Monte Carlo/ˈmɒntiˈkɑːrloʊ/ (Italian pronunciation:[ˈmonte ˈkarlo]; French:Monte-Carlo or colloquially Monte-Carl, Monégasque: Monte-Carlu) officially refers to an administrative area of the Principality of Monaco, specifically the ward of Monte Carlo/Spélugues, where the Monte Carlo Casino is located. Informally the name also refers to a larger district, the Monte Carlo Quarter (corresponding to the former municipality of Monte Carlo), which besides Monte Carlo/Spélugues also includes the wards of La Rousse/Saint Roman, Larvotto/Bas Moulins, and Saint Michel. The permanent population of the ward of Monte Carlo is about 3,500, while that of the quarter is about 15,000. Monaco has four traditional quarters. From west to east they are: Fontvieille (the newest), Monaco-Ville (the oldest), La Condamine, and Monte Carlo.
Monte Carlo (literally "Mount Charles") is situated on a prominent escarpment at the base of the Maritime Alps along the French Riviera. Near the western end of the quarter is the world-famous Place du Casino, the gambling center which has made Monte Carlo "an international byword for the extravagant display and reckless dispersal of wealth". It is also the location of the Hôtel de Paris, the Café de Paris, and the Salle Garnier (the casino theatre which is the home of the Opéra de Monte-Carlo).
These biscuits are made with two oval shaped Golden Syrup, honey and coconut biscuits joined by a layer of vanilla flavoured cream covered with raspberry jam. At an average mass of 20.8 grams each, the Monte Carlo is the heaviest biscuit available in Arnott's Assorted Cream product.
Arnott's identified trans fatty acids as an important issue over a decade ago. They then took action to reduce the level of TFAs in their biscuits. They replaced the partially hydrogenated animal fats with vegetable oils. MSG is naturally present in many foods. Monte Carlo products contain added MSG and labels them as flavor enhancers. Arnott's uses sea salt derived from South Australia's evaporating seawater. Lecithin, which is present in Monte Carlo biscuits, comes from soybeans and is a very common emulsifier in many foods.
Countess Helene Mara is engaged to be married to Prince Otto Von Liebenheim but leaves him at the altar. She flees on a train to Monte Carlo and checks into a hotel. When she arrives at the casino a count named Rudolph Falliere takes a liking to her and poses as a hairdresser whom she hires and falls in love with but could not marry if he is a commoner. Her fiance later arrives and takes her to an opera and she sees Rudolph there in one of the expensive seats indicating he is too wealthy to be a hairdresser. When he reveals to her that he is a count, she realises she can marry him.
Monte Carlo is a motor yacht in the superyacht category. She was named after the Monte Carlo quarter of Monaco.
History
Monte Carlo was built by Amels in their Hakvoort shipyard in The Netherlands and launched in 1988. She was designed by Diana Yacht Design BV. She underwent an extensive refit in 1999 (including an interior refit designed by Dee Robinson), and lesser refits in 2004 and 2006.
Monte Carlo currently cruises the Mediterranean Sea in the Summer cruising season, and the Caribbean in the Winter cruising season, crossing the Atlantic Ocean twice each year.
Boat International Publications Authors, The Superyachts, Volume Eighteen. Kingston upon Thames, Boat International Publications (2004) ISBN 1-898524-66-1
Cayman Islands Shipping Registry, Certificate of British Registry, Official Number: 731192
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Monte Carlo Simulation, also known as the Monte Carlo Method or a multiple probability simulation, is a mathematical technique, which is used to estimate the possible outcomes of an uncertain event. Watch master inventor Martin Keen explain how Monte Carlo Simulation may be your closest thing to a time machine - or more simply - how it may be a way to look into the future for making business decisions.
#AI #Software #ITModernization #MonteCarloSimulation #lightboard #IBM
published: 08 Jul 2022
Monte Carlo Simulation
A Monte Carlo simulation is a randomly evolving simulation. In this video, I explain how this can be useful, with two fun examples of Monte Carlo simulations: The first model shows how pi can be determined with Monte Carlo sampling, and in the second part of the video we will take a look how animations can be rendered with Monte Carlo path tracing.
If you want to see another Monte Carlo simulation in action, check out this video:
https://youtu.be/PPWEmjnqsF8
If you want to support my channel, subscribing, liking and sharing is an amazing help. Thank you! :) If you feel like this video added value to your life and you want to support MarbleScience even more, please consider becoming a patron.
https://www.patreon.com/MarbleScience
Chapters:
00:00 What are Monte Carlo simulations?
01:01 de...
published: 08 Sep 2020
What Is Monte Carlo Simulation?
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Monte Carlo Simulation is one of the most famous and widely applied finance techniques. This is a tool that helps us deal with uncertainty in complex situations. It steps on the premise that one of the best ways to deal with multiple uncertain variables is to generate a large number of random observations for each of them and hence create a joint distribution regarding the different possible outcomes resulting from the combination of the random variables.
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published: 26 Nov 2020
6. Monte Carlo Simulation
MIT 6.0002 Introduction to Computational Thinking and Data Science, Fall 2016
View the complete course: http://ocw.mit.edu/6-0002F16
Instructor: John Guttag
Prof. Guttag discusses the Monte Carlo simulation, Roulette
License: Creative Commons BY-NC-SA
More information at http://ocw.mit.edu/terms
More courses at http://ocw.mit.edu
published: 19 May 2017
Monte Carlo Methods : Data Science Basics
Solving complex problems using simulations
0:00 Easy Example
4:50 Harder Example
13:32 Pros and Cons of MC
published: 06 Jan 2021
A Simple Solution for Really Hard Problems: Monte Carlo Simulation
Today's video provides a conceptual overview of Monte Carlo simulation, a powerful, intuitive method to solve challenging probability questions. And we get to see how we can use it to answer a realistic question in Python!
0:00 Monte Carlo Applications
0:22 Party Problem: What is The Chance You'll Make It?
1:16 Monte Carlo Conceptual Overview
3:00 Monte Carlo Simulation in Python: NumPy and matplotlib
5:02 Party Problem: What Should You Do?
You can access the dataset and Jupyter Notebook used to run these scripts, which includes proper commenting, at: https://github.com/RiskByNumbers/Monte-Carlo-Simulation-Video.
#montecarlosimulation #probability #datascience #python #numpy #tutorial #sampling
=====================
Hello, and welcome to RiskByNumbers!
I am a professor sharing educ...
published: 12 Oct 2023
Monte Carlo Simulations: Run 10,000 Simulations At Once
Run Monte Carlo simulations in Excel with this simple workaround.
Produced by Sara Silverstein
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published: 27 Jan 2015
What is a Monte Carlo Simulation?
Learn all the basics of Project Management, in a structured program: https://geni.us/PM_CoreCourses
A Monte Carlo Simulation is a way of assessing the level of risk across a whole project. So, while you may not need to use this powerful methodology, it's vital knowledge for any project manager.
The Monte Carlo technique takes its names from the random chances at the gaming tables of Monte Carlo.
We most often use it to assess schedule risk, but we can also use it for budget risk.
How it works
For each activity on the project, estimate a range of probabilities for different possible durations. The set of durations and your estimates of their probability is the “probability distribution” for the activity durations.
The distribution we often use is called the “Beta Function”. But ea...
published: 17 Sep 2020
Value at Risk (VaR) Explained: A Comprehensive Overview
Dive into the world of financial risk management with this comprehensive guide to Value at Risk (VaR). Ryan O'Connell, CFA, FRM, breaks down the concept of VaR and its critical role in quantifying potential losses in investment portfolios. Explore the three primary VaR calculation methods - Parametric, Historical, and Monte Carlo - each explained in detail to provide a well-rounded understanding of risk assessment techniques. Whether you're a finance professional, student, or investor, this video offers invaluable insights into VaR methodologies, empowering you to make more informed decisions in managing financial risk.
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published: 05 Nov 2024
Monte Carlo in Reinforcement Learning
Let's talk about how Monte Carlo methods can be used in reinforcement learning
RESOURCES
[1] Other Monte Carlo Video: https://www.youtube.com/watch?v=mECgLyCzTQU
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Monte Carlo Simulation, also known as the Monte Carlo Method or a multiple probability simulation, is a mathem...
Learn more about watsonx: https://ibm.biz/BdvxDh
Monte Carlo Simulation, also known as the Monte Carlo Method or a multiple probability simulation, is a mathematical technique, which is used to estimate the possible outcomes of an uncertain event. Watch master inventor Martin Keen explain how Monte Carlo Simulation may be your closest thing to a time machine - or more simply - how it may be a way to look into the future for making business decisions.
#AI #Software #ITModernization #MonteCarloSimulation #lightboard #IBM
Learn more about watsonx: https://ibm.biz/BdvxDh
Monte Carlo Simulation, also known as the Monte Carlo Method or a multiple probability simulation, is a mathematical technique, which is used to estimate the possible outcomes of an uncertain event. Watch master inventor Martin Keen explain how Monte Carlo Simulation may be your closest thing to a time machine - or more simply - how it may be a way to look into the future for making business decisions.
#AI #Software #ITModernization #MonteCarloSimulation #lightboard #IBM
A Monte Carlo simulation is a randomly evolving simulation. In this video, I explain how this can be useful, with two fun examples of Monte Carlo simulations: T...
A Monte Carlo simulation is a randomly evolving simulation. In this video, I explain how this can be useful, with two fun examples of Monte Carlo simulations: The first model shows how pi can be determined with Monte Carlo sampling, and in the second part of the video we will take a look how animations can be rendered with Monte Carlo path tracing.
If you want to see another Monte Carlo simulation in action, check out this video:
https://youtu.be/PPWEmjnqsF8
If you want to support my channel, subscribing, liking and sharing is an amazing help. Thank you! :) If you feel like this video added value to your life and you want to support MarbleScience even more, please consider becoming a patron.
https://www.patreon.com/MarbleScience
Chapters:
00:00 What are Monte Carlo simulations?
01:01 determine pi with Monte Carlo
03:01 analogy to study design
04:56 back to Monte Carlo
05:57 Monte Carlo path tracing
08:51 summary
There is also a text version of this video on my website:
https://marblescience.com/blog/monte-carlo-simulations/
You can also find me at:
https://www.instagram.com/marblescience/
A Monte Carlo simulation is a randomly evolving simulation. In this video, I explain how this can be useful, with two fun examples of Monte Carlo simulations: The first model shows how pi can be determined with Monte Carlo sampling, and in the second part of the video we will take a look how animations can be rendered with Monte Carlo path tracing.
If you want to see another Monte Carlo simulation in action, check out this video:
https://youtu.be/PPWEmjnqsF8
If you want to support my channel, subscribing, liking and sharing is an amazing help. Thank you! :) If you feel like this video added value to your life and you want to support MarbleScience even more, please consider becoming a patron.
https://www.patreon.com/MarbleScience
Chapters:
00:00 What are Monte Carlo simulations?
01:01 determine pi with Monte Carlo
03:01 analogy to study design
04:56 back to Monte Carlo
05:57 Monte Carlo path tracing
08:51 summary
There is also a text version of this video on my website:
https://marblescience.com/blog/monte-carlo-simulations/
You can also find me at:
https://www.instagram.com/marblescience/
👉🏻 Sign up for Our Complete Finance Training with 57% OFF: https://bit.ly/3Z684AS
Monte Carlo Simulation is one of the most famous and widely applied finance t...
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Monte Carlo Simulation is one of the most famous and widely applied finance techniques. This is a tool that helps us deal with uncertainty in complex situations. It steps on the premise that one of the best ways to deal with multiple uncertain variables is to generate a large number of random observations for each of them and hence create a joint distribution regarding the different possible outcomes resulting from the combination of the random variables.
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Monte Carlo Simulation is one of the most famous and widely applied finance techniques. This is a tool that helps us deal with uncertainty in complex situations. It steps on the premise that one of the best ways to deal with multiple uncertain variables is to generate a large number of random observations for each of them and hence create a joint distribution regarding the different possible outcomes resulting from the combination of the random variables.
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MIT 6.0002 Introduction to Computational Thinking and Data Science, Fall 2016
View the complete course: http://ocw.mit.edu/6-0002F16
Instructor: John Guttag
Pr...
MIT 6.0002 Introduction to Computational Thinking and Data Science, Fall 2016
View the complete course: http://ocw.mit.edu/6-0002F16
Instructor: John Guttag
Prof. Guttag discusses the Monte Carlo simulation, Roulette
License: Creative Commons BY-NC-SA
More information at http://ocw.mit.edu/terms
More courses at http://ocw.mit.edu
MIT 6.0002 Introduction to Computational Thinking and Data Science, Fall 2016
View the complete course: http://ocw.mit.edu/6-0002F16
Instructor: John Guttag
Prof. Guttag discusses the Monte Carlo simulation, Roulette
License: Creative Commons BY-NC-SA
More information at http://ocw.mit.edu/terms
More courses at http://ocw.mit.edu
Today's video provides a conceptual overview of Monte Carlo simulation, a powerful, intuitive method to solve challenging probability questions. And we get to s...
Today's video provides a conceptual overview of Monte Carlo simulation, a powerful, intuitive method to solve challenging probability questions. And we get to see how we can use it to answer a realistic question in Python!
0:00 Monte Carlo Applications
0:22 Party Problem: What is The Chance You'll Make It?
1:16 Monte Carlo Conceptual Overview
3:00 Monte Carlo Simulation in Python: NumPy and matplotlib
5:02 Party Problem: What Should You Do?
You can access the dataset and Jupyter Notebook used to run these scripts, which includes proper commenting, at: https://github.com/RiskByNumbers/Monte-Carlo-Simulation-Video.
#montecarlosimulation #probability #datascience #python #numpy #tutorial #sampling
=====================
Hello, and welcome to RiskByNumbers!
I am a professor sharing educational resources around probability, statistics, optimization methods, algorithms, and programming to a broad audience.
Outside of Youtube, you can currently find me in Vancouver, Canada at the University of British Columbia.
Thank you, and I look forward to seeing you in future videos!
Email: [email protected].
LinkedIn: https://www.linkedin.com/in/omar-swei/
Today's video provides a conceptual overview of Monte Carlo simulation, a powerful, intuitive method to solve challenging probability questions. And we get to see how we can use it to answer a realistic question in Python!
0:00 Monte Carlo Applications
0:22 Party Problem: What is The Chance You'll Make It?
1:16 Monte Carlo Conceptual Overview
3:00 Monte Carlo Simulation in Python: NumPy and matplotlib
5:02 Party Problem: What Should You Do?
You can access the dataset and Jupyter Notebook used to run these scripts, which includes proper commenting, at: https://github.com/RiskByNumbers/Monte-Carlo-Simulation-Video.
#montecarlosimulation #probability #datascience #python #numpy #tutorial #sampling
=====================
Hello, and welcome to RiskByNumbers!
I am a professor sharing educational resources around probability, statistics, optimization methods, algorithms, and programming to a broad audience.
Outside of Youtube, you can currently find me in Vancouver, Canada at the University of British Columbia.
Thank you, and I look forward to seeing you in future videos!
Email: [email protected].
LinkedIn: https://www.linkedin.com/in/omar-swei/
Run Monte Carlo simulations in Excel with this simple workaround.
Produced by Sara Silverstein
--------------------------------------------------
Follow BI V...
Run Monte Carlo simulations in Excel with this simple workaround.
Produced by Sara Silverstein
--------------------------------------------------
Follow BI Video on Twitter: http://bit.ly/1oS68Zs
Follow BI Video On Facebook: http://on.fb.me/1bkB8qg
Read more: http://www.businessinsider.com/
--------------------------------------------------
Business Insider is the fastest growing business news site in the US. Our mission: to tell you all you need to know about the big world around you. The BI Video team focuses on technology, strategy and science with an emphasis on unique storytelling and data that appeals to the next generation of leaders – the digital generation.
Run Monte Carlo simulations in Excel with this simple workaround.
Produced by Sara Silverstein
--------------------------------------------------
Follow BI Video on Twitter: http://bit.ly/1oS68Zs
Follow BI Video On Facebook: http://on.fb.me/1bkB8qg
Read more: http://www.businessinsider.com/
--------------------------------------------------
Business Insider is the fastest growing business news site in the US. Our mission: to tell you all you need to know about the big world around you. The BI Video team focuses on technology, strategy and science with an emphasis on unique storytelling and data that appeals to the next generation of leaders – the digital generation.
Learn all the basics of Project Management, in a structured program: https://geni.us/PM_CoreCourses
A Monte Carlo Simulation is a way of assessing the level of...
Learn all the basics of Project Management, in a structured program: https://geni.us/PM_CoreCourses
A Monte Carlo Simulation is a way of assessing the level of risk across a whole project. So, while you may not need to use this powerful methodology, it's vital knowledge for any project manager.
The Monte Carlo technique takes its names from the random chances at the gaming tables of Monte Carlo.
We most often use it to assess schedule risk, but we can also use it for budget risk.
How it works
For each activity on the project, estimate a range of probabilities for different possible durations. The set of durations and your estimates of their probability is the “probability distribution” for the activity durations.
The distribution we often use is called the “Beta Function”. But each task will have its own distribution of likelihoods of duration; some simple, some complex. Each will apply to different types of activity.
The Monte Carlo method calculates how long the total project will take, by adding up the durations of all of the activities each with a duration randomly assigned. The probability of each task’s duration is defined by the probability function in our curve. To simulate the random nature, the Monte Carlo simulation repeats the calculation, with a different set of random durations many, many times. This gives a distribution of all of the possible total project durations.
Monte Carlo is more than just a calculation
The calculation is the easy part. Making the estimates of the probability distribution for each task is time-consuming. The quality of the estimates you make will entirely determine the validity of the resulting distribution. If all that you do is use the same distribution for each activity, you will simply reproduce that pattern for the whole project.
There is another flaw in the Monte Carlo method, which renders its results less reliable than you might think. It contains the assumption that the probability distribution for each task is independent of all others.
Yet we know that a delay in one activity can often make others more likely to be delayed too. And, also, that one event can affect multiple tasks. As in all risk management, the strides towards rigor have only got us so far. There is no substitute for good judgment, and appropriate skepticism and caution.
Recommended Videos.
Carefully curated video recommendations for you:
- What is Project Risk Management?
... https://youtu.be/QgALrPHrsk4
- Project Risk Management - How to Manage Project Risk
... https://youtu.be/xXV_gjtXMSk
- Risk Management - 5 Tips to do it right
... https://youtu.be/Q6JHsVEOVhM
- What to Put in Your Risk Register (Risk Log)
... https://youtu.be/vkEPGFVVwfM
- What is Risk Tolerance?
... https://youtu.be/2WJA1I4lPls
My basic introductory book to Project Management is How to Manage a Great Project (published by Pearson): https://geni.us/4Iz6M (affiliated link).
For more great Project Management videos, please subscribe to this channel: https://www.youtube.com/channel/UCMZfp1_wquyegVY9SoER0Nw?sub_confirmation=1
For all our great Project Management articles and resources, please check out the OnlinePMCourses website: https://onlinepmcourses.com/
For basic Management Courses - free training hosted on YouTube, with 2 new management lessons a week, check out our sister channel, Management Courses: http://youtube.com/c/managementcourses
For more of our Project Management videos in themed collections, join our Free Academy of Project Management: https://onlinepmcourses.com/free-academy-of-project-management/
#Project #ProjectManagement #MonteCarlo
Learn all the basics of Project Management, in a structured program: https://geni.us/PM_CoreCourses
A Monte Carlo Simulation is a way of assessing the level of risk across a whole project. So, while you may not need to use this powerful methodology, it's vital knowledge for any project manager.
The Monte Carlo technique takes its names from the random chances at the gaming tables of Monte Carlo.
We most often use it to assess schedule risk, but we can also use it for budget risk.
How it works
For each activity on the project, estimate a range of probabilities for different possible durations. The set of durations and your estimates of their probability is the “probability distribution” for the activity durations.
The distribution we often use is called the “Beta Function”. But each task will have its own distribution of likelihoods of duration; some simple, some complex. Each will apply to different types of activity.
The Monte Carlo method calculates how long the total project will take, by adding up the durations of all of the activities each with a duration randomly assigned. The probability of each task’s duration is defined by the probability function in our curve. To simulate the random nature, the Monte Carlo simulation repeats the calculation, with a different set of random durations many, many times. This gives a distribution of all of the possible total project durations.
Monte Carlo is more than just a calculation
The calculation is the easy part. Making the estimates of the probability distribution for each task is time-consuming. The quality of the estimates you make will entirely determine the validity of the resulting distribution. If all that you do is use the same distribution for each activity, you will simply reproduce that pattern for the whole project.
There is another flaw in the Monte Carlo method, which renders its results less reliable than you might think. It contains the assumption that the probability distribution for each task is independent of all others.
Yet we know that a delay in one activity can often make others more likely to be delayed too. And, also, that one event can affect multiple tasks. As in all risk management, the strides towards rigor have only got us so far. There is no substitute for good judgment, and appropriate skepticism and caution.
Recommended Videos.
Carefully curated video recommendations for you:
- What is Project Risk Management?
... https://youtu.be/QgALrPHrsk4
- Project Risk Management - How to Manage Project Risk
... https://youtu.be/xXV_gjtXMSk
- Risk Management - 5 Tips to do it right
... https://youtu.be/Q6JHsVEOVhM
- What to Put in Your Risk Register (Risk Log)
... https://youtu.be/vkEPGFVVwfM
- What is Risk Tolerance?
... https://youtu.be/2WJA1I4lPls
My basic introductory book to Project Management is How to Manage a Great Project (published by Pearson): https://geni.us/4Iz6M (affiliated link).
For more great Project Management videos, please subscribe to this channel: https://www.youtube.com/channel/UCMZfp1_wquyegVY9SoER0Nw?sub_confirmation=1
For all our great Project Management articles and resources, please check out the OnlinePMCourses website: https://onlinepmcourses.com/
For basic Management Courses - free training hosted on YouTube, with 2 new management lessons a week, check out our sister channel, Management Courses: http://youtube.com/c/managementcourses
For more of our Project Management videos in themed collections, join our Free Academy of Project Management: https://onlinepmcourses.com/free-academy-of-project-management/
#Project #ProjectManagement #MonteCarlo
Dive into the world of financial risk management with this comprehensive guide to Value at Risk (VaR). Ryan O'Connell, CFA, FRM, breaks down the concept of VaR ...
Dive into the world of financial risk management with this comprehensive guide to Value at Risk (VaR). Ryan O'Connell, CFA, FRM, breaks down the concept of VaR and its critical role in quantifying potential losses in investment portfolios. Explore the three primary VaR calculation methods - Parametric, Historical, and Monte Carlo - each explained in detail to provide a well-rounded understanding of risk assessment techniques. Whether you're a finance professional, student, or investor, this video offers invaluable insights into VaR methodologies, empowering you to make more informed decisions in managing financial risk.
🔑 Join this channel to get access to perks & support my work:
https://www.youtube.com/channel/UCAkyj2N9kd0HtKhCrejsYWQ/join
🎓 Tutor With Me: 1-On-1 Video Call Sessions Available
► Join me for personalized finance tutoring tailored to your goals: https://www.ryanoconnellfinance.com/finance-tutoring/
Chapters:
0:00 - Value at Risk (VaR) Explained
0:45 - The Parametric Method
4:36 - The Historical Method
6:16 - The Monte Carlo Method
*Disclosure: This is not financial advice and should not be taken as such. The information contained in this video is an opinion. Some of the information could be wrong. This channel is owned and operated by Portfolio Constructs LLC. Some of the links above are affiliate links, meaning, at no additional cost to you, I will earn a commission if you click through and make a purchase.
Dive into the world of financial risk management with this comprehensive guide to Value at Risk (VaR). Ryan O'Connell, CFA, FRM, breaks down the concept of VaR and its critical role in quantifying potential losses in investment portfolios. Explore the three primary VaR calculation methods - Parametric, Historical, and Monte Carlo - each explained in detail to provide a well-rounded understanding of risk assessment techniques. Whether you're a finance professional, student, or investor, this video offers invaluable insights into VaR methodologies, empowering you to make more informed decisions in managing financial risk.
🔑 Join this channel to get access to perks & support my work:
https://www.youtube.com/channel/UCAkyj2N9kd0HtKhCrejsYWQ/join
🎓 Tutor With Me: 1-On-1 Video Call Sessions Available
► Join me for personalized finance tutoring tailored to your goals: https://www.ryanoconnellfinance.com/finance-tutoring/
Chapters:
0:00 - Value at Risk (VaR) Explained
0:45 - The Parametric Method
4:36 - The Historical Method
6:16 - The Monte Carlo Method
*Disclosure: This is not financial advice and should not be taken as such. The information contained in this video is an opinion. Some of the information could be wrong. This channel is owned and operated by Portfolio Constructs LLC. Some of the links above are affiliate links, meaning, at no additional cost to you, I will earn a commission if you click through and make a purchase.
Let's talk about how Monte Carlo methods can be used in reinforcement learning
RESOURCES
[1] Other Monte Carlo Video: https://www.youtube.com/watch?v=mECgLyCzT...
Let's talk about how Monte Carlo methods can be used in reinforcement learning
RESOURCES
[1] Other Monte Carlo Video: https://www.youtube.com/watch?v=mECgLyCzTQU
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Let's talk about how Monte Carlo methods can be used in reinforcement learning
RESOURCES
[1] Other Monte Carlo Video: https://www.youtube.com/watch?v=mECgLyCzTQU
PLAYLISTS FROM MY CHANNEL
⭕ Reinforcement Learning: https://youtube.com/playlist?list=PLTl9hO2Oobd9kS--NgVz0EPNyEmygV1Ha&si=AuThDZJwG19cgTA8
Natural Language Processing: https://youtube.com/playlist?list=PLTl9hO2Oobd_bzXUpzKMKA3liq2kj6LfE&si=LsVy8RDPu8jeO-cc
⭕ Transformers from Scratch: https://youtube.com/playlist?list=PLTl9hO2Oobd_bzXUpzKMKA3liq2kj6LfE
⭕ ChatGPT Playlist: https://youtube.com/playlist?list=PLTl9hO2Oobd9coYT6XsTraTBo4pL1j4HJ
⭕ Convolutional Neural Networks: https://youtube.com/playlist?list=PLTl9hO2Oobd9U0XHz62Lw6EgIMkQpfz74
⭕ The Math You Should Know : https://youtube.com/playlist?list=PLTl9hO2Oobd-_5sGLnbgE8Poer1Xjzz4h
⭕ Probability Theory for Machine Learning: https://youtube.com/playlist?list=PLTl9hO2Oobd9bPcq0fj91Jgk_-h1H_W3V
⭕ Coding Machine Learning: https://youtube.com/playlist?list=PLTl9hO2Oobd82vcsOnvCNzxrZOlrz3RiD
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Learn more about watsonx: https://ibm.biz/BdvxDh
Monte Carlo Simulation, also known as the Monte Carlo Method or a multiple probability simulation, is a mathematical technique, which is used to estimate the possible outcomes of an uncertain event. Watch master inventor Martin Keen explain how Monte Carlo Simulation may be your closest thing to a time machine - or more simply - how it may be a way to look into the future for making business decisions.
#AI #Software #ITModernization #MonteCarloSimulation #lightboard #IBM
A Monte Carlo simulation is a randomly evolving simulation. In this video, I explain how this can be useful, with two fun examples of Monte Carlo simulations: The first model shows how pi can be determined with Monte Carlo sampling, and in the second part of the video we will take a look how animations can be rendered with Monte Carlo path tracing.
If you want to see another Monte Carlo simulation in action, check out this video:
https://youtu.be/PPWEmjnqsF8
If you want to support my channel, subscribing, liking and sharing is an amazing help. Thank you! :) If you feel like this video added value to your life and you want to support MarbleScience even more, please consider becoming a patron.
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Chapters:
00:00 What are Monte Carlo simulations?
01:01 determine pi with Monte Carlo
03:01 analogy to study design
04:56 back to Monte Carlo
05:57 Monte Carlo path tracing
08:51 summary
There is also a text version of this video on my website:
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Monte Carlo Simulation is one of the most famous and widely applied finance techniques. This is a tool that helps us deal with uncertainty in complex situations. It steps on the premise that one of the best ways to deal with multiple uncertain variables is to generate a large number of random observations for each of them and hence create a joint distribution regarding the different possible outcomes resulting from the combination of the random variables.
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MIT 6.0002 Introduction to Computational Thinking and Data Science, Fall 2016
View the complete course: http://ocw.mit.edu/6-0002F16
Instructor: John Guttag
Prof. Guttag discusses the Monte Carlo simulation, Roulette
License: Creative Commons BY-NC-SA
More information at http://ocw.mit.edu/terms
More courses at http://ocw.mit.edu
Today's video provides a conceptual overview of Monte Carlo simulation, a powerful, intuitive method to solve challenging probability questions. And we get to see how we can use it to answer a realistic question in Python!
0:00 Monte Carlo Applications
0:22 Party Problem: What is The Chance You'll Make It?
1:16 Monte Carlo Conceptual Overview
3:00 Monte Carlo Simulation in Python: NumPy and matplotlib
5:02 Party Problem: What Should You Do?
You can access the dataset and Jupyter Notebook used to run these scripts, which includes proper commenting, at: https://github.com/RiskByNumbers/Monte-Carlo-Simulation-Video.
#montecarlosimulation #probability #datascience #python #numpy #tutorial #sampling
=====================
Hello, and welcome to RiskByNumbers!
I am a professor sharing educational resources around probability, statistics, optimization methods, algorithms, and programming to a broad audience.
Outside of Youtube, you can currently find me in Vancouver, Canada at the University of British Columbia.
Thank you, and I look forward to seeing you in future videos!
Email: [email protected].
LinkedIn: https://www.linkedin.com/in/omar-swei/
Run Monte Carlo simulations in Excel with this simple workaround.
Produced by Sara Silverstein
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Learn all the basics of Project Management, in a structured program: https://geni.us/PM_CoreCourses
A Monte Carlo Simulation is a way of assessing the level of risk across a whole project. So, while you may not need to use this powerful methodology, it's vital knowledge for any project manager.
The Monte Carlo technique takes its names from the random chances at the gaming tables of Monte Carlo.
We most often use it to assess schedule risk, but we can also use it for budget risk.
How it works
For each activity on the project, estimate a range of probabilities for different possible durations. The set of durations and your estimates of their probability is the “probability distribution” for the activity durations.
The distribution we often use is called the “Beta Function”. But each task will have its own distribution of likelihoods of duration; some simple, some complex. Each will apply to different types of activity.
The Monte Carlo method calculates how long the total project will take, by adding up the durations of all of the activities each with a duration randomly assigned. The probability of each task’s duration is defined by the probability function in our curve. To simulate the random nature, the Monte Carlo simulation repeats the calculation, with a different set of random durations many, many times. This gives a distribution of all of the possible total project durations.
Monte Carlo is more than just a calculation
The calculation is the easy part. Making the estimates of the probability distribution for each task is time-consuming. The quality of the estimates you make will entirely determine the validity of the resulting distribution. If all that you do is use the same distribution for each activity, you will simply reproduce that pattern for the whole project.
There is another flaw in the Monte Carlo method, which renders its results less reliable than you might think. It contains the assumption that the probability distribution for each task is independent of all others.
Yet we know that a delay in one activity can often make others more likely to be delayed too. And, also, that one event can affect multiple tasks. As in all risk management, the strides towards rigor have only got us so far. There is no substitute for good judgment, and appropriate skepticism and caution.
Recommended Videos.
Carefully curated video recommendations for you:
- What is Project Risk Management?
... https://youtu.be/QgALrPHrsk4
- Project Risk Management - How to Manage Project Risk
... https://youtu.be/xXV_gjtXMSk
- Risk Management - 5 Tips to do it right
... https://youtu.be/Q6JHsVEOVhM
- What to Put in Your Risk Register (Risk Log)
... https://youtu.be/vkEPGFVVwfM
- What is Risk Tolerance?
... https://youtu.be/2WJA1I4lPls
My basic introductory book to Project Management is How to Manage a Great Project (published by Pearson): https://geni.us/4Iz6M (affiliated link).
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#Project #ProjectManagement #MonteCarlo
Dive into the world of financial risk management with this comprehensive guide to Value at Risk (VaR). Ryan O'Connell, CFA, FRM, breaks down the concept of VaR and its critical role in quantifying potential losses in investment portfolios. Explore the three primary VaR calculation methods - Parametric, Historical, and Monte Carlo - each explained in detail to provide a well-rounded understanding of risk assessment techniques. Whether you're a finance professional, student, or investor, this video offers invaluable insights into VaR methodologies, empowering you to make more informed decisions in managing financial risk.
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Chapters:
0:00 - Value at Risk (VaR) Explained
0:45 - The Parametric Method
4:36 - The Historical Method
6:16 - The Monte Carlo Method
*Disclosure: This is not financial advice and should not be taken as such. The information contained in this video is an opinion. Some of the information could be wrong. This channel is owned and operated by Portfolio Constructs LLC. Some of the links above are affiliate links, meaning, at no additional cost to you, I will earn a commission if you click through and make a purchase.
Let's talk about how Monte Carlo methods can be used in reinforcement learning
RESOURCES
[1] Other Monte Carlo Video: https://www.youtube.com/watch?v=mECgLyCzTQU
PLAYLISTS FROM MY CHANNEL
⭕ Reinforcement Learning: https://youtube.com/playlist?list=PLTl9hO2Oobd9kS--NgVz0EPNyEmygV1Ha&si=AuThDZJwG19cgTA8
Natural Language Processing: https://youtube.com/playlist?list=PLTl9hO2Oobd_bzXUpzKMKA3liq2kj6LfE&si=LsVy8RDPu8jeO-cc
⭕ Transformers from Scratch: https://youtube.com/playlist?list=PLTl9hO2Oobd_bzXUpzKMKA3liq2kj6LfE
⭕ ChatGPT Playlist: https://youtube.com/playlist?list=PLTl9hO2Oobd9coYT6XsTraTBo4pL1j4HJ
⭕ Convolutional Neural Networks: https://youtube.com/playlist?list=PLTl9hO2Oobd9U0XHz62Lw6EgIMkQpfz74
⭕ The Math You Should Know : https://youtube.com/playlist?list=PLTl9hO2Oobd-_5sGLnbgE8Poer1Xjzz4h
⭕ Probability Theory for Machine Learning: https://youtube.com/playlist?list=PLTl9hO2Oobd9bPcq0fj91Jgk_-h1H_W3V
⭕ Coding Machine Learning: https://youtube.com/playlist?list=PLTl9hO2Oobd82vcsOnvCNzxrZOlrz3RiD
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Monte Carlo/ˈmɒntiˈkɑːrloʊ/ (Italian pronunciation:[ˈmonte ˈkarlo]; French:Monte-Carlo or colloquially Monte-Carl, Monégasque: Monte-Carlu) officially refers to an administrative area of the Principality of Monaco, specifically the ward of Monte Carlo/Spélugues, where the Monte Carlo Casino is located. Informally the name also refers to a larger district, the Monte Carlo Quarter (corresponding to the former municipality of Monte Carlo), which besides Monte Carlo/Spélugues also includes the wards of La Rousse/Saint Roman, Larvotto/Bas Moulins, and Saint Michel. The permanent population of the ward of Monte Carlo is about 3,500, while that of the quarter is about 15,000. Monaco has four traditional quarters. From west to east they are: Fontvieille (the newest), Monaco-Ville (the oldest), La Condamine, and Monte Carlo.
Monte Carlo (literally "Mount Charles") is situated on a prominent escarpment at the base of the Maritime Alps along the French Riviera. Near the western end of the quarter is the world-famous Place du Casino, the gambling center which has made Monte Carlo "an international byword for the extravagant display and reckless dispersal of wealth". It is also the location of the Hôtel de Paris, the Café de Paris, and the Salle Garnier (the casino theatre which is the home of the Opéra de Monte-Carlo).
Monte Carlo Monte Carlo Paradies wie bist du schön. Welche Wonne wenn die Sonne und der Sommer nie vergeh'n. Wo die Liebe lacht und feiert nur das Glück alleine zählt Monte Carlo Monte Carlo dahin fährt die ganze Welt dahin fährt die ganze Welt. Wenn Mimosen und Jasmin im Sonnenschein erblüh'n und die Rosen wie Rubin aus allen Gärten blüh'n zähl' auch ich ganz insgeheim die Groschen und pack ein dann verschließ' ich meine Tür und fahr an die Cote D'azur. Monte Carlo Monte Carlo . . . Ich brauch' Sommer und das Meer vom Glück den kleinen Hauch weiße Boote lieb' ich sehr schöne Mädchen auch. Meine Träume die ich hab' geh'n vielleicht sehr schnell vorbei doch was soll's die nächste Nacht liebes Mädchen bin ich frei. Monte Carlo Monte Carlo . . .