Mutual-fund and other asset managers trying to get the best price on a stock purchase or sale face a formidable challenge from fast-moving high-frequency traders — but managers are not defenseless.
To be sure, it’s difficult to execute large trades when HFTs deploy sophisticated pattern-recognition software in search of order-flow information that they can use to their advantage. When an asset manager unintentionally leaves footprints that tip its hand to these HFTs, the price is often impacted to the detriment of the asset manager.
So what can an asset manager do to prevent this from happening? By answering this question, we can help institutional investors improve their execution, reduce transaction costs, and ultimately deliver better investment returns.
In a recent study, my colleague and I looked into this issue. Our goal was to provide a realistic analysis of the strategic interaction between investors trading for fundamental reasons, such as pension funds, mutual funds, and hedge funds, and traders seeking to exploit leaked order-flow information, such as certain types of HFTs.
We find that asset managers have a powerful weapon against HFTs that exploit order flow information: Randomness.
The dramatic speed of financial transactions can be matched only by the intensity of the controversy surrounding it, especially when it comes to high-frequency trading.
In markets for stocks, futures and foreign exchange, transactions take place in milliseconds to microseconds (or even nanoseconds). Markets for fixed-income securities including corporate bonds and over-the-counter derivatives such as interest-rate swaps are also catching up quickly by adopting electronic trading.
To many, the “Flash Crash” of May 2010 was a wake-up call for reevaluating market structure. A series of technology glitches proved to be highly costly for some brokers, proprietary firms and marketplaces in terms of both profits and reputation. The SEC launched investigations into HFT firms and their strategies. French regulators introduced a financial transaction tax. Author Michael Lewis wrote “Flash Boys.” The list goes on.
With this fallout comes important economic questions: What are the costs and benefits to investors for speeding up trading? Is there an “optimal” trading frequency at which the financial market should operate? And does a faster market affect one group of investors more than another?
Benchmarks are heavily wired into modern financial markets. For example, trillions of dollars in bank loans and several hundred trillion dollars (notional) of derivatives transactions depend on daily announcements of LIBOR. The WM/Reuters foreign exchange fixings dominate the currency markets, in which there are over $5 trillion of transactions per day. Benchmarks are the basis for trade of a wide range of commodities such as gold, silver, oil, and natural gas. They have also been the focus of scandals (Brousseau et al. 2013).
When big investors want to execute trades but fear the size of the transaction could move the market, they often go to dark pools—alternative trading systems where orders are not publicly displayed. These opaque trading venues, now accounting for about 12 percent of equity trading volume in the United States, have sparked concern among regulators and in the financial press. With so many transactions occurring out of public view, critics warn that price discovery, the accurate determination of asset prices, will become more difficult. Read More »