JP Morgan is backing the use of machine learning for the future of foreign exchange algorithmic trading, after applying the technology to its FX algos earlier this year.   

The investment bank launched Deep Neural Network for Algo Execution (DNA) as a tool to bolster its FX algorithms in April, using machine learning to bundle its existing algos into a single execution strategy.

“DNA is an optimisation feature that leverages simulated data from various types of market conditions to select the best order placement and execution style designed to minimise market impact,” said Chi Nzelu, head of macro eCommerce at JP Morgan. “It then uses reinforcement learning – a subset of machine learning – to assess the performance of individual order placement choices.”

JP Morgan added that in recent years, algo trading strategies such as time-weighted average price (TWAP) and volume-weighted average price (VWAP) have multiplied, forcing clients to choose from a suite of algos with various execution methods. As algo trading strategies continue to multiply, and following the launch of DNA, JP Morgan’s intention for the future is to develop a single algorithm to cover all algo trading strategies.

“While DNA is currently an enhancement for certain existing strategies, the future goal is to create one, all-encompassing algorithm that uses available data to provide users with information to improve execution under various market conditions,” JP Morgan said.

JP Morgan said that its decision to create DNA for its FX algos was inspired by technological developments in the equities trading space. The bank launched a proprietary equities trading execution service using machine learning technology in 2017, which also uses reinforcement learning techniques.

“To create the most scenarios and simulated environments possible, JP Morgan developers selected G7 currencies because they are the most heavily traded and therefore have the most data to teach the machine. While still in the initial stage, DNA has demonstrated its ability to push the performance of JP Morgan algos to an even higher level,” the bank said.

Positive end of Summer for the Wizards, but still down on the year for the average performance.

Below are the full results as of end August 2017:

Organisation / Fund Return YTD * AUM **
Abraham Trading1 +1.10% -4.81% $182M
Altis Partners2 +2.79% +6.56% $189M
Aspect Capital3 +3.29% -0.21% N/A
Beach Horizon4 +2.72% -7.14% $108M
Campbell & Company5 +0.66% -0.97% N/A
Chesapeake Capital6 +1.72% -0.27% $143M
Clarke Capital7 +0.51% -22.86% $6M
Covenant Cap. Mgt.8 -0.21% -1.60% $6M
Drury Capital9 +7.27% +1.38% $230M
Dunn Capital10 -0.48% -2.98% $547M
Eckhardt Trading11 +0.95% -1.84% $154M
EMC Capital12 +1.12% -3.16% $50M
Estlander & Partners13 -0.96% -9.74% $122M
Graham Capital14 +2.10% -0.99% N/A
Hawksbill Capital15 -0.20% -20.66% $40M
Hyman Beck & Co.16 N/A N/A N/A
ISAM17 +5.33% -2.70% $3,050M
Lynx Asset Mgt18 +5.07% -6.70% N/A
Man AHL Diversified19 +3.75% +4.48% N/A
Mark J. Walsh & Co.20 -3.62% -11.11% $50M
Millburn Ridgefield21 +3.71% +4.00% $3,094M
Mulvaney Capital22 +2.38% -5.33% $163M
Quantica Capital23 +2.70% +6.55% $450M
Rabar Market Research24 +2.26% +0.44% N/A
Sunrise Capital25 -1.34% -2.43% N/A
Tactical Investment Mgt26 +6.14% +8.90% $72M
Transtrend27 +5.07% -2.31% $3,979M
Winton Capital28 +2.56% +1.16% N/A
Summary Figures*** +2.09% -2.75% $12,635M

Notes * YTD: Year-To-Date performance.
** AUM: Assets Under Management for the program reported here (not total firm AUM)
*** The summary numbers are the mean of the monthly return and the mean of the YTD, with the total sum of AUM, across all managers

Note that the figures referenced in the performance table are not provided directly by any of the funds/CTAs featured in this report, but are sourced from other publications such as hedge fund/CTA websites and databases.

1 – Abraham Trading was founded by Salem Abraham, after he was introduced to Managed Futures and Trend Following by Jerry Parker. He is considered as a “second-generation” Turtle.
Program tracked: Diversified Program.

2 – Altis Partners started trading in 2001 and now manage over a $1B with their Altis Global Futures Portfolio. The figures referenced in the performance table are not provided by Altis Partners and no reliance should be taken as to their accuracy, and as a consequence the figures may not be in accordance with any CFTC / NFA performance reporting requirements.
Program tracked: Global Futures Portfolio.

3 – The four founders of Aspect (Eugene Lambert, Anthony Todd, Michael Adam and Martin Lueck) were significant members of one of the most successful funds in managed futures – AHL (Adam, Harding and Lueck).
Program tracked: Aspect Capital Diversified Program.

4 – Beach Horizon was created as a fully automated trend following subsidiary of Beach Capital Mgt, founded by David Beach. Two of the founders of Beach Horizon had early involvement in AHL.
Program Tracked: Managed Account.

5 – Campbell & Company is one of the oldest Trend Following firms, operating for around 4 decades.
Program tracked: Global Diversified Large.

6 – Chesapeake Capital was founded by Jerry Parker, a former Turtle.
Program tracked: Diversified Program.

7 – Clarke Capital was founded by Michael Clarke in 1993.
Program tracked: Millenium Program.

8 – Covenant Capital is a CTA from Nashville. Program tracked: Aggressive Program

9 – Drury Capital, Inc., was founded in Illinois in 1992 by Bernard Drury.
Program tracked: Diversified Trend-Following.

10 – Dunn Capital was founded by Bill Dunn.
Program tracked: World Monetary and Agriculture (WMA).

11 – Eckhardt Trading is the firm managed by William Eckhardt, who co-led the Turtle experiment with Richard Dennis.
Program tracked: Standard Program.

12 – EMC Capital was founded by Liz Cheval, a former Turtle.
Program tracked: EMC Classic Program.

13 – Estlander is a Finnish CTA, founded by Martin Estlander. Program tracked: Alpha Trend.

14 – Graham Capital was founded in 1994 by Ken Tropin, previously a Director of JWH.
Program tracked: K4-D10.

15 – Hawksbill Capital was founded by Tom Shanks, a former Turtle.
Program tracked: Global Diversified Program.

16 – Hyman Beck & Co. main principals are Alexander Hyman and Carl Beck.
Program tracked: Global Portfolio.

17 – ISAM’s main individuals are Larry Hite and Stanley Fink, both instrumental in the success of MAN AHL. Program tracked: ISAM Systematic Fund Class A

18 – Lynx Asset Management is a multi-billion CTA out of Sweden. Program tracked: Lynx Program

19 – Originally ED & F Man, a commodities broker business founded in 1783. Man became a succesful CTA starting in 1983, when partnering with Larry Hite’s Mint Investments. Subsequently Man gradually acquires AHL (1989-1994) to form Man AHL: the systematic trading division of the Man group.
Program tracked: Man AHL Diversified Plc

20 – Mark J. Walsh was not an official Turtle but trained and worked closely with Richard Dennis before starting his own fund management business.
Program tracked: Standard Program.

21 – Millburn Ridgefield have been trading Trend Following models since the early 1970’s.
Program tracked: Diversified Program.

22 – Mulvaney Capital Management was founded in 1999 by Paul Mulvaney and focuses on long-term trend following.
Program tracked: Mulvaney Global Markets

23 – Program tracked: Managed Futures Program

24 – Rabar Market Research is the company of Paul Rabar, a former Turtle.
Program tracked: Diversified Program.

25 – Sunrise Capital is a CTA based in San Diego. Founded in 1980 by Gary Davis, it merged in 1995 with Commodity Commodity Monitors, Inc., founded by Rick Slaughter in 1977.
Program tracked: Sunrise Evolution

26 – Tactical Investment Management was founded by David Druz, student of Ed Seykota.
Program tracked: Institutional Commodity Program.

27 – Transtrend is a Trend follower CTA based in Netherlands.
Program tracked: DTP – Enhanced Risk (USD).

28 – Winton Capital is a London-based CTA founded by Dave Harding (also co-founder of AHL).
Program tracked: Diversified Program.

 
 
These are the top CTAs/Managed Futures funds in the Trend Following space with:

  • Decades of successful track records (some managers approaching half a century such as Millburn or Campbell, founded in 1971 and 1972 respectively, with other pioneers following suit a few years later: Sunrise, Dunn, etc.)
  • Legendary stories and experience: the most famous of them being the Turtle Traders experiment led by Richard Dennis in the eighties. Nearly a third of the list originate from or were associated with the Turtles (Liz Cheval, Jerry Parker, Bill Eckhardt and more – check the foot notes for details). Also in the list is David Druz, an early “disciple” of computerized trend following pioneer Ed Seykota.
  • Billions of Assets under management: the list captures some top Trend Following managers in terms of AUM, including the “super-large” that are Winton, Man AHL, BlueTrend or Transtrend. Collectively, the Trend Following Wizards manage close to $100 Billion.

 
Several of the traders behind these funds have been involved in the Turtle Trading experiment (2 excellent books on this topic: Complete Turtle Trader – featuring the actual turtle rules and The Way of the Turtle), featured in the legendary books by Jack Schwager: Market Wizards and New Market Wizards, or in Michael Covel’s dedicated Trend Following book.

Banks can’t always afford to put analysts on the ground in developing nations—about the only places where investors can get yield right now. As lawmakers in Brasilia debated a controversial pension overhaul for months, a robot more than 5,000 miles away in London kept a close eye on all 513 of them. The algorithm, designed by technology startup Arkera Inc., tracked their comments in Brazilian newspapers and government web pages each day to predict the likelihood the bill would pass.

Weeks before the legislation cleared its biggest obstacle in July, the machine’s data crunching allowed Arkera analysts to predict the result almost to the letter, giving hedge fund clients in New York and London the insight to buy the Brazilian real near eight-month lows in May. It’s since rallied more than 8%.

Brazil's Lower House Votes On President Bolsonaro's Flagship Pension Proposal
Lawmakers supporting the pension reform bill wave Brazilian flags in the lower house of the National Congress in Brasilia on July 10.Photographer: Andre Coelho/Bloomberg

This is the kind of edge that a new generation of researchers are betting will upend the research marketplace. For Arkera’s clients on Wall Street and in the City of London, that means getting robots to filter through the noise in faraway lands.

“There’s too many people to follow on Twitter, too many websites, too many articles,” said Nav Gupta, the 48-year-old co-founder of Arkera, which says its software can process as much information as 1,000 human analysts. “That’s a very expensive problem and everybody faces it.”

The company raised 4 million pounds ($4.9 million) last year from investors including Alan Howard of hedge fund Brevan Howard Asset Management LLP.

Using so-called artificial intelligence to automate swathes of the research process is quickly gaining traction because cost-conscious investment banks are downsizing. In the U.K. alone, there was a 30% drop in research budgets last year, Financial Conduct Authority data show. At the 12 biggest banks, there’s been a 7% drop since 2015 in the number of front-office staff covering currencies, such as traders and researchers, according to London-based research analytics consultancy Coalition Development Ltd.

That means it’s even harder than it used to be to afford analysts on the ground in developing nations, about the only places in the world where investors can get yield right now.

Data-science companies like Arkera and New York-based Sigmoidal say they can solve this problem using machines that learn as they go to dredge through tens of thousands of news articles, government statements and social media accounts in languages as varied as Spanish, Arabic and Chinese.

After an initial investment of up to $100,000, banks can save $1 million over seven years using such systems because they don’t need to hire as many data analysts, said Marek Bardonski, who was chief executive officer of Sigmoidal when he spoke with Bloomberg in July. He has since left the company. Previously, Bardonski, 27, was a computer scientist at graphics chipmaker Nvidia.

Take this year’s protests in Hong Kong. Bardonski said Sigmoidal’s software was able to track developments in the Cantonese-language press and even identify the non-verified Twitter feeds of protest leaders to monitor the risk of further unrest. The technology is useful for far-away countries wracked by political turmoil, places where investors are keen to put money but don’t have easy access to information.

“The system can give an edge over traditional analysts working for financial institutions,” said Bardonski, who said typical reports will include charts on sentiment, key word statistics and short written summaries. “Instead of getting 100,000 news articles, clients can get all the insights on one page.”

Neither Sigmoidal nor Arkera would let Bloomberg see an example of an automated report to see how readable it is compared with one produced by a human, citing rules against sharing proprietary data. 

In Europe, the way investors consume research has evolved fast since new rules last year forced investors for the first time to pay separately for the analysis they receive. The so-called MiFID II legislation stopped a widespread practice of having the cost of research built into the fees that the likes of Goldman Sachs Group Inc. or Morgan Stanley got paid to execute trades.

The irony is that a year and a half since the rules came into force, many investment banks still offer research for free because clients aren’t willing to pay for it, according to Sarah Jane Mahmud, a senior Bloomberg Intelligence analyst who specializes in regulation. They get around the rules by publishing research on their websites for public consumption.

But the quality has gone downhill because mid-level analysts have left or been pushed out, leaving junior analysts to do the work so their more senior colleagues can go to client meetings. This is giving investors even more impetus to seek out bespoke research, like paying cash to speak with experts in the field or investing in automated research to support their senior fund managers and strategists.

“Asset managers now need to assess the value of every single research service to assess if it’s worth paying for, how much they should pay for it, and trying to filter the good from the bad,” Mahmud said.

relates to Robots Are Solving Banks’ Very Expensive Research Problem
Vinit Sahni and Nav GuptaSource: Arkera

Under MiFID II, asset managers must be prepared to demonstrate they’ve done due diligence on all investments they make for their clients, something that’s always been tricky in developing countries.

It was that very problem that inspired Gupta and his business partner Vinit Sahni, whose careers spanned firms including Citadel LP, DE Shaw & Co. and Goldman Sachs, to set up Arkera in 2015. During their 20-year careers in investment banking, trying to find information to substantiate something felt “like pulling teeth,” Sahni, 50, said.

So the pair set up a team of data scientists and engineers to design a search engine that investors can use to give them an edge in places like Turkey, Mexico and Egypt. It works kind of like Google, only it’s programmed to choose the most relevant sources from tens of thousands of articles, social media feeds and government releases.

As good as robots are getting at deciphering market jargon, even their developers admit they’ll never fully replace humans. In the next decade, Sahni said smart machines will significantly enhance the capabilities of human analysts.

“We will see advancements in cognitive abilities, communication and the physical potential of humans as we collaborate closely with machines and algorithms,” he said.