26. Standard Data in Algorithmic Trading

Published at 1683714893.269553

Market Data

Market data consists of the following essential data fields:

  • Stock ticker symbol;

  • Order execution time;

  • Order execution price;

  • Order execution volume;

  • Bid price 1, 2, 3 (10 price steps for HNX and UPCOM);

  • Bid volume 1, 2, 3 (10 price steps for HNX and UPCOM);

  • Ask price 1, 2, 3 (10 price steps for HNX and UPCOM);

  • Ask volume 1, 2, 3 (10 price steps for HNX and UPCOM).

These data fields allow investors to use most technical analysis strategies or OHLC charts (Open-High-Low-Close). This is the simplest and most common data group sold under data packages in Vietnam.

Execution data is also categorized based on the type of the transaction such as insider transaction data, foreign investment execution data, and deal execution data.

Insider transaction data is publicly available. However, in Vietnam, insiders may trade in different ways to avoid affecting stock prices and frequent reporting. This data is therefore often unreliable, and it should only be used as a reference.

Foreign investment data represents a strategic group of shareholders. This group plays an important role in making long-term investment decisions. However, it is not as useful for short-term investments.

Deal transaction data has a high volume and reflects the expected prices of the parties involved. In special cases, when foreign investors cannot buy shares directly on the stock exchange, the deal transaction often represents the valuation of foreign investors. However, the public information of the deal transaction may still differ from reality. This group of data is not completely reliable in the Vietnamese market.

Financial Statement Data

This data group includes: 

  • Income statement; 

  • Balance sheet;

  • Cash flow statement (direct or indirect).  

This data group is widely used in fundamental analysis. However, Vietnamese accounting standards still have many differences from the international standards. Different industries such as manufacturing, banking, securities, and insurance have specific financial report structures. To analyze the whole market, it’s essential to have reference benchmarks.

Dividend Data and ESOP

The company’s profit-sharing policy and the ESOP program over many years have greatly influenced investor sentiment in the long term. Therefore, data including cash dividends, stock dividends, and bonus shares can be used in algorithmic trading.

ESOP is a special policy to attract corporate talent. However, it’s often abused for personal purposes. When adopting the IFRS, international financial reporting standards, ESOP abuse in Vietnam should be more restricted.

Macroeconomics Data

Inflation data, interest rates, economic growth, import and export, exchange rates, export orders, money supply, and public investment reports are publicly available macro data. They are often used to predict the economy in the medium term. 

For instance, algorithmic traders can rely on inflation and interest rate data of 2022 to gain insights into the macroeconomic impact on the market and domain-specific businesses.

Commodity Data

Each particular industry and enterprise will be closely related to the price of imported and exported goods. These prices often move together with the global commodity prices, which are important data to collect. Investors in Vietnam are most interested in common commodities like oil, gold, soybeans, coffee, and meat. Other commodity prices are more complex but still collectible such as international freight shipping prices.

During the Covid pandemic, the supply chains were disrupted. Commodity prices no longer followed normal economic rules. They become important information for seeking trading advantages.

Index Data

A single stock or a particular industry usually has a certain correlation with the local and global market indices. Therefore market indices need to be stored to have an accurate view of the Vietnamese market or each individual stock in the global context. Besides the data above, there are other types of specialized data. Algorithmic traders can gather them to support algorithm development and seek trading alpha.