Sell-Side Technology Awards 2020: Best Sell-Side Automated Trading Platform—Tethys Technology

Sell-Side Technology Awards

Tethys Technology picked up the award for the best automated trading platform at this year’s Sell-Side Technology Awards, thanks to its Sellside Solutions offering, breaking FlexTrade’s three-year stranglehold on the category. The company’s global trading solution is a low-latency, multi-asset class, algorithmic trading platform. TethysEMS, TethysOMA, and TethysAlgo were combined to create the offering, which encompasses intra-dealer center connectivity and a cloud-based algorithmic trading suite. “There are several execution management system (EMS) and order management system (OMS) offerings in the market, and the niche we’ve focused on since the company was founded was all about automation in the sense that we saw where things were heading,” explains Nitin Gambhir, founder and CEO of New York-based Tethys Technology. 

Nitin Gambhir, Tethys Technology
Nitin Gambhir, Tethys Technology

The TethysEMS platform supports FIX, API and manual order flows and enables clients to trade global equities, futures, options and foreign exchange, in addition to supporting cross-asset algorithmic trading functions. Gambhir says the company has developed templates that cater to a wide variety of investment strategies. “Most investment managers today have complex strategies, which might include trading pairs, trading baskets and trading different assets like options,” he says. 

Tethys facilitates strategies for various investment styles, which can be deployed immediately or customized according to clients’ preferences. According to Gambhir, for any form of automation to succeed, there are two parts to the formula: The first step is to automate the workflow, while the second pertains to the quality of the results obtained on the back of automated and optimized workflows. “Automation doesn’t only mean that your workflows are automated; it should also result in the trading outcomes that you can measure properly so that you can calibrate and benchmark them,” he says.

Since 2014, the company has sought to incorporate machine learning into its execution algorithms with the aim of predicting short-term volatility, volume and alpha. According to Tethys, the models implemented in the last six years have improved clients’ execution performance by approximately 17%. 

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