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Multivariate realised kernels: Consistent positive semi-definite estimators of the covariation of equity prices with noise and non-synchronous trading

多元已实现核:噪声与非同步交易下协变动的一致半正定估计

We propose a multivariate realised kernel to estimate the ex-post covariation of log-prices. We show this new consistent estimator is guaranteed to be positive semi-definite and is robust to measurement error of certain types and can also handle non-synchronous trading. It is the first estimator which has these three properties which are all essential for empirical work in this area. We derive the large sample asymptotics of this estimator and assess its accuracy using a…

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Estimating the Jump Activity Index Under Noisy Observations Using High-Frequency Data

利用含噪高频观测估计跳跃活跃指数

It is widely accepted that the high-frequency data are contaminated by microstructure noise, whose effect on the statistical inference has been of increasing interest in the literature. Much of it, however, has focused on the integrated volatility. In this article, we investigate another important characteristic, namely, the jump activity index (JAI) of a discretely sampled semi-martingale corrupted by microstructure noise. We point out that ignoring the microstructure noise…

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Estimating the Term Structure With a Semiparametric Bayesian Hierarchical Model: An Application to Corporate Bonds

半参数贝叶斯层级模型估计利率期限结构:公司债应用

The term structure of interest rates is used to price defaultable bonds and credit derivatives, as well as to infer the quality of bonds for risk management purposes. We introduce a model that jointly estimates term structures by means of a Bayesian hierarchical model with a prior probability model based on Dirichlet process mixtures. The modeling methodology borrows strength across term structures for purposes of estimation. The main advantage of our framework is its…

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Estimation and Evaluation of Conditional Asset Pricing Models

条件资产定价模型的估计与评价

ABSTRACT We find that several recently proposed consumption‐based models of stock returns, when evaluated using an optimal set of managed portfolios and the associated model‐implied conditional moment restrictions, fail to capture key features of risk premiums in equity markets. To arrive at these conclusions, we construct an optimal Generalized Method of Moments (GMM) estimator for models in which the stochastic discount factor (SDF) is a conditionally affine function of a…

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ESTIMATION OF A SEMIPARAMETRIC IGARCH(1,1) MODEL

半参数 IGARCH(1,1) 模型的估计

We propose a semiparametric IGARCH model that allows for persistence in variance but also allows for more flexible functional form. We assume that the difference of the squared process is weakly stationary. We propose an estimation strategy based on the nonparametric instrumental variable method. We establish the rate of convergence of our estimator.

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An inflated multivariate integer count hurdle model: an application to bid and ask quote dynamics

膨胀型多元整数计数跨栏模型:买卖报价动态应用

Abstract In this paper we develop a model for the conditional inflated multivariate density of integer count variables with domain ℤ n , n ∈ ℕ . Our modelling framework is based on a copula approach and can be used for a broad set of applications where the primary characteristics of the data are: (i) discrete domain; (ii) the tendency to cluster at certain outcome values; and (iii) contemporaneous dependence. These kinds of properties can be found for high‐ or…

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Estimation for Lévy processes from high frequency data within a long time interval

长时间区间内基于高频数据的 Lévy 过程估计

In this paper, we study nonparametric estimation of the Lévy density for Lévy processes, with and without Brownian component. For this, we consider n discrete time observations with step Δ. The asymptotic framework is: n tends to infinity, Δ=Δn tends to zero while nΔn tends to infinity. We use a Fourier approach to construct an adaptive nonparametric estimator of the Lévy density and to provide a bound for the global ${\mathbb{L}}^{2}$-risk. Estimators of the drift and of…

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Asymptotic equivalence for inference on the volatility from noisy observations

含噪观测下波动率推断的渐近等价性

We consider discrete-time observations of a continuous martingale under measurement error. This serves as a fundamental model for high-frequency data in finance, where an efficient price process is observed under microstructure noise. It is shown that this nonparametric model is in Le Cam’s sense asymptotically equivalent to a Gaussian shift experiment in terms of the square root of the volatility function σ and a nonstandard noise level. As an application, new rate-optimal…

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Data-based ranking of realised volatility estimators

基于数据比较已实现波动率估计量的精度

This paper presents new methods for comparing the accuracy of estimators of the quadratic variation of a price process. I provide conditions under which the relative accuracy of competing estimators can be consistently estimated (as T-->[infinity]), and show that forecast evaluation tests may be adapted to the problem of ranking these estimators. The proposed methods avoid making specific assumptions about microstructure noise, and facilitate comparisons of estimators that…

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Subsampling high frequency data

高频数据的子抽样推断

The main contribution of this paper is to propose a novel way of conducting inference for an important general class of estimators that includes many estimators of integrated volatility. A subsampling scheme is introduced that consistently estimates the asymptotic variance for an estimator, thereby facilitating inference and the construction of valid confidence intervals. The new method does not rely on the exact form of the asymptotic variance, which is useful when the…

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Forecast Combination Across Estimation Windows

跨估计窗口的预测组合

In this article we consider combining forecasts generated from the same model but over different estimation windows. We develop theoretical results for random walks with breaks in the drift and volatility and for a linear regression model with a break in the slope parameter. Averaging forecasts over different estimation windows leads to a lower bias and root mean square forecast error (RMSFE) compared with forecasts based on a single estimation window for all but the…

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Estimation for Non-Negative Lévy-Driven CARMA Processes

非负 Lévy 驱动 CARMA 过程的估计

Continuous-time autoregressive moving average (CARMA) processes with a nonnegative kernel and driven by a nondecreasing Lévy process constitute a useful and very general class of stationary, nonnegative continuous-time processes that have been used, in particular, for the modeling of stochastic volatility. Brockwell, Davis, and Yang (2007) derived efficient estimates of the parameters of a nonnegative Lévy-driven CAR(1) process and showed how the realization of the…

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MULTIVARIATE ECOGARCH PROCESSES

多变量 ECOGARCH 过程

A multivariate extension of the exponential continuous time GARCH ( p , q ) model (ECOGARCH) is introduced and studied. Stationarity and mixing properties of the new stochastic volatility model are investigated, and ways to model a component-wise leverage effect are presented.

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Riemann Manifold Langevin and Hamiltonian Monte Carlo Methods

黎曼流形上的 Langevin 与 Hamiltonian 蒙特卡洛方法

Summary The paper proposes Metropolis adjusted Langevin and Hamiltonian Monte Carlo sampling methods defined on the Riemann manifold to resolve the shortcomings of existing Monte Carlo algorithms when sampling from target densities that may be high dimensional and exhibit strong correlations. The methods provide fully automated adaptation mechanisms that circumvent the costly pilot runs that are required to tune proposal densities for Metropolis–Hastings or indeed…

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Assessing and valuing the nonlinear structure of hedge fund returns

对冲基金收益非线性结构的评估与价值衡量

Several studies have put forward that hedge fund returns exhibit a nonlinear relationship with equity market returns, captured either through constructed portfolios of traded options or piece-wise linear regressions. This paper provides a statistical methodology to unveil such nonlinear features with respect to returns on benchmark risk portfolios. We estimate a portfolio of options that best approximates the returns of a given hedge fund, account for this search in the…

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Default estimation, correlated defaults, and expert information

违约率估计、相关违约与专家信息

Capital allocation decisions are made on the basis of an assessment of creditworthiness. Default is a rare event for most segments of a bank's portfolio and data information can be minimal. Inference about default rates is essential for efficient capital allocation, for risk management and for compliance with the requirements of the Basel II rules on capital standards for banks. Expert information is crucial in inference about defaults. A Bayesian approach is proposed and…

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EMPIRICAL-LIKELIHOOD-BASED CONFIDENCE INTERVALS FOR CONDITIONAL VARIANCE IN HETEROSKEDASTIC REGRESSION MODELS

异方差回归模型条件方差的经验似然置信区间

Fan and Yao (1998) proposed an efficient method to estimate the conditional variance of heteroskedastic regression models. Chen, Cheng, and Peng (2009) applied variance reduction techniques to the estimator of Fan and Yao (1998) and proposed a new estimator for conditional variance to account for the skewness of financial data. In this paper, we apply empirical likelihood methods to construct confidence intervals for the conditional variance based on the estimator of Fan and…

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Variance dynamics: Joint evidence from options and high-frequency returns

方差动态:期权与高频收益的联合证据

This paper analyzes the S&P 500 index return variance dynamics and the variance risk premium by combining information in variance swap rates constructed from options and quadratic variation estimators constructed from tick data on S&P 500 index futures. Estimation shows that the index return variance jumps. The jump arrival rate is not constant over time, but is proportional to the variance rate level. The variance jumps are not rare events but arrive frequently. Estimation…

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Volatility forecast comparison using imperfect volatility proxies

使用不完美波动率代理变量比较波动率预测

The use of a conditionally unbiased, but imperfect, volatility proxy can lead to undesirable outcomes in standard methods for comparing conditional variance forecasts. We motivate our study with analytical results on the distortions caused by some widely used loss functions, when used with standard volatility proxies such as squared returns, the intra-daily range or realised volatility. We then derive necessary and sufficient conditions on the functional form of the loss…

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Realized volatility forecasting and market microstructure noise

已实现波动率预测与市场微观结构噪声

We extend the analytical results for reduced form realized volatility based forecasting in ABM (2004) to allow for market microstructure frictions in the observed high-frequency returns. Our results build on the eigenfunction representation of the general stochastic volatility class of models developed byMeddahi (2001). In addition to traditional realized volatility measures and the role of the underlying sampling frequencies, we also explore the forecasting performance of…

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Subsampling realised kernels

已实现核估计量的子采样

In a recent paper we have introduced the class of realised kernel estimators of the increments of quadratic variation in the presence of noise. We showed that this estimator is consistent and derived its limit distribution under various assumptions on the kernel weights. In this paper we extend our analysis, looking at the class of subsampled realised kernels and we derive the limit theory for this class of estimators. We find that subsampling is highly advantageous for…

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Market microstructure noise, integrated variance estimators, and the accuracy of asymptotic approximations

市场微观结构噪声、积分方差估计与渐近近似的准确性

A growing literature has been advocating consistent kernel estimation of integrated variance in the presence of financial market microstructure noise. We find that, for realistic sample sizes encountered in practice, the asymptotic results derived for the proposed estimators may provide unsatisfactory representations of their finite sample properties. In addition, the existing asymptotic results might not offer sufficient guidance for practical implementations. We show how…

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High-frequency returns, jumps and the mixture of normals hypothesis

高频收益、跳跃与正态混合假说

Previous empirical studies find both evidence of jumps in asset prices and that returns standardized by 'realized volatility' are approximately standard normal. These findings appear to be contradictory. Using a sample of high-frequency returns for 20 heavily traded US stocks, we show how microstructure noise distorts the standard deviation and kurtosis of returns normalized using realized variance. When returns are standardized using a recently developed realized kernel…

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Realized jumps on financial markets and predicting credit spreads

金融市场的已实现跳跃与信用利差预测

This paper extends the jump detection method based on bipower variation to identify realized jumps on financial markets and to estimate parametrically the jump intensity, mean, and variance. Finite sample evidence suggests that the jump parameters can be accurately estimated and that the statistical inferences are reliable under the assumption that jumps are rare and large. Applications to equity market, treasury bond, and exchange rate data reveal important differences in…

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