Futures Traders Embrace Algorithms03.25.2014
Algorithmic futures trading is being used by commodity trading advisors (CTAs), global macro hedge funds, pension funds and asset managers, and those tools can be applied to the emerging OTC swaps dealing facilities known as swap execution facilities (SEFs).
SEFs provide an all-to-all trading mechanism known as central limit order books (CLOBs), which resemble the exchange-traded derivatives model.
“We see significant amount of opportunity in the SEF environment, particularly the CLOB-oriented SEFs,” said Christian Hauff, co-founder and CEO of Quantitative Brokers, an algorithmic brokerage which specializes in interest-rate futures. “That provides benefits in terms of improved execution for the primary users of swaps, the buy side. Traditionally, they had to transact on a mechanism where they were mandatorily required to cross the spread, whereas the CLOB, all-to-all SEFs provide the opportunity to capture spread, which means the a significant reduction in transaction costs.”
SEFs could lead to a bifurcation of liquidity for some products between bilateral trading and multilateral trading through SEFs, said the report. In such a case, there could be an increase in the cost of trading as liquidity fragments.
“Although the regulatory impetus has been to encourage the use of central limit order book (CLOB) protocol, it seems that for the near future, the request for quote (RFQ) and click to trade (CTT) protocols will remain more popular, due to the nature and the volumes of the products being traded.
In a more competitive market, pricing, spreads, and margins are expected to decline,” said Anshuman Jaswal, senior analyst at Celent.
Quantitative Brokers’ Hauff says that the potential for algorithmic trading on SEFs can be realized once the trading venues have been operating long enough to generate sufficient pricing data. “There are some subtleties which have to be researched and engineered regarding the pricing relationships between swaps and some of the other interest rate products we service,” he said. “We sense that we can add a lot of value in transacting into a CLOB or multiple CLOBs simultaneously through our algorithmic expertise.”
According to Jaswal, best execution practices are also expected to change with the evolving market structure, and firms will increasingly decide where to trade, in terms of bilateral and multilateral OTC trading or exchange-based derivatives trading, on the basis of the desired portfolio combination.
Buy side traders use algorithms to efficiently, anonymously, and cost effectively execute their futures trades across global markets.
“Above all, these traders value consistently good performance in line with benchmarks and expectations,” said Hauff. “In this environment, it has become utterly essential for traders to analyze and compare alternative sell side algorithm providers in order to select the best broker to achieve investment goals.”
Quantitative Brokers (QB) is an independent, agency-only broker that services fixed income, equity index, and energy futures traders with a suite of algorithms designed to minimize market impact on outright, spread, and multi-leg inter-commodity transactions.
“We uniquely have been focused on algorithmic execution in futures for over four years in production,” Hauff said. “Our approach is different in that we started with a specialized, niche focus on interest rate futures, and by tackling the complexities of those markets, such as pro rata matching engines, the concept of term structure and the differences between maturities, and volatilities of the underlying instruments.”
QB offers free access to both real-time and historical simulators for back testing and algorithm performance comparison analysis. QB encourages clients to simultaneously route similar actual orders through alternative algorithms to conduct the most realistic performance comparison analysis.
“The simulation environment is where clients can paper trade algorithmically with zero risk, but with all the transparency benefits and also indications of economic value from using an algorithmic offering such as ours,” Hauff said.
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