Algorithmic trading is the process of trading financial instruments in which decisions to buy or sell assets are made based on predetermined algorithms and rules. These algorithms can include various factors such as price movements, trading volumes, technical analysis indicators, and market liquidity and volatility data.

When it emerged

Algorithmic trading began to develop strongly in the late 20th and early 21st century with the spread of computer technology and the development of high-speed internet connections. However, its roots go back in time - the first attempts at automated trading can be found back in the 1970s.

Creators

Various companies and financial institutions were actively engaged in the development and implementation of algorithmic trading. Large banks, hedge funds, trading firms and investment companies have played a key role in the creation and application of algorithmic strategies. One of the pioneers in this field is considered to be Renaissance Technologies and its founder James Simons.

Prominent examples and personalities in the field of algorithmic trading:

Renaissance Technologies: The company founded by James Simons has become famous for its outstanding results in the field of algorithmic trading and quantum analysis.

The company was founded in 1982 by James Simons, who contributed immensely to the development of mathematical models and algorithmic trading. The basic philosophy of Renaissance Technologies is to use quantum analysis and complex mathematical models to predict market trends. The company went on to become one of the most successful in the world due to their outstanding investment returns, outperforming the performance of other investment funds. Especially highly regarded is their Medallion funds, which has earned huge returns over a long period of time. Renaissance Technologies actively utilizes high-performance computing technology and quantum analysis to create sophisticated trading algorithms.

Goldman Sachs: One of the leading investment banking firms actively utilizing algorithmic trading in global financial markets.

Goldman Sachs is one of the largest investment banks in the world. They became active in algorithmic trading in the late 20th century when computers became widely available and high-speed internet connections became the norm. The company provides a wide range of algorithmic trading services, including market making, high-frequency trading, arbitrage, and others. Goldman Sachs develops proprietary algorithmic strategies based on analyzing market dynamics, technical indicators, and other factors. Involved in IPOs and M&A: Goldman Sachs is well known for its involvement in many large IPOs (Initial Public Offering) and Mergers and Acquisitions (Mergers and Acquisitions), in which they actively use algorithmic technology to determine the best time to buy and sell shares, as well as to manage risk. For example, Goldman Sachs' participation in the 2014 IPO of Alibaba Group was one of the largest and most successful IPOs in the history of financial markets.

High-Frequency Trading Firms: Firms that specialize in the instantaneous buying and selling of financial instruments using algorithmic strategies, such as Jump Trading, Citadel Securities, and others.

 High-frequency trading firms specialize in the instantaneous buying and selling of financial instruments in large volumes using algorithmic strategies. They actively invest in high-speed trading systems, as well as in the development of specialized algorithms and software for market analysis and trading decisions.  Companies such as Jump Trading, Citadel Securities, DRW and others are leading players in high-frequency trading and are often listed among the largest participants in financial markets.

High returns through instant trading: High-frequency trading firms such as Citadel Securities and DRW earn significant profits due to their ability to react quickly to changing market conditions and execute trades instantly. For example, by utilizing high-speed trading systems and sophisticated algorithms, they can make money on even minor price differences between different exchanges or short-term market anomalies.

How you can use algorithmic trading every day:

Algorithmic trading can be used for both short-term trading in financial markets and long-term investing. For example, investment funds can use algorithmic strategies to determine the most efficient portfolio investments based on various factors, including market dynamics forecasts and risk parameters. In everyday life, algorithmic trading can also influence market behavior and asset prices, which can affect the buying and selling of goods and services. For example, automated trading algorithms can facilitate faster and more efficient trading on stock exchanges, which can affect the stock prices of companies.

Remember, before you start legally and loyally participating in trading on financial markets, please follow the rules and regulations of market behavior that minimize risks:

Open a personal brokerage account:

One of the most common ways to participate in trading is to open a brokerage account with a registered broker. Brokers provide access to trade various financial instruments such as stocks, bonds, funds, etc. In doing so, they are required to comply with laws and regulations, monitor compliance with trading rules and protect the interests of their clients.

Use algorithmic strategies in compliance with their regulation: (you can look at previously known strategies of big companies, friends, or come up with your own)

Be mindful of risk. Don't budget your debt money or your paycheck. If you are interested in algorithmic trading, it is important to use strategies that comply with market rules and regulation. For example, you should avoid manipulative strategies such as frontrunning or price manipulation. Instead, you should develop and employ strategies that are based on honest analytical methods and adequate risk assessment.

Adhere to ethical standards and principles:

It is important to follow ethical standards and principles when trading, such as honesty, transparency, respect for other market participants and adherence to confidentiality rules. For example, avoid using confidential information for personal gain or manipulating market prices.

Education and adequate training:

Before participating in trading in the markets, it is important to get adequate education and training in finance and investments. This will help you better understand market conditions, risks and opportunities and make informed investment decisions.

Collaboration with professionals:

When necessary, especially when using complex strategies or instruments, it is advisable to collaborate with financial advisors or asset managers who have experience and expertise in the field and can help make better informed decisions.

Adhering to these principles will help to participate in trading on financial markets legally and loyally to other players, contributing to the efficient and fair operation of market mechanisms.