Developing a successful trading algorithm is about finding the right balance between capturing market gains and managing risks. In this capstone project for the Flatiron School Data Science Bootcamp, I created and refined a QuantConnect trading algorithm that combines a dynamic strategy for SPY with a risk-managed approach for TQQQ. The goal was to optimize…
Tag: Python
Tweet Sentiment Classifier
https://github.com/brayvid/tweet-sentiment-classifier My Flatiron School Data Science Bootcamp Phase 3 Project was to address the business problem of brand reputation management by monitoring and analyzing Twitter sentiment. The goal was to develop a machine learning model that can correctly classify tweets as positive, negative, or neutral, and provide insights to improve brand perception and engagement strategies….
Space Debris Exploration
This is an exploratory data analysis of a Kaggle dataset made as part of the Flatiron School Data Science Bootcamp. The slides from an associated presentation I gave are available here. https://github.com/brayvid/space-debris-eda
Skyrim Alchemy Optimizer
This is a Colab notebook which can be used to maximize alchemy profitability using the ingredients you have on hand in The Elder Scrolls V: Skyrim. It uses integer linear programming from scipy.optimize.milp to determine which potions to make, and in what quantities, to maximize total value. It needs a csv file of the ingredients…
Efficient Portfolio Construction
This is a Python implementation of Robert C. Merton’s efficient or minimum-variance portfolio algorithm from the paper An Analytic Derivation of the Efficient Portfolio Frontier (1972). Building on the work of Harry Markowitz, Merton describes a way to assign weights to a list of securities to make a portfolio that has the lowest variance in…
Boolean Network Animation
This Streamlit app animates the dynamics of a random boolean network, a collection of interconnected binary variables with a rule for determining the next state from the current one. https://github.com/brayvid/boolean-network
Epidemic Simulator
Simulates a disease spreading through a community in random motion. Individuals are represented as points undergoing independent random walks in a bounded 2D environment. Parameters include: the population size, the average population density, the number of times to evolve the system, the number of trials to conduct, and the fraction of the available space that…