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Showing papers by "George Tauchen published in 2001"


Journal ArticleDOI
George Tauchen1
TL;DR: The authors showed that the sampling distribution of the regression estimator of this coefficient is upward-biased relative to unity and strongly skewed to the right, and that the estimator is biased in a direction opposite to what is observed.

42 citations


Journal ArticleDOI
TL;DR: In this article, the exchange rate can be modeled as a managed float system with a central parity that lacks a band, and the authors find strong evidence that a model with intramarginal intervention and a narrower implicit band can describe the dynamics of the French franc/Deutsche mark exchange rate from January 1, 1987 to July 30, 1993.
Abstract: The objectives of this article are threefold—(1) to test target-zone models using more efficient and direct econometric methodology than previous research, (2) to identify an implicit band, if it exists, from observed data and to test target-zone models based on the estimated implicit band rather than the stated official band, and (3) to examine whether the exchange rate can be modeled as a managed float system with a central parity that lacks a band We find strong evidence that a model with intramarginal intervention and a narrower implicit (unofficial) band can describe the dynamics of the French franc/Deutsche mark exchange rate from January 1, 1987–July 30, 1993

41 citations


Journal ArticleDOI
George Tauchen1
TL;DR: In this article, the authors review recent successes in modeling of discrete time financial data and argue that a direct approach is better suited than stochastic volatility, with emphasis on simulation-based techniques and joint estimation of the risk neutral and objective probability distributions.

21 citations


Journal ArticleDOI
TL;DR: In this paper, a two-factor log-linear stochastic volatility diffusion model (without jumps) appears to yield a remarkably good empirical fit for option pricing, where one factor controls the persistence in volatility and the second determines the tail behavior.
Abstract: The purpose of this paper is to shed further light on the tensions that exist between the empirical fit of stochastic volatility (SV) models and their linkage to option pricing. A number of recent papers have investigated several specifications of one-factor SV diffusion models associated with option pricing models. The empirical failure of one-factor affine, Constant Elasticity of Variance (CEV), and one-factor log-linear SV models leaves us with two strategies to explore: (1) add a jump component to better fit the tail behavior or (2) add an additional (continuous path) factor where one factor controls the persistence in volatility and the second determines the tail behavior. Both have been partially pursued and our paper embarks on a more comprehensive examination which yields some rather surprising results. Adding a jump component to the basic Heston affine model is known to be a successful strategy as demonstrated by Andersen et al. (1999), Eraker et al. (1999), Chernov et al. (1999), and Pan (1999). Unfortunately, the presence of a jump component introduces quite a few unpleasant econometric issues. In addition, several financial issues, like hedging and risk factors become more complex. In this paper we show that a two-factor log-linear SV diffusion model (without jumps) appears to yield a remarkably good empirical fit. We estimate the model via the EMM procedure of Gallant and Tauchen (1996) which allows us to compare the non-nested log-linear SV diffusion with the affine jump specification. Obviously, there is one drawback to the log-linear SV models when it comes to pricing derivatives since no closed-form solutions are available. Against this cost weights the advantage of avoiding all the complexities involved with jump processes.

20 citations


George Tauchen1
01 Jan 2001
TL;DR: The "rst part of the discussion reviews recent successes in modeling of discrete time "nancial data and argues that a direct approach is better suited than stochastic volatility and the second part reviews recent work on estimating continuous time models with emphasis on simulation-based techniques and joint estimation of the risk neutral and objective probability distributions.
Abstract: The "rst part of the discussion reviews recent successes in modeling of discrete time "nancial data and argues that a direct approach is better suited than stochastic volatility. The second part reviews recent work on estimating continuous time models with emphasis on simulation-based techniques and joint estimation of the risk neutral and objective probability distributions. ( 2001 Elsevier Science S.A. All rights reserved.

2 citations