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
Impulse MACD Futures Trading Strategy
LazyBear is a highly influential indicator developer on the internationally renowned trading platform, TradingView. He has created a large number of popular custom technical indicators, and his open-source code has inspired countless quantitative traders and technical analysis enthusiasts around the world. LazyBear’s indicators often focus on reducing the lag of traditional indicators and incorporate unique market observations to better capture trends and momentum. One of his representative works, the “Impulse MACD,” is adopted here. This indicator is not a traditional Moving Average Convergence Divergence (MACD), but rather a significantly improved version. It uses a zero-lag Double Exponential Moving Average (DEMA) to respond more quickly to price changes and combines a smoothed high-low price channel (SMMA) to determine market “impulse.” The core idea is that trading signals are more valuable only when price momentum aligns with the trend direction. This helps to filter out some of the noise typically found in ranging markets.
Quant Research
Golden Cross Futures Trading Strategy（MTX）
The concept of the Moving Average (MA) originates from the Dow Theory developed in the early 20th century. Dow Theory emphasizes that markets exhibit trends, and such trends can be observed through price movements themselves. From the Simple Moving Average (SMA) and Exponential Moving Average (EMA) to more sophisticated variants such as the Double Exponential Moving Average (DEMA) and Hull Moving Average (HMA), all these improvements aim to address the inherent lag problem of traditional moving averages, allowing them to reflect price trends more quickly or more smoothly.
Quant Research
When Others Fear, I Enter: Anthony Melia’s Contrarian Strategy for Winning in the Market
In financial markets, Contrary Thinking is a timeless strategic wisdom. It stems from a simple yet profound observation: when most people are overly optimistic, the market is often overheated; when the crowd falls into fear, it may actually present a buying opportunity. However, contrarian investing has long remained at the level of a proverb, lacking concrete and quantifiable standards of action, making it difficult to implement in practice.
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.
Quant Research
Shipping Leads, Semiconductors Follow? A Data-Driven View on Taiwan’s Sector Rotation
Analyze industry rotation between Taiwan’s shipping and semiconductor sectors using momentum and valuation factors. This study reveals how factor-based strategies capture cyclical shifts—and why semiconductors ultimately outperformed over time.
Quant Research
Starting from Robert Gaddie’s Stock-Picking Method: Searching for Small-Cap Growth Dark Horses in the Taiwan Stock Market
Discover how Robert Gaddie’s stock-picking method helps uncover hidden small-cap growth gems in Taiwan’s market. This strategy targets under-the-radar companies with earnings momentum and delivers strong backtested returns.
Quant Research
Implementing Peter Lynch’s Investment Philosophy: A Quantitative Strategy Combining Growth and Value
Discover how Peter Lynch’s legendary investment philosophy can be applied to Taiwan’s stock market. This article builds a quantitative GARP strategy using TEJ data to identify undervalued growth stocks—and tests its performance over seven years.
Quant Research
Derwood Chase’s Growth Momentum Stock-Picking Strategy: The Intersection of Value and Momentum
Discover how Derwood Chase’s value-momentum strategy—favoring low P/E stocks with strong price trends—delivers long-term outperformance in Taiwan’s market. Backtest results show strong alpha and lower drawdowns, proving the power of disciplined factor investing.
Quant Research
The Wisdom of Blue-Chip Stocks: Howard Rosman’s Prudent Path to Wealth
Rothman’s core investment philosophy is to “buy right and hold tight” or “buy strong and hold long.” He emphasizes selecting financially sound companies with stable and growing earnings, purchasing them at the right price, and holding them patiently for the long term. Without frequent portfolio adjustments, investors can achieve strong long-term returns. This simple yet resolute investment approach reflects Rothman’s practical wisdom and provides a clear, historically validated foundation for the strategy tested in this study.
Quant Research
Michael Murphy’s Risk Assessment Rules for Investing in High-Tech Stocks
With the rapid development of the high-tech industry, technology stocks have increasingly become the focus of the market. While these stocks offer significant growth potential, they also come with high volatility and substantial investment risk. Investors seeking high returns may face major losses if they fail to properly assess the associated risks. Therefore, effectively measuring and managing the downside risk of high-tech stocks has become a crucial component of sound investment decision-making.
Quant Research
Charles Brandes’ Value Investing Principles : Building a Portfolio with a Margin of Safety
In the field of investing, business cycles have always served as an important reference. Whether it’s fluctuations in the macroeconomy or the ups and downs of corporate earnings, these cycles play a crucial role. Charles Brandes, a distinguished disciple of Benjamin Graham, founded Brandes Investment Partners in 1974 and has since grown its assets under management from $130 million to over $75 billion. The firm’s Brandes Global Equity Fund achieved an impressive 20-year annualized return of 17.91%, significantly outperforming the MSCI World Index, and has received Morningstar’s five-star rating along with numerous international awards. Another flagship product, the AGF International Value Fund, has also demonstrated outstanding long-term performance. Brandes himself has been repeatedly ranked among the world’s top fund managers.
Quant Research
Enhancing Investment Performance of the Ichimoku Cloud with the XGBoost Machine Learning Algorithm
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.