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1.
This paper analyses the robustness of Least-Squares Monte Carlo, a technique proposed by Longstaff and Schwartz (2001) for
pricing American options. This method is based on least-squares regressions in which the explanatory variables are certain
polynomial functions. We analyze the impact of different basis functions on option prices. Numerical results for American
put options show that this approach is quite robust to the choice of basis functions. For more complex derivatives, this choice
can slightly affect option prices.
This revised version was published online in June 2006 with corrections to the Cover Date. 相似文献
2.
Natalia Beliaeva 《Journal of Banking & Finance》2012,36(1):151-163
This paper demonstrates how to value American interest rate options under the jump-extended constant-elasticity-of-variance (CEV) models. We consider both exponential jumps (see Duffie et al., 2000) and lognormal jumps (see Johannes, 2004) in the short rate process. We show how to superimpose recombining multinomial jump trees on the diffusion trees, creating mixed jump-diffusion trees for the CEV models of short rate extended with exponential and lognormal jumps. Our simulations for the special case of jump-extended Cox, Ingersoll, and Ross (CIR) square root model show a significant computational advantage over the Longstaff and Schwartz’s (2001) least-squares regression method (LSM) for pricing American options on zero-coupon bonds. 相似文献
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The least squares Monte Carlo method of Longstaff and Schwartz has become a standard numerical method for option pricing with many potential risk factors. An important choice in the method is the number of regressors to use and using too few or too many regressors leads to biased results. This is so particularly when considering multiple risk factors or when simulation is computationally expensive and hence relatively few paths can be used. In this paper we show that by imposing structure in the regression problem we can improve the method by reducing the bias. This holds across different maturities, for different categories of moneyness and for different types of option payoffs and often leads to significantly increased efficiency. 相似文献
5.
Abstract: This paper conducts a UK test of a version of the Ohlson (1995) model. We should only expect abnormal earnings to revert to zero if the book value of assets is economically meaningful. In this paper we make use of the property revaluations common in UK accounts, but estimate other asset values and earnings in inflation‐adjusted terms. This, we argue, gives rise to estimates of abnormal earnings that can reasonably be expected to revert to zero. We then test this modified model on UK data using the Dechow, Hutton and Sloan (1999) method. In line with the predictions of the Ohlson model, we find that these modified abnormal earnings appear to mean revert, and that a first order autoregressive process is sufficient to capture the persistence of UK real abnormal earnings. The modified abnormal earnings model in general predicts one year ahead earnings more successfully than an unmodified model. Furthermore, for much of the sample period, one year ahead predictions of abnormal earnings are better for the real model during periods of higher inflation. The undervaluation problem found in prior studies appears to be replaced with an overvaluation problem in the real model which is more acute during periods of high inflation. Last, we show that an estimate of the model based upon an industry level specification appears to perform no better than a market‐wide specification of the model. 相似文献
6.
The Dynamics of Short-Term Interest Rate Volatility Reconsidered 总被引:10,自引:0,他引:10
Kees G. Koedijk FranÇois Nissen Peter C. Schotman Christian C. P. Wolff 《European Finance Review》1997,1(1):105-130
In this paper we present and estimate a model of short-term interest rate volatility that encompasses both the level effect of Chan, Karolyi, Longstaff and Sanders (1992) and the conditional heteroskedasticity effect of the GARCH class of models. This flexible specification allows different effects to dominate as the level of the interest rate varies. We also investigate implications for the pricing of bond options. Our findings indicate that the inclusion of a volatility effect reduces the estimate of the level effect, and has option implications that differ significantly from the Chan, Karolyi, Longstaff and Sanders (1992) model. 相似文献
7.
In this paper we compare the forecasting performance of different models of interest rates using parametric and nonparametric estimation methods. In particular, we use three popular nonparametric methods, namely, artificial neural networks (ANN), k-nearest neighbour (k-NN), and local linear regression (LL). These are compared with forecasts obtained from two-factor continuous time interest rate models, namely, Chan, Karolyi, Longstaff, and Sanders [CKLS, J. Finance 47 (1992) 1209]; Cos, Ingersoll, and Ross [CIR, Econometrica 53 (1985) 385]; Brennan and Schwartz [BR-SC, J. Financ. Quant. Anal. 15 (1980) 907]; and Vasicek [J. Financ. Econ. 5 (1977) 177]. We find that while the parametric continuous time method, specifically Vasicek, produces the most successful forecasts, the nonparametric k-NN performed well. 相似文献
8.
We apply a set of structural models (Black and Cox 1976; Collin-Dufresne and Goldstein 2001; Ericsson and Reneby 1998; Leland
and Toft 1996; Longstaff and Schwartz 1995; Merton 1974) to estimate expected default probabilities (EDPs) for a sample of
failed and non-failed UK real estate companies. Results are generally consistent with models’ predictions and estimates of
EDPs for different models are closely clustered. The results of z-scores and synthetic ratings misclassify 33% of the total
sample in contrast to 8% misclassification by structural models. Further analysis of EDPs based on logistic regressions suggests
the observed misclassification of the companies by structural models is due to special company management and/or regulatory
circumstances rather than limitations of these models.
相似文献
9.
This paper investigates the presence of the leverage effect in commodities, in comparison with financial markets. The EGARCH model with a Mixture of Normals distribution (EGARCH-MN) is used to capture (i) heavy tails and skewness in the conditional returns, and (ii) leverage effects and time-varying long-term component in the volatility specification. Besides, the estimation strategy relies on an innovative recursive (REC) method, which allows disentangling the leverage effect from the unconditional skewness as an empirical result. When applied to a broadly diversified dataset of assets during 1995–2012, the EGARCH-MN models offers state-of-the-art specifications with leverage and fat-tailed skewed densities, that allow to contrast the specific characteristics of commodities with traditional assets (equities, bonds, FX). 相似文献
10.
The effect of inflation on the credit spreads of corporate bonds is investigated utilising real instead of nominal interest rates in extensions of the models proposed by Longstaff and Schwartz (1995) and Collin-Dufresne et al. (2001). Inflation is a critical, non-default, component incorporated in nominal bond yields, whose effect has not been considered by existing credit spread theory. In this sense the only true test of models of credit spread pricing must utilise real rates. To illustrate these requirements the Canadian bond data of Jacoby, Liao, and Batten (2009) is utilised. This Canadian data accommodates callability and the tax effects otherwise present in U.S. bond markets. The relation with historical default rates of both U.S. and Canadian bonds is also investigated since this approach is clean of both callability and tax effects. Overall, the analysis provides additional insights into the theoretical drivers of credit spreads as well as helping to explain observed corporate bond yield behaviour in financial markets. 相似文献