Lecture

Multiperiod Binomial Pricing

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In course

MGT-301: Foundations in financial economics

The aim of this course is to expose EPFL bachelor students to some of the main areas in financial economics. The course will be organized around six themes. Students will obtain both practical insights through real-world examples and understand how one can ...

Description

This lecture covers the concept of multiperiod binomial pricing, explaining recursive algorithms, binomial pricing, examples of put options, setting up different scalings, limit distribution, the Black-Scholes formula, implied volatility, and pricing by replication.

Instructors (3)

Rüdiger Fahlenbrach

RUEDIGER FAHLENBRACH is Full Professor at Ecole Polytechnique Fédérale de Lausanne (EPFL), Switzerland. Formerly on the faculty of the Fisher College of Business of the Ohio State University (USA), he holds a Ph.D. in Finance from the University of Pennsylvania (Wharton). He holds a senior research chair from the Swiss Finance Institute, and is research member at the European Corporate Governance Institute (ECGI). He has research interests in empirical corporate finance, in particular corporate governance and entrepreneurship. Ruediger Fahlenbrach has published in the leading academic journals in finance, including the Journal of Finance, the Journal of Financial Economics, the Review of Financial Studies and the Journal of Financial and Quantitative Analysis. Ruediger currently serves a three year term as elected director of the European Finance Association (2018-2020). He is Associate Editor of the Review of Finance, and former associate editor of the Review of Financial Studies and Financial Management. His research has been reported in many large-circulation newspapers such as The New York Times, The Wall Street Journal, The Economist, Le Temps, NZZ, Handelsblatt, Forbes Magazine, USA Today, and Fortune Magazine.

Julien Hugonnier

Expertise Asset pricing theory, incomplete markets and financial frictions, general equilibrium theory, decision making under uncertainty Teaching & PhD PhD Students Luca Pagliuca, Darius Nik Nejad Past EPFL PhD Students Rodolfo Javier Prieto Katunaric, Michael Hasler, Giuliano Antonio Curatola, Julien Cujean, Thomas Antonius Geelen, Nicolas Gauderon, Benoit Vincent Sylvain Cornet Past EPFL PhD Students as codirector Rémy Praz, Cagil Kocyigit, Alexis Marchal Courses Derivatives FIN-404 Thi

Pierre Collin-Dufresne

Official source

Ontological neighbourhood

Economics

Microeconomics: Financial economics

Statistics

Statistical inference: Mathematical statistics

Related concepts (32)

Normal distribution

In statistics, a normal distribution or Gaussian distribution is a type of continuous probability distribution for a real-valued random variable. The general form of its probability density function is The parameter is the mean or expectation of the distribution (and also its median and mode), while the parameter is its standard deviation. The variance of the distribution is . A random variable with a Gaussian distribution is said to be normally distributed, and is called a normal deviate.

Rational pricing

Rational pricing is the assumption in financial economics that asset prices – and hence asset pricing models – will reflect the arbitrage-free price of the asset as any deviation from this price will be "arbitraged away". This assumption is useful in pricing fixed income securities, particularly bonds, and is fundamental to the pricing of derivative instruments. Arbitrage is the practice of taking advantage of a state of imbalance between two (or possibly more) markets. Where this mismatch can be exploited (i.

Log-normal distribution

In probability theory, a log-normal (or lognormal) distribution is a continuous probability distribution of a random variable whose logarithm is normally distributed. Thus, if the random variable X is log-normally distributed, then Y = ln(X) has a normal distribution. Equivalently, if Y has a normal distribution, then the exponential function of Y, X = exp(Y), has a log-normal distribution. A random variable which is log-normally distributed takes only positive real values.

Lattice model (finance)

In finance, a lattice model is a technique applied to the valuation of derivatives, where a discrete time model is required. For equity options, a typical example would be pricing an American option, where a decision as to option exercise is required at "all" times (any time) before and including maturity. A continuous model, on the other hand, such as Black–Scholes, would only allow for the valuation of European options, where exercise is on the option's maturity date.

Cauchy distribution

The Cauchy distribution, named after Augustin Cauchy, is a continuous probability distribution. It is also known, especially among physicists, as the Lorentz distribution (after Hendrik Lorentz), Cauchy–Lorentz distribution, Lorentz(ian) function, or Breit–Wigner distribution. The Cauchy distribution is the distribution of the x-intercept of a ray issuing from with a uniformly distributed angle. It is also the distribution of the ratio of two independent normally distributed random variables with mean zero.

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