Since the inception of the financial crisis more than five years ago, algorithmic trading
has been under serious scrutiny.
Algorithmic trading, or high-frequency trading
, has come under fire from the Department of Justice (DoJ), FBI, Securities and Exchange Commission (SEC), Commodity Futures Trading Commission
(CFTC), New York State Attorney General and Financial Industry Regulatory Authority (FINRA).
The DoJ, in coordination with the SEC, CFTC and FINRA, has been exploring whether these high-speed firms have been unfairly manipulating market prices to their advantage to the detriment of other investors.
The CFTC has been examining whether the algorithmic firms receive preferential treatment that places other investors at a competitive disadvantage and if they routinely engage in wash trades, acting as buyer and seller to distort the futures markets.
New York State Attorney General Eric Schneiderman has been investigating if these firms have access to data feeds before the general public.
The FBI is also scrutinizing these high-speed trading firms to determine if they receive information that other market participants are not privy to, including client orders before their execution, after-hours trading data used by proprietary traders and brokerage operations such as mutual funds and pension plans. Specifically, they are examining if orders were placed then canceled to encourage trading based on false orders, thereby manipulating the market and whether transactions are constructed to conceal illegal insider trading.
The SEC is looking into whether these firms are using different order types to trade ahead of other investors.
Since 2009, the aggregate revenue generated by high-frequency trading firms fell to $1.1 billion from $7.3 billion, according to Larry Tabb, founder and CEO of TABB Group, a financial markets research and strategic advisory firm.
An abysmal 15 percent of Americans trust the stock market, according to a survey conducted in December by the University of Chicago's Booth School and Northwestern University's Kellogg School of Management.
A recent report from John McPartland, senior policy advisor of Financial Markets at the Chicago Federal Reserve Bank, identifies several strategies used by high-speed traders that seriously distort the market. They include spoofing, layering and stuffing. All involve fictitious trades that are ultimately canceled in an attempt to deceive the investing public of the true aggregate demand and supply of the securities being traded or to delay the accurate and timely reporting of price quotes.
These market distortions enable algorithmic-trading firms to unfairly capture extremely large short-term arbitrage profits at the expense of the public.
McPartland recommends the use of term-limit orders that allocate trades based on the time they are committed. The trade-matching algorithm would occur randomly within half-second intervals, thereby reducing the probability that high-speed traders can game the system effectively.
In addition to these investigations, along with possible prosecutions, positive policy prescriptions like those provided by the Federal Reserve are essential to create a more competitive and effective marketplace that is respected and trusted by the masses.
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