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American options with stochastic dividends and volatility: A nonparametric investigation

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In this paper, the authors provide a full discussion of the theoretical foundations of American option valuation and exercise boundaries and show how they depend on the various sources of uncertainty which drive dividend rates and volatility, and derive equilibrium asset prices, derivative prices and optimal exercise boundaries in a general equilibrium model.
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This article is published in Journal of Econometrics.The article was published on 2000-01-01 and is currently open access. It has received 95 citations till now. The article focuses on the topics: Implied volatility & Volatility smile.

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Citations
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Journal ArticleDOI

Black-Scholes-Merton revisited under stochastic dividend yields

TL;DR: In this paper, the authors extended the standard Black-Scholes-Merton formula to incorporate stochastic dividend yield under a stochastically mean-reverting market price of risk.

Nonparametric Option Pricing by Transformation

TL;DR: In this article, a nonparametric option pricing theory and numerical method for European, American and path-dependent derivatives is developed, which can deal with asset returns that are either i.i.d. or dynamic.
Journal ArticleDOI

American option pricing under two stochastic volatility processes

TL;DR: This paper considers the pricing of an American call option whose underlying asset dynamics evolve under the influence of two independent stochastic volatility processes as proposed in Christoffersen, Heston and Jacobs (2009) and considers the associated partial differential equation for the option price and its solution.
Journal ArticleDOI

American option pricing under stochastic volatility: an efficient numerical approach

TL;DR: A new numerical technique to price an American option written upon an underlying asset that follows a bivariate diffusion process that has the advantage of avoiding two main issues associated with LSM, namely its inherent bias and the basis functions selection problem.
Journal ArticleDOI

Semi-parametric estimation of American option prices

TL;DR: In this paper, a semi-parametric estimator of American option prices is proposed based on a parameterized stochastic discount factor and is nonparametric w.r.t. the historical dynamics of the Markovian state variables.
References
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BookDOI

Density estimation for statistics and data analysis

TL;DR: The Kernel Method for Multivariate Data: Three Important Methods and Density Estimation in Action.
Journal ArticleDOI

Conditional heteroskedasticity in asset returns: a new approach

Daniel B. Nelson
- 01 Mar 1991 - 
TL;DR: In this article, an exponential ARCH model is proposed to study volatility changes and the risk premium on the CRSP Value-Weighted Market Index from 1962 to 1987, which is an improvement over the widely-used GARCH model.
Journal ArticleDOI

Generalized Additive Models.

Book

Brownian Motion and Stochastic Calculus

TL;DR: In this paper, the authors present a characterization of continuous local martingales with respect to Brownian motion in terms of Markov properties, including the strong Markov property, and a generalized version of the Ito rule.
Journal ArticleDOI

A Closed-Form Solution for Options with Stochastic Volatility with Applications to Bond and Currency Options

TL;DR: In this paper, a closed-form solution for the price of a European call option on an asset with stochastic volatility is derived based on characteristi c functions and can be applied to other problems.
Frequently Asked Questions (10)
Q1. What contributions have the authors mentioned in the paper "American options with stochastic dividends and volatility: a nonparametric investigation" ?

In this paper, the authors study the effect of volatility on the performance of the OEX contract on the S & P100 stock index. 

To choose the bandwith parameter the authors followed a procedure called generalized cross-validation, described in Craven and Wahba (1979) and used in the context of option pricing in Broadie et. al. (1995). 

1Two critical assumptions, namely (1) a constant dividend rate and(2) constant volatility, are often cited as restrictive and counter-factual. 

the nonparametric approach does achieve the main goal of their econometric anaylsis, namely to determine whether the volatility and/or the dividend rate a ect the valuation of the contract and the exercise policy. 

The most widely used kernel estimator of g in (3.11) is the NadarayaWatson estimator de ned byĝ (z) =Pn i=1K Zi zYiPni=1K Zi z ; (3.12) so thatĝ (Z1); : : : ; ĝ (Zn) 0 =WKn ( )Y; where Y = (Y1; : : : ; Yn) 0 and WKn is a n n matrix with its (i; j)-th element equal to K Zj Zi Pn k=1K Zk Zi : WKn is called the in uence matrix associated with the kernel K: 

The argument is that for a wide variety of misspeci ed ARCH models the di erence between the (EG)ARCH volatility estimates and the true underlying di usion volatilities converges to zero in probability as the length of the sampling time interval goes to zero at an appropriate rate. 

Several papers were devoted to the subject, namely Nelson (1990, 1991, 1992, 1996a,b) and Nelson and Foster (1994, 1995), which brought together two approaches, ARCH and continuous time SV, for modelling time-varying volatility in nancial markets. 

In this context, the value ofany contingent claim is simply given by its shadow price, i.e., the priceat which the representative agent is content to forgo holding the asset. 

Two state variables are required tomodel a stochastic dividend yield which is imperfectly correlated with thevolatility coe cients of the stock price process. 

The results so far seem to suggest two things: (1) conditioning on t does not displace pricing of options and (2) the volatility e ect seems to be present only for large (fourth quartile) volatilities.