In this article I will show you the formulas to calculate daily, monthly, yearly and continuous compound interest by using examples and Python.
In this article I show how to pull in data for various stocks and simulate how dollar cost averaging would have performed over a custom time period using Python code.
In this blog post I’ve consolidated several resources to get you on your way with using Python to trade at Robinhood through the ‘Robinhood API’. Robinhood’s democratization of investing for small time investors has been a great boon for bringing complex investing tools to the masses.
When investing, we are bound by the limits of our own consciousness. Psychologists have studied numerous biases that limit our worldview and these extend into our investment decisions.
The Stock Market is cyclical. We are humans with emotions. Combining the two is an observable boom and bust of wild but predictable emotions.
An up to date collection of financial data sources for use with Machine Learning Models and Algorithmic Trading. CSVs, APIs, Python and R packages are included.
If you just happened upon a lump some of change then you have probably wondered if you should spend it, invest it, pay down debt or even give it away. I’ll go over a few good and bad ideas on how to spend your new found wealth.
In this article, I’ve compiled up to date viewpoints by famous and traditional investors or thought leaders. Assuming such people have more access to the industry, and/or its possible negative and positive aspects can be useful in trying to inform your own decision-making process.
Use Python Code to calculate the Compound Annual Growth Rate of various Stock Market Tickers giving you an accurate and timely comparison of performance.
To get an accurate measure of performance you should calculate the Compound Annual Growth Rate, also known simply as the CAGR. The CAGR will give you a number that fully reveals the performance of whatever you are measuring.