HFT - Robot Wars

Robot Wars

This animated GIF created by the Nanex pictures the rise of high-frequency trading (or HFT) volumes across all US stock exchanges between 2007 and 2012. The initial murmur, the brewing storm, the final detonation: not just unsettling, it’s terrifying.

HFT trading volumes across all U.S. stock exchanges between 2007 and 2012
credit: Nanex Research, hosted by imgur.com

This is what high frequency trading looks like, when specially programmed computers make massive bets at lightning speed.

We don’t know is what the long term consequences are of all this hyper-volume as depicted by the Nanex GIF and the kind of systemic risks created from the market’s ongoing evolution from human traders to rapidfire AI. Sometimes things go wrong, a software glitch, an algorithm gone rogue and the music stops, like a couple weeks ago when Knight Capital lost $10 million a minute when it’s trading platform went haywire or during the infamous Flash Crash when the Dow dropped 1000 points in mere minutes.

Read the excellent full Mother Board article here.

The Ties That Bind

Researchers from Tel Aviv University, in collaboration with the Kiel Institute of World Economy in Germany, have developed a new methodology that measures the interconnections between stock markets across the globe.

It has the potential to serve as an early warning system and provide measures to manage and mitigate the spread of financial crisis.

There’s nothing new in analyzing the correlations between stocks in an individual market, using parameters such as market index and volatility to determine whether prices of stocks will rise or fall in tandem. But with this project, the researchers have introduced the concept of the meta-correlation, in which they measure the average correlation of countries’ stock markets against one another. The result is a precise understanding of how changes in one market impact another. At worst, these connections can lead to a fast spread of financial crisis.

To develop their method, the researchers looked at data from six major world markets — the U.S., the U.K., Germany, Japan, China, and India — from the beginning of 2000 to the end of 2010. Choosing the leading stocks in each market, the team then mapped the correlations between the groups of stocks from each country over the 11-year period. With the exception of China, which tended to operate independently, the researchers discovered an interesting pattern of interdependencies between these markets. Some markets, such as the U.K. and U.S., were closely connected, as predicted. But there were also surprising findings, such the fact that Japan fluctuates in its financial alignment between western and eastern countries.

A Financial Seismograph

According to the researchers, this method of understanding market connections could help each country predict when a financial crisis is imminent, allowing it to set up policies that will protect their own markets from becoming dangerously intertwined with struggling markets. As Prof. Ben-Jacob of TAU’s School of Physics and Astronomy says:

In the current era, when the global financial village is highly prone to systematic collapses, our approach can provide a sensitive ‘financial seismograph’ to detect early signs of global crisis.

Citing Greece’s financial problems and their impact on the European market as a whole, Ben-Jacob’s Ph.D. student Dror Kenett continues:

There are different safety mechanisms that each country can implement. Germany is so invested in Greece that they don’t have an option other than to bail Greece out

noting that if it had been able to see the extent of their dangerous connection with Greece, Germany could have opted to reduce its investments earlier.

Eye in the Sky

Eye in the Sky

The idea that a few bankers control a large chunk of the global economy might not seem like news to New York’s Occupy Wall Street movement and protesters elsewhere. But the study by a trio of complex systems theorists at the Swiss Federal Institute of Technology in Zurich is the first to go beyond ideology to empirically identify such a network of power. It combines the mathematics long used to model natural systems with comprehensive corporate data to map ownership among the world’s transnational corporations (TNCs).

The study determines that global corporate control is far more concentrated than many people think: a core of just 147 firms — many of them financial companies — control 40 percent of the wealth of 43,060 transnational corporations. A broader core of 737 control 80 percent, according to the theorists.

Map of the 1,318 companies at the heart of the global economy

Creating a ‘map’ of 1,318 companies at the heart of the global economy, the study found that 147 companies formed a super entity within this, controlling 40 per cent of its wealth. All own part or all of one another. Most are banks – the top 20 includes Barclays and Goldman Sachs. But the close connections mean that the network could be vulnerable to collapse.

In effect, less than one per cent of the companies were able to control 40 per cent of the entire network

says James Glattfelder, a complex systems theorist at the Swiss Federal Institute in Zurich, who co-wrote the research.

Some of the assumptions underlying the study have come in for criticism – such as the idea that ownership equates to control. But the Swiss researchers simply applied mathematical models usually used to model natural systems to the world economy. Moreover, the value of the study wasn’t to see who controlled the global economy, but the tight connections between the world’s largest companies. The financial collapse of 2008 showed that such tightly-knit networks can be unstable.

If one company suffers distress, this propagates

Glattfelder says.

The data used by the Swiss theorists was from 2007. IMHO that ownership is even more concentrated now. For example, Barclays is at the top of the list from the 2007 data. But Lehman Brothers, which was acquired out of bankruptcy by Barclays, is also on the list. The global financial consolidation that followed the financial crisis has only made the concentration worse.

The top 50 of the 147 superconnected companies

1. Barclays plc
2. Capital Group Companies Inc
3. FMR Corporation
4. AXA
5. State Street Corporation
6. JP Morgan Chase & Co
7. Legal & General Group plc
8. Vanguard Group Inc
9. UBS AG
10. Merrill Lynch & Co Inc
11. Wellington Management Co LLP
12. Deutsche Bank AG
13. Franklin Resources Inc
14. Credit Suisse Group
15. Walton Enterprises LLC
16. Bank of New York Mellon Corp
17. Natixis
18. Goldman Sachs Group Inc
19. T Rowe Price Group Inc
20. Legg Mason Inc
21. Morgan Stanley
22. Mitsubishi UFJ Financial Group Inc
23. Northern Trust Corporation
24. Société Générale
25. Bank of America Corporation
26. Lloyds TSB Group plc
27. Invesco plc
28. Allianz SE
29. TIAA
30. Old Mutual Public Limited Company
31. Aviva plc
32. Schroders plc
33. Dodge & Cox
34. Lehman Brothers Holdings Inc*
35. Sun Life Financial Inc
36. Standard Life plc
37. CNCE
38. Nomura Holdings Inc
39. The Depository Trust Company
40. Massachusetts Mutual Life Insurance
41. ING Groep NV
42. Brandes Investment Partners LP
43. Unicredito Italiano SPA
44. Deposit Insurance Corporation of Japan
45. Vereniging Aegon
46. BNP Paribas
47. Affiliated Managers Group Inc
48. Resona Holdings Inc
49. Capital Group International Inc
50. China Petrochemical Group Company
* Lehman still existed in the 2007 dataset used

The full study is available in PDF format:
S. Vitali, J.B. Glattfelder, and S. BattistonThe network of global corporate control (2011)

Race to Zero

Advances in technology continue to transform how our financial markets operate. The volume of financial products traded through computer automated trading taking place at high speed and with little human involvement has increased dramatically in the past few years. For example, today, over one third of UK equity trading volume is generated through high frequency automated computer trading while in the US this figure is closer to three-quarters.

Unfortunately, there is a downside.

[…] one strange and disturbing episode that lasted a mere 20 minutes on the afternoon of 6 May 2010, beginning around 2.40 p.m. The overall prices of US shares, and of the index futures contracts that are bets on those prices, fell by about 6 per cent in around five minutes, a fall of almost unprecedented rapidity (it’s typical for broad market indices to change by a maximum of between 1 and 2 per cent in an entire day). Overall prices then recovered almost as quickly, but gigantic price fluctuations took place in some individual shares. Shares in the global consultancy Accenture, for example, had been trading at around $40.50, but dropped to a single cent. Sotheby’s, which had been trading at around $34, suddenly jumped to $99,999.99. The market was already nervous that day because of the Eurozone debt crisis (in particular the dire situation of Greece), but no ‘new news’ arrived during the critical 20 minutes that could account for the huge sudden drop and recovery, and nothing had been learned about Accenture to explain its shares losing almost all their value.

Donald MacKenzie – How to Make Money in Microseconds

On that day, the US equity market dropped by 600 points in 5 minutes, eliminating approximately US$800bn of value, and then regained almost all of the losses within 30 minutes. Wow.

After five months of investigation it was found that this “flash crash” was triggered by an algorithm used in an automated trading programme. Fortunately the electronic platform on which these trades were executed had a “stop logic” functionality designed to detect and interrupt such self-feeding crashes by giving human traders time to assess what was happening, step in and pick up bargains.

Algorithmic trading, including high frequency trading (HFT), is rapidly replacing human decision making, according to a UK government panel which warned that the right regulations need to be introduced to protect stock markets. The Government  Department for Business, Innovation and Skills (BIS) has released a very good paper documenting this phenomenon. If you want a deeper view on this subject, it is definitely worth to give it a look: The Future of Computer Trading in Financial Markets | Working paper (pdf file)

The impact of technology developments

On the tech side, the impact is huge as well.  Automated trading involves a bunch of time-critical aspects. Moreover, future trading machines will be able to adapt and learn with little human involvement in their design. There is a compelling article on HPCWire addressing this issues and, again, my advice would be to go through it.

Oddjob

Odd Job(s)

A young boy collecting funds for karate lessons

Have you read my previous post on the US Postal Service problem aka How to cope with human work replaced by technology? Unless an external source of funding comes in, the USPS will have to scale back its operations drastically, or simply shut down altogether. That’s 600,000 people who would be out of work, and another 480,000 pensioners facing an adjustment in terms. Huge numbers. And these issues are going to multiply as many human jobs/tasks will become obsolete due to technology shifts.

Douglas Rushkoff, a media theorist, in a special to CNN says that it’s not about jobs, it’s about productivity models. In other words, it is not a matter of demand and supply of jobs: actually, employment is abundant but we need

a way of fairly distributing the bounty we have generated through our technologies, and a way of creating meaning in a world that has already produced far too much stuff.

Can we organize the society around something other than employment? That is, can we find a third way NOT in the middle between communism and libertarianism in order to shift

the spirit of enterprise we currently associate with “career” to something entirely more collaborative, purposeful, and even meaningful?

Think about social networks. No, I don’t mean logging to Facebook to brag your last caribbean trip. I mean, networks of people who shares ideas, culture, know-how, time. In a single word, work. Not ego-boosting.

We have this idea that we put all this stuff out there and what we get back are intangible or abstract benefits of reputation. But why could not this be monetized?

Why can’t there be a universal marketplace where people could buy and sell bytes from each other, where information would be paid for? It would be much greater than the sum of parts: a future where people could make a living and earn money from what they did with their hearts and heads in an information system, the Internet.

Is the Information Age really replacing Industrial Age?

It seems so, but, IMHO, none of the so-called Internet giants is genuinely addressing this paradigm shift. Consequently, the question is not only “when”, but “how”.

Any hints? 💡