Insights

In-depth research and data-driven insights on quantitative finance, factor investing, risk, and ESG from the TEJ research team.

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Fundamental Factor Research: Monthly Revenue Information – part1

The Taiwan equity market possesses a rare institutional advantage globally: under the Securities and Exchange Act, listed companies are required to announce and report their operational results for the preceding month by the 10th of each month (Exception: starting from FY2026, insurance companies and entities with insurance subsidiaries may extend their disclosure deadline to the 15th of each month). This is commonly referred to in the market as "Monthly Revenue".

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Factor Research –  Tracking Smart Money Footprints via Foreign Institutional Concentration – QFII Part 1

Track QFII ‘smart money’ footprints in Taiwan large-cap stocks! Learn how the Foreign-Institutional Trading Concentration (conc_qfii) factor predicts returns.

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Empirical Research on Behavioral Factors in the Taiwan Stock Market: A Case Study of the Share Distribution

In an AI-driven Taiwan stock market, mastering chip distribution (ownership structure) is the key to profitability. This study delves into the Share Distribution data from the TDCC, transforming 15 tiers of shareholding data into behavioral finance factors such as investor attention, opinion dispersion, and retail speculation. By utilizing Fama–MacBeth two-stage regression and the alphalens-tej quantitative tool, we precisely validate the predictive power of psychological biases on stock returns, providing investors with actionable Alpha strategies and robust risk management solutions.

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Quant Data Science

[TQuant From 0 to 1 – Day 5] Introduction to Order Placement Methods in the TQuant Lab Backtesting System

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.

2025.09.26 more
Quant Data Science

【TQuant : From 0 to 1 – Day 4】 Core Architecture of Backtesting: What are the key settings for Initialize?

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.

2025.04.09 more
Quant Data Science

[TQuant from 0 to 1 – Day 3] Building a Comprehensive Investment Data Perspective: Stock Pool Screening and Data Retrieval with TejToolAPI

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 […]

2025.03.21 more
Quant Data Science

How to Collect Quantitative Data: Common Methods

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

2025.02.17 more
Factor Investing

Analyzing Factor Performance with Alphalens: Price and Volume Factors

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.

2025.02.07 more
Quant Data Science

What is Quantitative Data: Definition, Types, & Analysis

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

2025.01.20 more
Quant Data Science

Differences Among TEJ API, TEJ Tool API, and TQuant Lab

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.

2025.01.14 more
Quant Data Science

【TQuant : From 0 to 1 – Day 2】 Avoid the Invisible Killers of Quantitative Trading: Use TQuant Lab to Precisely Manage Commission and Slippage, Giving Your Strategies the Edge!

In the world of investment markets, a critical issue is often overlooked: trading comes with costs! Transaction fees and slippage might seem trivial, but they can silently erode your profits. Today, we’ll explain in the simplest terms what transaction fees and slippage are, and show you how to use TQuant Lab to precisely control these trading costs, making your investment strategies twice as effective with half the effort! No matter how new you are to quantitative trading, don’t worry—just follow our steps, and you’ll be able to get started with ease!

2025.01.02 more
Quant Data Science

【TQuant : From 0 to 1 – Day 1】 Your Gateway to Quantitative Trading: Become a Quant Expert with TQuant Lab, No Experience Needed!

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!

2024.12.05 more
Quant Data Science

Algorithmic Trading Guide:Leveraging TQuant Lab Strategies with the SinoPac API for Automated 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!

2024.11.22 more
Quant Data Science

MasterLink Securities API Beginner’s Guide: How to Use TQuant Lab Strategies for Automated Trading

In modern financial markets, algorithmic trading is increasingly becoming essential for investors to enhance efficiency and reduce risk. More and more brokerage firms offer API services, enabling investors to automate order placement and quickly respond to market changes. This article will demonstrate using MasterLink Securities API for automated trading while integrating strategies from TQuant Lab. Through a practical example, we’ll show how a systematic approach can optimize investment decisions, helping investors seize market opportunities and improve performance.

2024.11.08 more
Quant Data Science

Newbie Troubleshooting:Answering All Your Questions About TQuant Lab.

When using TQuant Lab for backtesting and strategy analysis, beginners may encounter various technical challenges and questions. This article provides solutions and tips to help users develop and backtest strategies more smoothly, improving efficiency and accuracy. Hopefully, this information will help resolve common problems faced by newcomers.

2024.10.28 more