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The future of financial autonomy – How computer science will shape the financial markets

Historical Financial Practices

It is undeniable that trade and finance have been influenced by the development of technology. From the 1900s to the present day, technology has shaped everyday commerce. Within a century, trading went from intense NYSE chaos to electronic brokers. Modern technology enables simple and large-volume trading for retail investors, while also enabling experienced investors to trade at hypersonic speed around the world. The history of trade revolves around 4 generations of technological breakthroughs and possibly the fifth.


A century ago, all trading was done through a physical location like the New York Stock Exchange. Most of the trading was done in person and a very select group was given the privilege of trading. This system of securities trading is incredibly inefficient and slow. The volume flowing in the financial markets at the time was incredibly small, and much of it was the difficulty of investing.


A few decades later, computers and electronics were listed on the New York Stock Exchange. During this trading phase, bulky computer trades executed more efficiently. However, despite this new financial technology, these computers were still incredibly slow and many American households did not own one.


A few years later, computer science and technology revolutionized stocks and stock exchanges. About 30 years earlier, the Nasdaq Exchange was founded, which, unlike the NYSE, did trading entirely electronically. Alongside the Nasdaq, the rise of retail investors and stockbrokers like Charles Schwab made investing so much more efficient and widespread.


Just recently, popular trading broker Robinhood launched a new concept. The app created the idea of ​​commission-free trading to show how far trading has come because of the technology. In addition, there have been some trade modifications related to autonomy. Bots are designed to execute millions of trades for a fraction of the profit in milliseconds.

Drive into autonomy

As mentioned earlier, trading bots have started to shape the financial world. They have revolutionized digital scalping and have consistently achieved great returns. However, despite the greater popularity of trading bots, much of the bot community is still unexplored and untouched. As mentioned earlier, many of today’s trading bots are used for scalping and day trading, where the autonomy given to the bot is very low. However, as future bots become more accurate and trustworthy, there may be a chance that these incredible bots could make trading completely autonomous.

How can this happen

Today’s bots use technical analysis to accurately execute trades. In many cases, they would look at indicators like RSI, MACD, VWAP, and more to determine when to buy or sell. Well-coded bots have phenomenal yield and great profit potential. However, it will be many years before humans trust bots with their money.

Research analysis

After extensive research, it was concluded that computer science will enable fully automated trading. According to the study, autonomous trading isn’t as daunting or risky as it might seem. In order for the bots to act effectively, thorough and sophisticated code must be developed. Research suggests that bots can choose from a select group of stocks or ETFs to trade. These groups can include the S&P 500 or the Russell 2000 to ensure that the stocks the bot is trading are real and safe. After a selected group of stocks is chosen, a person can tell the bot whether to do scalping, day trading, swing trading or position trading (mostly used for scalping, day trading and swing trading). Next, the bot needs to identify variables through code. These variables will be the indicators for technical analysis, including MACD, RSI, the ability to identify pennants and key levels, and more. The bots can get this information from a third party trading software provider like Bloomberg or Tradingview and apply it to a client’s portfolio.

According to Rickhardypro, a professional data analyst and programmer from the University of Nation World Economy in Bulgaria, he says, “Sooner or later trading will be really quantitatively difficult and the old fundamental investment methods will not work.” He explains how to trade in the near future Future will be automated by variables and numbers as opposed to mental logic as a bot can identify key areas of stocks with precise timing. This gives the bot an advantage over private investors. While this software may seem incredibly challenging, it’s actually not that complex. Instead, the biggest challenge for this type of technology isn’t the technology itself, but rather credibility and trust.

Computer Science Incorporation (variable use)

As mentioned earlier, this type of technology heavily contains software. There are several variables to consider, including 2 separate sets of variables. The first sentence determines a person’s preferred trading style. In this part of the process, the most preferred trading style is assigned a certain value from input from the bot owner, which is used to determine whether the bot is leveraging its scalping or swing trade investing skills. Within technical analysis, the bot uses indicators as variables. These variables are assigned a numerical value depending on how bullish or bearish the indicator suggests. After processing several indicators, the bot will average the numerical value of the bullishness / bearishness of all indicators in order to be able to better judge on the basis of variables whether and for a certain time frame should be executed.

Why not fundamental analysis?

There are two forms of equity valuation in trading. One form is technical analysis in which a trader uses charts, graphs, indicators, and models to decide whether to buy or sell stocks. Another is fundamental analysis, in which a trader positions the trade by holding his stocks for the long term. Although long-term investing is a good approach to trading, precision bots’ fast, accurate, and short-term trades are more profitable because of the bot’s capabilities.


One of the biggest concerns with this type of software technology is trust. With this technology fully supported by software, data breaches and cyberattacks are a major concern for users and merchants. Additionally, this type of technology can conflict with the Securities and Exchanges Commission because of its autonomous system.


Autonomous trade is on the rise. The ability for bots to recognize important buy signals for milliseconds in a row gives them a competitive advantage over many private investors. However, this technology brings with it concerns, and much of it comes with cyber attacks. The future of autonomous bots is uncertain, but it may revolutionize stock trading in the near future.

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