Regular Variation of Popular GARCH Processes Allowing for Distributional Asymmetry
Linear GARCH(1,1) and threshold GARCH(1,1) processes are established as regularly varying, meaning their heavy tails are Pareto like, under conditions that allow the innovations from the, respective, processes to be skewed. Skewness is considered a stylized fact for many financial returns assumed to follow GARCH-type processes. The result in this note aids in establishing the asymptotic properties of certain GARCH estimators proposed in the literature.
Term Structure Analysis with Big Data
Analysis of the term structure of interest rates almost always takes a two-step approach. First, actual bond prices are summarized by interpolated synthetic zero-coupon yields, and second, a small set of these yields are used as the source data for further empirical examination. In contrast, we consider the advantages of a one-step approach that directly analyzes the universe of bond prices. To illustrate the feasibility and desirability of the onestep approach, we compare arbitrage-free dynamic term structure models estimated using both approaches. We also provide a simulation study showing ...
Asian financial linkage: macro-finance dissonance
How are Asian financial markets interlinked and how are they linked to markets in developed countries? What is the main driver of fluctuations in Asian financial markets as well as real economic activities? In order to answer these questions, we estimate the spillover index proposed by Diebold and Yilmaz (2009) and gauge the degree of interactions in both financial markets and real economic activities among Asian economies.> ; We first show that the degree of the international spillover in stock markets is like cookie-cutter products, namely, uniform, irrespective of the groups of countries, ...
Deconstructing the yield curve
We investigate the factor structure of the term structure of interest rates and argue that characterizing the minimal dimension of the data generating process is more challenging than currently appreciated. As a result, inference procedures for yield curve models that commit to a parsimoniously parameterized factor structure may be omitting important information about the underlying true factor space. To circumvent these difficulties, we introduce a novel nonparametric bootstrap that is robust to general forms of time and cross-sectional dependence and conditional heteroskedasticity of ...
When Simplicity Offers a Benefit, Not a Cost: Closed-Form Estimation of the GARCH(1,1) Model that Enhances the Efficiency of Quasi-Maximum Likelihood
Simple, multi-step estimators are developed for the popular GARCH(1,1) model, where these estimators are either available entirely in closed form or dependent upon a preliminary estimate from, for example, quasi-maximum likelihood. Identification sources to asymmetry in the model's innovations, casting skewness as an instrument in a linear, two-stage least squares estimator. Properties of regular variation coupled with point process theory establish the distributional limits of these estimators as stable, though highly non-Gaussian, with slow convergence rates relative to the ??n-case. Moment ...
The role of jumps in volatility spillovers in foreign exchange markets: meteor shower and heat waves revisited
This paper extends the previous literature on geographic (heat waves) and intertemporal (meteor showers) foreign exchange volatility transmission to characterize the role of jumps and cross-rate propagation. We employ heterogeneous autoregressive (HAR) models to capture the quasi-long-memory properties of volatility and the Shapley-Owen R2 measure to quantify the contributions of components. We conclude that meteor showers are more influential than heat waves, that jumps play a modest but significant role in volatility transmission and that significant, bidirectional cross-rate volatility ...
The Contribution of Jump Activity and Sign to Forecasting Stock Price Volatility
This paper proposes a novel approach to decompose realized jump measures by type of activity (finite/infinite) and by sign. We also provide noise-robust versions of the ABD jump test (Andersen et al. 2007) and realized semivariance measures for use at high frequency sampling intervals. The volatility forecasting exercise involves the use of different types of jumps, forecast horizons, sampling frequencies, calendar and transaction time-based sampling schemes, as well as standard and noise-robust volatility measures. We find that infinite (finite) jumps improve the forecasts at shorter ...
The equity risk premium: a review of models
We estimate the equity risk premium (ERP) by combining information from twenty models. The ERP in 2012 and 2013 reached heightened levels?of around 12 percent?not seen since the 1970s. We conclude that the high ERP was caused by unusually low Treasury yields.
Time-varying Volatility and the Power Law Distribution of Stock Returns
While many studies find that the tail distribution of high frequency stock returns follow a power law, there are only a few explanations for this finding. This study presents evidence that time-varying volatility can account for the power law property of high frequency stock returns. The power law coefficients obtained by estimating a conditional normal model with nonparametric volatility show a striking correspondence to the power law coefficients estimated from returns data for stocks in the Dow Jones index. A cross-sectional regression of the data coefficients on the model-implied ...
Identifying shocks via time-varying volatility
An n-variable structural vector auto-regression (SVAR) can be identified (up to shock order) from the evolution of the residual covariance across time if the structural shocks exhibit heteroskedasticity (Rigobon (2003), Sentana and Fiorentini (2001)). However, the path of residual covariances can only be recovered from the data under specific parametric assumptions on the variance process. I propose a new identification argument that identifies the SVAR up to shock orderings using the autocovariance structure of second moments of the residuals, implied by an arbitrary stochastic process for ...