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 Research
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".
Quant Research
James O’Shaughnessy’s Cornerstone Value Strategy: Unearthing High-Quality Gold Mines in Large Cap Revenue Stocks
James P. O’Shaughnessy demonstrated in his book What Works on Wall Street that market returns do not fully conform to the Efficient Market Theory, showing that selecting stocks with low P/B, low P/CF, and low P/S ratios significantly enhances long-term returns. Among his methodologies, the “Cornerstone Value Strategy” targets high-revenue, cash-rich large-cap stocks. It screens equities across four dimensions—size, cash flow quality, revenue scale, and relative valuation—and uses dividend yield ranking for final selection. Applying this strategy to the Taiwan stock market (excluding financial sector) with six quantitative filters and an annual July rebalancing protocol validates its capacity to deliver sustained alpha by balancing deep value with high shareholder yield.
Factor Investing
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.
Quant Research
Burton G. Malkiel’s Rules for Successful Stock Selection
Burton G. Malkiel is the Chemical Bank Chairman’s Professor of Economics at Princeton University. He previously worked in the investment banking division of Smith Barney & Co. and has served as a director of several large investment institutions, including The Vanguard Group and The Prudential Insurance Company of America. He was also appointed as a member of the U.S. President’s Council of Economic Advisers. In both academic and investment circles, he is a highly respected and influential figure.
Quant Research
ETF Premium-Discount Arbitrage: Market Maker vs. Retail Performance
Market makers, equipped with high-frequency trading capabilities, institutional-grade cost structures, and real-time creation/redemption privileges, are the primary participants in ETF premium–discount arbitrage. In contrast, Non-Institutional Participants face multiple constraints—including information latency and higher transaction frictions—which make it difficult to capture arbitrage opportunities promptly or profitably.
Market Knowledge & Data Guides
Panic or Opportunity? Spotting Market Turning Points Through Margin Maintenance Ratios
In the Taiwan stock market, credit trading (margin buying and short selling) serves as a critical mechanism for observing market leverage and investor sentiment. Unlike institutional investors with ample capital, retail investors often face capital constraints and therefore resort to margin buying to increase their purchasing power. Consequently, margin data serves as a key barometer for retail trading heat. Key indicators for monitoring credit trading include daily margin/short volume, balance, margin utilization rates, and—most crucially—the Margin Maintenance Ratio (MMR). The MMR is a core metric used to assess the risk status of margin accounts and determine how close investors are to a margin call. Brokers set specific MMR thresholds to mitigate default risks during periods of high market volatility.
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.
Industry Insights
Turning Industry Rotation into Alpha: A Quant Backtest Strategy
In our previous article” Shipping Leads, Semiconductors Follow? “we identified a recurring pattern in Taiwan’s market: rallies in the shipping sector often precede gains in semiconductor stocks. This article builds on that insight by transforming the observed rotation sequence into a quantitative investment strategy.
Event & Alternative Signals
Alternative Data Integration: Step-by-Step Guide for Investors
Dividend arbitrage focuses on the price inefficiencies between dividend payouts and option pricing. This article will explore its execution process, examples, and challenges.
Event & Alternative Signals
Investing with Labor Market Alternative Data: Insights & Tips
Dividend arbitrage focuses on the price inefficiencies between dividend payouts and option pricing. This article will explore its execution process, examples, and challenges.
Event & Alternative Signals
Alternative Data in Hedge Funds: Strategies & Success Story
Dividend arbitrage focuses on the price inefficiencies between dividend payouts and option pricing. This article will explore its execution process, examples, and challenges.
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.