Python for Finance: Analyze Big Financial Data

Further Reading

The original article introducing Monte Carlo simulation to finance is:

Boyle, Phelim (1977): “Options: A Monte Carlo Approach.” Journal of Financial

Economics, Vol. 4, No. 4, pp. 322–338.

Other original papers cited in this chapter are (see also Chapter 16):

Black, Fischer and Myron Scholes (1973): “The Pricing of Options and Corporate

Liabilities.” Journal of Political Economy, Vol. 81, No. 3, pp. 638–659.

Cox, John, Jonathan Ingersoll and Stephen Ross (1985): “A Theory of the Term

Structure of Interest Rates.” Econometrica, Vol. 53, No. 2, pp. 385–407.

Heston, Steven (1993): “A Closed-From Solution for Options with Stochastic

Volatility with Applications to Bond and Currency Options.” The Review of Financial

Studies, Vol. 6, No. 2, 327–343.

Merton, Robert (1973): “Theory of Rational Option Pricing.” Bell Journal of

Economics and Management Science, Vol. 4, pp. 141–183.

Merton, Robert (1976): “Option Pricing When the Underlying Stock Returns Are

Discontinuous.” Journal of Financial Economics, Vol. 3, No. 3, pp. 125–144.

The books by Glassermann (2004) and Hilpisch (2015) cover all topics of this chapter in

depth (however, the first one does not cover any technical implementation details):

Glasserman, Paul (2004): Monte Carlo Methods in Financial Engineering. Springer,

New York.

Hilpisch, Yves (2015): Derivatives Analytics with Python. Wiley Finance, Chichester,

England. http://www.derivatives-analytics-with-python.com.

It took until the turn of the century for an efficient method to value American options by

Monte Carlo simulation to finally be published:

Longstaff, Francis and Eduardo Schwartz (2001): “Valuing American Options by

Simulation: A Simple Least Squares Approach.” Review of Financial Studies, Vol.

14, No. 1, pp. 113–147.

A broad and in-depth treatment of credit risk is provided in:

Duffie, Darrell and Kenneth Singleton (2003): Credit Risk — Pricing, Measurement,

and Management. Princeton University Press, Princeton, NJ.

[ 35 ]

For simplicity, we will speak of random numbers knowing that all numbers used will be pseudorandom.