Quantitative Analysis

Dividend arbitrage focuses on the price inefficiencies between dividend payouts and option pricing. This article will explore its execution process, examples, and challenges.

This article will explore what quantitative data is, outlining its meaning, types, and examples, while briefly viewing its collection and analysis methods.

This series of articles uses Alphalens to examine the application and effectiveness of various factors in the market. In previous articles, we analyzed "foreign capital factors," exploring how foreign investments influence the market. This article will focus on "value factors," examining valuation-related indicators that reveal intrinsic value and affect long-term returns. You can use the alphalens-tej tool within TQuant Lab. This tool not only integrates TEJ data but also eliminates tedious data processing, allowing you to easily assess factor performance and further support the development of investment strategies.

what is the right way to invest? If you’ve had the same doubts, you’re not alone. While seeking answers, I stumbled upon a term that was entirely new to me: quantitative finance. Learning this field helps resolve personal financial challenges and enhances career competitiveness. More importantly, it sharpens your logical thinking and data analysis skills—benefits that are hard to overlook. TQuant Lab provides everything you need to get started efficiently and effectively. Let’s embark on this journey together and explore the endless possibilities of quantitative trading!

This article will guide you through leveraging the TQuant Lab SuperTrend strategy in combination with the SinoPac API to quickly master the essentials of algorithmic trading. Let’s become pioneers of algorithmic trading in the Taiwan stock market together!

This series of articles will use Alphalens to explore several key factors, gradually analyzing their impact on market performance. The first article focuses on "foreign capital," examining the effects of foreign capital flows into the market. Next, we'll delve into "value factors," studying how they reflect a company's intrinsic value. Finally, the last article will analyze "price-volume factors," uncovering the interplay between price and trading volume.

What is market data? Learn about its definition, types, sources, and applications to leverage it for informed decision-making in trading and investment.

How to Gain Insight into Stock Price Movements from Quarterly Reports? This article will use quarterly reports stock selection to filter the top 20% of listed companies in Taiwan by quarterly revenue and implement long positions. Through this revenue-based backtesting approach, we can identify potential strong stocks in the market and verify the effectiveness of this quarterly stock selection strategy with accurate data. It is simple and provides investors with a stable and systematic basis for stock picking, uncovering the hidden signals behind stock price movements.

What is quantitative data analysis? See how numerical data is analyzed using proven methods, with examples and practical applications in finance and analytics.

When market efficiency is low or inefficient, stock prices tend to overreact or underreact to new information. This phenomenon allows investors to achieve significant positive average returns by buying stocks that have performed well in the past or short-selling stocks that have performed poorly (Jegadeesh and Titman, 1993). From a behavioral finance perspective, George and Hwang (2004) pointed out that traders might be reluctant to buy even if there is favorable news when stock prices approach a new high within the past year. This reluctance leads to stock prices reaching new highs driven by positive news, indicating that even professional investors might underreact to new information. Zhang (2006) found from an information asymmetry perspective that in markets with a higher degree of information asymmetry, future returns of stocks following bad or good news tend to be lower or higher, respectively. Momentum strategies perform better in stocks with higher levels of information asymmetry. This study attempts to use the daily reports of brokers branches trading provided by the Taiwan Stock Exchange to derive relevant indicators from an information asymmetry perspective, combining these with momentum factors to identify stocks that have yet to catch the market's attention but are gradually rising in price. The study will conduct overlapping period tests, IC/IR value tests, and factor portfolio backtesting on this composite factor.

In recent years, as the stock prices of popular AI companies continue to reach new highs, investors are increasingly focused not only on these companies' operational status but also on the trading behavior of their insiders. Company insiders have more information compared to external investors, giving them an informational advantage when trading the company's stock.

As the name suggests, high dividends refer to companies distributing higher profits to investors in the form of cash dividends. There is no specific definition of how much dividend constitutes a high dividend. This article will utilize TQuant Lab to conduct a backtesting performance analysis of buying and holding High Dividend ETF.