Emerging Trends in Algorithmic Trading
Algorithm trading is mainly used for High-Frequency Trading (HFT), which involves placing a large number of high-speed trading orders in multiple markets and decision parameters on the basis of pre-programmed instructions. This increases the reach of the market and profits.
Investment partnerships are essentially hedge funds. A group of people deposits a large amount of money under the responsibility of a fund manager who manages the money with the help of his own company. One of the main benefits of a hedge fund is that it can reduce risk and diversification in every portfolio.
The start-up of Silicon Valley Quantiacs has invested $2 million to make algorithmic trade accessible. The business model is fairly easy; the best three trading algorithms on the platform are allocated $1 million, $750 million, and $500 million. The creators of each algorithm pay half the fee for performance. The way hedge funds work in the real world is similar. If the algorithms don't make money, not even the consumers. The last competition to be completed was in August 2017, in which three algorithms were selected from a total of 492. The platform also allows consumers to trade foreign currencies, options, futures, and even cryptocurrencies.
The San Francisco start-up Numerai was founded in 2015 and has invested $7.5 million in developing a platform that regularizes financial data into machine learning problems for a global data scientist network. Although other platforms offer competitive environments, Numerai provides a collaborative platform. Numerai is unique in that it solves the problem of crowdsourcing. The start-up collects abstract financial information and then provides it to data scientists who do not know what the data is. Another unique feature of the platform is that data scientist who solves the cryptocurrency of the platform itself offsets these problems. It is impressive to look at people who count Numerai as investors and advisers.
While hedge funds provide an appropriate solution for the business-to-business algorithmic market, the recent introduction of robo-advisors has made algorithmic trade accessible to individual investors with self-managed portfolios. These automated trade solutions make the selection of individual stocks based on personal risk profiles. And despite an explosive year as an asset class for bitcoin and other cryptocurrencies, algo trade market has a long way to go.