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结合统计区间与市场价格：最坏情形状态价格分布AI 解读

The paper shows how to combine (historical) statistical data and (current) market prices to form conservative trading strategies for options. This gives rise to a “worst case” state price distribution, which provides sharp price bounds for all convex European options. The paper provides for existence and computational algorithms under conditions which can be understood as “no arbitrage”. The worst case distribution converges to a regular state price distribution if the…

多个条件变量下大型动态协方差矩阵的半参数估计新方法AI 解读

This paper studies the estimation of large dynamic covariance matrices with multiple conditioning variables. We introduce an easy-to-implement semiparametric method to estimate each entry of the covariance matrix via model averaging marginal regression, and then apply a shrinkage technique to obtain the dynamic covariance matrix estimation. Under some regularity conditions, we derive the asymptotic properties for the proposed estimators including the uniform consistency with…

网络分位数自回归AI 解读

The complex tail dependency structure in a dynamic network with a large number of nodes is an important object to study. We propose a network quantile autoregression model (NQAR), which characterizes the dynamic quantile behavior. Our NQAR model consists of a system of equations, of which we relate a response to its connected nodes and node specific characteristics in a quantile autoregression process. We show the estimation of the NQAR model and the asymptotic properties…

交易成本与模型不确定性下的大规模投资组合配置AI 解读

We theoretically and empirically study portfolio optimization under transaction costs and establish a link between turnover penalization and covariance shrinkage with the penalization governed by transaction costs. We show how the ex ante incorporation of transaction costs shifts optimal portfolios towards regularized versions of efficient allocations. The regulatory effect of transaction costs is studied in an econometric setting incorporating parameter uncertainty and…

使用高频数据检验因子数量的秩检验AI 解读

In the literature, consistency of the estimates of the number of factors for large-dimensional factor models had been extensively studied recently. But the second-order property of the estimator has long been unsolved due to lack of limiting distribution of the estimators. In this paper, we propose a rank test of the number of factors using large panel high-frequency data contaminated with microstructure noise. The rank test is realized by forming a fixed number of…

预期短缺与风险价值的动态半参数模型AI 解读

Expected Shortfall (ES) is the average return on a risky asset conditional on the return being below some quantile of its distribution, namely its Value-at-Risk (VaR). The Basel III Accord, which will be implemented in the years leading up to 2019, places new attention on ES, but unlike VaR, there is little existing work on modeling ES. We use recent results from statistical decision theory to overcome the problem of “elicitability” for ES by jointly modeling ES and VaR, and…

以个股检验资产定价模型：处理风险溢价估计中的变量测量误差偏差AI 解读

To attenuate an inherent errors-in-variables bias, portfolios are widely employed to test asset pricing models; but portfolios might mask relevant risk- or return-related features of individual stocks. We propose an instrumental variables approach that allows the use of individual stocks as test assets, yet delivers consistent estimates of ex post risk premiums. This estimator also yields well-specified tests in small samples. The market risk premium under the capital asset…

资产定价的需求系统方法AI 解读

We develop an asset pricing model with flexible heterogeneity in asset demand across investors, designed to match institutional and household holdings. A portfolio choice model implies characteristics-based demand when returns have a factor structure and expected returns and factor loadings depend on the assets’ own characteristics. We propose an instrumental variables estimator for the characteristics-based demand system to address the endogeneity of demand and asset…

股票与债券风险—收益权衡中的非线性与避险转移AI 解读

ABSTRACT We document a highly significant, strongly nonlinear dependence of stock and bond returns on past equity market volatility as measured by the VIX. We propose a new estimator for the shape of the nonlinear forecasting relationship that exploits variation in the cross‐section of returns. The nonlinearities are mirror images for stocks and bonds, revealing flight‐to‐safety: expected returns increase for stocks when volatility increases from moderate to high levels…

尾部的故事：高维尾部相依性AI 解读

Summary We propose a simple and flexible framework that allows for a comprehensive analysis of tail interdependence in high dimensions. We use co‐exceedances to capture the structure of the dependence in the tails and, relying on the concept of multi‐information, define the coefficient of tail interdependence. Within this framework, we develop statistical tests of (i) independence in the tails, (ii) goodness‐of‐fit of the tail interdependence structure of a hypothesized…

美国各州住房价格的共同变动与非对称尾部依赖：非参数方法AI 解读

Summary We reexamine the methods used in estimating comovements among US regional home prices and find that there are insufficient moments to ensure a normal limit necessary for employing the quasi‐maximum likelihood estimator. Hence we propose applying the self‐weighted quasi‐maximum exponential likelihood estimator and a bootstrap method to test and account for the asymmetry of comovements as well as different magnitudes across state pairs. Our results reveal interstate…

泡沫与危机：对Anundsen等人研究结果的复现AI 解读

Summary This paper both narrowly and widely replicates the results of Anundsen et al. ( Journal of Applied Econometrics , 2016, 31 (7), 1291–1311). I am able to reproduce the same results as theirs. Furthermore, I find that allowing for time‐varying parameters of early warning system models can considerably improve the in‐sample model fit and out‐of‐sample forecasting performance based on an expanding window forecasting exercise.

时变因子载荷下的资产定价检验AI 解读

Summary This paper proposes an empirical asset pricing test based on the homogeneity of the factor risk premia across risky assets. Factor loadings are considered to be dynamic and estimated from data at higher frequencies. The factor risk premia are obtained as estimates from time series regressions applied to each risky asset. We propose Swamy‐type tests robust to the presence of generated regressors and dependence between the pricing errors to assess the homogeneity of…

大规模已实现协方差矩阵的贝叶斯参数与半参数因子模型AI 解读

Summary This paper introduces a new factor structure suitable for modeling large realized covariance matrices with full likelihood‐based estimation. Parametric and nonparametric versions are introduced. Because of the computational advantages of our approach, we can model the factor nonparametrically as a Dirichlet process mixture or as an infinite hidden Markov mixture, which leads to an infinite mixture of inverse‐Wishart distributions. Applications to 10 assets and 60…

Extremiles：非对称最小二乘的新视角AI 解读

Quantiles and expectiles of a distribution are found to be useful descriptors of its tail in the same way as the median and mean are related to its central behavior. This article considers a valuable alternative class to expectiles, called extremiles, which parallels the class of quantiles and includes the family of expected minima and expected maxima. The new class is motivated via several angles, which reveals its specific merits and strengths. Extremiles suggest better…

检验预测回归无效性的自助法平稳性检验AI 解读

In order for predictive regression tests to deliver asymptotically valid inference, account has to be taken of the degree of persistence of the predictors under test. There is also a maintained assumption that any predictability in the variable of interest is purely attributable to the predictors under test. Violation of this assumption by the omission of relevant persistent predictors renders the predictive regression invalid, and potentially also spurious, as both the…

资产价格瞬时协变的估计：统计理论与经验证据AI 解读

We propose a new estimator for the spot covariance matrix of a multi-dimensional continuous semimartingale log asset price process, which is subject to noise and nonsynchronous observations. The estimator is constructed based on a local average of block-wise parametric spectral covariance estimates. The latter originate from a local method of moments (LMM), which recently has been introduced by Bibinger et al.. We prove consistency and a point-wise stable central limit…

高频数据中市场微观结构噪声的Hausman检验AI 解读

We develop tests that help assess whether a high frequency data sample can be treated as reasonably free of market microstructure noise at a given sampling frequency for the purpose of implementing high frequency volatility and other estimators. The tests are based on the Hausman principle of comparing two estimators, one that is efficient but not robust to the deviation being tested, and one that is robust but not as efficient. We investigate the asymptotic properties of…

Wiener 泛函最大值的高斯近似及高频数据应用AI 解读

This paper establishes an upper bound for the Kolmogorov distance between the maximum of a high-dimensional vector of smooth Wiener functionals and the maximum of a Gaussian random vector. As a special case, we show that the maximum of multiple Wiener–Itô integrals with common orders is well approximated by its Gaussian analog in terms of the Kolmogorov distance if their covariance matrices are close to each other and the maximum of the fourth cumulants of the multiple…

多元正态性的刻画与拟合优度检验：含 GARCH 应用AI 解读

We provide novel characterizations of multivariate normality that incorporate both the characteristic function and the moment generating function, and we employ these results to construct a class of affine invariant, consistent and easy-to-use goodness-of-fit tests for normality. The test statistics are suitably weighted L 2 -statistics, and we provide their asymptotic behavior both for i.i.d. observations as well as in the context of testing that the innovation distribution…

动态模型与数据驱动投资组合策略的预测密度组合AI 解读

A dynamic asset-allocation model is specified in probabilistic terms as a combination of return distributions resulting from multiple pairs of dynamic models and portfolio strategies based on momentum patterns in US industry returns. The nonlinear state space representation of the model allows efficient and robust simulation-based Bayesian inference using a novel non-linear filter. Combination weights can be cross-correlated and correlated over time using feedback…

具有非参数先验的多变点面板模型：贝叶斯推断与预测AI 解读

Change point models using hierarchical priors have been very successful estimating the parameter values of short-lived regimes. However, hierarchical priors have been parametric which leads to shrinkage in the estimates of extraordinary regime parameters. We overcome this by modeling the hierarchical priors nonparametrically. We also extend the change point to a panel of change point processes where the prior shares in the probabilities of changing regimes. When applied to…

用马尔可夫转换图结构SUR模型刻画系统性风险AI 解读

We propose a Markov Switching Graphical Seemingly Unrelated Regression (MS-GSUR) model to investigate time-varying systemic risk based on a range of multi-factor asset pricing models. Methodologically, we develop a Markov Chain Monte Carlo (MCMC) scheme in which latent states are identified on the basis of a novel weighted eigenvector centrality measure. An empirical application to the constituents of the S&P100 index shows that cross-firm connectivity significantly…

高维时变协方差的稀疏贝叶斯估计AI 解读

We address the curse of dimensionality in dynamic covariance estimation by modeling the underlying co-volatility dynamics of a time series vector through latent time-varying stochastic factors. The use of a global–local shrinkage prior for the elements of the factor loadings matrix pulls loadings on superfluous factors towards zero. To demonstrate the merits of the proposed framework, the model is applied to simulated data as well as to daily log-returns of 300 S&P 500…