# Category: Quant Basics

AI, Quantitative Analysis and Data Science Solutions for Finance and Manufacturing.

### Breaking the Sharpe ratio

by Qian Zhu and Tom Starke If you want to learn about things deeply, you need to break them. Sharpe Ratio is one of the top metrics used by traders and investors to evaluate their trading strategy/investment systems. It is often referred to as the ‘risk-adjusted performance measures’, which gives confidence to investors by comparing…

### Quant Basics 5: Parameter Sweep

Introduction In the last section we ran a single backtest. However, for our strategy to work we should optimise our strategy parameters. If we blindly run through a large set of parameters and then pick the best one we are very likely to fall for an issue called Data Mining Bias. This means that if…

### Quant Basics 4: Analysing A Single Backtest

In the previous posts we have downloaded market data, developed a vectorised backtest and calculated PnL, Sharpe ratio and drawdown. In this post we will set up, run and analyse a single backtest. This is the basis for running parameter sweeps and optimisations with hundreds or thousands of backtests. So, let’s set some important parameters…

### Quant Basics 3: Sharpe and Drawdown

Sharpe Ratio In the previous sections of Quant Basics we looked at producing data sources and how to write a vectorised backtest. We also calculated our first metric – PnL and tested its functionality. In this section we will add two more metrics that are very important for strategy evaluation: Sharpe ratio and drawdown. Let’s…

### Quant Basics 2: Vectorised Backtest

Why Vectorise? There are several ways to backtest a strategy on historical data. In this section we demonstrate vectorisation. This and the previous section will serve as preliminary exercises before we dive deeply into the quantitative section. However, one should not underestimate the pitfalls of backtesting. It is very easy to make mistakes here, so…

### Quant Basics 1: Data Sources

Introduction Welcome to the Quant Basics series. This mini series came from the observation that most people starting in quantitative trading focus almost entirely on the generation of trading signals. While this is important, several other areas in quantitative trading strategy development are even more cruicial such as: Data Vectorised Backtesting Performance analysis and…