Trading Dashboard with Yfinance & Python.
To begin, let’s first understand the goal of this article, which is to provide the average retail investor with a quick and easy way to pull live data, use that data to highlight key indicators ...
Trading
Using Probabilistic Machine Learning to improve your Stock Trading
Probabilistic Machine Learning comes hand in hand with Stock Trading: Probabilistic Machine Learning uses past instances to predict probabilities of certain events happening in future instances. This can be directly applied to stock trading, to ...
Machine Learning for Day Trading
In this post, I’m going to explore machine learning algorithms for time-series analysis and explain why they don’t work for day trading. If you’re a novice in this field you might get fooled by authors ...
A Step-By-Step Guide To Building a Trading Bot In Any Programming Language
Pick Your Weapon of Choice and I’ll Show You How to Fight Source
Using Deep Learning to Create a Stock Trading Bot
There are so many articles on predicting stock prices, but this article provides two things to the reader, that no other article talks about: The use of confidence intervals in stock trading to determine stop-loss ...
Using Python to Download Sentiment Data for Financial Trading
Market sentiment is an extremely important part of trading. It allows us to understand the positioning of the players who potentially could move the markets. Knowing that the majority of hedge funds are bullish on ...
Stock Buy/Sell Prediction Using Convolutional Neural Network
This project is loosely based on a research paper titled “Algorithmic Financial Trading with Deep Convolutional Neural Networks: Time Series to Image Conversion Approach”. Source
Using TensorTrade for Making a Simple Trading Algorithm
In this tutorial, I’m going to show how to use Ray with TensorTrade (TT) in order to create a profitable algorithm on a predictable sine curve. You may be asking yourself, why use something so ...
Algorithmic Trading in Less than 100 Lines of Python Code
The barriers to entry for algorithmic trading have never been lower. Not too long ago, only institutional investors with IT budgets in the millions of dollars could take part, but today even individuals equipped only ...
Implementation of Technical Indicators into a Machine Learning framework for Quantitative Trading
Building an ML forecasting tool to predict stock price movement using Technical Indicators on S&P100 companies Source