Tejapi Data Analysis

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 […]

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.

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.

Data analytics in the stock market plays a vital role in understanding market dynamics, making informed decisions, and optimizing investment strategies. This process involves deep analysis of extensive datasets to extract market trends, actionable insights, and predictive indicators. It's the key to forecasting market movements, identifying investment opportunities, and managing risks with a data-driven approach.

In the Taiwan stock market, retail investors account for the highest proportion and have the highest trading volume in the market. This article uses factor analysis to delve into the relationship between retail investor trading behavior and stock expected returns.

By analyzing the motives behind insider block trades, we aim to explore the relationship between stock prices and insider transfers.

This article explores how the combination of LLM and TEJAPI enhances the efficiency and precision of stock market analysis. It elucidates how this integration contributes to identifying market trends, analyzing stock performance, discovering key information in market news, and providing third-party investment insights. This synergy not only aids professional traders and investors but also offers ordinary investors more ways to grasp the dynamics of the market.

Exploiting the Logit & Probit regression model to analyze the chances of a company’s bankruptcy. Highlights Preface Predicting the future is what every investor wants to pursue, whether it is for the future market or the future of the companies and the industries. Still, there is always uncertainty and randomness in predicting the future, so […]

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 […]