Rajandran R

  Bangalore http://www.marketcalls.in Telecom Engineer turned Full-time Derivative Trader. Mostly Trading Nifty, Banknifty, USDINR and High Liquid Stock Derivatives. Trading the Markets Since 2006 onwards. Using Market Profile and Orderflow for more than a decade. Designed and published 100+ open source trading systems on various trading tools. Strongly believe that market understanding and robust trading frameworks are the key to the trading success. Writing about Markets, Trading System Design, Market Sentiment, Trading Softwares & Trading Nuances since 2007 onwards. Author of Marketcalls.in and Co-Creator of Algomojo (Algorithmic Trading Platform for DIY Traders)


3262 Stories by Rajandran R

How to Perform Machine Learning Using Amibroker and Python

Amibroker is a powerful technical analysis and trading system development platform, used extensively by traders and analysts for developing and deploying trading strategies. Python,...
0 5 min read

Bulls Make a Comeback: 9th Consecutive Positive Close for Nifty Futures

The financial landscape has taken an exciting turn as the bulls return with full force, marking a remarkable 9th consecutive positive close for Nifty...
0 1 min read

Top Quant Python Libraries for Quantitative Finance

quantitative-finance, python, pandas, NumPy, SciPy, scikit-learn, statsmodels, QuantLib, zipline, TensorFlow, pyfolio, yfinance, seaborn, Plotly, Streamlit, TA-Lib, pandas_ta
0 4 min read

Understanding the Behavior of Long-Term Investors – Market Profile Tutorial

Long-term traders/investors typically have a buy-and-hold strategy, meaning they hold positions in the market for an extended period, usually months or years. They are...
0 2 min read

Introduction to NumPy – Python Tutorials for Traders

NumPy is a Python library that provides support for large, multi-dimensional arrays and matrices, along with a large collection of mathematical functions to operate...
0 3 min read

Predicting Gap Up, Gap Down, or No Gap in Stock Prices using Logistic Regression

Logistic Regression is a popular statistical method used for predicting binary outcomes, such as predicting whether an email is spam or not, whether a...
0 4 min read

A Quick Start Guide to Compute Correlation Matrix in Python using yFinance, Seaborn and Pandas

A correlation matrix is a quantitative tool used in finance, statistics, and other fields to measure and visualize the relationships between multiple variables. In...
2 min read

AdaBoost – Ensembling Methods in Machine Learning for Stock Market Prediction using Python

In this article, we will discuss how ensembling methods, specifically bagging, boosting, stacking, and blending, can be applied to enhance stock market prediction. And...
0 7 min read

Feature Scaling – Normalization Vs Standardization Explained in Simple Terms – Machine Learning Basics

Feature scaling is a preprocessing technique used in machine learning to standardize or normalize the range of independent variables (features) in a dataset. The...
0 3 min read

ES-Mini Making a Short-Term Top Formation – Market Profile

ES-Mini Futures formed a short-term Top formation with G2 High formation at the major swing high with trading inventory getting long to too long...
0 15 sec read

Python Code for Generating Nifty Weekly Expiry Dates Using ChatGPT-4

The National Stock Exchange of India (NSE) is one of the largest stock exchanges in the world, with Nifty being its flagship index. Nifty...
0 2 min read

Predicting Stock Price and Market Direction using XGBoost Machine Learning Algorithm

Forecasting the trajectory of the stock market remains an elusive endeavor for both investors and traders alike. A myriad of methods and algorithms have...
0 4 min read