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公司层面的资产定价异象AI 解读

We introduce a hierarchical Bayes approach to model conditional firm-level alphas as a function of firm characteristics. Our empirical framework is motivated by growing concerns in the literature regarding the reliability of inferences from portfolio-based methods. In our initial tests, we confirm the existence of several CAPM anomalies at the firm level. Prominent multifactor models deliver only a modest improvement, however, as they often resolve only those anomalies which…

基于期权面板的参数推断与动态状态恢复AI 解读

We develop a new parametric estimation procedure for option panels observed with error. We exploit asymptotic approximations assuming an ever increasing set of option prices in the moneyness (cross-sectional) dimension, but with a fixed time span. We develop consistent estimators for the parameters and the dynamic realization of the state vector governing the option price dynamics. The estimators converge stably to a mixed-Gaussian law and we develop feasible estimators for…

通过分位数匹配实现分布匹配估计AI 解读

Motivated by the problem of selecting representative portfolios for backtesting counterparty credit risks, we propose a matching quantiles estimation (MQE) method for matching a target distribution by that of a linear combination of a set of random variables. An iterative procedure based on the ordinary least-squares estimation (OLS) is proposed to compute MQE. MQE can be easily modified by adding a LASSO penalty term if a sparse representation is desired, or by restricting…

密度调温的边际化序贯蒙特卡洛采样器AI 解读

We propose a density-tempered marginalized sequential Monte Carlo (SMC) sampler, a new class of samplers for full Bayesian inference of general state-space models. The dynamic states are approximately marginalized out using a particle filter, and the parameters are sampled via a sequential Monte Carlo sampler over a density-tempered bridge between the prior and the posterior. Our approach delivers exact draws from the joint posterior of the parameters and the latent states…

高斯动态期限结构模型的新线性估计量AI 解读

This article proposes a novel regression-based approach to the estimation of Gaussian dynamic term structure models. This new estimator is an asymptotic least-square estimator defined by the no-arbitrage conditions upon which these models are built. Further, we note that our estimator remains easy-to-compute and asymptotically efficient in a variety of situations in which other recently proposed approaches might lose their tractability. We provide an empirical application in…

条件因子模型推断的组合方法AI 解读

This article develops a new methodology for estimating and testing conditional factor models in finance. We propose a two-stage procedure that naturally unifies the two existing approaches in the finance literature—the parametric approach and the nonparametric approach. Our combined approach possesses important advantages over both methods. Using our two-stage combined estimator, we derive new test statistics for investigating key hypotheses in the context of conditional…

基于 Copula 多元模型的半参数条件分位数估计AI 解读

We consider a new approach in quantile regression modeling based on the copula function that defines the dependence structure between the variables of interest. The key idea of this approach is to rewrite the characterization of a regression quantile in terms of a copula and marginal distributions. After the copula and the marginal distributions are estimated, the new estimator is obtained as the weighted quantile of the response variable in the model. The proposed…

高频数据中的纯跳过程检验AI 解读

Pure-jump processes have been increasingly popular in modeling high-frequency financial data, partially due to their versatility and flexibility. In the meantime, several statistical tests have been proposed in the literature to check the validity of using pure-jump models. However, these tests suffer from several drawbacks, such as requiring rather stringent conditions and having slow rates of convergence. In this paper, we propose a different test to check whether the…

透过镜面：借助简单均衡进行间接推断AI 解读

This paper develops an indirect inference (Gourieroux et al., 1993; Smith, 1993) estimation method for a large class of dynamic equilibria. Our approach consists of constructing econometrically tractable auxiliary equilibria, obtained by simplifying the economic primitives of the structural equilibrium model, via which estimation can proceed. We use this approach to develop an accurate estimator for the long-run risk model of Bansal and Yaron (2004). We demonstrate the…

AR–GARCH 类模型的残差秩设定检验AI 解读

This paper derives the asymptotic distribution for a number of rank-based and classical residual specification tests in AR–GARCH type models. We consider tests for the null hypotheses of no linear and quadratic serial residual autocorrelation, residual symmetry, and no structural breaks. We also apply our method to backtesting Value-at-Risk. For these tests we show that, generally, no size correction is needed in the asymptotic test distribution when applied to AR–GARCH…

非参数预测回归AI 解读

A unifying framework for inference is developed in predictive regressions where the predictor has unknown integration properties and may be stationary or nonstationary. Two easily implemented nonparametric F-tests are proposed. The limit distribution of these predictive tests is nuisance parameter free and holds for a wide range of predictors including stationary as well as non-stationary fractional and near unit root processes. Asymptotic theory and simulations show that…

波动率成分模型的计量分析AI 解读

Volatility component models have received considerable attention recently, not only because of their ability to capture complex dynamics via a parsimonious parameter structure, but also because it is believed that they can handle well structural breaks or nonstationarities in asset price volatility. This paper revisits component volatility models from a statistical perspective and attempts to explore the stationarity of the underlying processes. There is a clear need for…

Summary Motivated by the need for a positive‐semidefinite estimator of multivariate realized covariance matrices, we model noisy and asynchronous ultra‐high‐frequency asset prices in a state‐space framework with missing data. We then estimate the covariance matrix of the latent states through a Kalman smoother and expectation maximization (KEM) algorithm. Iterating between the two EM steps, we obtain a covariance matrix estimate which is robust to both asynchronicity and…

边际期望损失的估计：当相关变量处于极端值时AI 解读

Summary Denote the loss return on the equity of a financial institution as X and that of the entire market as Y. For a given very small value of p > 0, the marginal expected shortfall (MES) is defined as E{X|Y>QY(1−p)}, where Q Y(1 − p) is the (1 − p)th quantile of the distribution of Y. The MES is an important factor when measuring the systemic risk of financial institutions. For a wide non-parametric class of bivariate distributions, we construct an estimator of the MES…

含可张成或不可张成随机波动率的仿射期限结构模型估计AI 解读

We develop new procedures for maximum likelihood estimation of affine term structure models with spanned or unspanned stochastic volatility. Our approach uses linear regression to reduce the dimension of the numerical optimization problem yet it produces the same estimator as maximizing the likelihood. It improves the numerical behavior of estimation by eliminating parameters from the objective function that cause problems for conventional methods. We find that spanned…

This paper addresses the debate about the usefulness of high-frequency (HF) data in large-scale portfolio allocation. We construct global minimum variance portfolios based on the constituents of the S&P 500. HF-based covariance matrix predictions are obtained by applying a blocked realized kernel estimator, different smoothing windows, various regularization methods and two forecasting models. We show that HF-based predictions yield a significantly lower portfolio volatility…

Price indices for heterogeneous goods such as real estate or fine art constitute crucial information for institutional or private investors considering alternative investment decisions in times of financial markets turmoil. Classical mean-variance analysis of alternative investments has been hampered by the lack of a systematic treatment of volatility in these markets. In this paper we propose a hedonic regression framework which explicitly defines an underlying stochastic…

含噪声高频数据中共同跳跃的计量分析AI 解读

We establish estimation methods to determine co-jumps in multivariate high-frequency data with non-synchronous observations and market microstructure. A rate-optimal estimator of the entire quadratic covariation of an Itô-semimartingale is constructed by a locally adaptive spectral approach. Thresholding allows to disentangle the co-jump from the continuous part. We derive a feasible limit theorem for a truncated estimator of integrated covolatility which facilitates…

SR 方法：非线性非高斯动态期限结构模型的新估计程序AI 解读

This paper suggests a new approach for estimating linear and non-linear dynamic term structure models with latent factors. We impose no distributional assumptions on the factors which therefore may be non-Gaussian. The novelty of our approach is to use many observables (yields or bond prices) in the cross-section dimension. This implies that the latent factors can be determined quite accurately by a sequence of cross-section regressions. We also show how output from these…

执行价与到期时间无套利约束下的看涨期权价格曲面半非参数估计AI 解读

We suggest a semi-nonparametric estimator for the call-option price surface. The estimator is a bivariate tensor-product B-spline. To enforce no-arbitrage constraints across strikes and expiry dates, we establish sufficient no-arbitrage conditions on the control net of the B-spline surface. The conditions are linear and therefore allow for an implementation of the estimator by means of standard quadratic programming techniques. The consistency of the estimator is proved. By…

模糊性重要吗？多重先验递归效用资产定价模型的估计AI 解读

This paper considers asset pricing models with stochastic differential utility incorporating decision makers׳ concern with ambiguity on true probability measure. Under a representative agent setting, we empirically evaluate alternative preference specifications including a multiple-priors recursive utility. We find that relative risk aversion is estimated around 1–8 with ambiguity aversion and 7.4–15 without ambiguity aversion. Estimated ambiguity aversion is both…

非线性动态模型的规格检验AI 解读

We propose a new adequacy test and a graphical evaluation tool for nonlinear dynamic models. The proposed techniques can be applied in any set‐up where parametric conditional distribution of the data is specified and, in particular, to models involving conditional volatility, conditional higher moments, conditional quantiles, asymmetry, Value at Risk models, duration models, diffusion models, etc. Compared to other tests, the new test properly controls the nonlinear dynamic…

订单簿数据的模拟与分析：队列反应模型AI 解读

Through the analysis of a dataset of ultra high frequency order book updates, we introduce a model which accommodates the empirical properties of the full order book together with the stylized facts of lower frequency financial data. To do so, we split the time interval of interest into periods in which a well chosen reference price, typically the midprice, remains constant. Within these periods, we view the limit order book as a Markov queuing system. Indeed, we assume that…

非线性非高斯状态空间模型的数值加速重要性抽样AI 解读

We propose a general likelihood evaluation method for nonlinear non-Gaussian state-space models using the simulation-based method of efficient importance sampling. We minimize the simulation effort by replacing some key steps of the likelihood estimation procedure by numerical integration. We refer to this method as numerically accelerated importance sampling. We show that the likelihood function for models with a high-dimensional state vector and a low-dimensional signal…