Banks should throw in the towel on proprietary trading, after all the robots have already won
No one really knows if the pursuit of proprietary trading profits is worthwhile as robots and algorithms fight it out- server versus server
“Making America Great Again” means returning American banks to the land of greater profits and returns. President Donald Trump and the US Federal Reserve intend to reintroduce proprietary trading to US banks.
These banks are eager to return to what was once a source of huge profits even though it generated plenty of controversy after the global financial crisis and was eventually closed by the Volker rule in 2010. But the landscape of proprietary and quantitative trading have been reshaped internationally by massive changes in financial technology and computing. You can’t go home again.
Randal Quarles, vice-chairman for supervision of the US Federal Reserve (and a former private equity manager) recently gave his first speech on bank regulation. His discussion of adjusting capital requirements and constraints led to him saying for the first time that regulators have commenced working on a “Volker rule 2.0”. He emphasised that it was a priority of the Fed to change the ban on proprietary trading by banks.
Banks, especially US ones, have complained that the eight-year-old Volker rule has been difficult to implement. Separating trading on your own book versus market making to purely serve clients has been confusing.
Of quantitative trading- especially using algorithms, which increasingly characterises institutional investing. And no one really knows if a return to proprietary trading profits are worthwhile as robots and algorithms fight it out- server versus server.
It’s only natural that banks and investors seek more returns through active investing. After all, it’s human nature to want to beat the market. Post-global financial crisis, while banks have been forced to stay on the sidelines and withhold liquidity from markets, hedge funds finished 2017 with the strongest capital inflows since 2015 driving total industry assets under management to US$3.21 trillion, an increase of US$59 billion according to consultants HFR. And the quantitative sector surged to almost US$1 trillion.
Growing investor interest in computer and system driven investment strategies has become so widespread that it is hard to define the meaning of quantitative investing. From high speed arbitrage processing to day trading, even teenagers trading from their parents’ basement can claim access to algorithms through mobile devices.
Pre-global financial crisis trading rooms of big banks were like cathedrals and fertile grounds for the intellectual cultivation of financial ideas and tactics. Market talk among traders and bankers- immersion in the market, information flow of derivatives, commodities and other businesses was crucial in driving prop trading success.
Post-crisis, almost all trading desks are monitored by compliance officers, to the irritation of traders, who can have their trades stopped for non-compliance. The halcyon days of free wheeling prop traders who conjured up bold ideas off a Bloomberg machine have long disappeared.
Then, came those cold and efficient robots. Quantitative and passive strategies, where computers place most of the orders now comprise 60 per cent of US trading volume, twice the level of a decade ago according to a JPMorgan report.
Today, algorithms utilising cloud data, which is growing to encompass more data, talk to each other, almost replacing human traders. Humans are still needed because regulators will allow financial institutions to outsource and automate work, but not responsibility.
A rush of interest into automated, programmed trading that will eventually be powered by artificial intelligence has forced even traditional hedge funds to recruit data scientists and programmers.
Computing power has only intensified and democratised competition for returns across the market. Like all technology innovations its growth has been explosive rather than linear. It has forced investment strategies to converge around its advantages. If the Volker rule is rolled back for US banks, expect Euro zone counterparts and Chinese financial institutions to exacerbate the competition as they pile in to enhance quarterly profits. The imperatives of mark-to-market and near term profits force asset managers and prop traders to forage for difficult returns in a 30-year bond bull market and nine years of zero to low interest rates.
The golden age of stock pickers peaked in the 1950s and early 1960s, when 90 per cent of all US stock holdings were held by individuals who generally did not understand business fundamentals. Eventually, too many quant funds and passive index funds will force down returns. It will encourage more manually intensive, obscure asset and stock picking approaches.
Ultimately, all the algorithms will compete themselves out. Quant analysts will jump from firm to firm and develop similar models that exploit the same market inefficiencies. As more and more billions chase the same opportunities, the potential returns will decline quickly in a networked world. And then they will have to use increased leverage to earn the same return. Then, the familiar tragedy of systemic over leverage and crowded trades breeds its own woeful outcome for a new generation of geniuses.
Peter Guy is a financial writer and a former international banker