The PyQuant Newsletter

10 ways to find systematic trading strategies. In today’s newsletter, you’ll learn 10 ways to find systematic trading strategies

How to download historic tick data for trade surveillance. Refinitiv’s tick history provides real-time pricing data from more than 500 trading venues.

Explore 10 quick Python video blueprints for trading strategies, data analysis, and portfolio optimization to sharpen your quant skills.

In today’s newsletter, I’m going to show you how to use factor risk analysis to figure out a portfolio’s exposure to those factors.

The 8-step framework for algo trading strategies. Your map to go from lost to executing automated strategies with python.

In today’s newsletter, I’m going to show you how to build an implied volatility surface using Python.

In today’s issue, I’m going to show you how to isolate alpha with principal component analysis (PCA) to analyze a portfolio of stocks.

How to tell if options are cheap with volatility cones. The hardest part of options trading is determining if they are cheap or expensive.

Value exotic options with Python. When you think of exotic options, what comes to mind? Lamborghini or Ferrari, palm trees or ski chalet?

How the Treynor ratio helped build a $100 million trading book. Learn to measure risk-adjusted portfolio performance with Python.

2 tools for professional backtesting: Step-by-step Zipline for beginners. Today, you use professional backtesting tools Zipline and PyFolio.

How to easily improve your Sharpe ratio (in no time). Systematic risk is the risk that affects the entire market.

Your forecast is broken: Decompose your time series. I’m going to show you how to decompose a time series of US unemployment data.

I’m going to show you how to forecast volatility with GARCH. Market mispricing happens when the market price is different that the price it should be.

How To Compute Volatility 6 Ways Most People Don’t Know. In today’s issue, I’m going to show you 6 ways to compute statistical volatility in Python.

Simulate stock prices is fundamental for pricing derivatives. In the case of GBM, it is the key part of pricing equity options using Black-Scholes

How to compute drawdown on an investment. I’m going to show you how to compute the drawdown of the SPY ETF with Python.

I’m going to show you how to use the Kalman filter to smooth stock prices. I also introduce the OpenBB SDK: The free Bloomberg alternative.

In today’s issue, I’m going to show you how to beta-hedge a stock portfolio against a benchmark, with Python.

You will be able to backtest a real trading strategy with Backtrader. Backtesting is a way to test trading ideas market data.