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Factor Model Approach to Derivative Pricing

James A. Primbs
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A01=James A. Primbs
advanced derivative pricing techniques
Arbitrage Equation
asset pricing theory
Author_James A. Primbs
Binomial Tree
Black Scholes Formula
bond
brownian
Brownian Motion
Call Option
Cash Flow Diagram
Category=KFF
Category=KFFM
Category=PB
Category=PBT
Compound Poisson Process
credit risk modeling
differential
eq_bestseller
eq_business-finance-law
eq_isMigrated=1
eq_isMigrated=2
eq_nobargain
eq_non-fiction
equation
European Call Option
finanacial mathematics
financial engineering
financial risk management
Forward Rate
free
geometric
Geometric Brownian Motion
Hedged Portfolio
hedging
Instantaneous Forward Rates
interest rate modeling
Ito's Lemma
itos
Ito’s Lemma
Jump Diffusion Model
LIBOR Market Model
motion
Poisson Processes
quantitative finance
risk
Risk Free Bond
Risk Free Rate
Risk Neutral Pricing
risk neutrality
Step Procedure
stochastic
Stochastic Differential Equation
stochastic processes applications
Strike Price
Tradable Table
Underlying Variables
Vector Brownian Motion

Product details

  • ISBN 9781498763325
  • Weight: 540g
  • Dimensions: 178 x 254mm
  • Publication Date: 08 Dec 2016
  • Publisher: Taylor & Francis Inc
  • Publication City/Country: US
  • Product Form: Paperback
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Description

Written in a highly accessible style, A Factor Model Approach to Derivative Pricing lays a clear and structured foundation for the pricing of derivative securities based upon simple factor model related absence of arbitrage ideas. This unique and unifying approach provides for a broad treatment of topics and models, including equity, interest-rate, and credit derivatives, as well as hedging and tree-based computational methods, but without reliance on the heavy prerequisites that often accompany such topics.

Whether being used as text for an intermediate level course in derivatives, or by researchers and practitioners who are seeking a better understanding of the fundamental ideas that underlie derivative pricing, readers will appreciate the book’s ability to unify many disparate topics and models under a single conceptual theme.

About James A. Primbs
James A. Primbs holds undergraduate degrees in Mathematics and Electrical Engineering from UC Davis, an MS degree in Electrical Engineering from Stanford, and a PhD in Control and Dynamical System from Caltech. From 2001-2012 he served as an Assistant and then a Consulting Associate Professor in the Management Science and Engineering department at Stanford University. From 2012 to 2014 he was an Associate Professor in the Systems Engineering department at UT Dallas. He is currently an Associate Professor of Finance in the Mihaylo College of Business and Economics at California State University, Fullerton. He has won teaching awards at both the undergraduate and graduate level, given short courses to and consulted for the financial industry, and organized numerous conference tutorials and workshops, especially in the application of systems and control methods to finance. He is active in INFORMS where he has held various officer positions in the Section on Finance. His research interests involve the use of systems, optimization, and control theory in finance.

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