Constructing a Killer Investment Portfolio with Python
As an investor, not only do you want to watch your investment grow, you want it to grow as much as possible. However, being far from a sure thing, an investment carries a certain degree ...
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Technical Indicators and GRU/LSTM to Predict Stock price
Predictive model using multivariate time-Series and Python Code Source
Predict Bitcoin Prices with Deep Learning
Use Neural Networks to Forecast Cryptocurrency Prices with Python Source
Portfolio Analysis Basics: Returns and Drawdowns
In this story, we are going to do some basic portfolio returns analysis in python. Source
A Time Series Anomaly Detection Model for All Types of Time Series
Imagine you own a website and sell your products online. Unfortunately, for your recent product release, you made a mistake and put a ridiculously low price for your products. You are a busy person, of ...
A Full Crypto Trading Bot in Python
The trading strategy doesn’t try to be optimal — that’s hard. It simply tries to buy at a low point, hold for a day or two until the price rises a bit, and then sell. ...
Outstanding Returns Using Sentiment Analysis to Predict Alphabet (Google) Stock Price
The goal of this article is to predict if the stock price for Alphabet (GOOGL) will be higher or lower at the end of any given day, using news from the closing time of the ...
Analysis of Stock Market Cycles with fbprophet package in Python
Stock market cycles are the long-term price patterns of stock markets and are often associated with general business cycles. They are key to technical analysis where the approach to investing is based on cycles or ...
Creating Bitcoin trading bot that could beat the market
In this tutorial, we will continue developing a Bitcoin trading bot, but this time instead of doing trades randomly, we’ll use the power of reinforcement learning. Source
AI for algorithmic trading: rethinking bars, labeling, and stationarity
In a series of articles I was applying a very straightforward approach to forecast financial time series: take the whole dataset, using a sliding window approach generate X and Y, split it into historical and ...