Quant

In this installment, we expand the backtester to use it as a broad-spectrum search engine to find seasonal edges. We run a backtest on all the necessary parameters to analyze the intraday seasonality of the asset

In this article, we analyze the Sharpe ratio, Value at Risk (VaR), Conditional Value at Risk (CVaR), the System Quality Number (SQN), and other relevant ratios to analyze the backtest.

After a long period completely disconnected, we return to writing some notes for you. On this occasion, we are going to program from scratch a complete research process, and instead of going for a specific asset, we are going to create a complete method, reusable in the future, to be able to run it

A quant strategy is a systematic strategy, driven by data and the model, which is programmed to generate investment decisions. The main pillar within quant research is the scientific method.

Learn algorithmic trading with Python from scratch. Discover how to create, analyze, and optimize trading strategies step by step in this practical course.

Over time, some codes can start to see the light of day publicly, and reviewing old repositories, I found a very primitive version of a reporting library that made our lives much easier at the time.

In this article, we explain how to get free market data for stocks, futures, options, forex, and more using OpenBB and Python.

In the complex field of economics and monetary policy, it is essential to have the ability to analyze and understand trends and the effects of economic policies. In this context, Python, a versatile programming language, has become indispensable for economists and financial analysts.