Quant

The Zipline engine, integrated within TQuant Lab, offers a high-quality and realistic backtesting framework. It leverages four core functions—initialize、handle_data、analyze、run_algorithm——to construct a comprehensive simulation environment. These components enable trading strategies to dynamically adjust to market conditions, incorporating elements such as slippage and transaction costs to ensure that backtest results closely reflect real-world performance. This article begins with a brief overview of the four key components and their applications. It then focuses in detail on the initialize function, exploring its specific configurations and role within the backtesting process.

Traditional Ichimoku strategies rely on fixed parameters (9-26-52) and visual interpretation, making them inflexible in adapting to different market conditions. XGBoost learns complex high-dimensional relationships between different data points and enhances the filtering and decision-making process of trading signals. This article use XGBoost to enhance investment performance of Ichimoku Cloud.

Quantitative data collection methods include surveys, interviews, observations, and dataset reviews. Explore the techniques, pros, and cons of each method.

This article will explore what quantitative data is, outlining its meaning, types, and examples, while briefly viewing its collection and analysis methods.

Event-driven investing exploits pricing inefficiencies caused by significant corporate events. Discover common event-driven strategies and examples below.

what is the right way to invest? If you’ve had the same doubts, you’re not alone. While seeking answers, I stumbled upon a term that was entirely new to me: quantitative finance. Learning this field helps resolve personal financial challenges and enhances career competitiveness. More importantly, it sharpens your logical thinking and data analysis skills—benefits that are hard to overlook. TQuant Lab provides everything you need to get started efficiently and effectively. Let’s embark on this journey together and explore the endless possibilities of quantitative trading!

This article will explore the common types of quantitative investment strategies as well as the advantages and potential challenges of this trading model.

This guide will introduce the types of data analysis used in quantitative research, then discuss relevant examples and applications in the finance industry.

In recent years, as the stock prices of popular AI companies continue to reach new highs, investors are increasingly focused not only on these companies' operational status but also on the trading behavior of their insiders. Company insiders have more information compared to external investors, giving them an informational advantage when trading the company's stock.

Creating a convergence strategy with the RSI moving average strategy. The RSI is an oscillating technical indicator representing the comparative strength between buyers and sellers in the market.

In this article, we use Event Study to explore the impact of announcement of different corporate events on the stock retuens. Let's find out the results and learn more about event-driven data!

Aroon Indicator, developed by Tushar Chande in 1995, is typically for measuring market tendency. It consists of two lines - Aroon Up and Aroon Down.