发布求助
文献互助 智能选刊 最新文献

Journal of Econometrics最新文献

筛选
英文 中文
Intraday volatility patterns from short-dated options 短期期权的日内波动率模式
IF 4 3区 经济学
Journal of Econometrics Pub Date : 2026-03-01 Epub Date: 2024-04-19 DOI: 10.1016/j.jeconom.2024.105732
Viktor Todorov , Yang Zhang
{"title":"Intraday volatility patterns from short-dated options","authors":"Viktor Todorov ,&nbsp;Yang Zhang","doi":"10.1016/j.jeconom.2024.105732","DOIUrl":"10.1016/j.jeconom.2024.105732","url":null,"abstract":"<div><div>We propose a nonparametric estimator for the deterministic periodic component of volatility from short-dated options within an in-fill asymptotic setting. The estimator uses options with zero and one day to expiration sampled at high-frequency during a trading day. At each point in time, we aggregate the options to form nonparametric estimates of conditional risk-neutral expectations of future integrated return variation for the two available option tenors. A suitable ratio of these estimates removes the stochastic components of the conditional expectations<span><span> of future volatility, up to asymptotically higher-order terms, and allows to form estimates of the deterministic periodic component of volatility. We derive a Central Limit Theorem for the estimator, with its </span>rate of convergence determined from the mesh of the strike grid and the length of the time to expiration of the options. The newly-developed estimation procedure is applied to S&amp;P 500 index options data.</span></div></div>","PeriodicalId":15629,"journal":{"name":"Journal of Econometrics","volume":"254 ","pages":"Article 105732"},"PeriodicalIF":4.0,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140769219","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
Diffusion index forecasting with tensor data 用张量数据预测扩散指数
IF 4 3区 经济学
Journal of Econometrics Pub Date : 2026-03-01 Epub Date: 2026-02-10 DOI: 10.1016/j.jeconom.2026.106204
Bin Chen , Yuefeng Han , Qiyang Yu
{"title":"Diffusion index forecasting with tensor data","authors":"Bin Chen ,&nbsp;Yuefeng Han ,&nbsp;Qiyang Yu","doi":"10.1016/j.jeconom.2026.106204","DOIUrl":"10.1016/j.jeconom.2026.106204","url":null,"abstract":"<div><div>In this paper, we consider diffusion index forecasting with both tensor and non-tensor predictors, where the tensor structure is preserved with a Canonical Polyadic (CP) tensor factor model. When the number of non-tensor predictors is small, we study the asymptotic properties of the least squares estimator in this tensor factor-augmented regression, allowing for factors with different strengths. We derive an analytical formula for prediction intervals that accounts for the estimation uncertainty of the latent factors. In addition, we propose a novel thresholding estimator for the high-dimensional covariance matrix that is robust to cross-sectional dependence. When the number of non-tensor predictors exceeds or diverges with the sample size, we introduce a multi-source factor-augmented sparse regression model and establish the consistency of the corresponding penalized estimator. Simulation studies validate our theoretical results and an empirical application to U.S. trade flows demonstrates the advantages of our approach over other popular methods in the literature.</div></div>","PeriodicalId":15629,"journal":{"name":"Journal of Econometrics","volume":"254 ","pages":"Article 106204"},"PeriodicalIF":4.0,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146171157","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
Bespoke realized volatility: Tailored measures of risk for volatility prediction 定制的已实现波动率：为波动率预测量身定制的风险度量
IF 4 3区 经济学
Journal of Econometrics Pub Date : 2026-03-01 Epub Date: 2025-11-10 DOI: 10.1016/j.jeconom.2025.106122
Andrew J. Patton , Haozhe Zhang
{"title":"Bespoke realized volatility: Tailored measures of risk for volatility prediction","authors":"Andrew J. Patton ,&nbsp;Haozhe Zhang","doi":"10.1016/j.jeconom.2025.106122","DOIUrl":"10.1016/j.jeconom.2025.106122","url":null,"abstract":"<div><div>Standard realized volatility (RV) measures estimate the latent volatility of an asset price using high frequency data with no reference to how or where the estimate will subsequently be used. This paper presents methods for “tailoring” the estimate of volatility to the application in which it will be used. For example, if the volatility measure will be used in a specific parametric forecasting model, it may be possible to exploit that knowledge to construct a better measure of volatility. We use methods from machine learning to estimate optimal “bespoke” RVs for heterogeneous autoregressive (HAR) and GARCH-X forecasting applications. We apply the methods to 886 U.S. stock returns and find that bespoke RVs significantly improve out-of-sample forecast performance. We find that, across a variety of volatility models, the bespoke RV places more weight on data from the end of the trade day, and that the optimal bespoke weights can be well-approximated by a simple parametric function.</div></div>","PeriodicalId":15629,"journal":{"name":"Journal of Econometrics","volume":"254 ","pages":"Article 106122"},"PeriodicalIF":4.0,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147399101","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
Probability distributions for realized covariance measures 已实现协方差测度的概率分布
IF 4 3区 经济学
Journal of Econometrics Pub Date : 2026-03-01 Epub Date: 2025-02-04 DOI: 10.1016/j.jeconom.2025.105954
Michael Stollenwerk
{"title":"Probability distributions for realized covariance measures","authors":"Michael Stollenwerk","doi":"10.1016/j.jeconom.2025.105954","DOIUrl":"10.1016/j.jeconom.2025.105954","url":null,"abstract":"<div><div>Realized covariance measures (RCs) are an essential input for assessing the risks of different investment allocations. Thus, it is useful to model and forecast them. To this end, a realistic distributional assumption is needed. In this paper, we compare all probability distributions that have so far in the literature been applied to time-series of RCs. We derive them in a unified framework based on their stochastic representations using random lower and upper triangular matrices. These matrices are composed of standard normal distributions in the off-diagonal elements and <span><math><mi>χ</mi></math></span>-distributions on the diagonals (Barlett matrices). Furthermore, we derive a novel family of probability distributions (the <span><math><mi>t</mi></math></span>-Riesz distribution family), which has a property we call <em>tail-homogeneity</em>. This property means that in crisis periods, i.e. large RCs, our distribution family realistically assumes high dependence between the individual entries of the RCs. We show theoretically how all the distributions differ from each other, and how they are related to each other. In the empirical part, we demonstrate how the theoretical differences translate into differences in fit and forecasting performance. We show that our novel distribution family achieves the best fit. Out-of-sample forecasting comparisons further corroborate the excellent performance of our novel distribution family.</div></div>","PeriodicalId":15629,"journal":{"name":"Journal of Econometrics","volume":"254 ","pages":"Article 105954"},"PeriodicalIF":4.0,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147399102","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
Statistical inference of optimal allocations I: Regularities and their implications 最优配置的统计推断ⅰ：规律及其启示
IF 4 3区 经济学
Journal of Econometrics Pub Date : 2026-03-01 Epub Date: 2026-02-28 DOI: 10.1016/j.jeconom.2026.106217
Kai Feng , Han Hong , Denis Nekipelov
{"title":"Statistical inference of optimal allocations I: Regularities and their implications","authors":"Kai Feng ,&nbsp;Han Hong ,&nbsp;Denis Nekipelov","doi":"10.1016/j.jeconom.2026.106217","DOIUrl":"10.1016/j.jeconom.2026.106217","url":null,"abstract":"<div><div>In this paper, we develop a functional differentiability approach for solving statistical optimal allocation problems. We derive Hadamard differentiability of the value functions through analyzing the properties of the sorting operator using tools from geometric measure theory. Building on our Hadamard differentiability results, we apply the functional delta method to obtain the asymptotic properties of the value function process for the binary constrained optimal allocation problem and the plug-in ROC curve estimator. Moreover, the convexity of the optimal allocation value functions facilitates demonstrating the degeneracy of first order derivatives with respect to the policy. We then present a double / debiased estimator for the value functions. Importantly, the conditions that validate Hadamard differentiability justify the margin assumption from the statistical classification literature for the fast convergence rate of plug-in methods.</div></div>","PeriodicalId":15629,"journal":{"name":"Journal of Econometrics","volume":"254 ","pages":"Article 106217"},"PeriodicalIF":4.0,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147384790","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
Efficient sampling for realized variance estimation in time-changed diffusion models 时变扩散模型中实现方差估计的有效采样方法
IF 4 3区 经济学
Journal of Econometrics Pub Date : 2026-03-01 Epub Date: 2025-11-26 DOI: 10.1016/j.jeconom.2025.106150
Timo Dimitriadis , Roxana Halbleib , Jeannine Polivka , Jasper Rennspies , Sina Streicher , Axel Friedrich Wolter
{"title":"Efficient sampling for realized variance estimation in time-changed diffusion models","authors":"Timo Dimitriadis ,&nbsp;Roxana Halbleib ,&nbsp;Jeannine Polivka ,&nbsp;Jasper Rennspies ,&nbsp;Sina Streicher ,&nbsp;Axel Friedrich Wolter","doi":"10.1016/j.jeconom.2025.106150","DOIUrl":"10.1016/j.jeconom.2025.106150","url":null,"abstract":"<div><div>This paper analyzes the benefits of sampling intraday returns in intrinsic time for the realized variance (RV) estimator. We theoretically show in finite samples that depending on the permitted sampling information, the RV estimator is most efficient under either hitting time sampling that samples whenever the price changes by a pre-determined threshold, or under the new concept of realized business time that samples according to a combination of observed trades and estimated tick variance. The analysis builds on the assumption that asset prices follow a diffusion that is time-changed with a jump process that separately models the transaction times. This provides a flexible model that allows for leverage specifications and Hawkes-type jump processes and separately captures the empirically varying trading intensity and tick variance processes, which are particularly relevant for disentangling the driving forces of the sampling schemes. Extensive simulations confirm our theoretical results and show that for low levels of noise, hitting time sampling remains superior while for increasing noise levels, realized business time becomes the empirically most efficient sampling scheme. An application to stock data provides empirical evidence for the benefits of using these intrinsic sampling schemes to construct more efficient RV estimators as well as for an improved forecast performance.</div></div>","PeriodicalId":15629,"journal":{"name":"Journal of Econometrics","volume":"254 ","pages":"Article 106150"},"PeriodicalIF":4.0,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147399600","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 estimation of integrated and spot volatility 综合和现货波动的鲁棒估计
IF 4 3区 经济学
Journal of Econometrics Pub Date : 2026-03-01 Epub Date: 2023-12-01 DOI: 10.1016/j.jeconom.2023.105614
Z. Merrick Li , Oliver Linton
{"title":"Robust estimation of integrated and spot volatility","authors":"Z. Merrick Li ,&nbsp;Oliver Linton","doi":"10.1016/j.jeconom.2023.105614","DOIUrl":"10.1016/j.jeconom.2023.105614","url":null,"abstract":"<div><div>We introduce a new method to estimate the integrated volatility (IV) and the spot volatility (SV) based on noisy high-frequency data. Our method employs the ReMeDI approach introduced by <span><span>Li and Linton (2022)</span></span> to estimate the moments of microstructure noise and thereby eliminate their influence, and the pre-averaging method to target the volatility parameter. The method is robust: it can be applied when the efficient price exhibits stochastic volatility and jumps, the observation times are random, and the noise process is nonstationary, autocorrelated, asymptotically vanishing and dependent on the efficient price. We derive the limit distributions for the proposed estimators under the infill asymptotics in a general setting. Our extensive simulation studies demonstrate the robustness, accuracy and computational efficiency of our estimators compared to several alternative estimators recently proposed in the literature. Empirically, we show that neglecting the complexities of noise and the random observation times generates substantial biases in volatility estimation and may yield a different intraday volatility pattern.</div></div>","PeriodicalId":15629,"journal":{"name":"Journal of Econometrics","volume":"254 ","pages":"Article 105614"},"PeriodicalIF":4.0,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138516586","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
Regularizing fairness in optimal policy learning with distributional targets 分配目标下最优策略学习公平性的正则化
IF 4 3区 经济学
Journal of Econometrics Pub Date : 2026-03-01 Epub Date: 2026-01-28 DOI: 10.1016/j.jeconom.2026.106186
Anders Bredahl Kock , David Preinerstorfer
{"title":"Regularizing fairness in optimal policy learning with distributional targets","authors":"Anders Bredahl Kock ,&nbsp;David Preinerstorfer","doi":"10.1016/j.jeconom.2026.106186","DOIUrl":"10.1016/j.jeconom.2026.106186","url":null,"abstract":"<div><div>A decision maker typically (i) incorporates training data to learn about the relative effectiveness of treatments, and (ii) chooses an implementation mechanism that implies an “optimal” predicted outcome distribution according to some target functional. Nevertheless, a fairness-aware decision maker may not be satisfied achieving said optimality at the cost of being “unfair” against a subgroup of the population, in the sense that the outcome distribution in that subgroup deviates too strongly from the overall optimal outcome distribution. We study a framework that allows the decision maker to regularize such deviations, while allowing for a wide range of target functionals and fairness measures to be employed. We establish regret and consistency guarantees for empirical success policies with (possibly) data-driven preference parameters, and provide numerical results. Furthermore, we briefly illustrate the methods in two empirical settings.</div></div>","PeriodicalId":15629,"journal":{"name":"Journal of Econometrics","volume":"254 ","pages":"Article 106186"},"PeriodicalIF":4.0,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146076155","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
Sign-based tests for structural changes in multivariate volatility 基于符号的多元波动结构变化检验
IF 4 3区 经济学
Journal of Econometrics Pub Date : 2026-03-01 Epub Date: 2026-02-14 DOI: 10.1016/j.jeconom.2026.106211
Jilin Wu , Zhijie Xiao , Mengxi Zhang , Zhenhuan Zhang
{"title":"Sign-based tests for structural changes in multivariate volatility","authors":"Jilin Wu ,&nbsp;Zhijie Xiao ,&nbsp;Mengxi Zhang ,&nbsp;Zhenhuan Zhang","doi":"10.1016/j.jeconom.2026.106211","DOIUrl":"10.1016/j.jeconom.2026.106211","url":null,"abstract":"<div><div>This paper proposes sign-based CUSUM and QS tests for structural changes in multivariate volatility using least absolute deviation (LAD) regression. These tests offer the advantage of relaxing moment conditions and providing greater robustness against various heavy-tailed innovations. To address potential power losses in the two basic statistics due to inaccurate estimation of the long-run variance (LRV) under alternatives, the paper then proposes two modified statistics that utilize LAD nonparametric methods for consistent estimation of the LRV under both the null and alternative hypotheses. The study establishes relatively mild conditions under which these tests have standard null distributions and are powerful against various fixed alternatives, including smooth changes and single or multiple breakpoints in multivariate volatility. Additionally, the paper examines the asymptotic properties of the modified statistics under two different types of local alternatives. Monte Carlo simulations demonstrate that the proposed tests outperform other widely used tests in finite samples when dealing with heavy-tailed data. Two empirical applications to financial datasets further confirm the effectiveness of the new testing methods.</div></div>","PeriodicalId":15629,"journal":{"name":"Journal of Econometrics","volume":"254 ","pages":"Article 106211"},"PeriodicalIF":4.0,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147384789","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
A multivariate realized GARCH model 一种多元实现GARCH模型
IF 4 3区 经济学
Journal of Econometrics Pub Date : 2026-03-01 Epub Date: 2025-05-31 DOI: 10.1016/j.jeconom.2025.106040
Ilya Archakov , Peter Reinhard Hansen , Asger Lunde
{"title":"A multivariate realized GARCH model","authors":"Ilya Archakov ,&nbsp;Peter Reinhard Hansen ,&nbsp;Asger Lunde","doi":"10.1016/j.jeconom.2025.106040","DOIUrl":"10.1016/j.jeconom.2025.106040","url":null,"abstract":"<div><div><span>We propose a novel class of multivariate GARCH models that incorporate realized measures of volatility and correlations. The key innovation is an unconstrained vector </span>parametrization<span> of the conditional correlation matrix, which enables the use of factor models for correlations. This approach elegantly addresses the main challenge faced by multivariate GARCH models in high-dimensional settings. As an illustration, we explore block correlation matrices that naturally simplify to linear factor models for the conditional correlations. The model is applied to the returns of nine assets, and its in-sample and out-of-sample performance compares favorably against several popular benchmarks.</span></div></div>","PeriodicalId":15629,"journal":{"name":"Journal of Econometrics","volume":"254 ","pages":"Article 106040"},"PeriodicalIF":4.0,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147399103","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
首页 上一页 下一页 尾页
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整，为了账户安全，请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
请完成安全验证×
相关产品
×
本文献相关产品
联系我们：info@booksci.cn Book学术提供免费学术资源搜索服务，方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号：604180095
Book学术官方微信
小红书