论文检索

多元广义正交因子 GARCH 模型AI 解读

We propose a factor generalized autoregressive conditional heteroscedasticity (GARCH) model and develop test procedures for checking the correctness of the number of factors. Maximum likelihood estimation of the model is straightforward once computationally simple preliminary estimates are obtained. Motivated by the empirical application of the article, a mixture of Gaussian distributions is considered in addition to the conventional Gaussian likelihood. Interestingly, some…

更及时、更有用的先行指标指数AI 解读

Effectively predicting cyclical movements in the economy is a major challenge. The U.S. leading index (LI) has long been used to analyze and predict economic fluctuations. We describe and test a new procedure for making the LI more timely. The new LI significantly outperforms its older counterpart. It offers substantial gains in real-time, out-of-sample forecasts of changes in aggregate economic activity (real GDP, the index of coincident indicators, and industrial…

利用有限数据估计并合成国家收入分布AI 解读

A major problem encountered in studies of income inequality at regional and global levels is estimating income distributions from data that are in summary form. In this article we estimate national and regional income distributions within a general framework that relaxes the assumption of constant income within groups. We propose a technique to estimate the parameters of a beta-2 distribution using grouped data. We model regional income distribution using a mixture of…

大 N、大 T 面板中动态因子数量的一致估计AI 解读

Bai and Ng proposed a consistent estimator for the number of static factors in a large N and T approximate factor model. This article shows how the Bai–Ng estimator can be modified to consistently estimate the number of dynamic factors in a restricted dynamic factor model. The modification is straightforward: The standard Bai–Ng estimator is applied to residuals obtained by projecting the observed data onto lagged values of principal-components estimates of the static…

澳大利亚股票收益的波动率预测AI 解读

This article develops multivariate factor models for forecasting volatility in Australian stocks. We suggest estimation procedures for approximate factor models that are robust to jumps when the cross-sectional dimension is not very large, and also work with volatility measures that have been constructed so that they contain no jump components. Out-of-sample forecast analysis shows that multivariate factor models of volatility outperform univariate models, but there is…

检验标普500的连续半鞅假设AI 解读

Large amounts of intraday data of the S&P 500 stock index futures are used to test the hypothesis that the log-return process, corrected for drift, is a continuous martingale. We use the time change for martingales theorem to rephrase the hypothesis and test whether the return process, corrected for drift, is a time-changed Brownian motion. This hypothesis cannot be rejected.

私人保险、自选择与医疗服务使用AI 解读

Observed differences in medical utilization between the privately insured and uninsured reflect the combined effects of self-selection and insurance incentives (moral hazard). This article provides a Bayesian framework for decomposing the disparity into incentive and selection components. The effect of self-selection in private insurance on the number of doctor visits is estimated using a multiyear sample of the U.S. adult non-Medicare population obtained from the Medical…

短时段内协整关系失效的检验AI 解读

This article introduces tests for cointegration breakdown that may occur over a relatively short time period, such as at the end of the sample. The breakdown may be due to a shift in the cointegrating vector or due to a shift in the errors from being I(0) to being I(1). Tests are introduced based on the postbreakdown sum of squared residuals and sum of squared reverse partial sums of residuals. Critical values are provided using a subsampling method. Asymptotic results take…

将购买行为建模为重复事件AI 解读

We put forward a statistical model for interpurchase times that incorporates all current and past information available for all purchases as time runs along the calendar time scale. It delivers forecasts for the number of purchases in the next period, as well as for the timing of subsequent and consecutive purchases. Purchase occasions are viewed as a counting process that counts the recurrent purchases for each house-hold as they evolve over time. We illustrate our model…

Lévy 驱动的连续时间 CARMA 随机波动率模型模拟方法AI 解读

We develop simulation schemes for the new classes of non-Gaussian pure jump Lévy processes for stochastic volatility. We write the price and volatility processes as integrals against a vector Lévy process, which makes series approximation methods directly applicable. These methods entail simulation of the Lévy increments and formation of weighted sums of the increments; they do not require a closed-form expression for a tail mass function or specification of a copula…

基于价格极差的 EGARCH 模型与波动率预测AI 解读

We provide a simple, yet highly effective framework for forecasting return volatility by combining exponential generalized autoregressive conditional heteroscedasticity models with data on the range. Using Standard and Poor's 500 index data for 1983–2004, we demonstrate the importance of a long-memory specification, based on either a two-factor structure or fractional integration, that allows for some asymmetry between market returns and volatility innovations. Out-of-sample…

利率的树结构多状态模型AI 解读

This article develops a generalized tree-structured (GTS) model of the short-term interest rate that accommodates regime-dependent mean reversion and regime-dependent volatility clustering and level effects in the conditional variance. The model is constructed using the idea of multivariate tree-structured thresholds and nests the popular generalized autoregressive conditional heteroscedasticity and square root processes as simple special cases. It allows us to estimate the…

从消费者行为识别固定成本AI 解读

Some household expenditures, such as those for subsistence or basic needs, are fixed. Using the methodology of equivalence scales, we develop a model in which differences in fixed costs of characteristics across households can be identified from household behavior. Equivalent expenditure for a household is the expenditure needed to bring a reference household, such as a single childless adult, to the level of well-being of household members. The equivalence scale for the…

基于 Wishart 过程的多变量随机波动率模型AI 解读

Financial models for asset and derivatives pricing, risk management, portfolio optimization, and asset allocation rely on volatility forecasts. Time-varying volatility models, such as generalized autoregressive conditional heteroscedasticity and stochastic volatility (SVOL), have been successful in improving forecasts over constant volatility models. We develop a new multivariate SVOL framework for modeling financial data that assumes covariance matrices stochastically…

以标准误作为多边价格指数的权重AI 解读

Various multilateral methods for computing price indexes use bilateral comparisons as their basic building blocks. Some give greater weight to those bilateral comparisons deemed more reliable. However, none of the existing reliability measures adjusts for gaps in the data. We show how the standard errors on bilateral price indexes derived using weighted least squares provide reliability measures that solve this problem. We then apply our methodology to a dataset on…

追踪欧元区商业周期AI 解读

This article proposes a multivariate bandpass filter based on the trend plus cycle decomposition model. The underlying multivariate dynamic factor model relies on specific formulations for trend and cycle components and produces smooth business cycle indicators with bandpass filter properties. Furthermore, cycle shifts for individual time series are incorporated as part of the multivariate model and estimated simultaneously with the remaining parameters. The inclusion of…

美国实际产出状态切换时间序列模型的有效性评估AI 解读

Two types of state-switching models for U.S. real output have been proposed: models that switch randomly between states and models that switch states deterministically, as in the threshold autoregressive model of Potter. These models have been justified primarily on how well they fit the sample data, yielding statistically significant estimates of the model coefficients. Here we propose a new approach to the evaluation of an estimated nonlinear time series model that…

修剪数据下的分布支配AI 解读

Distributional dominance criteria are commonly applied to draw welfare inferences about comparisons, but conclusions drawn from empirical implementations of dominance criteria may be influenced by data contamination. We examine a nonparametric approach to refining Lorenz-type comparisons and apply the technique to two important examples from the Luxembourg Income Study database.

含极端异常值金融时间序列的二阶滤波分布近似AI 解读

Particle filters are regularly used to obtain the filter distributions associated with state–space financial time series. The most common use today is the auxiliary particle filter (APF) method in conjunction with a first-order Taylor expansion of the log-likelihood. We argue that for series such as stock returns, which exhibit fairly frequent and extreme outliers, filters based on this first-order approximation can easily break down. However, an APF based on the much more…

摘要暂缺

摘要暂缺

摘要暂缺

摘要暂缺

不同抽样方案下已实现方差的性质AI 解读

This article investigates the statistical properties of the realized variance estimator in the presence of market microstructure noise. Different from the existing literature, the analysis relies on a pure jump process for high-frequency security prices and explicitly distinguishes among alternative sampling schemes, including calendar time sampling, business time sampling, and transaction time sampling. The main finding in this article is that transaction time sampling is…