CS 7646 Project 1: Martingale (Report) Latest Update with complete solution
Project 1: Martingale (Report)
Start Assignment
• Due Jan 20 by 7am
• Points 100
• Submitting a file upload
• File Types pdf
• Available Jan 6 at 9am - Jan 20 at 7:15am
Instructions for Project 1: Martingale
This assignment is subject to change up until 3 weeks before the due
date. We do not anticipate changes; any changes will be logged in this
section.
1. Published - Start of Term
2. 01/09/25 - Added "(i.e., reach a maximum (or minimum) value
and then stabilize)" to Questions 3 and 6, for clarification.
In this course, you are building a simplified AI-based trading system.
This system is constructed over the course of 8 projects, where each
project you complete is a step towards building an intricate system
that synthesizes your knowledge of machine learning with practical
algorithmic trading strategies. For detailed context and an overview
of how each piece fits into the broader system, please refer to
the Machine Learning for Trading Project page.
, In this project, you will write software that will perform probabilistic
experiments involving an American Roulette wheelLinks to an
external site.. The project will help provide you with some initial feel
for risk, probability, and “betting.” Purchasing a stock is, after all, a
bet that the stock will increase (or, in some cases, decrease) in value.
You will submit the code for the project to Gradescope SUBMISSION.
You will also submit to Canvas a report that discusses your
experimental findings.
1.1 Learning Objectives
The specific learning objectives for this assignment are focused on the
following areas:
• Mathematical Tools: Developing an understanding of common
probabilistic and statistical tools associated with machine
learning, including expectations, standard deviations, sampling,
minimum values, maximum values, and convergence.
• Research: Experience researching additional material
(conceptual and programming) to ensure the successful
completion of the assignment.
• Programming & Academic Writing: Each assignment will
build upon one another. The techniques around
experimentation, graphs, interpretation (and so on) will play
important roles in this and future projects.
• Course Conduct: Developing and testing code locally in the
local Conda ml4t environment, submitting it for pre-validation in
the Gradescope TESTING environment, and submitting it for
grading in the Gradescope SUBMISSION environment.
In this project, you will build a Simple Gambling Simulator.
Specifically, you will revise the code in the martingale.py file to
simulate 1000 successive bets on the outcomes (i.e., spins) of the
American roulette wheel using the betting scheme outlined in the
pseudo-code below. Each series of 1000 successive bets is called an
Project 1: Martingale (Report)
Start Assignment
• Due Jan 20 by 7am
• Points 100
• Submitting a file upload
• File Types pdf
• Available Jan 6 at 9am - Jan 20 at 7:15am
Instructions for Project 1: Martingale
This assignment is subject to change up until 3 weeks before the due
date. We do not anticipate changes; any changes will be logged in this
section.
1. Published - Start of Term
2. 01/09/25 - Added "(i.e., reach a maximum (or minimum) value
and then stabilize)" to Questions 3 and 6, for clarification.
In this course, you are building a simplified AI-based trading system.
This system is constructed over the course of 8 projects, where each
project you complete is a step towards building an intricate system
that synthesizes your knowledge of machine learning with practical
algorithmic trading strategies. For detailed context and an overview
of how each piece fits into the broader system, please refer to
the Machine Learning for Trading Project page.
, In this project, you will write software that will perform probabilistic
experiments involving an American Roulette wheelLinks to an
external site.. The project will help provide you with some initial feel
for risk, probability, and “betting.” Purchasing a stock is, after all, a
bet that the stock will increase (or, in some cases, decrease) in value.
You will submit the code for the project to Gradescope SUBMISSION.
You will also submit to Canvas a report that discusses your
experimental findings.
1.1 Learning Objectives
The specific learning objectives for this assignment are focused on the
following areas:
• Mathematical Tools: Developing an understanding of common
probabilistic and statistical tools associated with machine
learning, including expectations, standard deviations, sampling,
minimum values, maximum values, and convergence.
• Research: Experience researching additional material
(conceptual and programming) to ensure the successful
completion of the assignment.
• Programming & Academic Writing: Each assignment will
build upon one another. The techniques around
experimentation, graphs, interpretation (and so on) will play
important roles in this and future projects.
• Course Conduct: Developing and testing code locally in the
local Conda ml4t environment, submitting it for pre-validation in
the Gradescope TESTING environment, and submitting it for
grading in the Gradescope SUBMISSION environment.
In this project, you will build a Simple Gambling Simulator.
Specifically, you will revise the code in the martingale.py file to
simulate 1000 successive bets on the outcomes (i.e., spins) of the
American roulette wheel using the betting scheme outlined in the
pseudo-code below. Each series of 1000 successive bets is called an
