Lecture

Asset Pricing and Hedging in Complete Markets

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In course

FIN-609: Asset Pricing (2011 - 2024)

This course provides an overview of the theory of asset pricing and portfolio choice theory following historical developments in the field and putting emphasis on theoretical models that help our understanding of financial decision making and financial mar ...

Description

This lecture covers asset pricing and hedging in complete markets, where self-financing trading strategies are used to replicate contingent claims. Linear pricing rules are defined, and the difficulty of identifying hedging strategies is discussed. The lecture explores American contingent claims, stopping times, and the Snell envelope of an adapted process. The optimal exercise policy is motivated using backward induction arguments. The lecture concludes with dynamic programming techniques for solving optimization problems in finance.

Instructor

Semyon Malamud

Teaching & PhD PhD Students Johannes Schwab, Onur Demiray, Giuseppe Matera Past EPFL PhD Students Rémy Praz, Evgeny Petrov, Yuan Zhang, Julien Arsène Blatt, Erik Hapnes, Teng Andrea Xu, Boris Kuznetsov Courses Big Data and Machine Learning for Financial Economics FIN-622 This class is an introduction to Machine Learning and High Dimensional Statistics in Finance. We start with purely empirical approach, focusing first on high dimensional regressions then moving to kernel methods and deep l

Official source

Ontological neighbourhood

Economics

Microeconomics: Financial economics

Related concepts (32)

Asset pricing

In financial economics, asset pricing refers to a formal treatment and development of two main pricing principles, outlined below, together with the resultant models. There have been many models developed for different situations, but correspondingly, these stem from either general equilibrium asset pricing or rational asset pricing, the latter corresponding to risk neutral pricing.

Optimization problem

In mathematics, computer science and economics, an optimization problem is the problem of finding the best solution from all feasible solutions. Optimization problems can be divided into two categories, depending on whether the variables are continuous or discrete: An optimization problem with discrete variables is known as a discrete optimization, in which an object such as an integer, permutation or graph must be found from a countable set.

Capital asset pricing model

In finance, the capital asset pricing model (CAPM) is a model used to determine a theoretically appropriate required rate of return of an asset, to make decisions about adding assets to a well-diversified portfolio. The model takes into account the asset's sensitivity to non-diversifiable risk (also known as systematic risk or market risk), often represented by the quantity beta (β) in the financial industry, as well as the expected return of the market and the expected return of a theoretical risk-free asset.

Fundamental theorem of asset pricing

The fundamental theorems of asset pricing (also: of arbitrage, of finance), in both financial economics and mathematical finance, provide necessary and sufficient conditions for a market to be arbitrage-free, and for a market to be complete. An arbitrage opportunity is a way of making money with no initial investment without any possibility of loss. Though arbitrage opportunities do exist briefly in real life, it has been said that any sensible market model must avoid this type of profit.

Mathematical optimization

Mathematical optimization (alternatively spelled optimisation) or mathematical programming is the selection of a best element, with regard to some criterion, from some set of available alternatives. It is generally divided into two subfields: discrete optimization and continuous optimization. Optimization problems arise in all quantitative disciplines from computer science and engineering to operations research and economics, and the development of solution methods has been of interest in mathematics for centuries.

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Dynamic Portfolio Choice: Wealth Dynamics and HJB Equation

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Dynamic Programming: Portfolio Optimization

Explores dynamic programming for optimizing portfolio choices and asset pricing theory.

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