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An aggregated method of nonparametric estimators based on time-domain and state-domain estimators is proposed and studied. To attenuate the curse of dimensionality, we propose a factor modeling strategy. We first investigate the asymptotic behavior of nonparametric estimators of the volatility...
The well-known ARCH/GARCH models for financial time series have been criticized of late for their poor performance in volatility prediction, that is, prediction of squared returns.1 Focusing on three representative data series, namely a foreign exchange series (Yen vs. Dollar), a stock index...
Maximum-likelihood estimates of the parameters of stochastic differential equations are consistent and asymptotically efficient, but unfortunately difficult to obtain if a closed-form expression for the transitional probability density function of the process is not available. As a result, a...
We propose an affine term structure model which accommodates nonlinearities in the drift and volatility function of the short-term interest rate. Such nonlinearities are a consequence of discrete beta-distributed regime shifts constructed on multiple thresholds. We derive iterative closed-form...
This article proposes a bias-adjusted estimator for use in cointegrated panel regressions when the errors are cross-sectionally correlated through an unknown common factor structure. The asymptotic distribution of the new estimator is derived and is examined in small samples using Monte Carlo...
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