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…
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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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Creating a Database with an API (Stock Price Data)
NOTE: because I live in Montana (and was too lazy to deal with time zones) the data stored in this database (therefore, the dates and times passed to the API endpoints) are recorded in Mountain…
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Improving GBM Stock Path Generation With Exponentially Weighted Statistics
In a recent post, I wrote about using Monte Carlo simulations to determine the likelihood of a stock option being profitable by generating multiple paths using Geometric Brownian Motion (GBM) and computing some statistics of…
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Retrieving Historical Stock Data in C++
Examples abound of multiple different ways to retrieve historical stock data in Python using many different sources. I have personally written about an API I created which downloads the data from Yahoo Finance and have…
Simulating Stock Prices Using Geometric Brownian Motion
Disclaimer: This project/post is for fun/education please don’t use the results of this project to make investment decisions. If you chose to ignore this disclaimer and do just that I am not responsible for the (very…
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DataTables: A C++ Tabular Data Structure Project
This project’s GitHub can be found here. Quick-Nav: Implementation, Installation, Examples, Future Work For statistical programming languages or languages with good statistics processing libraries, the DataFrame is an essential structure. Most features of these languages…
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Time Series Forecasting: The Most Basic Models
What is Time Series Forecasting? A time series is a collection of observations made sequentially through time, e.g. the value of a company’s stock. Time series forecasting is the practice of making predictions based on…
A MACD Implementation in Python From Scratch
Disclaimer: This post is for entertainment/educational purposes only. The content of this post is not meant to provide investment advice or to help with investment decision making. QUICK-NAV:– MACD– Implementation– Full Code Moving Average Convergence…