Quant Data Science

In TQuant backtesting and live trading, order functions serve as the central link between strategy logic and capital management. Choosing the right order method not only makes the code cleaner and easier to read but also improves the efficiency of risk control and portfolio rebalancing. TQuant provides order functions across three dimensions — share quantity, capital amount, and portfolio weight. For each dimension, there are two variants: a basic order and a target order. In total, this gives us six order placement methods. In the following sections, we will explain the features, parameters, and recommended applications of each.

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.

Preface In financial investment, mastering accurate and comprehensive data is an indispensable skill, and effectively managing stock pools and acquiring stock price data is the key to unlocking this skill. With the tools and APIs provided by TQuant Lab, we can easily define screening criteria, quickly establish stock pools that meet specific requirements, and retrieve […]

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

In investment decision-making, price-volume factors are essential for investors to gain insights into market behavior. The relationship between price and trading volume supply and demand dynamics of an asset also reveals capital flows and shifts in market sentiment. These factors play a crucial role in capturing short-term opportunities and identifying potential risks in asset allocation.

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

TEJ (Taiwan Economic Journal) is a renowned financial information service platform in Taiwan. It provides a wide range of data and analysis tools covering various aspects such as economics, finance, stock markets, bond markets, and futures. With its extensive database and professional analytical features, the TEJ platform is widely used by financial institutions, research units, and investors to access real-time, accurate market data and conduct in-depth data analysis to support decision-making.

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 guide you through leveraging the TQuant Lab SuperTrend strategy in combination with the SinoPac API to quickly master the essentials of algorithmic trading. Let’s become pioneers of algorithmic trading in the Taiwan stock market together!