What is the Monte Carlo method? | Monte Carlo Simulation in Finance | Pricing Options
In today's video we learn all about the Monte Carlo Method in Finance. These classes are all based on the book Trading and Pricing Financial Derivatives, available on Amazon at this link. https://amzn.to/2WIoAL0 Check out our website http://www.onfinance.org/ Follow Patrick on twitter h
From playlist Exotic Options & Structured Products
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
Monte Carlo Integration In Python For Noobs
Monte Carlo is probably one of the more straightforward methods of numerical Integration. It's not optimal if working with single-variable functions, but nonetheless is easy to use, and readily generalizes to multi-variable functions. In this video I motivate the method, then solve a one-d
From playlist Daily Uploads
Monte Carlo Simulation and Python
Monte Carlo Simulation with Python Playlist: http://www.youtube.com/watch?v=9M_KPXwnrlE&feature=share&list=PLQVvvaa0QuDdhOnp-FnVStDsALpYk2hk0 Here we bring at least the initial batch of tutorials to a close with the 3D plotting of our variables in search for preferable settings to use.
From playlist Monte Carlo Simulation with Python
Monte Carlo Simulation and Python 18 - 2D charting monte carlo variables
Monte Carlo Simulation with Python Playlist: http://www.youtube.com/watch?v=9M_KPXwnrlE&feature=share&list=PLQVvvaa0QuDdhOnp-FnVStDsALpYk2hk0 Here we use Matplotlib to chart a 2D representation of our variables and their relationship to profit. In the monte carlo simulation with Python
From playlist Monte Carlo Simulation with Python
Monte Carlo Simulation and Python 7 - More comparison
Monte Carlo Simulation with Python Playlist: http://www.youtube.com/watch?v=9M_KPXwnrlE&feature=share&list=PLQVvvaa0QuDdhOnp-FnVStDsALpYk2hk0 In the monte carlo simulation with Python series, we test various betting strategies. A simple 50/50 strategy, a martingale strategy, and the d'ale
From playlist Monte Carlo Simulation with Python
Monte Carlo Simulation and Python 11 - Using Monte Carlo to find best multiple
Monte Carlo Simulation with Python Playlist: http://www.youtube.com/watch?v=9M_KPXwnrlE&feature=share&list=PLQVvvaa0QuDdhOnp-FnVStDsALpYk2hk0 In this video, we employ our monte carlo simulator to help us locate the best possible multiple to use with our martingale strategy, curious if the
From playlist Monte Carlo Simulation with Python
Monte Carlo Simulation and Python 1 - Intro
Monte Carlo Simulation with Python Playlist: http://www.youtube.com/watch?v=9M_KPXwnrlE&feature=share&list=PLQVvvaa0QuDdhOnp-FnVStDsALpYk2hk0 In the monte carlo simulation with Python series, we test various betting strategies. A simple 50/50 strategy, a martingale strategy, and the d'ale
From playlist Monte Carlo Simulation with Python
Swap Monte Carlo Method and its Enormous Impact In the Study of Structural... by Smarajit Karmakar
DISCUSSION MEETING : CELEBRATING THE SCIENCE OF GIORGIO PARISI (ONLINE) ORGANIZERS : Chandan Dasgupta (ICTS-TIFR, India), Abhishek Dhar (ICTS-TIFR, India), Smarajit Karmakar (TIFR-Hyderabad, India) and Samriddhi Sankar Ray (ICTS-TIFR, India) DATE : 15 December 2021 to 17 December 2021 VE
From playlist Celebrating the Science of Giorgio Parisi (ONLINE)
Stanford CS234: Reinforcement Learning | Winter 2019 | Lecture 3 - Model-Free Policy Evaluation
For more information about Stanford’s Artificial Intelligence professional and graduate programs, visit: https://stanford.io/ai Professor Emma Brunskill, Stanford University https://stanford.io/3eJW8yT Professor Emma Brunskill Assistant Professor, Computer Science Stanford AI for Human
From playlist Stanford CS234: Reinforcement Learning | Winter 2019
Lecture 05: Temporal-Difference Learning
Fifth lecture video on the course "Reinforcement Learning" at Paderborn University during the summer term 2020. Source files are available here: https://github.com/upb-lea/reinforcement_learning_course_materials
From playlist Reinforcement Learning Course: Lectures (Summer 2020)
Iterative stochastic numerical methods for statistical sampling: Professor Ben Leimkuhler
I study the design, analysis and implementation of algorithms for time-dependent phenomena and modelling for problems in engineering and the sciences. My previous works have helped to establish the foundations of molecular simulation, providing efficient deterministic and stochastic numeri
From playlist Data science classes
Lecture 04: Monte Carlo Methods
Fourth lecture video on the course "Reinforcement Learning" at Paderborn University during the summer term 2020. Source files are available here: https://github.com/upb-lea/reinforcement_learning_course_materials
From playlist Reinforcement Learning Course: Lectures (Summer 2020)
Frank Noe - Advancing molecular simulation with deep learning - IPAM at UCLA
Recorded 23 January 2023. Frank Noe of Freie Universität Berlin presents "Advancing molecular simulation with deep learning" at IPAM's Learning and Emergence in Molecular Systems Workshop. Learn more online at: http://www.ipam.ucla.edu/programs/workshops/learning-and-emergence-in-molecular
From playlist 2023 Learning and Emergence in Molecular Systems
Measuring the configurational entropy in computer simulations (Lecture - 03) by Ludovic Berthier
Program Entropy, Information and Order in Soft Matter ORGANIZERS: Bulbul Chakraborty, Pinaki Chaudhuri, Chandan Dasgupta, Marjolein Dijkstra, Smarajit Karmakar, Vijaykumar Krishnamurthy, Jorge Kurchan, Madan Rao, Srikanth Sastry and Francesco Sciortino DATE: 27 August 2018 to 02 November
From playlist Entropy, Information and Order in Soft Matter
Classical Monte Carlo of Frustrated Systems (Tutorial) by Ludovic Jaubert
PROGRAM FRUSTRATED METALS AND INSULATORS (HYBRID) ORGANIZERS: Federico Becca (University of Trieste, Italy), Subhro Bhattacharjee (ICTS-TIFR, India), Yasir Iqbal (IIT Madras, India), Bella Lake (Helmholtz-Zentrum Berlin für Materialien und Energie, Germany), Yogesh Singh (IISER Mohali, In
From playlist FRUSTRATED METALS AND INSULATORS (HYBRID, 2022)
Manuel Athenes - Thermodynamic & transport properties of metal alloys: thermoelasticity & diffusion
Recorded 28 March 2023. Manuel Athenes of Commissariat à l'Énergie Atomique (CEA) - Centre d'Études Nucléaires de Saclay (CENS) presents "Conditioning schemes for accurately estimating thermodynamic and transport properties of metallic alloys: application to thermo-elasticity and elasto-di
From playlist 2023 Increasing the Length, Time, and Accuracy of Materials Modeling Using Exascale Computing
Monte Carlo Simulation and Python 12 - Checking Results
Monte Carlo Simulation with Python Playlist: http://www.youtube.com/watch?v=9M_KPXwnrlE&feature=share&list=PLQVvvaa0QuDdhOnp-FnVStDsALpYk2hk0 In the monte carlo simulation with Python series, we test various betting strategies. A simple 50/50 strategy, a martingale strategy, and the d'ale
From playlist Monte Carlo Simulation with Python
DeepMind's Richard Sutton - The Long-term of AI & Temporal-Difference Learning
Link to the slides: http://videolectures.net/site/normal_dl/tag=1137922/deeplearning2017_sutton_td_learning_01.pdf DeepMind announced in July, 2017 that Prof. Richard Sutton would be leading DeepMind Alberta. Richard S. Sutton is a Canadian computer scientist. Currently he is professor o
From playlist Talks