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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.
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Quant Data Science
GRU and LSTM
Highlights: Preface Profit-chasing and risk-averse are the innate naturals of all investors. One way to achieve these goals is to predict the future stock movement. In the past, time series models such as ARIMA and GARCH are widely used to characterize the trajectory of future stock prices. Nowadays, As the boom of artificial intelligence, […]
Quant Data Science
PCA Feature Portfolio
Principal Component Analysis (PCA) is a key technique in unsupervised learning widely used in machine learning and statistics to analyze data and reduce data dimensionality. Its core idea is to break down the original data into representative principal components, achieving dimensionality reduction and providing a new description of the data.
Quant Data Science
Seeking Alpha
The alpha obtained from the Fama&French three-factor model is used to construct a long-short strategy and backtest the performance against the market return. Highlights： Difficulty：★★☆☆☆ The Fama&French three-factor model is used to calculate the alpha of Taiwan-listed stocks, and the top 20% of stocks with the highest alpha and the bottom 20% of stocks with […]
Quant Data Science
Herding indicators
Using the number of margin trading and short selling and volume to establish the herding indicators then analyze by regression model. Keyword：Herding Indicators、Margin Trading、Application What are Herding indicators? The emergence of behavioral finance has challenged the traditional view in investment theory that individuals make rational investment decisions. The “herd behavior” represents the tendency of investors […]
Quant Data Science
LSTM
Using deep learning model to predict stock price? Highlights Preface Predicting stock prices has been pursued by people, but the randomness of stock prices not easy to forecast. With the progress of data science, the calculation cost has been greatly reduced. This article use more complex deep learning model for stock prices prediction compare to [Quantitative […]
Quant Data Science
SVM Model
Apply Financial Data to Predict Stock Price Fluctuation Highlights Preface Support Vector Machine, short as SVM, is a machine learning algorithm based on Statistics theorem. It is widely used in data classifier and regression. As for this article, we would focus on Classifier. Simply put, classification of SVM is conducted by draw straight or irregular […]
Quant Data Science
Lasso Regression Model
Effective Explanatory Variables for Economic Growth Highlights Preface Least Absolute Shrinkage and Selection Operator, short as Lasso, is mainly used for variable selection and regularization in Regression. The function of “Penalty” setting would in Lasso lets us adjust the complexity. Therefore, with Lasso, we are able to alleviate “Overfitting”. Penalty in the model is used […]
Quant Data Science
Portfolio VaR
In 1997, Robert Merton and Myron Scholes won the Nobel Prize in Economics for their Black-Scholes options pricing formula, beating out many other contenders. The Black-Scholes model is still a widely-used option pricing model in the financial industry and by investors due to its excellent mathematical properties, simplicity, and ease of use. Today, we will focus on programming this model and Greeks derived from Black Scholes model.
Quant Data Science
ARIMA-GARCH Model(Part 2)
First of all, we would implement the process to construct models so as to make you understand the application of python packages. However, in case of redundancy of this article, there is no hypothesis test. Subsequently, we would calculate the forecasted return and price. Last but not least, apply visualization to compare the prediction and actual trend to assess the result of ARMA-GARCH.
Quant Data Science
Pairs Trading
Establish a pairs trading strategy between Evergreen Shipping and Yang Ming Shipping with Python. Highlights Preface When the market capital is excessively flooded, to avoid systemic risks, investors often establish long and short positions at the same time through asset allocation to eliminate most market risks and obtain stable returns. However, we select Evergreen and […]
Quant Data Science
ARIMA-GARCH Model(Part 1)
First of all, we need to declare the Time Series concept. It is a kind of data structure showing the development of historical data by the order of time. As for Time Series Model, it is applied to analyze time series data. Further, by this model, we manage to find high-likelihood trend and make forecasting.
Quant Data Science
RSI Indicator
Use common technical indicators to backtesting Highlights Preface Relative strength index (RSI) is the momentum technical indicator. It is usually used as an oscillator interval to evaluate overbought or oversold condition by measuring recent trend of price movements. Following is the way to calculate this indicator: Criterion of RSI: RSI’s Deactivation: Gain and loss is […]