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Model uncertainty in the cross-section of stock returns 股票收益横截面的模型不确定性
IF 4.7 3区 经济学
Journal of Econometrics Pub Date : 2026-07-01 Epub Date: 2025-07-22 DOI: 10.1016/j.jeconom.2025.106066
Jiantao Huang, Ran Shi
{"title":"Model uncertainty in the cross-section of stock returns","authors":"Jiantao Huang,&nbsp;Ran Shi","doi":"10.1016/j.jeconom.2025.106066","DOIUrl":"10.1016/j.jeconom.2025.106066","url":null,"abstract":"<div><div>We develop a transparent Bayesian framework to measure uncertainty in asset pricing models. By assigning a modified class of <span><math><mi>g</mi></math></span>-priors to the risk prices of asset pricing factors, our method quantifies the trade-off between mean–variance efficiency and parsimony for asset pricing models to achieve high posterior probabilities. Model uncertainty is defined as the entropy of these model probabilities. We prove the model selection consistency property of our procedure, which is missing from the classic <span><math><mi>g</mi></math></span>-priors. Acknowledging the possibility of omitting true asset pricing factors in real applications, we also characterize the maximum degree of contamination that the omitted factors can introduce to our model uncertainty measure. Empirically, we find that model uncertainty escalates during major market events and carries a significantly negative risk premium of approximately half the magnitude of the market. Positive shocks to model uncertainty predict persistent outflows from US equity funds and inflows to Treasury funds.</div></div>","PeriodicalId":15629,"journal":{"name":"Journal of Econometrics","volume":"256 ","pages":"Article 106066"},"PeriodicalIF":4.7,"publicationDate":"2026-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148523827","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Stochastic volatility in mean: Efficient analysis by a generalized mixture sampler 均值随机波动：广义混合采样器的有效分析
IF 4.7 3区 经济学
Journal of Econometrics Pub Date : 2026-07-01 Epub Date: 2025-01-30 DOI: 10.1016/j.jeconom.2025.105949
Daichi Hiraki, Siddhartha Chib, Yasuhiro Omori
{"title":"Stochastic volatility in mean: Efficient analysis by a generalized mixture sampler","authors":"Daichi Hiraki,&nbsp;Siddhartha Chib,&nbsp;Yasuhiro Omori","doi":"10.1016/j.jeconom.2025.105949","DOIUrl":"10.1016/j.jeconom.2025.105949","url":null,"abstract":"<div><div>In this paper we consider the simulation-based Bayesian analysis of stochastic volatility in mean (SVM) models. Extending the highly efficient Markov chain Monte Carlo mixture sampler for the SV model proposed in Kim et al. (1998) and Omori et al. (2007), we develop an accurate approximation of the logarithm of the non-central chi-squared distribution as a mixture of thirty normal distributions. Under this mixture representation, we sample the parameters and latent volatilities in one block. We also detail a correction of the small approximation error by using additional Metropolis–Hastings steps. The proposed method is extended to the SVM model with leverage. The methodology and models are applied to excess holding yields and S&amp;P500 returns in empirical studies, and the SVM models are shown to outperform other volatility models based on marginal likelihoods.</div></div>","PeriodicalId":15629,"journal":{"name":"Journal of Econometrics","volume":"256 ","pages":"Article 105949"},"PeriodicalIF":4.7,"publicationDate":"2026-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148523831","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Text-term selection and analysis: Frequentist and Bayesian strategies and interpretations 文本术语选择与分析：频率论与贝叶斯策略与解释
IF 4.7 3区 经济学
Journal of Econometrics Pub Date : 2026-07-01 Epub Date: 2025-12-16 DOI: 10.1016/j.jeconom.2025.106163
Cathy Yi-Hsuan Chen, George Kapetanios, Wei-Biao Wu
{"title":"Text-term selection and analysis: Frequentist and Bayesian strategies and interpretations","authors":"Cathy Yi-Hsuan Chen,&nbsp;George Kapetanios,&nbsp;Wei-Biao Wu","doi":"10.1016/j.jeconom.2025.106163","DOIUrl":"10.1016/j.jeconom.2025.106163","url":null,"abstract":"<div><div>Economic analysis based on text data has expanded rapidly, yet the ultra-high dimensionality of text data presents substantial challenges for term selection and estimation. We propose the Information-Adaptive Lasso and Information-Adaptive Spike-and-Slab Lasso as novel frequentist and Bayesian approaches to address these challenges. A key theoretical contribution of this study is the establishment of the rate of convergence in term-selection consistency, which we show to be faster than those achieved in the existing Lasso literature. Applying our methods to Federal Open Market Committee (FOMC) statements, we identify and estimate high-impact terms driving fluctuations in monetary policy uncertainty.</div></div>","PeriodicalId":15629,"journal":{"name":"Journal of Econometrics","volume":"256 ","pages":"Article 106163"},"PeriodicalIF":4.7,"publicationDate":"2026-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148523825","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Concentrated MCMC estimation 集中MCMC估计
IF 4.7 3区 经济学
Journal of Econometrics Pub Date : 2026-07-01 Epub Date: 2026-05-05 DOI: 10.1016/j.jeconom.2026.106252
Xuan Xiao, Xingbai Xu, Chengwei Tang, Tuo Liu
{"title":"Concentrated MCMC estimation","authors":"Xuan Xiao,&nbsp;Xingbai Xu,&nbsp;Chengwei Tang,&nbsp;Tuo Liu","doi":"10.1016/j.jeconom.2026.106252","DOIUrl":"10.1016/j.jeconom.2026.106252","url":null,"abstract":"<div><div>This paper studies a concentrated Markov Chain Monte Carlo (MCMC) estimation method that offers significant computational advantages while delivering valid inference for parameters of interest. By reducing the dimension of parameters to be sampled, this method substantially decreases computational time and memory usage relative to both traditional and some state-of-the-art Bayesian algorithms. Its applicability extends to correctly specified or misspecified likelihood functions, as well as generalized method of moments objective functions. Monte Carlo studies demonstrate that the biases and root mean squared errors of the concentrated MCMC estimators are typically smaller than or comparable to those of conventional Bayesian estimators. Furthermore, this method exhibits reliable model selection performance. We establish the large sample properties of the concentrated MCMC estimator. An empirical application analyzing the network spillover effect of stock returns in the Chinese A-share market further illustrates the advantages of this method.</div></div>","PeriodicalId":15629,"journal":{"name":"Journal of Econometrics","volume":"256 ","pages":"Article 106252"},"PeriodicalIF":4.7,"publicationDate":"2026-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148523829","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Transfer estimates for causal effects across heterogeneous sites 跨异质站点因果效应的转移估计
IF 4 3区 经济学
Journal of Econometrics Pub Date : 2026-05-01 Epub Date: 2026-04-25 DOI: 10.1016/j.jeconom.2026.106250
Konrad Menzel
{"title":"Transfer estimates for causal effects across heterogeneous sites","authors":"Konrad Menzel","doi":"10.1016/j.jeconom.2026.106250","DOIUrl":"10.1016/j.jeconom.2026.106250","url":null,"abstract":"<div><div>We consider the problem of extrapolating treatment effects across heterogeneous populations (“sites”/“contexts”). We consider an idealized scenario in which the researcher observes cross-sectional data for a large number of units across several “experimental” sites in which an intervention has already been implemented to a new “target” site for which a baseline survey of unit-specific, pre-treatment outcomes and relevant attributes is available. Our approach treats the baseline as functional data. This choice is motivated by the observation that unobserved site-specific confounders manifest themselves not only in average levels of outcomes, but also how these interact with observed unit-specific attributes. We consider the problem of determining the optimal finite-dimensional feature space in which to solve that prediction problem. We follow a fixed-population approach which evaluates the performance of the predictor given the specific, finite selection of experimental and target sites. Our approach is nonparametric, and our formal results concern the construction of an optimal basis of predictors as well as convergence rates for the estimated conditional average treatment effect relative to the constrained-optimal population predictor for the target site. We quantify the potential gains from adapting experimental estimates to a target location in an application to conditional cash transfer (CCT) programs using a combined data set from five multi-site randomized controlled trials.</div></div>","PeriodicalId":15629,"journal":{"name":"Journal of Econometrics","volume":"255 ","pages":"Article 106250"},"PeriodicalIF":4.0,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147802233","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Implicit score-driven filters for time-varying parameter models 时变参数模型的隐式分数驱动滤波器
IF 4 3区 经济学
Journal of Econometrics Pub Date : 2026-05-01 Epub Date: 2026-04-29 DOI: 10.1016/j.jeconom.2026.106251
Rutger-Jan Lange , Bram van Os , Dick van Dijk
{"title":"Implicit score-driven filters for time-varying parameter models","authors":"Rutger-Jan Lange ,&nbsp;Bram van Os ,&nbsp;Dick van Dijk","doi":"10.1016/j.jeconom.2026.106251","DOIUrl":"10.1016/j.jeconom.2026.106251","url":null,"abstract":"<div><div>We propose an observation-driven modeling framework that allows model parameters to vary over time through an implicit score-driven (ISD) update. The ISD update maximizes the logarithmic observation density with respect to the parameter vector while penalizing the weighted ℓ<sub>2</sub> norm relative to a one-step-ahead predicted parameter. This yields an implicit stochastic-gradient update. We show that the popular class of explicit score-driven (ESD) models arises when the observation log density is linearly approximated around the prediction. By preserving the full density, the ISD update extends the favorable local properties of the ESD update to a global setting. For log-concave observation densities, whether correctly specified or not, the ISD filter is stable for all learning rates, and its updates are contractive in mean squared error toward the (pseudo-)true parameter at every time step. We demonstrate the usefulness of ISD filters in simulations and empirical applications in finance and macroeconomics.</div></div>","PeriodicalId":15629,"journal":{"name":"Journal of Econometrics","volume":"255 ","pages":"Article 106251"},"PeriodicalIF":4.0,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147802234","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Identification of first-price auctions with endogenous entry and possibly biased beliefs 鉴定第一价格拍卖与内生进入和可能有偏见的信念
IF 4 3区 经济学
Journal of Econometrics Pub Date : 2026-05-01 Epub Date: 2026-04-25 DOI: 10.1016/j.jeconom.2026.106248
Tong Li , Yu Zhu
{"title":"Identification of first-price auctions with endogenous entry and possibly biased beliefs","authors":"Tong Li ,&nbsp;Yu Zhu","doi":"10.1016/j.jeconom.2026.106248","DOIUrl":"10.1016/j.jeconom.2026.106248","url":null,"abstract":"<div><div>This paper studies identification of first-price auctions where bidders enter auctions endogenously and may have biased beliefs about the valuation distribution. We analyze the symmetric independent private setup under three commonly used entry models. In the Levin-Smith entry model, the primitives are point-identified. In the Samuelson entry model, the primitives are identified only on a subset of the support of valuations. In the arbitrarily selective entry model, the primitives are partially identified in general but can be point-identified with exogenous variation in both the number of potential bidders and an entry cost shifter.</div></div>","PeriodicalId":15629,"journal":{"name":"Journal of Econometrics","volume":"255 ","pages":"Article 106248"},"PeriodicalIF":4.0,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147802337","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Reprint of: Nonparametric estimation for high-frequency data incorporating trading information 转载自：包含交易信息的高频数据的非参数估计
IF 4 3区 经济学
Journal of Econometrics Pub Date : 2026-03-01 Epub Date: 2026-01-30 DOI: 10.1016/j.jeconom.2026.106202
Wenhao Cui , Jie Hu , Jiandong Wang
{"title":"Reprint of: Nonparametric estimation for high-frequency data incorporating trading information","authors":"Wenhao Cui ,&nbsp;Jie Hu ,&nbsp;Jiandong Wang","doi":"10.1016/j.jeconom.2026.106202","DOIUrl":"10.1016/j.jeconom.2026.106202","url":null,"abstract":"<div><div>We propose nonparametric estimators for the explicative part of the noise in a model where the market microstructure noise is an unknown function of the trading information while allowing for the presence of an additional residual noise component. Our method allows for dependence in the observable trading information and accommodates the presence of infinite variation jumps in the efficient price process. We establish the convergence and asymptotic normality of the proposed estimators. We also propose a two-step Laplace estimator of integrated volatility where we replace the observed price with the estimated price by removing the explicative part of the market microstructure noise. The finite sample properties of both the nonparametric estimators and the two-step Laplace estimator are examined through Monte Carlo simulations. We find that our method is robust to misspecification of the unknown functional form given finite sample size. Furthermore, an empirical application using high-frequency data demonstrates that our method outperforms commonly employed parametric methods.</div></div>","PeriodicalId":15629,"journal":{"name":"Journal of Econometrics","volume":"254 ","pages":"Article 106202"},"PeriodicalIF":4.0,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147399598","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Robust realized integrated beta estimator with application to dynamic analysis of integrated beta 稳健的已实现综合贝塔估计器及其在综合贝塔动态分析中的应用
IF 4 3区 经济学
Journal of Econometrics Pub Date : 2026-03-01 Epub Date: 2024-07-16 DOI: 10.1016/j.jeconom.2024.105810
Minseog Oh , Donggyu Kim , Yazhen Wang
{"title":"Robust realized integrated beta estimator with application to dynamic analysis of integrated beta","authors":"Minseog Oh ,&nbsp;Donggyu Kim ,&nbsp;Yazhen Wang","doi":"10.1016/j.jeconom.2024.105810","DOIUrl":"10.1016/j.jeconom.2024.105810","url":null,"abstract":"<div><div>In this paper, we develop a robust non-parametric realized integrated beta estimator using high-frequency financial data contaminated by microstructure noise, which is robust to the stylized features, such as the time-varying beta and the price-dependent and autocorrelated microstructure noise. With this robust realized integrated beta estimator, we investigate dynamic structures of integrated betas and find a persistent autoregressive structure. To model this dynamic structure, we utilize the autoregressive–moving-average (ARMA) model for daily integrated market betas. We call this the dynamic realized beta (DR Beta). Then, we propose a quasi-likelihood procedure for estimating the parameters of the ARMA model with the robust realized integrated beta estimator as the proxy. We establish asymptotic theorems for the proposed estimator and conduct a simulation study to check the performance of finite samples of the estimator. The proposed DR Beta model with the robust realized beta estimator is also illustrated by using data from the E-mini S&amp;P 500 index futures and the top 50 large trading volume stocks from the S&amp;P 500 and an application to constructing market-neutral portfolios.</div></div>","PeriodicalId":15629,"journal":{"name":"Journal of Econometrics","volume":"254 ","pages":"Article 105810"},"PeriodicalIF":4.0,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141714586","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
High dimensional regression coefficient test with high frequency data 高频数据的高维回归系数测试
IF 4 3区 经济学
Journal of Econometrics Pub Date : 2026-03-01 Epub Date: 2024-07-17 DOI: 10.1016/j.jeconom.2024.105812
Dachuan Chen , Long Feng , Per A. Mykland , Lan Zhang
{"title":"High dimensional regression coefficient test with high frequency data","authors":"Dachuan Chen ,&nbsp;Long Feng ,&nbsp;Per A. Mykland ,&nbsp;Lan Zhang","doi":"10.1016/j.jeconom.2024.105812","DOIUrl":"10.1016/j.jeconom.2024.105812","url":null,"abstract":"<div><div><span>This paper presents the first study on high-dimensional regression coefficient tests with high-frequency financial data. These tests allow the number of regressors to be larger than the number of observations within each estimation block and can grow to infinity in asymptotics. In this paper, the sum-type test and max-type test have been proposed, where the former is suitable for the dense alternative (many small betas) and the latter is suitable for the sparse alternative (a very small number of large betas). By showing the asymptotic independence between the sum-type test and max-type test, the paper proposes a third test – Fisher’s combination test, which is robust to both dense and sparse alternatives. The paper derives the limiting null distributions of the three proposed tests and analyzes the </span>asymptotic behavior of their powers. Monte Carlo simulations demonstrate the validity of the theoretical results developed in this paper. Empirical study shows the impact of high frequency (HF) factors when being added to a Fama–French-style factor model. We found that the HF effects are time varying. The proposed tests can help identify those time periods when the HF factors carry (significant) incremental information for the test asset. Our tests could shed light on market timing in a trading strategy.</div></div>","PeriodicalId":15629,"journal":{"name":"Journal of Econometrics","volume":"254 ","pages":"Article 105812"},"PeriodicalIF":4.0,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141841084","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
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