TQuant Lab

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.

When using TQuant Lab for backtesting and strategy analysis, beginners may encounter various technical challenges and questions. This article provides solutions and tips to help users develop and backtest strategies more smoothly, improving efficiency and accuracy. Hopefully, this information will help resolve common problems faced by newcomers.

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.

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.

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 time, the Williams %R strategy was used for backtesting. The Williams indicator is also called the Williams index, wmsr, or W%R. Its English name is The Williams Percent Range. It was created by the famous American trader Larry Williams in 1973. It is a standard indicator in technical analysis. One. The KD line and other indicators commonly used by investors to judge overbought or oversold are developed based on the William indicator.

The Ichimoku Kinko Hyo strategy employed in this simulation utilizes the concept of the three-line conversion in the Ichimoku Cloud chart for backtesting, coupled with trailing stop-loss testing for profitability. Under the pen name Ichimoku Sanjin (いちもくさんじん / Ichimoku Sanjin), Goichi Hosoda authored seven series of works detailing the philosophy behind this indicator and its trading system.

ESG is an important indicator for evaluating a company's sustainable development and is also one of the important issues that investors pay attention to. Environmental risks are an issue that the world must pay attention to. Both investors and social groups have begun to supervise companies' or governments' response measures to environmental risks. This article will buy-and-hold ESG ETF and backtest risk and performance.

The KD Indicator is a practical and widely used tool in technical analysis. It's primarily used to determine the short-term strength of stock prices and potential reversal timing.