Monte Carlo methods in finance | Financial models
A stochastic investment model tries to forecast how returns and prices on different assets or asset classes, (e. g. equities or bonds) vary over time. Stochastic models are not applied for making point estimation rather interval estimation and they use different stochastic processes. Investment models can be classified into single-asset and multi-asset models. They are often used for actuarial work and financial planning to allow optimization in asset allocation or asset-liability-management (ALM). (Wikipedia).
"Data-Driven Optimization in Pricing and Revenue Management" by Arnoud den Boer - Lecture 1
In this course we will study data-driven decision problems: optimization problems for which the relation between decision and outcome is unknown upfront, and thus has to be learned on-the-fly from accumulating data. This type of problems has an intrinsic tension between statistical goals a
From playlist Thematic Program on Stochastic Modeling: A Focus on Pricing & Revenue Management
Basic stochastic simulation b: Stochastic simulation algorithm
(C) 2012-2013 David Liao (lookatphysics.com) CC-BY-SA Specify system Determine duration until next event Exponentially distributed waiting times Determine what kind of reaction next event will be For more information, please search the internet for "stochastic simulation algorithm" or "kin
From playlist Probability, statistics, and stochastic processes
Introduction to the paper https://arxiv.org/abs/2002.06707
From playlist Research
“Data-Driven Pricing” – Prof. Omar Besbes
Pricing is central to many industries and academic disciplines ranging from Operations Research to Economics and Computer Science. At the heart of pricing lies a fundamental informational dimension regarding the level of knowledge about customers' values. In practice, the latter comes from
From playlist Thematic Program on Stochastic Modeling: A Focus on Pricing & Revenue Management
"Diffusion Approximation and Sequential Experimentation" by Victor Araman
We consider a Bayesian sequential experimentation problem. We identify environments in which the average number of experiments that is conducted per unit of time is large and the informativeness of each individual experiment is low. Under such regimes, we derive a diffusion approximation f
From playlist Thematic Program on Stochastic Modeling: A Focus on Pricing & Revenue Management
"Data-Driven Optimization in Pricing and Revenue Management" by Arnoud den Boer - Lecture 3
In this course we will study data-driven decision problems: optimization problems for which the relation between decision and outcome is unknown upfront, and thus has to be learned on-the-fly from accumulating data. This type of problems has an intrinsic tension between statistical goals a
From playlist Thematic Program on Stochastic Modeling: A Focus on Pricing & Revenue Management
"Data-Driven Optimization in Pricing and Revenue Management" by Arnoud den Boer - Lecture 2
In this course we will study data-driven decision problems: optimization problems for which the relation between decision and outcome is unknown upfront, and thus has to be learned on-the-fly from accumulating data. This type of problems has an intrinsic tension between statistical goals a
From playlist Thematic Program on Stochastic Modeling: A Focus on Pricing & Revenue Management
An introduction to multilevel Monte Carlo methods – Michael Giles – ICM2018
Numerical Analysis and Scientific Computing Invited Lecture 15.7 An introduction to multilevel Monte Carlo methods Michael Giles Abstract: In recent years there has been very substantial growth in stochastic modelling in many application areas, and this has led to much greater use of Mon
From playlist Numerical Analysis and Scientific Computing
Paolo Guasoni, Lesson II - 19 december 2017
QUANTITATIVE FINANCE SEMINARS @ SNS PROF. PAOLO GUASONI TOPICS IN PORTFOLIO CHOICE
From playlist Quantitative Finance Seminar @ SNS
Paolo Guasoni, Lesson I - 18 december 2017
QUANTITATIVE FINANCE SEMINARS @ SNS PROF. PAOLO GUASONI TOPICS IN PORTFOLIO CHOICE
From playlist Quantitative Finance Seminar @ SNS
Fifteenth SIAM Activity Group on FME Virtual Talk
Date: Thursday, December 10, 1PM-2PM Early Career Talks Speaker 1: Dena Firoozi, HEC Montréal - University of Montreal Title: Belief Estimation by Agents in Major-Minor LQG Mean Field Games Speaker 2: Sveinn Olafsson, Columbia University Title: Personalized Robo-Advising: Enhancing Inves
From playlist SIAM Activity Group on FME Virtual Talk Series
Paolo Guasoni, Lesson III - 20 december 2017
QUANTITATIVE FINANCE SEMINARS @ SNS PROF. PAOLO GUASONI TOPICS IN PORTFOLIO CHOICE
From playlist Quantitative Finance Seminar @ SNS
[T1 2022] Sebastian Schreiber - Coevolution of habitat choice in a stochastic world
Joint work with Alex Hening and Dang Nguyen. Species live and interact in patchy landscapes where environmental conditions vary both in time and space. In the face of this spatial-temporal heterogeneity, species may co-evolve how they select habitat patches. Under equilibrium conditions,
From playlist [T1 2022] Workshop - Mathematical models in ecology and evolution - March 21st to 25th, 2022
Fourteenth SIAM Activity Group on FME Virtual Talk
Speakers: Damir Filipovic, EPFL and Swiss Finance Institute Title: A Machine Learning Approach to Portfolio Pricing and Risk Management for High-Dimensional Problems Moderator: Rene Carmona, Princeton University
From playlist SIAM Activity Group on FME Virtual Talk Series
The coordination of centralised and distributed generation - René Aid, Univeristé Paris-Dauphine PSL
This workshop is kindly sponsored by London Mathematical Society, EPSRC and is part of the Lloyd's Register Foundation programme on Data-centric engineering at The Alan Turing Institute. The workshop "Mean-field games, energy and environment" aims to bring together leading experts in the f
From playlist Mean-field games, energy and environment
Elias Khalil - Neur2SP: Neural Two-Stage Stochastic Programming - IPAM at UCLA
Recorded 02 March 2023. Elias Khalil of the University of Toronto presents "Neur2SP: Neural Two-Stage Stochastic Programming" at IPAM's Artificial Intelligence and Discrete Optimization Workshop. Abstract: Stochastic Programming is a powerful modeling framework for decision-making under un
From playlist 2023 Artificial Intelligence and Discrete Optimization
8 2 Stochastic Volatility Part 2
BEM1105x Course Playlist - https://www.youtube.com/playlist?list=PL8_xPU5epJdfCxbRzxuchTfgOH1I2Ibht Produced in association with Caltech Academic Media Technologies. ©2020 California Institute of Technology
From playlist BEM1105x Course - Prof. Jakša Cvitanić
Dr Lukasz Szpruch, University of Edinburgh
Bio I am a Lecturer at the School of Mathematics, University of Edinburgh. Before moving to Scotland I was a Nomura Junior Research Fellow at the Institute of Mathematics, University of Oxford, and a member of Oxford-Man Institute for Quantitative Finance. I hold a Ph.D. in mathematics fr
From playlist Short Talks
6 1 Black Scholes Merton pricing Part 1
BEM1105x Course Playlist - https://www.youtube.com/playlist?list=PL8_xPU5epJdfCxbRzxuchTfgOH1I2Ibht Produced in association with Caltech Academic Media Technologies. ©2020 California Institute of Technology
From playlist BEM1105x Course - Prof. Jakša Cvitanić