Journal of Econometrics最新文献

英文中文

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 Q1 ECONOMICS

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

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.

本文分析了对已实现方差（RV）估计器在固有时间内进行日内收益抽样的好处。我们从理论上表明，在有限的样本中，根据允许的抽样信息，RV估计器在以下两种情况下是最有效的：即在价格以预先确定的阈值变化时进行抽样，或者在实现业务时间的新概念下，根据观察到的交易和估计的tick方差的组合进行抽样。该分析建立在这样一个假设之上，即资产价格遵循一种随时间变化的扩散，这种扩散伴随着一个跳跃过程，该过程分别模拟了交易时间。这提供了一个灵活的模型，允许杠杆规范和霍克斯型跳跃过程，并单独捕获经验变化的交易强度和tick方差过程，这对于解耦抽样方案的驱动力特别相关。大量的模拟证实了我们的理论结果，并表明对于低噪声水平，撞击时间采样仍然是优越的，而对于增加噪声水平，实现业务时间成为经验上最有效的采样方案。对股票数据的应用为使用这些内在抽样方案构建更有效的RV估计器以及改进的预测性能提供了经验证据。

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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 Q1 ECONOMICS

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

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.

本文利用最小绝对偏差（LAD）回归，提出了基于符号的多元波动率结构变化CUSUM和QS检验。这些测试提供了放松力矩条件的优势，并对各种重尾创新提供了更大的鲁棒性。为了解决由于备选假设下长期方差（LRV）估计不准确而导致的两种基本统计量的潜在功率损失，本文提出了两种改进的统计量，它们利用LAD非参数方法在零假设和备选假设下对LRV进行一致估计。该研究建立了相对温和的条件，在这些条件下，这些测试具有标准的零分布，并且对各种固定的替代方案具有强大的功能，包括多元波动中的平稳变化和单个或多个断点。此外，本文还研究了在两种不同类型的局部选择下修正统计量的渐近性质。蒙特卡罗模拟表明，当处理重尾数据时，所提出的测试在有限样本中优于其他广泛使用的测试。对金融数据集的两个实证应用进一步证实了新测试方法的有效性。

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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 Q1 ECONOMICS

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

We propose a novel class of multivariate GARCH models that incorporate realized measures of volatility and correlations. The key innovation is an unconstrained vector parametrization 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.

我们提出了一类新的多元GARCH模型，其中包括波动性和相关性的实现措施。关键的创新是条件相关矩阵的无约束向量参数化，这使得使用因素模型的相关性。这种方法优雅地解决了高维环境下多元GARCH模型面临的主要挑战。作为一个例子，我们探索块相关矩阵，自然地简化为线性因子模型的条件相关性。该模型应用于九种资产的回报，其样本内和样本外表现优于几种流行的基准。

引用次数: 0

BUMVU estimators

IF 4 3区经济学 Q1 ECONOMICS

Journal of Econometrics

Pub Date : 2026-03-01 Epub Date: 2025-01-17 DOI: 10.1016/j.jeconom.2024.105942

Aleksey Kolokolov , Roberto Renò , Patrick Zoi

We provide necessary and sufficient conditions for an (Unbiased) Block estimator to have Uniformly Minimum Variance. Our theory parallels the theory of UMVU estimation, the main novel insight being the focus on the covariance among blocks. We use this theory to derive lower variance bounds for block estimators of functionals of high-frequency volatility when the block size is fixed. We further show the relevance of the new theory for the classical problem of estimation of homoskedastic nonparametric regressions with varying mean. Finally, we introduce a new test for the presence of drift in financial data which exploits the precision of BUMVU estimators. The test shows abundant presence of drift in financial data.

给出了（无偏）块估计具有一致最小方差的充分必要条件。我们的理论与UMVU估计理论相似，主要的新颖见解是关注块之间的协方差。当块大小固定时，我们利用这一理论推导出高频波动函数块估计的低方差界。我们进一步证明了新理论对变均值同方差非参数回归估计的经典问题的相关性。最后，我们介绍了一种新的金融数据漂移的检验方法，该方法利用了BUMVU估计器的精度。检验表明，金融数据中存在大量的漂移现象。

引用次数: 0

FX futures invariance 外汇期货不变性

IF 4 3区经济学 Q1 ECONOMICS

Journal of Econometrics

Pub Date : 2026-03-01 Epub Date: 2025-12-16 DOI: 10.1016/j.jeconom.2025.106165

Torben G. Andersen , Oleg Bondarenko , Eleni Gousgounis , Esen Onur

We develop and empirically examine a novel intraday invariance relation among trading activity variables across a set of currencies in the foreign exchange (FX) futures market exploiting tick level data. Our Trading Invariance (TI) hypothesis reflects an equilibrium involving trade-offs between the risk per trade versus market liquidity as captured by the bid-ask spread and market depth. We observe exogenous breaks in the trading costs for many of the currencies, as the exchange lowered the tick size for individual contracts at different points in time. Using these incidents as quasi-natural experiments, we confirm that the remaining components of the TI hypothesis adjust to maintain the equilibrium by shifts in the trading intensity and market depth. In contrast, alternative invariance relations fail dramatically when confronted with this type of exogenous shock. We further confirm that the values of key coefficients in the TI relation are similar across assets and in good correspondence with the theoretically predicted values. Our results point towards a fundamental equilibrium mechanism that should be accommodated within existing market microstructure paradigms. Moreover, they have direct implications for market design and surveillance.

我们开发并实证检验了外汇（FX）期货市场中一组货币的交易活动变量之间的一种新的日内不变性关系。我们的交易不变性（TI）假设反映了一种均衡，涉及每笔交易的风险与市场流动性之间的权衡，这是由买卖价差和市场深度捕获的。我们观察到许多货币的交易成本出现了外生断裂，因为交易所在不同的时间点降低了单个合约的价格。利用这些事件作为准自然实验，我们证实TI假设的剩余成分通过交易强度和市场深度的变化来调整以保持均衡。相反，当面对这种外生冲击时，替代不变性关系会急剧失效。我们进一步证实，TI关系中的关键系数值在资产之间是相似的，并且与理论预测值很好地对应。我们的研究结果指向了一个基本的均衡机制，该机制应适应现有的市场微观结构范式。此外，它们对市场设计和监管有直接影响。

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引用次数: 0

Realized drift 实现的漂移

IF 4 3区经济学 Q1 ECONOMICS

Journal of Econometrics

Pub Date : 2026-03-01 Epub Date: 2024-07-16 DOI: 10.1016/j.jeconom.2024.105813

Sébastien Laurent , Roberto Renò , Shuping Shi

Drift and volatility are two mainsprings of asset price dynamics. While volatilities have been studied extensively in the literature, drifts are commonly believed to be impossible to estimate and largely ignored in the literature. This paper shows how to detect drift using realized autocovariance implemented on high-frequency data. We use a theoretical treatment in which the classical model for the efficient price, an Itō semimartingale possibly contaminated by microstructure noise, is enriched with drift and volatility explosions. Our theory advocates a novel decomposition for realized variance into a drift and a volatility component, which leads to significant improvements in volatility forecasting.

漂移和波动是资产价格动态的两个主要动力。虽然波动性在文献中得到了广泛的研究，但漂移通常被认为是不可能估计的，在文献中很大程度上被忽略了。本文介绍了如何利用在高频数据上实现的自协方差来检测漂移。我们使用了一种理论处理，其中有效价格的经典模型，一个可能被微观结构噪声污染的ititi半鞅，富含漂移和挥发性爆炸。我们的理论主张将已实现方差分解为漂移和波动分量，从而显著改善波动预测。

引用次数: 0

Estimation of common factors for microstructure noise and efficient price in a high-frequency dual factor model 高频双因素模型中微观结构噪声和有效价格共同因素的估计

IF 4 3区经济学 Q1 ECONOMICS

Journal of Econometrics

Pub Date : 2026-03-01 Epub Date: 2023-02-01 DOI: 10.1016/j.jeconom.2022.12.005

Yu-Ning Li , Jia Chen , Oliver Linton

We develop the Double Principal Component Analysis (DPCA) based on a dual factor structure for high-frequency intraday returns contaminated with microstructure noise. The dual factor structure allows a factor structure for microstructure noise in addition to the factor structure for efficient log-prices. We construct estimators of factors for both efficient log-prices and microstructure noise as well as their common components, and provide uniform consistency of these estimators when the number of assets and the sampling frequency go to infinity. In a Monte Carlo exercise, we compare our DPCA method to a PCA-VECM method. Finally, an empirical analysis of intraday returns of S&P 500 Index constituents provides evidence of co-movement of the microstructure noise that distinguishes from latent systematic risk factors.

我们开发了基于双因子结构的双主成分分析（DPCA），用于受微观结构噪声污染的高频日内收益。双因素结构允许微观结构噪声的因素结构除了有效的对数价格的因素结构。我们构造了有效对数价格和微观结构噪声及其共同成分的因子估计量，并提供了这些估计量在资产数量和采样频率趋于无穷大时的一致一致性。在蒙特卡罗练习中，我们将DPCA方法与PCA-VECM方法进行比较。最后，对标准普尔500指数成分股日内收益的实证分析提供了微观结构噪声共同运动的证据，这种噪声区别于潜在的系统性风险因素。

引用次数: 0

High-dimensional conditional factor model 高维条件因子模型

IF 4 3区经济学 Q1 ECONOMICS

Journal of Econometrics

Pub Date : 2026-03-01 Epub Date: 2026-02-07 DOI: 10.1016/j.jeconom.2026.106203

Zhonghao Fu , Shang Gao , Liangjun Su , Xia Wang

This paper studies estimation and variable selection in conditional factor models with high-dimensional instruments, where the coefficient matrix exhibits a low-rank and row-sparse structure. We propose a multi-stage estimation procedure that combines nuclear norm regularization and adaptive group LASSO regression to consistently estimate latent factors and row-sparse loading coefficients, while selecting relevant instrumental characteristics. We establish theoretical results for estimation consistency, selection consistency, and post-LASSO inference for estimators of factors and loading coefficients at multiple stages. Furthermore, we implement a singular value thresholding procedure to determine the number of factors. Simulation results demonstrate the effectiveness of our estimators in consistently estimating factor loadings, selecting the appropriate number of factors, and conducting inference. Finally, we apply the proposed method to an empirical study on asset return prediction, showcasing its practical utility in real-world applications.

本文研究了高维仪器条件因子模型中系数矩阵呈现低秩、行稀疏结构的估计和变量选择问题。我们提出了一种结合核范数正则化和自适应群体LASSO回归的多阶段估计方法，以一致地估计潜在因素和行稀疏负载系数，同时选择相关的工具特征。我们建立了多阶段因子和载荷系数估计一致性、选择一致性和lasso后推理的理论结果。此外，我们实现了一个奇异值阈值过程来确定因子的数量。仿真结果证明了我们的估计器在一致地估计因子负载、选择适当数量的因子和进行推理方面的有效性。最后，我们将该方法应用于资产收益预测的实证研究，展示了其在实际应用中的实用性。

引用次数: 0

Statistical inference for systemic risk-driven portfolio selection 系统性风险驱动投资组合选择的统计推断

IF 4 3区经济学 Q1 ECONOMICS

Journal of Econometrics

Pub Date : 2026-01-01 Epub Date: 2025-11-19 DOI: 10.1016/j.jeconom.2025.106127

Tsz Chai Fung , Yinhuan Li , Liang Peng , Linyi Qian

Portfolio selection in modern finance involves constructing optimal asset allocation strategies that balance risk and return. However, traditional portfolio selection faces new challenges due to systemic events, as exemplified by the financial crisis and the COVID-19 pandemic. In response, we introduce a nonparametric systemic risk-driven portfolio selection approach that models market and portfolio losses using kernel density estimation. In the event of market underperformance, we aim to minimize the conditional expected shortfall (CoES) of portfolio losses while targeting a specific return. We observe that directly estimating CoES using nonparametric kernel methods does not produce a convex objective function with respect to portfolio weights. To address this, we propose an augmentation of the objective function to ensure convexity, guaranteeing a unique solution for optimal portfolio weights regardless of the sample size. Through simulations, we demonstrate our proposed approach’s consistency and out-of-sample performance compared to benchmark portfolio criteria and CoES-based parametric models. Applying this method to a real dataset showcases its superior risk–return performance relative to existing approaches.

现代金融中的投资组合选择涉及构建平衡风险与收益的最优资产配置策略。然而，由于金融危机和COVID-19大流行等系统性事件，传统的投资组合选择面临新的挑战。为此，我们引入了一种非参数系统风险驱动的投资组合选择方法，该方法使用核密度估计对市场和投资组合损失进行建模。在市场表现不佳的情况下，我们的目标是最小化投资组合损失的条件预期损失（CoES），同时以特定的回报为目标。我们观察到，使用非参数核方法直接估计CoES不会产生关于投资组合权重的凸目标函数。为了解决这个问题，我们提出了一个目标函数的增强以确保凸性，保证无论样本大小如何，最优投资组合权重都有唯一的解决方案。通过仿真，与基准投资组合标准和基于coes的参数模型相比，我们证明了我们提出的方法的一致性和样本外性能。将该方法应用于真实数据集，相对于现有方法，它具有更好的风险回报性能。

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引用次数: 0

Corrigendum to “Robust mutual fund selection with false discovery rate control” [Journal of Econometrics 252 (2025) 106121] “控制错误发现率的稳健共同基金选择”的勘误表[计量经济学杂志252 (2025)106121]

IF 4 3区经济学 Q1 ECONOMICS

Journal of Econometrics

Pub Date : 2026-01-01 Epub Date: 2025-12-03 DOI: 10.1016/j.jeconom.2025.106162

Hongfei Wang , Ping Zhao , Long Feng , Zhaojun Wang

引用次数: 0

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Journal of Econometrics

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