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Course# FIN-415: Probability and stochastic calculus

Summary

This course gives an introduction to probability theory and stochastic calculus in discrete and continuous time. We study fundamental notions and techniques necessary for applications in finance such as option pricing, hedging, optimal portfolio choice and prediction problems.

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Related concepts (94)

Lectures in this course (29)

Instructors (2)

Brownian motion

Brownian motion is the random motion of particles suspended in a medium (a liquid or a gas).
This motion pattern typically consists of random fluctuations in a particle's position inside a fluid s

Stochastic process

In probability theory and related fields, a stochastic (stəˈkæstɪk) or random process is a mathematical object usually defined as a sequence of random variables, where the index of the sequence has

Central limit theorem

In probability theory, the central limit theorem (CLT) establishes that, in many situations, for independent and identically distributed random variables, the sampling distribution of the standardiz

Geometric Brownian motion

A geometric Brownian motion (GBM) (also known as exponential Brownian motion) is a continuous-time stochastic process in which the logarithm of the randomly varying quantity follows a Brownian motion

Kalman filter

For statistics and control theory, Kalman filtering, also known as linear quadratic estimation (LQE), is an algorithm that uses a series of measurements observed over time, including statistical noi

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