data. We prove that once the initial matrix estimator is good enough to maintain the element-wise optimal rate, the whole procedure will generate an estimated covariance with desired…

基于均方误差与条件均方误差的最优阈值选择AI 解读

We consider a univariate semimartingale model for (the logarithm of) an asset price, containing jumps having possibly infinite activity. The nonparametric threshold estimator IV̂n of the integrated variance IV≔∫0Tσs2ds proposed in Mancini (2009) is constructed using observations on a discrete time grid, and precisely it sums up the squared increments of the process when they are below a threshold, which depends on the observation time step and, sometimes, model parameters or…

基于逐笔观测的积分波动率估计AI 解读

We develop a volatility estimator that can be directly applied to tick-by- tick data. More specifically, we consider a model that allows for (i) irregular observation times that can be endogenous, (ii) dependent noise that can have diurnal features and be dependent on the latent price process, and (iii) jumps in the latent price process. We show that our estimator yields consistent estimates and enjoys the optimal rate of convergence. Simulation as well as empirical studies…

基于变换因子的资产收益因子模型AI 解读

The Fama–French three factor models are commonly used in the description of asset returns in finance. Statistically speaking, the Fama–French three factor models imply that the return of an asset can be accounted for directly by the Fama–French three factors, i.e. market, size and value factor, through a linear function. A natural question is: would some kind of transformed Fama–French three factors work better? If so, what kind of transformation should be imposed on each…

自相关稳健检验的尺寸控制AI 解读

Autocorrelation robust tests are notorious for suffering from size distortions and power problems. We investigate under which conditions the size of autocorrelation robust tests can be controlled by an appropriate choice of critical value.

是否应再进一步？GMM一步法与两步法的精确比较AI 解读

According to conventional asymptotic theory, the two-step generalized method of moments (GMM) estimator and test perform at least as well as the one-step estimator and test in large samples. The conventional asymptotic theory completely ignores the estimation uncertainty in the weighting matrix, and as a result it may not reflect finite-sample situations well. In this paper, we employ the more accurate fixed-smoothing asymptotic framework to compare the performances of the…

ArCo：高维面板时间序列的人工反事实方法AI 解读

We consider a new, flexible and easy-to-implement method to estimate thecausal effects of an intervention on a single treated unit when a control group is not available and which nests previous proposals in the literature. It is a two-step methodology where in the first stage, a counterfactual is estimated based on a large-dimensional set of variables from a pool of untreated units by means of shrinkage methods, such as the least absolute shrinkage and selection operator…