Creating a ‘Trading Sentiment Analyzer’ in Python

How to develop a program in Python that can analyze the sentiment of any trading instrument.

Market Analysis and Data Cleaning with Python

Learn how to import a CSV file and plot S&P data by Market Cap

Monte Carlo Simulations for Predicting American Stock Prices

In this article we are interested in explaining how we can establish a maximum and minimum price for any asset (in this case we will work on American equities) with a certain probability.

Mr. Market has Already Prophesied How the Post-Covid World Will Look Like

Mr. Market has Already Prophesied How the Post-Covid World Will Look Like. The market knows it all, and it has prepared itself for the post-Covid world using millions of data points, Have you?

Trading With Moving Averages -  SMA’s & EMA’s

Entering the realm of technical indicators, it’s easy to get lost in the jargon and the countless techniques available. As an introduction, we’re starting with the oldest and most widely used technical indicator. It also just happens to be the simplest - the moving average. 

How To Use Reduce To Merge Stock Data in Python

How To Use Reduce To Merge Stock Data in Python - If you just started using Python to analyze historical stock prices with the aim of visualizing trends and build investment strategies, or if you are a more experienced coder tired to use loops, you should stick around and learn how to improve your scripts with the reduce() function.

Algorithmic Trading with Technical Indicators in R

In this post I will walk you gently to build your algorithmic trading code in R. R has several powerful quantitative finance libraries because of its long development history including Quantmod, TTR, PerformanceAnalytics.

Future Prediction of Call and Put Prices using Deep Learning by generating data

In this blog, I will demonstrate the prediction for AMD by taking few other company stock price data. Please note that for future dates we will not get any data related to news polarity(.i.e fundamental data) we will only make predictions by using technical data.

3 Basic Steps of Stock Market Analysis in Python

In this article you will learn: the easiest way to get the stock data in Python; what are trading indicators and how to calculate them; how to plot the stock data with OHLC chart

Characterising Companies Based on Financial Metrics During Covid19

Characterising Companies Based on Financial Metrics During Covid19. Here, we will dive deep at the first 5 PCs/factors and their respective underlying features.

SaaS Revenue Multiples, Interest Rates, and Modeling in R

SaaS Revenue Multiples, Interest Rates, and Modeling in R. 6 Simple Steps to Prove that Interest Rates don't Fully Explain SaaS Valuation.

Creating Trading Strategies and Backtesting With R

Create fully functional trading strategies using technical indicators and backtest the results with R and its powerful libraries. In this article, we are going to create six trading strategies and backtest its results using R and its powerful libraries.

Stock Market and Python

Stocker is a Python class-based tool used for stock prediction and analysis. (for complete code refer GitHub) Stocker is designed to be very easy to handle.

Reinforcement Learning V.S Supervised Learning in Financial Markets

Reinforcement Learning V.S Supervised Learning in Financial Markets. My opinion on why Reinforcement Learning is superior to Supervised Learning when it comes to Financial Markets.

Downloading historical stock prices in Python

We will be looking at a quick and automated way to download the historical stock prices in Python. This article will cover creating the analytical dataset to aid in analyzing the stock market.

The Science of Portfolio Optimization

How to use Data Science to {re}allocate investments. I decided to implement some products, including pricing estimators, algorithmic traders and the idea that I will present in this post: a portfolio optimizer.

Statistical analysis of a stock price

A simple statistical analysis of Google stock price. In this article, I’m going to show you a statistical analysis of Google stock price.

Technical Analysis of Stocks using TA-Lib

We can visualize a large number of indicators in order to decide our future strategy. In this article, we will explore how to use TA-Lib to create different technical indicators.

How to Automate the Extraction and Organization of Stock Data: Yahoo Finance API

How to Automate the Extraction and Organization of Stock Data: Yahoo Finance API. I decided to design code that would extract the data I needed so I could simply glance over the data table to decide if a company was profitable.

Essential Guidelines for Building Machine Learning Models on Stock Market Data

Machine Learning Models on Stock Market Data. Three important things to consider when building machine learning models on stock market data