NVIDIA Touts 6,000x Speedup on Key Algorithm for Hedge Funds
May 13, 2019
NVIDIA DGX-2 and accelerated Python libraries provide unprecedented speedup for STAC-A3 algorithm used to benchmark backtesting of trading strategies.
AI platform is delivering more than 6,000x acceleration for running an
algorithm that the hedge fund industry uses to benchmark backtesting of
Financial trading algorithms account
for about 90 percent of public trading, according to the Global
Algorithmic Trading Market 2016–2020 report. Quants, specifically, have
grown to about a third of all trading on the U.S. stock markets today,
according to the Wall Street Journal.
NVIDIA demonstrated its computing
platform’s capability using STAC-A3, the financial services industry
benchmark suite for backtesting trading algorithms to determine how
strategies would have performed on historical data.
STAC-A3 parameter-sweep benchmarks use realistic volumes of data and backtest many variants of a simplified trading algorithm to determine profit and loss scores for each simulation. While the underlying algorithm is simple, testing many variants in parallel was designed to stress systems in realistic ways.
According to Michel Debiche, a former
Wall Street quant who is now STAC’s director of analytics research, “The
ability to run many simulations on a given set of historical data is
often important to trading and investment firms. Exploring more
combinations of parameters in an algorithm can lead to more optimized
models and thus more profitable strategies.”