Quantitative Strategy

TEJ Factor Library provides a comprehensive set of pre-calculated quantitative factors designed for the Taiwan equity market. TEJ Factor Library covers over 100 localized factors across 11 major categories, enabling investors and researchers to efficiently conduct factor-based analysis, backtesting, and strategy development. Unlike raw data inputs, TEJ Factor Library delivers ready-to-use signals, significantly reducing the time required for data cleaning, factor construction, and alignment.

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.

Discover how TEJ's Taiwan Market Data captivated global investors at the Neudata London Summit 2025, offering unique insights into Asia's financial landscape.

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.

In the world of investing, accurate predictions and systematic analysis are key to achieving long-term success. Strategists who can decipher market trends become sought-after figures for investors eager to learn. Michael Sivy is undoubtedly one of the best. With precise market forecasts and unique investment insights, he has built a stellar reputation in the U.S. investment community. From warning of the 1987 stock market crash to predicting a market turnaround in 1995 and foreseeing the bursting of the tech bubble in 1999, Sivy has demonstrated exceptional market foresight through decades of research and hands-on experience. His book, The Rule of 72, has become a must-read classic, offering systematic analysis and clear guidelines for investors of all types.

The article delves into the performance of momentum strategy under different take-profit and stop-loss conditions, analyzing how to balance risk and reward in a highly volatile market using actual backtesting data.

The SuperTrend Indicator is a technical analysis tool used to identify trends in financial markets. It assists investors in determining relative high and low points during market swings, helping them make buy and sell decisions. However, one drawback of the SuperTrend Indicator is its tendency to be less effective during consolidation phases. To address this, we will use the Average Directional Index (ADX) to optimize the SuperTrend strategy in this article.

In recent times, there has been a global surge in AI, with Taiwan's electronics industry attracting a lot of interest from institutional investors due to its comprehensive supply chain. In addition to trading stocks through conventional methods on stock exchange markets, investors can also utilize block trading offered by exchanges for transactions exceeding a fixed amount.

Joseph Piotroski's F-score strategy, based on evaluating 9 financial conditions, helps investors gain insights into a company's profitability, safety, and growth potential. This article uses TQuant Lab to construct the F-score strategy, helping investors gain deeper insights into the investment benefits that the F-score can offer.

Over the past two decades, trend-following has been a successful trading strategy used by many fund managers, professional traders, and global macro hedge funds to profit in global futures markets. Recently, the application of trend following strategies to stocks has gained significant attention, with a surge in published research and articles. Increasingly, literature suggests that the trend effects observed in futures markets can similarly apply to stock markets.

The insider transfer strategy was constructed by adding the RSI indicator to the timing of insider transfers, aiming to explore whether following insiders into the market in a constantly rising stock market has good timing capabilities. The performance of insider transfer strategy is also backtested in this article.

This article selects disposal stocks as investment targets and uses TQuant Lab to conduct backtest performance analysis of buy, sell, and hold targets to confirm whether the investment strategy of popular stocks is a profitable and well-performing target.