A Sneak Peek at New Investing Apps

A Sneak Peek at New Investing Apps

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Financial-technology junkies gathered in San Jose, Calif., for a couple of days at the end of April to check out up-and-coming apps and websites at the Finovate Spring conference. Each presenting company was allotted exactly seven minutes to give the audience a live demo of its featured product.

There were a number aimed directly at banks and brokers in the business-to-business space, with a focus on security and “know your customer” functionality. Barron’s was particularly interested in those that can be used by individual investors and traders. Here are our highlights from among the 59 presentations.

CAPITALISE (CAPITALISE.AI), an Israel-based fintech firm, offers a natural-language trading engine that lets the user turn investment ideas into orders, using plain English. You can test an idea, and the app will suggest improvements to make the trade more profitable. You could, for example, tell Capitalise, “Buy 500 shares ofStarbucks if the price drops below $60 and the price of coffee futures drops more than 1%.” You can also specify the conditions under which you’d like to exit, and let your strategy be executed automatically. Capitalise is partnering with Interactive Brokers Group (ticker: IBKR) for order execution, and hopes to partner with other banks and brokers.

QUANTIACS (QUANTIACS.COM) allows traders to write a trading algorithm in its tool, Quantinator, and gives them access to 27 years of data for back-testing. Access to the data and to the open source back-testing toolbox is free. The data include stock prices for the Standard & Poor’s 500, as well as 44 kinds of futures. The tests consider both long and short trades; you can restrict your system if you’d like. You’ll have to be able to program either in Python or on Matlab, so this isn’t for the faint of heart. However, Quantiacs sponsors competitions, and the winning algorithms are made available to hedge funds and other quant traders. Those who use the algorithm pay a management fee, with half going to the developer. This is an interesting way for algorithm creators to profit from their work.