In: Computational Economics, 2007, vol. 29, no. 2, p. 151-158
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In: Computational Management Science, 2005, vol. 2, no. 2, p. 87-106
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In: Applied mathematical finance, 2011, vol. 18, no. 4, p. 277-289
Over the years a number of two-factor interest rate models have been proposed that have formed the basis for the valuation of interest rate contingent claims. This valuation equation often takes the form of a partial differential equation, that is solved using the finite difference approach. In the case of two factor models this has resulted in solving two second order partial derivatives...
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In: Computational statistics & data analysis, 2006, vol. 51, no. 4, p. 2267-2277
A multivariate methodology based on Functional Gradient Descent to estimate and forecast time-varying expected bond returns is presented and discussed. Backtesting this procedure on US monthly data, empirical evidence of its strong forecasting potential in terms of the accuracy of the predictions is collected. The proposed methodology clearly outperforms the classical univariate analysis used...
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In: Journal of forecasting, 2006, vol. 25, no. 8, p. 579–600
We propose a simple class of multivariate GARCH models, allowing for time-varying conditional correlations. Estimates for time-varying conditional correlations are constructed by means of a convex combination of averaged correlations (across all series) and dynamic realized (historical) correlations. Our model is very parsimonious. Estimation is computationally feasible in very large dimensions...
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In: The journal of derivatives, 2008, vol. 16, no. 2, p. 36-53
In the existing literature on barrier options much effort has been exerted to ensure convergence through placing the barrier in close proximity to, or directly onto, the nodes of the tree lattice. For a variety of barrier option types we show that such a procedure may not be a necessary prerequisite to achieving accurate option price approximations. Using the Kamrad and Ritchken (1991)...
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In: Computational management science, 2005, vol. 2, no. 2, p. 87-106
It is difficult to compute Value-at-Risk (VaR) using multivariate models able to take into account the dependence structure between large numbers of assets and being still computationally feasible. A possible procedure is based on functional gradient descent (FGD) estimation for the volatility matrix in connection with asset historical simulation. Backtest analysis on simulated and real data...
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In: The review of financial studies, 2008, vol. 21, no. 3, p. 1223-1258
We propose a new method for pricing options based on GARCH models with filtered historical innovaions. In an incomplete market framework, we allow for different distributions of historical and pricing return dynamics, which enhances the model’s flexibility to fit market option prices. An extensive empirical analysis based on S&P 500 Index options shows that our model outperforms other...
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In: Computational economics, 2007, vol. 29, no. 2, p. 151-159
Hedging equations from a method suggested by Barone-Adesi, Engle and Mancini, are presented and discussed. This model assumes the option price is homogeneous and the calculation is model independent, providing delta hedge ratios immediately from market data.
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The CKLS (1992) short-term risk-free interest rate process leads to valuation model for both default free bonds and contingent claims that can only be solved numerically for the general case. Valuation equations of this nature in the past have been solved using the Crank Nicholson scheme. In this paper, we introduce a new numerical scheme – the Box method, and compare it with the traditional...
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