Category: Quant Trading

Introduction Backtesting is the process of testing a trading strategy using historical data to see how it would have performed in the past. This helps traders understand if their strategy has potential profitability before risking real money. The goal is to simulate the trading strategy in a past market environment and analyze the outcomes. If…

Introduction Data analysis is essential in any research, decision-making, or business strategy. However, before any meaningful insights can be drawn from data, the data must be prepared and polished. This is where data cleaning and preprocessing come into play. These two steps are crucial for ensuring data quality, accuracy, and relevance. Let’s break down each…

Introduction Programming languages are tools that help us write instructions for computers to perform tasks. They vary in design and use cases, with some specialized for data analysis, others for web development, and more. Let’s explore two prominent languages, Python and R, with a focus on their key libraries and frameworks. 1. Python: A Versatile…

Introduction Probability theory is a branch of mathematics that helps us measure how likely an event is to happen. Imagine you have a coin, and you flip it. It can either land on “heads” or “tails.” Probability theory allows us to figure out the chance of each of these outcomes happening. Key Concepts in Probability…

Introduction Statistical distributions describe how values in a dataset are spread or distributed across possible outcomes. Understanding distributions helps us predict, analyze, and interpret data. Let’s break down some common statistical distributions in simple terms: 1. Normal Distribution Also called a Gaussian distribution or a bell curve, the normal distribution is one of the most…

Introduction Hypothesis testing is a statistical method used to make decisions or draw conclusions about a population based on a sample of data. It’s like having a “mini-experiment” to test whether what we see in the sample also applies to the larger group (the population). Let’s break down the key concepts: 1. What is a…

Introduction A Confidence Interval (CI) is a range of values that we believe, with a certain level of confidence, includes the true value of a parameter (like the average or proportion) in a population. Confidence intervals are commonly used in statistics because they help us understand the accuracy of our estimates. Key Components of Confidence…

Introduction Time Series Analysis is a statistical method used to analyze data points collected or recorded at specific time intervals over a period. It’s widely used in various fields, like finance, weather forecasting, stock market analysis, and more, to identify patterns, trends, and seasonality in data. Two fundamental concepts in time series analysis are stationarity…