Pricing Options and Implied Volatility with Python In 2012, my first options trade lost $9,000. 12 months later I was making $1,100 per week trading in my free time. What...
Read moreReal-world datasets are important when building and testing machine learning models. You can test your model by establishing a benchmark or identifying its flaws using several data sets. You might...
Read moreAnalyzing Stock Data Near Events with Pandas Stock returns can be heavily impacted by certain events. Sometimes these events are unexpected or a surprise (natural disasters, global pandemics, terrorism) and...
Read moreIntroduction to Atomic Simulations by Metropolis Monte Carlo In this lecture, we review the theory behind Metropolis Monte Carlo modeling and apply these concepts to the simulations of atomic systems....
Read moreTime magazine’s Man of the Year 2021, Elon Musk. Could a trading strategy based on Elon Musk's tweets also be the driver of your most profitable investment strategy? It’s no...
Read moreRapidly build and deploy quantitative models for stocks, crypto, and forex Blankly is a live trading engine, backtest runner and development framework wrapped into one powerful open-source package. Models can...
Read moreAnalyzing intraday and overnight stock returns with pandas This paper discusses the contrast between overnight and intraday stock returns. In the paper, we learn that overnight stock returns far outpace returns seen...
Read moreGenerate stock charts in the terminal with tsock tstock is a tool to easily generate stock charts from the command line. Go to the code on GitHub
Read moreA Streamlit Dashboard for the Alpaca API Algo Trading Platform The Alpaca brokerage service is very useful for algorithmic traders that comes with an API to retrieve data and execute trades in...
Read moreDatasets, DataLoaders and PyTorch's New DataPipes PyTorch is an open source machine learning framework. It enables fast and efficient production through easy front-end training. It also has an ecosystem of...
Read moreAs a user, you get the predictions in your apps through an application you're already using. A problem software engineers face is deploying machine learning models into existing applications. PostgresML...
Read more8 Visualizations with Python to Handle Multiple Time-Series Data This article demonstrates 8 visualizations with Python to handle time-series data. A single-line time-series data or plot is a useful graph...
Read moreEconomic Data Analysis Project with Python Pandas - Data scraping, cleaning and exploration In this video, Kaggle grandmaster Rob Mulla takes you through an economic data analysis project with Python...
Read moreIn this blog, we’ll review how we took a raw .ipynb notebook that does time series forecasting with Arima, modularized it into a Ploomber pipeline, and ran parallel jobs on...
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