In the previous blog post, we have given a short walk through the history of how the stocks and stock market were born. We can observe that the history of the stock market is the history of the changing economy usually followed by some significant structural changes.
The beginning of computational finance dates back to 1930s when some investors started calculating mathematics formulas to price stocks and bonds. In 1950s Harry Markowitz introduced computational finance in order to solve the portfolio selection problem. One of the major problems was the shortage of computer power at the time what made analysis difficult. Therefore, the mathematical science diverged by making simplifying assumptions to establish patterns in forms that did not require sophisticated computer science analysis.
Further, in the 1960s, hedge fund managers Ed Thorp and Michael Goodkin in collaboration with Harry Markowitz were the first to ever use computers for arbitrage trading. The introduction of a personal computer in the late 1970s and early 1980s brought about an exploration of wide range of computational finance applications. Although, many of the new techniques emerged from signal processing, rather than the traditional field of computational economics e.g optimization and time series analysis.
As a result of the cold war by the end of the 1980s, a large number of physicists and applied mathematicians moved into the study of finance forming new groups of financial engineer and quantitative portfolio managers who started to develop technologies for automated trading as we know it today.
First technologies were, of course, primitive because also the computers were not yet developed, however, they presented the foundations to the technologies we know and use today.
The computerization of the 70s and 80s had a lot of impact on the processing of orders and the exchange of information.
In the 1970s, a Designated Order Turnaround System (DOT) was introduced in the New York Stock Exchange. And what exactly is DOT? DOT is “computerized order entry system that allows orders to buy or sell large baskets of stock to be transmitted immediately to the specialist on the exchange, where execution will occur quickly, depending on the basket size. Also used for odd-lot transactions to occur at the prices and quantities available.” This system for the first time allowed to bypass the middleman — the broker.
The second very important thing that changed the world of finance and trading itself is without any doubt the Terminal developed by Michael Bloomberg and launched to the market in 1981. Bloomberg designed and built the first computer system to use real-time market data to quote stock prices and relay information. Bringing revolutionary innovation to the field nearly forty years ago, today, it is developing highly sophisticated technology that monitors, tracks, and collects huge amounts of data offered then to the subscribers of the Bloomberg Professional Services. How important the emergence of Bloomberg was for the financial industry speaks the fact that the Terminal found its way to the Silicon Valley’s Computer History Museum that traces the history of financial technology and to the Smithsonian’s National Museum of American History.
By the late 90s, the SEC ruled in favor of creating electronic stock exchanges, although the first electronic stock market NASDAQ dates already to 1971. However, this laid the groundwork for a new type of trading: algorithmic trading. We are talking about the trading platforms that execute buy and sell orders based on an algorithmic computer program that is capable of carrying out trading strategies a thousand times faster than traditional human-to-human stock trading. The impetus of the algorithmic trading is to automate and enhance some trading strategies like arbitrage, intermarket spreading, market making, and speculation. The modern approach to the development of algorithmic trading is focusing on implementing machine learning and deployment of Artificial Intelligence in order to achieve optimal automation of trading processes.
At RIALTO.AI, we are developing automated algorithms for cryptocurrency arbitrage, market making, and prediction trading. On our platform, users have until now been able to use arbitrage and market-making algorithm, but as of next week, we will also offer the prediction trading bot.
The end of the Q2 2018 marks an important stage in our development. We are proud to announce that our prediction trading bot is ready and we have started deploying it to our platform. Alongside the existing arbitrage and market making algorithm, the bot will be available on platform as of Monday, July 9, 2018.
Stay tuned to find out about the results of the bot’s testing period we are going to publish next week and make sure you don’t miss any of our updates by following our social media channels and subscribing to our newsletter.
