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Empirical Asset Pricing with Many Test Assets Journal of Financial Econometrics (IF 3.976) Pub Date : 2024-03-15 Rasmus Lönn, Peter C Schotman
We formulate the problem of estimating risk prices in a stochastic discount factor (SDF) model as an instrumental variables regression. The IV estimator allows efficient estimation for models with non-traded factors and many test assets. Optimal instruments are constructed using a regularized sparse first stage regression. In a simulation study, the IV estimator is close to the infeasible GMM estimator
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Measures of Model Risk for Continuous-Time Finance Models Journal of Financial Econometrics (IF 3.976) Pub Date : 2024-02-03 Emese Lazar, Shuyuan Qi, Radu Tunaru
Measuring model risk is required by regulators in financial and insurance markets. We separate model risk into parameter estimation risk (PER) and model specification risk (MSR), and we propose expected shortfall type model risk measures applied to Lévy jump, affine jump-diffusion, and multifactor models. We investigate the impact of PER and MSR on the models’ ability to capture the joint dynamics
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Unifying Estimation and Inference for Linear Regression with Stationary and Integrated or Near-Integrated Variables Journal of Financial Econometrics (IF 3.976) Pub Date : 2023-11-06 Shaoxin Hong, Daniel J Henderson, Jiancheng Jiang, Qingshan Ni
There is a discrepancy in the limiting distributions of least-squares estimators for stationary and integrated variables. For statistical inference, it must be decided which distribution should be used in advance. This motivates us to develop a unifying inference procedure based on weighted estimation. The asymptotic distributions of the proposed estimators are developed and a random weighting bootstrap
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A Stochastic Price Duration Model for Estimating High-Frequency Volatility Journal of Financial Econometrics (IF 3.976) Pub Date : 2023-10-24 Denis Pelletier, Wei Wei
We propose a stochastic price duration model to estimate high-frequency volatility. A price duration is directly linked to volatility from the passage time theory for Brownian motions, and it possesses several advantages over returns for estimating volatility. We employ price durations in a parametric model that directly specifies stochastic volatility dynamics. Our approach allows us to estimate intraday
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A Tale of Two Tails: A New Unique Information Share Measure Based on Copulas Journal of Financial Econometrics (IF 3.976) Pub Date : 2023-08-28 Yanlin Shi
I propose a novel measure of information share, termed tail information share (TIS), which focuses on modeling the tail dependence of price innovations using copulas. I discuss its detailed technical properties, including unique identifiability, estimation procedures, and statistical properties. The proposed TIS improves over two commonly used measures by providing meaningful economic rationale and
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A Truncated Mixture Transition Model for Interval-Valued Time Series Journal of Financial Econometrics (IF 3.976) Pub Date : 2023-08-14 Yun Luo, Gloria González-Rivera
We propose a model for interval-valued time series that specifies the conditional joint distribution of the upper and lower bounds as a mixture of truncated bivariate normal distributions. It preserves the interval natural order and provides great flexibility on capturing potential conditional heteroscedasticity and non-Gaussian features. The standard expectation maximization (EM) algorithm applied
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Estimation of an Order Book Dependent Hawkes Process for Large Datasets Journal of Financial Econometrics (IF 3.976) Pub Date : 2023-08-12 Luca Mucciante, Alessio Sancetta
A point process for event arrivals in high-frequency trading is presented. The intensity is the product of a Hawkes process and high-dimensional functions of covariates derived from the order book. Conditions for stationarity of the process are stated. An algorithm is presented to estimate the model even in the presence of billions of data points, possibly mapping covariates into a high-dimensional
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Disagreement in Market Index Options Journal of Financial Econometrics (IF 3.976) Pub Date : 2023-06-30 Guilherme Salome, George Tauchen, Jia Li
We generate new evidence on disagreement among traders in the S&P 500 options market from high-frequency intraday price and volume data. Inference on disagreement is based on a model where investors observe public information but agree to disagree on its interpretation; disagreement among investors is captured by the volume–volatility elasticity. For options, there are two natural variables related
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A New Test on Asset Return Predictability with Structural Breaks Journal of Financial Econometrics (IF 3.976) Pub Date : 2023-06-09 Zongwu Cai, Seong Yeon Chang
This article considers predictive regressions in which a structural break is allowed on an unknown date. We establish novel testing procedures for asset return predictability using empirical likelihood (EL) methods based on weighted score equations. The theoretical results are useful in practice because our unified framework does not require distinguishing whether the predictor variables are stationary
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Test for Trading Costs Effect in a Portfolio Selection Problem with Recursive Utility Journal of Financial Econometrics (IF 3.976) Pub Date : 2023-05-23 Marine Carrasco, N’Golo Koné
This article addresses a portfolio selection problem with trading costs on stock market. More precisely, we develop a simple generalized method of moments (GMM)-based test procedure to test the significance of trading costs effect in the economy with a flexible form of transaction costs. We also propose a two-step procedure to test overidentifying restrictions in our GMM estimation. In an empirical
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Real-Time Identification and High-Frequency Analysis of Deposits Outflows Journal of Financial Econometrics (IF 3.976) Pub Date : 2023-05-18 Edoardo Rainone
We propose a method based on control charts to identify in real-time sudden deposits outflows through the payment system. The performance of the methodology is assessed with both Monte Carlo simulations and real transaction-level TARGET2 data for a large sample of Italian banks. We identify a set of idiosyncratic bank stress episodes. Using high-frequency payment system data, we provide new evidences
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Forecasting Value-at-Risk Using Deep Neural Network Quantile Regression Journal of Financial Econometrics (IF 3.976) Pub Date : 2023-05-15 Ilias Chronopoulos, Aristeidis Raftapostolos, George Kapetanios
In this article, we use a deep quantile estimator, based on neural networks and their universal approximation property to examine a non-linear association between the conditional quantiles of a dependent variable and predictors. This methodology is versatile and allows both the use of different penalty functions, as well as high dimensional covariates. We present a Monte Carlo exercise where we examine
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Forecasting Large Realized Covariance Matrices: The Benefits of Factor Models and Shrinkage Journal of Financial Econometrics (IF 3.976) Pub Date : 2023-05-11 Rafael P Alves, Diego S de Brito, Marcelo C Medeiros, Ruy M Ribeiro
We propose a model to forecast large realized covariance matrices of returns, applying it to the constituents of the S&P 500 daily. To address the curse of dimensionality, we decompose the return covariance matrix using standard firm-level factors (e.g., size, value, and profitability) and use sectoral restrictions in the residual covariance matrix. This restricted model is then estimated using vector
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Beyond Co-integration: New Tools for Inference on Co-movements Journal of Financial Econometrics (IF 3.976) Pub Date : 2023-05-11 Karim M Abadir, Gabriel Talmain
Macroeconomic and aggregate financial series were shown empirically to share an unconventional form of cyclical and persistent dynamics, whose functional form was obtained from the solution of general-equilibrium models with heterogeneous firms. The econometric modeling of equations that link such series requires a new methodology, as existing parametric techniques can cause paradoxical regression
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Optimal Portfolio Using Factor Graphical Lasso Journal of Financial Econometrics (IF 3.976) Pub Date : 2023-04-12 Tae-Hwy Lee, Ekaterina Seregina
Graphical models are a powerful tool to estimate a high-dimensional inverse covariance (precision) matrix, which has been applied for a portfolio allocation problem. The assumption made by these models is a sparsity of the precision matrix. However, when stock returns are driven by common factors, such assumption does not hold. We address this limitation and develop a framework, Factor Graphical Lasso
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When Safe-Haven Asset Is Less than a Safe-Haven Play Journal of Financial Econometrics (IF 3.976) Pub Date : 2023-04-03 Leon Li, Carl R Chen
We propose a four-state regime-switching model that pairs low-volatility and high-volatility (HV) states to test eight stock–safe-haven asset portfolios’ risk properties. We find the correlations between gold, U.S. T-bond, and the Swiss franc and stock markets are negative or zero in all states, including the HV–HV state, while the correlations between Bitcoin (BTC) and stock markets are positive in
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Endogenous Volatility in the Foreign Exchange Market Journal of Financial Econometrics (IF 3.976) Pub Date : 2023-03-27 Leonardo Bargigli, Giulio Cifarelli
We study two sources of heteroscedasticity in high-frequency financial data and estimate their contribution to overall volatility by means of a Markov switching (MS) structural VAR model. We achieve identification for all coefficients by assuming that the structural errors follow a GARCH-DCC process. Using transaction data of the EUR/USD interdealer market in 2016, we first detect three regimesof volatility
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Modeling Price and Variance Jump Clustering Using the Marked Hawkes Process Journal of Financial Econometrics (IF 3.976) Pub Date : 2023-03-21 Jian Chen, Michael P Clements, Andrew Urquhart
We examine the clustering behavior of price and variance jumps using high-frequency data, modeled as a marked Hawkes process (MHP) embedded in a bivariate jump-diffusion model with intraday periodic effects. We find that the jumps of both individual stocks and a broad index exhibit self-exciting behavior. The three dimensions of the model, namely positive price jumps, negative price jumps, and variance
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Testing for Alpha in Linear Factor Pricing Models with a Large Number of Securities Journal of Financial Econometrics (IF 3.976) Pub Date : 2023-02-10 M Hashem Pesaran, Takashi Yamagata
This article considers tests of alpha in linear factor pricing models when the number of securities, N, is much larger than the time dimension, T, of the individual return series. We focus on class of tests that are based on Student’s t-tests of individual securities which have a number of advantages over the existing standardized Wald type tests, and propose a test procedure that allows for non-Gaussianity
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Dynamic Covariance Matrix Estimation and Portfolio Analysis with High-Frequency Data Journal of Financial Econometrics (IF 3.976) Pub Date : 2023-02-10 Binyan Jiang, Cheng Liu, Cheng Yong Tang
The covariance matrix associated with multiple financial returns plays foundational roles in many empirical applications, for example, quantifying risks and managing investment portfolios. Such covariance matrices are well known to be dynamic, that is, their structures change with the underlying market conditions. To incorporate such dynamics in a setting with high-frequency noisy data contaminated
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Score-Driven Modeling with Jumps: An Application to S&P500 Returns and Options Journal of Financial Econometrics (IF 3.976) Pub Date : 2023-02-08 Luca Vincenzo Ballestra, Enzo D’Innocenzo, Andrea Guizzardi
We introduce a novel score-driven model with two sources of shock, allowing for both time-varying volatility and jumps. A theoretical investigation is performed which yields sufficient conditions to ensure stationarity and ergodicity. We extend the model to consider a time-varying jump intensity. Both an in-sample and an out-of-sample analysis based on the S&P500 time series show that the proposed
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Geographic Dependence and Diversification in House Price Returns: The Role of Leverage Journal of Financial Econometrics (IF 3.976) Pub Date : 2022-12-28 Andréas Heinen, Mi Lim Kim, Malika Hamadi
We analyze the time variation in the average dependence within a set of regional monthly house price index returns in a regime-switching multivariate copula model with a high and a low dependence regime. Using equidependent Gaussian copulas, we show that the dependence of house price returns varies across time with changes in credit market conditions, which reduces the gains from the geographic diversification
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Dynamic Nonparametric Clustering of Multivariate Panel Data Journal of Financial Econometrics (IF 3.976) Pub Date : 2022-12-15 Igor Custodio João, Julia Schaumburg, André Lucas, Bernd Schwaab
We introduce a new dynamic clustering method for multivariate panel data characterized by time-variation in cluster locations and shapes, cluster compositions, and possibly the number of clusters. To avoid overly frequent cluster switching (flickering), we extend standard cross-sectional clustering techniques with a penalty that shrinks observations toward the current center of their previous cluster
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A Consistent and Robust Test for Autocorrelated Jump Occurrences Journal of Financial Econometrics (IF 3.976) Pub Date : 2022-08-29 Simon Kwok
We develop a nonparametric test for the temporal dependence of jump occurrences in the population. The test is consistent against all pairwise serial dependence, and is robust to the jump activity level and the choice of sampling scheme. We establish asymptotic normality and local power property for a rich set of local alternatives, including both self-exciting and/or self-inhibitory jumps. Simulation
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Semi-Strong Factors in Asset Returns Journal of Financial Econometrics (IF 3.976) Pub Date : 2022-08-18 Gregory Connor, Robert A Korajczyk
We refine the approximate factor model of asset returns by distinguishing between strong factors, whose sum of squared factor betas grow at the same rate as the number of assets, and semi-strong factors, whose sum of squared factor betas grow to infinity, but at a slower rate. We develop a test statistic for strength of factors based on the cross-sectional mean-square of regression-estimated betas
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A New Test for Multiple Predictive Regression Journal of Financial Econometrics (IF 3.976) Pub Date : 2022-08-12 Ke-Li Xu, Junjie Guo
We consider inference for predictive regressions with multiple predictors. Extant tests for predictability (especially for joint predictability) may perform unsatisfactorily and tend to discover spurious predictability as the number of predictors increases. We propose a battery of new instrumental variables-based tests which involve enforcement or partial enforcement of the null hypothesis in variance
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Market Maker Inventory, Bid–Ask Spreads, and the Computation of Option Implied Risk Measures Journal of Financial Econometrics (IF 3.976) Pub Date : 2022-08-10 Bjørn Eraker, Daniela Osterrieder
We present empirical evidence showing that option-implied risk measures (OIRMs) are substantially impacted by bid–ask spreads in underlying options. Asking prices are more sensitive to shocks than bids, leading to highly skewed distributions of spreads. We derive and estimate a model of market making that empirically matches these asymmetric responses as well as the time-series properties of bid–ask
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An Enhanced Factor Model for Portfolio Selection in High Dimensions Journal of Financial Econometrics (IF 3.976) Pub Date : 2022-08-08 Fangquan Shi, Lianjie Shu, Xinhua Gu
This article extends Fama and French (FF) models of observed factors by introducing latent factors (LFs) to further extract information from FF residual returns. A diagonally dominant (DD) rather than a diagonal or sparse matrix structure is adopted in this study to estimate remaining covariance between disturbance terms. Such an enhanced factor (EF) model provides a more comprehensive analysis for
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Ask BERT: How Regulatory Disclosure of Transition and Physical Climate Risks Affects the CDS Term Structure Journal of Financial Econometrics (IF 3.976) Pub Date : 2022-07-27 Julian F Kölbel, Markus Leippold, Jordy Rillaerts, Qian Wang
We use BERT, an AI-based algorithm for language understanding, to quantify regulatory climate risk disclosures and analyze their impact on the term structure in the credit default swap (CDS) market. Risk disclosures can either increase or decrease CDS spreads, depending on whether the disclosure reveals new risks or reduces uncertainty. Training BERT to differentiate between transition and physical
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Estimation and Inference of Quantile Impulse Response Functions by Local Projections: With Applications to VaR Dynamics Journal of Financial Econometrics (IF 3.976) Pub Date : 2022-07-23 Heejoon Han, Whayoung Jung, Ji Hyung Lee
This article investigates the estimation and inference of quantile impulse response functions. We propose a new estimation method using the idea of local projections by Jordà (2005). We establish consistency and asymptotic normality of the estimator, thereby enabling asymptotic inference. We also consider the confidence interval construction based on the stationary bootstrap and prove its consistency
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How Does Post-Earnings Announcement Sentiment Affect Firms’ Dynamics? New Evidence from Causal Machine Learning Journal of Financial Econometrics (IF 3.976) Pub Date : 2022-07-12 Francesco Audrino, Jonathan Chassot, Chen Huang, Michael Knaus, Michael Lechner, Juan-Pablo Ortega
We revisit the role played by sentiment extracted from news articles related to earnings announcements as a driver of firms’ return, volatility, and trade volume dynamics. To this end, we apply causal machine learning on the earnings announcements of a wide cross-section of U.S. companies. This approach allows us to investigate firms’ price and volume reactions to different types of post-earnings announcement
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Estimating a Non-parametric Memory Kernel for Mutually Exciting Point Processes Journal of Financial Econometrics (IF 3.976) Pub Date : 2022-07-09 A E Clements, A S Hurn, K A Lindsay, V V Volkov
Self- and cross-excitation in point processes are commonly captured in the financial econometrics literature using a multivariate exponential memory kernel. In this article, the exponential assumption is relaxed and the resultant non-parametric memory kernel is estimated by a method based on second-order cumulants. The estimator is shown to be consistent and asymptotically normally distributed and
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Estimating Unobserved Soft Adjustment in Credit Rating Models: Before and after the Dodd–Frank Act Journal of Financial Econometrics (IF 3.976) Pub Date : 2022-07-09 Zhutong Gu, Yixiao Jiang, Shuyang Yang
Credit Rating Agencies (CRAs) adjust preliminary bond ratings with knowledge beyond publicly available information. These unobserved “soft adjustments” may reflect material nonpublic information and rating biases due to conflicts of interest, making certain bond characteristics endogenous. We model and quantify soft adjustments as bond-specific thresholds in a semiparametric ordered-response model
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High-Dimensional Granger Causality Tests with an Application to VIX and News Journal of Financial Econometrics (IF 3.976) Pub Date : 2022-07-04 Andrii Babii, Eric Ghysels, Jonas Striaukas
We study Granger causality testing for high-dimensional time series using regularized regressions. To perform proper inference, we rely on heteroskedasticity and autocorrelation consistent (HAC) estimation of the asymptotic variance and develop the inferential theory in the high-dimensional setting. To recognize the time-series data structures, we focus on the sparse-group LASSO (sg-LASSO) estimator
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Identifying Risk Factors and Their Premia: A Study on Electricity Prices Journal of Financial Econometrics (IF 3.976) Pub Date : 2022-06-24 Wei Wei, Asger Lunde
Risk premia are difficult to identify in nonstorable commodities such as electricity. In this article, we propose a modified Fama–French regression framework and show that when the spot prices do not follow a martingale—a common assumption in the electricity market—model specifications play an important role in detecting time-varying risk premia in the futures market. With this insight, we propose
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Anatomy of a Sovereign Debt Crisis: Machine Learning, Real-Time Macro Fundamentals, and CDS Spreads Journal of Financial Econometrics (IF 3.976) Pub Date : 2022-06-24 Pierluigi Balduzzi, Roberto Savona, Lucia Alessi
We employ a Least Absolute Shrinkage and Selection Operator (LASSO)-based extension of the Fama–MacBeth procedure to characterize the time-varying dependence of sovereign Credit Default Swap (CDS) spreads on macro indicators during the samples 2009–2013 and 2013–2020. While CDS spreads are mainly reflective of fundamentals, this relationship varies substantially over time, leading to price variation
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A Machine Learning Approach to Volatility Forecasting Journal of Financial Econometrics (IF 3.976) Pub Date : 2022-06-21 Kim Christensen, Mathias Siggaard, Bezirgen Veliyev
We inspect how accurate machine learning (ML) is at forecasting realized variance of the Dow Jones Industrial Average index constituents. We compare several ML algorithms, including regularization, regression trees, and neural networks, to multiple heterogeneous autoregressive (HAR) models. ML is implemented with minimal hyperparameter tuning. In spite of this, ML is competitive and beats the HAR lineage
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News Arrival, Time-Varying Jump Intensity, and Realized Volatility: Conditional Testing Approach Journal of Financial Econometrics (IF 3.976) Pub Date : 2022-06-08 Deniz Erdemlioglu, Xiye Yang
This paper introduces new econometric tests to identify stochastic intensity jumps in high-frequency data. Our approach exploits the behavior of a time-varying stochastic intensity and allows us to assess how intensely stock market reacts to news. We describe the asymptotic properties of our test statistics, derive the associated central limit theorem and show in simulations that the tests have good
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Time Variation in Cash Flows and Discount Rates Journal of Financial Econometrics (IF 3.976) Pub Date : 2022-06-07 Tolga Cenesizoglu, Denada Ibrushi
We analyze the decomposition of the conditional, rather than the unconditional, variance of market returns based on an extension of the standard Campbell–Shiller approach. The relative importance of cash flow and discount rate news in determining the conditional variance of market returns exhibits significant variation over time and relates to economic conditions. The components of the conditional
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Testing Hypotheses on the Innovations Distribution in Semi-Parametric Conditional Volatility Models Journal of Financial Econometrics (IF 3.976) Pub Date : 2022-04-29 Christian Francq,Jean-Michel Zakoïan
Abstract Testing symmetry or quantile assumptions on the innovations distribution can be of invaluable help to improve or simplify the statistical procedures designed for GARCH-type models. In particular, evaluation of the conditional value-at-risk (VaR) or construction of confidence intervals for predictions requires estimating quantiles of the innovations distribution. We propose tests of different
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Identification Robust Testing of Risk Premia in Finite Samples Journal of Financial Econometrics (IF 3.976) Pub Date : 2022-04-28 Frank Kleibergen,Lingwei Kong,Zhaoguo Zhan
Abstract The reliability of tests on the risk premia in linear factor models is threatened by limited sample sizes and weak identification of risk premia frequently encountered in applied work. We, therefore, propose novel tests on the risk premia that are robust to both limited sample sizes and the identification strength of the risk premia as reflected by the quality of the risk factors. These tests
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Arbitrage Pricing Theory for Idiosyncratic Variance Factors Journal of Financial Econometrics (IF 3.976) Pub Date : 2022-04-26 Eric Renault,Thijs Van Der Heijden,Bas J M Werker
Abstract We develop an arbitrage pricing theory framework extension to study the pricing of squared returns/volatilities. We analyze the interplay between factors at the return level and those in idiosyncratic variances. We confirm the presence of a common idiosyncratic variance factor, but do not find evidence that this represents a missing risk factor at the (linear) return level. Thereby, we consistently
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Time-Transformed Test for Bubbles under Non-stationary Volatility Journal of Financial Econometrics (IF 3.976) Pub Date : 2022-04-23 Eiji Kurozumi,Anton Skrobotov,Alexey Tsarev
Abstract This paper is devoted to testing for bubbles under time-varying non-stationary volatility. Because the limiting distribution of the seminal Phillips, Wu, and Yu (2011) test depends on the variance function and usually requires a bootstrap implementation under heteroskedasticity, we construct the test based on a deformation of the time domain. The proposed test is asymptotically pivotal under
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Discussion of Identification Robust Testing of Risk Premia in Finite Samples Journal of Financial Econometrics (IF 3.976) Pub Date : 2022-04-15 Francisco Peñaranda
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Empirical Asset Pricing with Functional Factors Journal of Financial Econometrics (IF 3.976) Pub Date : 2022-04-06 Philip Nadler,Alessio Sancetta
Abstract We propose a methodology to use functional factors in empirical asset pricing models. We establish conditions under which it is possible to recover linear beta pricing. The proposed estimation approach allows us to use high-dimensional functional curves, such as the term structure of interest rates or the implied volatility smile, as factors. This framework enables the estimation of functional
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Maximum-Likelihood Estimation Using the Zig-Zag Algorithm Journal of Financial Econometrics (IF 3.976) Pub Date : 2022-04-01 Nikolaus Hautsch,Ostap Okhrin,Alexander Ristig
Abstract We analyze the properties of the Maximum Likelihood (ML) estimator when the underlying log-likelihood function is numerically maximized with the so-called zig-zag algorithm. By splitting the parameter vector into sub-vectors, the algorithm maximizes the log-likelihood function alternatingly with respect to one sub-vector while keeping the others constant. For situations when the algorithm
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Modeling Realized Covariance Matrices: A Class of Hadamard Exponential Models Journal of Financial Econometrics (IF 3.976) Pub Date : 2022-03-22 Luc Bauwens,Edoardo Otranto
Abstract Time series of realized covariance matrices can be modeled in the conditional autoregressive Wishart model family via dynamic correlations or via dynamic covariances. Extended parameterizations of these models are proposed, which imply a specific and time-varying impact parameter of the lagged realized covariance (or correlation) on the next conditional covariance (or correlation) of each
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Modeling and Forecasting Volatilities of Financial Assets with an Asymmetric Zero-Drift GARCH Model Journal of Financial Econometrics (IF 3.976) Pub Date : 2022-02-17 Yanlin Shi
In this study, we extend the zero-drift generalized autoregressive conditional heteroskedasticity (GARCH) model to incorporate the well-known asymmetric effects of shocks on financial volatility and propose an asymmetric zero-drift GARCH (AZD-GARCH) model. Relevant asymptotics of the new model, including those for the quasi-maximum-likelihood estimator and the powers of the stability test and the model
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A Joint Model for the Term Structure of Interest Rates and Realized Volatility Journal of Financial Econometrics (IF 3.976) Pub Date : 2022-02-03 Anne Lundgaard Hansen
This paper presents a term structure model for no-arbitrage bond yields and realized bond market volatility. Based on well-known results, realized yield curve covariation is linked to generalized autoregressive conditional heteroskedasticity (GARCH)-type conditional covariation. The model is tractable and its latent state variables can be filtered using an exact algorithm. In an empirical study of
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The Determinants of Volatility Timing Performance Journal of Financial Econometrics (IF 3.976) Pub Date : 2022-01-24 Nick Taylor
The exact conditions under which volatility timing strategies yield value are documented. These conditions include: the ability to correctly forecast next period stochastic variance, and violation of a strict version of Merton’s intertemporal capital asset pricing model (ICAPM). While the empirical evidence supports the first of these conditions, the latter remains open to debate. Our empirical results
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Arbitrage Pricing with Heterogeneous Spatial Effects and Heteroscedastic Disturbances Journal of Financial Econometrics (IF 3.976) Pub Date : 2022-01-01 Jianhua Hu, Hao Ding, Xiaoqian Liu
We develop a heterogeneous spatial arbit and regression coefficients, and heteroscedastic variances, and further establish identification of parameters and asymptotic normality of the conditional QML estimators under some mild conditions. We apply the proposed model to study a real data set of 11 eurozone stock index returns and extend the Fama–French five-factor model to regional stock indices, in
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Modeling Bid and Ask Price Dynamics with an Extended Hawkes Process and Its Empirical Applications for High-Frequency Stock Market Data Journal of Financial Econometrics (IF 3.976) Pub Date : 2021-12-10 Kyungsub Lee, Byoung Ki Seo
This study proposes a versatile model for the dynamics of the best bid and ask prices using an extended Hawkes process. The model incorporates the zero intensities of the spread-narrowing processes at the minimum bid–ask spread, spread-dependent intensities, possible negative excitement, and nonnegative intensities. We apply the model to high-frequency best bid and ask price data from U.S. stock markets
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The Role of Jumps in Realized Volatility Modeling and Forecasting Journal of Financial Econometrics (IF 3.976) Pub Date : 2021-12-10 Massimiliano Caporin
Building on an extensive empirical analysis, I investigate the relevance of jumps and signed variations in predicting realized volatility. I show that properly accounting for intra-day volatility patterns and staleness sensibly reduces the identified jumps, in particular for low and moderate liquidity assets. Modeling realized variance using jumps and intra-day return sign improves the in-sample fit
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Realized Semi(co)variation: Signs That All Volatilities are Not Created Equal Journal of Financial Econometrics (IF 3.976) Pub Date : 2021-11-20 Tim Bollerslev
Abstract I provide a selective review of recent developments in financial econometrics related to measuring, modeling, forecasting, and pricing “good” and “bad” volatilities based on realized variation type measures constructed from high-frequency intraday data. An especially appealing feature of the different measures concerns the ease with which they may be calculated empirically, merely involving
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Increasing the information content of realized volatility forecasts Journal of Financial Econometrics (IF 3.976) Pub Date : 2021-11-12 Razvan Pascalau, Ryan Poirier
Assuming N available calendar days, each with M intraday returns, the realized volatility literature suggests creating N end-of-day estimators by summing the M squared returns from each particular date. Instead of this “Calendar” [realized variance (RV)] approach, we propose a “Rolling” [rolling RV (RRV)] approach that simply sums trailing M returns at each timestamp, regardless if all M returns belong
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Introduction to the 2018 Hal White Memorial Lecture Journal of Financial Econometrics (IF 3.976) Pub Date : 2021-08-06 Timmerman A, Trojani F.
Every year the Society for Financial Econometrics celebrates the fundamental contributions to econometric theory and practice made by our late colleague and friend Hal White. Central to these celebrations is a lecture presented by an established scholar during a plenary session of the Society’s Annual Conference. This lecture is subsequently published in the journal.
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Testing for Regime Changes in Portfolios with a Large Number of Assets: A Robust Approach to Factor Heteroskedasticity Journal of Financial Econometrics (IF 3.976) Pub Date : 2021-10-01 Daniele Massacci
We develop a new test for threshold-type regime changes in the risk exposures in portfolios with a large number of financial assets whose returns exhibit an approximate factor structure. Unlike existing procedures to detect discrete shifts in factor models, our test is robust to regime-specific second moment of the common factors. We rely on an auxiliary threshold regression: we take a weighted cross-sectional
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Comment on: Identification Robust Testing of Risk Premia in Finite Samples Journal of Financial Econometrics (IF 3.976) Pub Date : 2021-09-30 Lynda Khalaf
The paper by Kleibergen, Kong and Zhan is an excellent contribution on finite sample methods in asset pricing, and provides an insightful application to consumption-based asset pricing models. In particular, informative simulations and a serious empirical analysis confirm that shortcomings of available and popular methods are not small enough to be ignored.
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Granger Causality Testing in High-Dimensional VARs: A Post-Double-Selection Procedure Journal of Financial Econometrics (IF 3.976) Pub Date : 2021-09-10 Alain Hecq, Luca Margaritella, Stephan Smeekes
We develop an LM test for Granger causality in high-dimensional (HD) vector autoregressive (VAR) models based on penalized least squares estimations. To obtain a test retaining the appropriate size after the variable selection done by the lasso, we propose a post-double-selection procedure to partial out effects of nuisance variables and establish its uniform asymptotic validity. We conduct an extensive
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Multivariate Fractional Components Analysis Journal of Financial Econometrics (IF 3.976) Pub Date : 2021-09-10 Tobias Hartl, Roland Jucknewitz
We propose a setup for fractionally cointegrated time series which is formulated in terms of latent integrated and short-memory components. It accommodates nonstationary processes with different fractional orders and cointegration of different strengths and is applicable in high-dimensional settings. In an application to realized covariance matrices, we find that orthogonal short- and long-memory components