TEJ API

TEJ (Taiwan Economic Journal) is a renowned financial information service platform in Taiwan. It provides a wide range of data and analysis tools covering various aspects such as economics, finance, stock markets, bond markets, and futures. With its extensive database and professional analytical features, the TEJ platform is widely used by financial institutions, research units, and investors to access real-time, accurate market data and conduct in-depth data analysis to support decision-making.

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.

No matter which brokerage app you use, you can view the historical trading information and real-time market data of various securities on the app. This allows investors to make informed investment decisions based on accurate information. This is possible because the Stock API facilitates smooth data transmission between the market trading system and the brokerage app. In this article, we will introduce what a Stock API is and highlight the three most commonly used Taiwan Stock Market APIs, providing valuable references for investors.

This article will introduce algorithmic trading with Python, the benefits of using the Python programming language for financial trading, and how to apply it to financial transactions, allowing investors to harness the power of technology to build their ideal investment portfolios.

In the first article—Verifying LSTM Stock Price Prediction Effectiveness Using TQuant Lab (Part 1)—we compared the predicted data with the actual data to conduct an initial evaluation of the performance of two trained models (for stocks 2618 and 8615). The results were promising. For a more detailed analysis, you can click the link above to learn more, as we will not go into further details here due to space constraints.

If you’ve been involved in investing for some time, you’ve likely heard a lot about algorithmic trading and quantitative trading strategies. For beginners with no software or coding background, it might seem daunting at first. However, with the rise of AI in recent years, the ability to automate investment strategies could become an essential tool […]

This article uses the LSTM time series model for deep learning-based LSTM stock price prediction, utilizing the opening, high, low, and closing prices of the past five days, quarterly ROE, MOM (indicating the magnitude of price trend changes, and the direction of market trends), and RSI indicators to predict the next day's closing price.

For students who want to use TQuant Lab, in addition to the original GitHub installation tutorial, we now offer a faster and simpler way to use it directly on Google Colab. The tutorial on running TQuant Lab in Google Colab eliminates the need to set up a virtual environment, significantly lowering the barrier to entry.

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.

This article will utilize the Stock Exchange's provided 7 financial information indicators and explore their correlation with stock price counter-indicators using the TEJ API.