One notable trend within the fintech sector are machine learning big data firms that are focusing on developing products for the trading industry. Developing innovative ways to analyze and use data, many of these firms first started by creating machine learning technology, later adapting it for the financial markets.
Among the reasons for this explanation given by several startups to Finance Magnates is that finance and trading is a natural fit for big data innovation due to the abundance of available data to analyze. In addition, it’s a competitive field of which financial firms are eager to try out new technologies that can potentially provide them with a field. As such, many startup teams that delve into big data and machine learning and are creating solutions for a variety of industries will include finance among their target audiences.
Part of this trend, is machine learning technology firm, Alpaca. Recently announcing the closing of $1 million in seed funding from venture capital and angel investors, Alpaca is building technology that can be used to analyze past data points to build models for the future.
Using its technology, Alpaca has created Capitalico, a machine learning trading platform for analyzing and creating trading strategies. Along with announcing its new funding, Alpaca has also revealed the launch of the private beta stage for Capitalico.
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Speaking with Alpaca founders, they stated to Finance Magnates that when creating Capitalico, the goal was a platform that would allow traders without a programming background to develop algorithmic trading strategies.
A visual-based trading system to highlight chart patterns and find trading strategies
Yoshi Yokokawa, Alpaca CEO and Co-Founder, explained that from personal experience and learning from others in trading forums, it was apparent that there is a large group of discretionary traders who have developed sophisticated trading strategies. This includes chart reading, analyzing market trends and using risk management. However, many of them lack the programming experience to quantify their strategies or to build automated systems.
As a solution, Alpaca designed a visual-based trading system allowing traders to highlight chart patterns that fit their trading strategies. Capitalico then analyzes the chart to quantify potential technical analysis scenarios that were behind the market move. Using this information, traders can then build algorithmic strategies to be used to automate their trading to catch future market moves that fit their strategies.
Having launched its private beta period, Alpaca is currently sourcing beta testers for its product, with a goal to begin public beta at the beginning of the next year. Along with several other big data related startups, Alpaca will be displaying its Capitalico solution at the Fintech Spotlight section of next month’s Finance Magnates’ London Summit.