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".
Factor Strategy – Integrating Broker Consensus to Enhance Foreign Concentration Strategies – QFII Part 2
Boost your quantitative strategy with QFII concentration & broker consensus! Discover how the conc_qfii fusion strategy delivers a 30.12% annualized return in the Taiwan large-cap market.
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.
Insights
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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.
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 […]
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.
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.
Market Knowledge & Data Guides
What is Market Data: Meaning, Types, Examples, Pros, & Cons
What is market data? Learn about its definition, types, sources, and applications to leverage it for informed decision-making in trading and investment.
Quant Data Science
What is a Stock API? A Guide to Quickly Acquiring Taiwan Stock Market Information Using Financial Tools
No matter which brokerage app you use, you can view the historical trading information and real-time market data of various securities on the app. This allows investors to make informed investment decisions based on accurate information. This is possible because the Stock API facilitates smooth data transmission between the market trading system and the brokerage app. In this article, we will introduce what a Stock API is and highlight the three most commonly used Taiwan Stock Market APIs, providing valuable references for investors.
Quant Data Science
How to Use Python for Algorithmic Trading? A Guide to Understanding the Benefits and Operation of Algorithmic Trading
This article will introduce algorithmic trading with Python, the benefits of using the Python programming language for financial trading, and how to apply it to financial transactions, allowing investors to harness the power of technology to build their ideal investment portfolios.
Quant Data Science
Verifying LSTM Stock Price Prediction Effectiveness Using TQuant Lab (Part 2)
In the first article—Verifying LSTM Stock Price Prediction Effectiveness Using TQuant Lab (Part 1)—we compared the predicted data with the actual data to conduct an initial evaluation of the performance of two trained models (for stocks 2618 and 8615). The results were promising. For a more detailed analysis, you can click the link above to learn more, as we will not go into further details here due to space constraints.
Market Knowledge & Data Guides
What is Algorithmic Trading? A Beginner’s Guide to Algorithmic Trading, Including Tutorials, Pros and Cons, and Common Strategies.
If you’ve been involved in investing for some time, you’ve likely heard a lot about algorithmic trading and quantitative trading strategies. For beginners with no software or coding background, it might seem daunting at first. However, with the rise of AI in recent years, the ability to automate investment strategies could become an essential tool […]
Quant Data Science
Verifying LSTM Stock Price Prediction Effectiveness Using TQuant Lab (Part 1)
This article uses the LSTM time series model for deep learning-based LSTM stock price prediction, utilizing the opening, high, low, and closing prices of the past five days, quarterly ROE, MOM (indicating the magnitude of price trend changes, and the direction of market trends), and RSI indicators to predict the next day’s closing price.
Industry Insights
Analyzing the Changes in Sharpe Ratio of NVIDIA Concept Stocks Using TEJ API from Jensen Huang’s Speech at National Taiwan University
During Jensen Huang’s speech at National Taiwan University, he revealed a list of NVIDIA’s business partners in Taiwan, which led to the viral spread of the term “the world’s strongest AI ETF”. What impact did this announcement have on the stocks of these business partners? We will use TEJAPI to calculate the Sharpe ratio to determine whether the effect was positive or negative. Additionally, we will visualize the observed results.
Market Knowledge & Data Guides
Counter-Indicator Analysis: Using TEJ API to Examine the Relationship Between Stock Prices and Counter-Indicators Issued By Authority”
This article will utilize the Stock Exchange’s provided 7 financial information indicators and explore their correlation with stock price counter-indicators using the TEJ API.