Binary option pricing model with the underlying stock price driven by OrnsteinᾯUhlenbeck process under risk-free rate as a stochastic interest rates

2013 ◽  
Author(s):  
Zheng Xiaoyang ◽  
Zhang Yuanyuan
Keyword(s):  
Option Pricing ◽  
Interest Rates ◽  
Stock Price ◽  
Pricing Model ◽  
Stochastic Interest Rates ◽  
Stochastic Interest ◽  
Option Pricing Model ◽  
Risk Free Rate ◽  
Free Rate

scholarly journals Valuing Coca-Cola And PepsiCo Options Using The Black-Scholes Option Pricing Model And Data Downloads From The Internet

2012 ◽  
Vol 8 (6) ◽  
pp. 559-564
Author(s):  
John C. Gardner ◽  
Carl B. McGowan Jr
Keyword(s):  
Option Pricing ◽  
Stock Price ◽  
Option Price ◽  
Option Prices ◽  
Pricing Model ◽  
Black Scholes ◽  
Option Pricing Model ◽  
Risk Free Rate ◽  
Daily Returns ◽  
Free Rate

In this paper, we demonstrate how to collect the data and compute the actual value of Black-Scholes Option Pricing Model call option prices for Coca-Cola and PepsiCo.The data for the current stock price and option price are taken from Yahoo Finance and the daily returns variance is computed from daily prices.The time to maturity is computed as the number of days remaining for the stock option.The risk-free rate is obtained from the U.S. Treasury website.

scholarly journals EFFECTS OF RETURN PREDICTABILITY ON OPTION PRICES WITH STOCHASTIC VOLATILITY FOR THE MARKET PORTFOLIO

2005 ◽  
Vol 01 (01) ◽  
pp. 0550005
Author(s):  
MELANIE CAO
Keyword(s):  
Option Pricing ◽  
Interest Rates ◽  
Stochastic Volatility ◽  
Return Predictability ◽  
Option Prices ◽  
Pricing Model ◽  
Stochastic Interest Rates ◽  
Market Portfolio ◽  
Stochastic Interest ◽  
Option Pricing Model

I examine the effects of return predictability on option prices for the market portfolio in the presence of stochastic volatility and/or stochastic interest rates. The analysis is implemented in an equilibrium framework where a consistent option pricing model is derived with the return predictability and stochastic volatility and the precise link between the actual and the risk neutral measures is endogenized. The equilibrium analysis indicates that the return predictability is induced by the mean-reverting and heteroskedastic features of aggregate dividends. It is shown that risk-neutral option pricing model with the stochastic volatility and/or stochastic interest rates can be consistent with return predictability. Numerical results suggest that (i) models with either perfect predictability or no predictability will significantly overprice long-term options across different strike prices when the return of the underlying exhibits modest predictability; (ii) the stochastic volatility does not affect option prices in a significant way when asset return predictability is properly reflected in the actual stock price process; (iii) when return predictability is correctly specified, the effects of stochastic interest rates are not uniform.

scholarly journals Good Volatility, Bad Volatility, and Option Pricing

2018 ◽  
Vol 54 (2) ◽  
pp. 695-727 ◽  
Author(s):  
Bruno Feunou ◽  
Cédric Okou
Keyword(s):  
Option Pricing ◽  
Stock Price ◽  
Asset Price ◽  
Jump Diffusion ◽  
Quadratic Variation ◽  
Pricing Model ◽  
Economic Gain ◽  
Underlying Asset ◽  
Model Free ◽  
Option Pricing Model

Advances in variance analysis permit the splitting of the total quadratic variation of a jump-diffusion process into upside and downside components. Recent studies establish that this decomposition enhances volatility predictions and highlight the upside/downside variance spread as a driver of the asymmetry in stock price distributions. To appraise the economic gain of this decomposition, we design a new and flexible option pricing model in which the underlying asset price exhibits distinct upside and downside semivariance dynamics driven by the model-free proxies of the variances. The new model outperforms common benchmarks, especially the alternative that splits the quadratic variation into diffusive and jump components.

Predicting the stock price of frontier markets using machine learning and modified Black–Scholes Option pricing model

2020 ◽  
Vol 555 ◽  
pp. 124444 ◽  
Author(s):  
Reaz Chowdhury ◽  
M.R.C. Mahdy ◽  
Tanisha Nourin Alam ◽  
Golam Dastegir Al Quaderi ◽  
M. Arifur Rahman
Keyword(s):  
Machine Learning ◽  
Option Pricing ◽  
Stock Price ◽  
Pricing Model ◽  
Black Scholes ◽  
Option Pricing Model

scholarly journals Convergence of discrete time option pricing models under stochastic interest rates

2000 ◽  
Vol 4 (1) ◽  
pp. 81-93 ◽  
Author(s):  
J.-P. Lesne ◽  
J.-L. Prigent ◽  
O. Scaillet
Keyword(s):  
Option Pricing ◽  
Interest Rates ◽  
Discrete Time ◽  
Pricing Models ◽  
Stochastic Interest Rates ◽  
Stochastic Interest
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