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Bayesian Emulation and Calibration of a Dynamic Epidemic Model for A/H1N1 Influenza

甲型 H1N1 流感动态传播模型的贝叶斯仿真与校准

In this article, we develop a Bayesian framework for parameter estimation of a computationally expensive dynamic epidemic model using time series epidemic data. Specifically, we work with a model for A/H1N1 influenza, which is implemented as a deterministic computer simulator, taking as input the underlying epidemic parameters and calculating the corresponding time series of reported infections. To obtain Bayesian inference for the epidemic parameters, the simulator is…

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Central Bank Macroeconomic Forecasting During the Global Financial Crisis: The European Central Bank and Federal Reserve Bank of New York Experiences

全球金融危机期间的央行宏观预测:欧洲央行与纽约联储的经验

This article documents macroeconomic forecasting during the global financial crisis by two key central banks: the European Central Bank and the Federal Reserve Bank of New York. The article is the result of a collaborative effort between staff at the two institutions, allowing us to study the time-stamped forecasts as they were made throughout the crisis. The analysis does not exclusively focus on point forecast performance. It also examines methodological contributions,…

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A Realized Stochastic Volatility Model With Box–Cox Transformation

采用 Box–Cox 变换的已实现随机波动率模型

This article presents a new class of realized stochastic volatility model based on realized volatilities and returns jointly. We generalize the traditionally used logarithm transformation of realized volatility to the Box–Cox transformation, a more flexible parametric family of transformations. A two-step maximum likelihood estimation procedure is introduced to estimate this model on the basis of Koopman and Scharth (Citation2013). Simulation results show that the two-step…

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A Varying-Coefficient Expectile Model for Estimating Value at Risk

用于估计风险价值的变系数期望分位数模型

This article develops a nonparametric varying-coefficient approach for modeling the expectile-based value at risk (EVaR). EVaR has an advantage over the conventional quantile-based VaR (QVaR) of being more sensitive to the magnitude of extreme losses. EVaR can also be used for calculating QVaR and expected shortfall (ES) by exploiting the one-to-one mapping from expectiles to quantiles, and the relationship between VaR and ES. Previous studies on conditional EVaR estimation…

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Testing the Martingale Hypothesis

鞅假设检验

We propose new tests of the martingale hypothesis based on generalized versions of the Kolmogorov–Smirnov and Cramér–von Mises tests. The tests are distribution-free and allow for a weak drift in the null model. The methods do not require either smoothing parameters or bootstrap resampling for their implementation and so are well suited to practical work. The article develops limit theory for the tests under the null and shows that the tests are consistent against a wide…

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Estimating time-changes in noisy Lévy models

含噪Lévy模型中的时间变换估计

In quantitative finance, we often model asset prices as a noisy Itô semimartingale. As this model is not identifiable, approximating by a time-changed Lévy process can be useful for generative modelling. We give a new estimate of the normalised volatility or time change in this model, which obtains minimax convergence rates, and is unaffected by infinite-variation jumps. In the semimartingale model, our estimate remains accurate for the normalised volatility, obtaining…

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Identification robust inference in cointegrating regressions

协整回归中对识别状态稳健的推断

In cointegrating regressions, estimators and test statistics are nuisance parameter dependent. This paper addresses this problem from an identification-robust perspective. Confidence sets for the long-run coefficient (denoted β) are proposed that invert LR-tests against an unrestricted or a cointegration-restricted alternative. For empirically relevant special cases, we provide analytical solutions to the inversion problem. A simulation study, imposing and relaxing strong…

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Pricing default events: Surprise, exogeneity and contagion

违约事件定价:意外、外生性与传染

In order to derive closed-form expressions of the prices of credit derivatives, standard credit-risk models typically price the default intensities, but not the default events themselves. The default indicator is replaced by an appropriate prediction and the prediction error, that is the default-event surprise, is neglected. Our paper develops an approach to get closed-form expressions for the prices of credit derivatives written on multiple names without neglecting…

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Disentangling systematic and idiosyncratic dynamics in panels of volatility measures

分离波动率面板中的系统性与个体动态

Realized volatilities observed across several assets show a common secular trend and some idiosyncratic pattern which we accommodate by extending the class of Multiplicative Error Models (MEMs). In our model, the common trend is estimated nonparametrically, while the idiosyncratic dynamics are assumed to follow univariate MEMs. Estimation theory based on seminonparametric methods is developed for this class of models for large cross-sections and large time dimensions. The…

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Modified local Whittle estimator for long memory processes in the presence of low frequency (and other) contaminations

低频及其他污染下长记忆过程的修正局部 Whittle 估计

We propose a modified local-Whittle estimator of the memory parameter of a long memory time series process which has good properties under an almost complete collection of contamination processes that have been discussed in the literature, mostly separately. These contaminations include processes whose spectral density functions dominate at low frequencies such as random level shifts, deterministic level shifts and deterministic trends. We show that our modified estimator…

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Modeling multivariate extreme events using self-exciting point processes

利用自激点过程建模多变量极端事件

We propose a model that can capture the typical features of multivariate extreme events observed in financial time series, namely, clustering behaviors in magnitudes and arrival times of multivariate extreme events, and time-varying dependence. The model is developed within the framework of the peaks-over-threshold approach in extreme value theory and relies on a Poisson process with self-exciting intensity. We discuss the properties of the model, treat its estimation, and…

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Macroeconomic risk and hedge fund returns

宏观经济风险与对冲基金收益

This paper estimates hedge fund and mutual fund exposure to newly proposed measures of macroeconomic risk that are interpreted as measures of economic uncertainty. We find that the resulting uncertainty betas explain a significant proportion of the cross-sectional dispersion in hedge fund returns. However, the same is not true for mutual funds, for which there is no significant relationship. After controlling for a large set of fund characteristics and risk factors, the…

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UNIFORM CONVERGENCE FOR NONPARAMETRIC ESTIMATORS WITH NONSTATIONARY DATA

非平稳数据下非参数估计量的一致收敛

Sharp upper and lower uniform bounds are established for a general class of functionals of integrated and fractionally integrated time series. The main result is used to develop optimal uniform convergence for the Nadaraya-Watson estimator and the local linear nonparametric estimator in a nonlinear cointegrating regression model. Unlike the point-wise situation, it is shown that the performance of the local linear nonparametric estimator is superior to that of the…

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TIME IRREVERSIBLE COPULA-BASED MARKOV MODELS

基于 Copula 的时间不可逆 Markov 模型

Economic and financial time series frequently exhibit time irreversible dynamics. For instance, there is considerable evidence of asymmetric fluctuations in many macroeconomic and financial variables, and certain game theoretic models of price determination predict asymmetric cycles in price series. In this paper, we make two primary contributions to the econometric literature on time reversibility. First, we propose a new test of time reversibility, applicable to stationary…

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EFFICIENCY IN LARGE DYNAMIC PANEL MODELS WITH COMMON FACTORS

含共同因子的大型动态面板模型的估计效率

This paper deals with asymptotically efficient estimation in exchangeable nonlinear dynamic panel models with common unobservable factors. These models are relevant for applications to large portfolios of credits, corporate bonds, or life insurance contracts. For instance, the Asymptotic Risk Factor (ARF) model is recommended in the current regulation in Finance (Basel II and Basel III) and Insurance (Solvency II) for risk prediction and computation of the required capital.…

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DISTRIBUTIONS OF QUADRATIC FUNCTIONALS OF THE FRACTIONAL BROWNIAN MOTION BASED ON A MARTINGALE APPROXIMATION

基于鞅近似的分数布朗运动二次泛函分布

The present paper deals with the distributions related to the fractional Brownian motion (fBm). In particular, we try to compute the distributions of (ratios of) its quadratic functionals, not by simulations, but by numerically inverting the associated characteristic functions (c.f.s). Among them is the fractional unit root distribution. It turns out that the derivation of the c.f.s based on the standard approaches used for the ordinary Bm is inapplicable. Here the…

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Point-optimal panel unit root tests with serially correlated errors

误差序列相关下的点最优面板单位根检验

Generalizations of the point‐optimal panel unit root tests of Moon, Perron and Phillips (MPP) are developed to cover cases of serially correlated errors. The resulting statistics involve two modifications relative to those of MPP: (a) the error variance is replaced by the long‐run variance; (b) centring of the statistic is adjusted to correct for second‐order bias effects induced by the correlation between the error and lagged dependent variable.

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Multivariate functional-coefficient regression models for nonlinear vector time series data

非线性向量时间序列的多元函数系数回归模型

Vector time series data are widely met in practice. In this paper we propose a multivariate functional-coefficient regression model with heteroscedasticity for modelling such data. A local linear smoother is employed to estimate the unknown coefficient matrices. Asymptotic normality of the proposed estimators is established, and bandwidth selection is considered. To deal with the co-integration commonly observed in financial markets, we propose an error-corrected…

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A Scalable Bootstrap for Massive Data

面向海量数据的可扩展自助法

Summary The bootstrap provides a simple and powerful means of assessing the quality of estimators. However, in settings involving large data sets—which are increasingly prevalent—the calculation of bootstrap-based quantities can be prohibitively demanding computationally. Although variants such as subsampling and the m out of n bootstrap can be used in principle to reduce the cost of bootstrap computations, these methods are generally not robust to specification of tuning…

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Theory-coherent forecasting

与经济理论一致的预测

We consider a method for producing multivariate density forecasts that satisfy moment restrictions implied by economic theory, such as Euler conditions. The method starts from a base forecast that might not satisfy the theoretical restrictions and forces it to satisfy the moment conditions using exponential tilting. Although exponential tilting has been considered before in a Bayesian context (Robertson et al. 2005), our main contributions are: (1) to adapt the method to a…

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A predictability test for a small number of nested models

针对少量嵌套模型的预测能力检验

We introduce quasi-likelihood ratio tests for one sided multivariate hypotheses to evaluate the null that a parsimonious model performs equally well as a small number of models which nest the benchmark. The limiting distributions of the test statistics are non-standard. For critical values we consider: (i) bootstrapping and (ii) simulations assuming normality of the mean square prediction error difference. The proposed tests have good size and power properties compared with…

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Testing for structural stability of factor augmented forecasting models

因子扩展预测模型的结构稳定性检验

Mild factor loading instability, particularly if sufficiently independent across the different constituent variables, does not affect the estimation of the number of factors, nor subsequent estimation of the factors themselves (see e.g. Stock and Watson (2009)). This result does not hold in the presence of large common breaks in the factor loadings, however. In this case, information criteria overestimate the number of breaks. Additionally, estimated factors are no longer…

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