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Tag: NumPy

Compare Stock Returns

Posted on June 1, 2025July 6, 2025 by Blake

This page lets you enter multiple stock tickers (eg. AAPL, MSFT, GOOGL) and even portfolio expressions (eg. 1.75*NVDA+2.5*AMZN+5.5*KO) and compare their returns visually against a benchmark (like SPY). It’s built with Python and Flask on the backend. Data comes from Yahoo Finance via the yfinance library, pandas crunches the numbers, and matplotlib generates the plots….

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TQQQ Trading Algorithm

Posted on August 21, 2024July 5, 2025 by Blake

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…

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Skyrim Alchemy Optimizer

Posted on June 10, 2024June 11, 2025 by Blake

This Jupyter notebook 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 you have with…

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Efficient Portfolio

Posted on December 7, 2020July 5, 2025 by Blake

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…

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Boolean Network Animation

Posted on November 19, 2020June 11, 2025 by Blake

This page 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. 🔗 network.blakerayvid.com View on GitHub

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Epidemic Simulator

Posted on April 19, 2020July 4, 2025 by Blake

This Jupyter notebook 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…

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D3.js Desmos Flask Gemini API JavaScript JQuery MATLAB Matplotlib Netlify NLTK NumPy P5.js Pandas PostgreSQL Python QuantConnect Railway Scikit-Learn SciPy Spacy TensorFlow YFinance

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