Recently I’ve been reading Benoit Mandelbrot’s book The (Mis)Behavior of Markets: A Fractal View of Financial Turbulence. Early in this book Mandelbrot discusses one major issue with the underlying assumption of certain financial simulations. In particular,…
Trading Trends with Bollinger Bands
Determining the trend of a stock price is very powerful when devising a technical trading system. If we are able to determine when a trend is reversing, that is reaching a top or a bottom,…
Improving the Results and Efficiency of My Options Trading GA
In a previous post, I wrote about a genetic algorithm (GA) whose goal is to find stocks that could potentially create a promising put-selling portfolio. Currently, the GA searches through stocks that offer weekly options…
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Cluster Monitoring in Python with Glances
Some years ago my wife bought me a few (6) Raspberry Pi 3 B+ single board computers for Christmas so that I could experiment with creating and managing clusters of computers (it’s what I’d asked…
Finding (Potentially) Undervalued Stocks in the Stock Market
In a previous post, I wrote about finding undervalued sectors in the stock market by determining the divergence of the sector from some representation of the market itself. This post was intended to be a…
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Using Genetic Algorithms to Efficiently Trade the Wheel (Python)
The wheel is a loss-limited option selling strategy that is very effective at generating income in a portfolio. Typically when trading the wheel, stocks with weekly options are preferred since they fetch higher premiums (percentage-wise)…
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A Primer on Latin Squares With Some Research Objectives
Deviating from my usual content, in this post I’m going to provide some necessary knowledge for working with a combinatorial object known as a Latin square. These objects were the centerpiece of my (IMO poorly…
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Building Machine Learning Ensembles in Python
Ensemble learning is a process used in deep learning wherein multiple models, or experts or classifiers, are combined in an ensemble to improve forecasting results. Each individual model in the ensemble, once trained, produces a…
Finding Undervalued Sectors in the Stock Market
For an investor making investment decisions based on the underlying fundamentals of a company, i.e. fundamental analysis, finding companies to buy can be a daunting task. With ~3,600 publically listed companies in the United States…
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Building Redundancy Into Data Gathering for My Stock Data API
In a previous post, I wrote about an API I have created to retrieve data for stocks belonging to the Russell 2000 and S&P 500 indexes. One glaringly obvious issue with the data-gathering techniques discussed…
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