How much money do high frequency traders make
The traders of most concern to regulators are the ones trying to game the complexity of the market itself for competitive advantage.
Their success has been rooted in gaining the fastest conceivable connections to various markets and doing the best job of parsing vast amounts of trade data. The arms race has yielded numerous firms with different strategies, but observers now put them into a couple of separate categories. One type of firm buys and sells various products on a continuous basis, providing liquidity and quickly closing out its positions to limit ist own risk.
Defenders of these "electronic market-makers" argue that they can help provide liquidity in the markets where they operate. One of these, Virtu Financial, last year became the first high-frequency trading firm to go public. Such big players are becoming more mainstream and more accepted, even by some of the staunchest critics of high-frequency trading. Then there are the traders you hear about when the Securities and Exchange Commission files a lawsuit against them.
Take Athena Capital Research. They're predatory in nature. So far, Washington has handled the issue cautiously. Former CFTC general counsel Dan Berkovitz said regulators have moved away from the question of whether the technology is inherently good or bad.
Now the focus is more about ensuring a fair market structure. Is somebody getting hurt by it? Rather than trying to roll back the clock of technology, agencies overseeing U. The CFTC, which oversees the futures market, has drafted a controversial proposal that would go further, extending its record-keeping requirements to the source code underlying automated trading systems.
The rule, which has yet to be finalized, would require algorithmic traders to maintain repositories that would track changes to their code, which could then be made available to investigators in the event something went wrong in the markets.
During that brief window, the yield on the year Treasury note—a benchmark security critical to funding the federal government—dropped dramatically and then surged, and no one could tell why. Government agencies spent months dissecting millions of data points from the Treasury market to find out just what had happened that day. Their conclusion was unsettling: They still had no idea what had caused it.
What they were able to document, however, was the rise of a new major player in Treasury notes: The agencies found that the firms, privately trading their own capital rather than the money of outside investors, accounted for the majority of trading in this crucial market. High-speed algorithmic trading had long been a big concern in stock markets, where sophisticated but obscure firms with lightning-fast connections to exchanges were forcing regulators to grapple with potential problems, including market volatility.
The findings underscored just how hard it could be to keep markets stable and fair as faster, more opaque players show up. The most aggressive algorithmic trading firms have been viewed with suspicion for years because of concerns that their business is essentially predatory, exploiting tiny technical gaps in the market to the disadvantage of other investors. Though HFT might sound like an inside-baseball issue in the finance world, the debate has bubbled to the point that it has surfaced in the presidential race.
Donald Trump's plans are far less specific. But as criticism focuses on the hard-to-monitor world of automated trading, questions remain—what is harmful trading and who is doing it? The traders themselves defend their work as not only legal, but helpful in keeping markets liquid.
And even if we were to decide the trading is harmful, is there any way to get the horse back in the barn? The technology behind this new breed of trader is part of the fundamental fabric of the markets, used by a wide variety of firms and investors. The traders of most concern to regulators are the ones trying to game the complexity of the market itself for competitive advantage.
Their success has been rooted in gaining the fastest conceivable connections to various markets and doing the best job of parsing vast amounts of trade data.