This project is a Stock Trader trained to trade stocks from the S&P 500. It was made using a Deep Q-Learning model and libraries such as TensorFlow, Keras, and OpenAI Gym. It was trained on data from 2006-2016, cross validated on data from 2016-2018, and tested on data from 2018-202...
Statistical Methods are part of the tools for analyzing securities. The following chapter explains the central limit theorem, returns, ranges, boxplots, histograms and other sets of statistical measures for the analysis of securities using Yahoo Finance API....
Python-Financial-Analysis-Algorithmic-Trading Data Visualization - using python with pandas and matplotlib libraries to read and display stocks data such as candle stick, volume display, EMA, SMA, Bollinger (upper & lower) and also portfolio optimization ChartVisualization: The user need to enter a...
Trading with Coinbase Pro (GDAX) API in Python Coinbase Pro (formerly known as GDAX) is one of the biggest cryptocurrency exchange, you can trade a large panel of cryptocurrencies against USD, EUR and GBP. I chose to trade on Coinbase Pro because it supports a lot of pairs and the liq...
Place orders for various instruments such as stocks, futures, options, and currencies. Track the status of your orders and your portfolio position in real time. Pros: Simplicity of use: IBridgePy makes it easier for developers and traders with different degrees of Python expertise to connect to...
In the realm of stock market prediction, a substantial amount of research has been focused on forecasting short-term movements using daily or sub-daily stock prices and trade volumes as features. However, the endeavor to predict long-term stock returns for specific stocks based on fundamental fina...
Learn how to apply cutting-edge machine learning techniques to trade options strategies and analyse the performance. Enroll now! File in the download Covered call strategy using Machine learning - Python notebook Login to Download Author: Chainika Thakar (Originally written by Varun Divakar) Note...
The node ‘Negative capital formation’ corresponds to the use of stocks from previous years that have not been replaced. It is possible for NCF to be positive for some sectors and negative for others. In some diagrams (such as Fig. 1), the node ‘Positive capital formation’ and ‘...
Today, it requires only a few mouse clicks to trade stocks, futures, and currencies. In this article, I’d like to give you an overview of algorithmic trading and provide a practical guide on how to start your algorithmic trading business. Algorithmic Trading A-Z with Python, Machine ...
Most commonly, students would use Python or Java to submit trades via REST. These languages require a significant amount of coding overhead that Excel would typically automatically handle for the student. For context, programming a simple two-stock arbitrage algorithm in VBA requires about 12 lines...