On Universa’s Black Monday

Last week Zerohedge reported that Nassim Nicholas Taleb’s hedge fund Universa Investments LP made a $US1 billion gain from last week’s Black Monday.

 

Taleb’s success has several potential lessons given his Incerto philosophy:

 

  • Find a contrarian yet possible / plausible future that has optionality and positive expectancy – such as a significant stockmarket correction or VIX change (vega or volatility arbitrage).
  • Map out the possible / plausible future as an event chain or Bayesian belief network / graph  where there is a rapid change in the rate of change (the gamma or second derivative of the delta in options pricing) — such as a Wyckoff mark-down / deleveraging / flash crash event.
  • Use game-theoretic reasoning to foresee how others in the event chain or Bayesian belief network / graph will act.
  • Use ‘out of the money’ optionality to make small losses during regular conditions with outsized gains when your event chain or Bayesian belief network / graph occurs – and the ‘out of the money’ optionality becomes ‘in the money’.

Metis Alpha

I’ve started a TinyLetter account about “Resilience strategies for living in an antifragile world.”

 

Metis Alpha will feature excerpts from my reflective trading diary; on-going PhD work; a reassessment of Masters work in futures studies and strategic foresight; and things I find during personal therapeutic work using cognitive behavioural therapy. The title refers to Nassim Nicholas Taleb’s book Antifragile: Things That Gain From Disorder (New York: The Penguin Press, 2012).

 

The first entry is on the Kovner Effect.

Special Order 937

Special Order 937 from Alien (1979)
Special Order 937 from Alien (1979)

 

In organisational strategic subcultures the decision elite / leadership may have different ranked grand preferences to its followers. Ridley Scott’s film Alien (1979) dramatises this two-level game of principal-agent and moral hazard risks in the revelation that the Weyland-Yutani Corporation’s priority is to retrieve the alien xenomorph for its weapons division, and the USCSS Nostromo crew are considered expendable.

 

The Nostromo crew evoke the MacLeod-Gervais-Rao-Church model of role power dynamics in organisations. Parker (Yaphet Kotto) and Brett (Harry Dean Stanton) are Losers: low-level employees who argue with other crew members about bonuses. The rest of the crew are largely Clueless: Kane (John Hurt) puts the crew at risk when he ventures into a derelict alien spacecraft; navigator Lambert (Veronica Cartwright) is a dedicated worker who becomes emotionally unstable; and captain Dallas (Tom Skerritt) makes bad risk management decisions. Science officer Ash (Ian Holm) is a Sociopath who is aware of Special Order 937 and hides this agenda until Ripley (Sigourney Weaver) discovers it. Ripley transforms from Clueless to possible Sociopath near Alien‘s end and becomes a Sociopath in James Cameron’s sequel Aliens (1986).

 

Special Order 937 is a powerful narrative-like metaphor that has wider applicability. It depicts the potential breakdown or fraying of employer-employee relations in circumstances of disruptive industry change, distressed debt, and organisational restructures. The MacLeod-Gervais-Rao-Church model predicts that Sociopaths will externally transfer the negative risks to Clueless and Loser employees – whilst simultaneously covering this up through selective framing / interpretation of facts, policies, and procedures.

 

Awareness of Special Order 937 gives Clueless employees the opportunity to see the underlying Reality of the organisational strategic culture from the decision elite / leadership’s perspective (and perhaps from a whole-systems viewpoint). This provides some optionality and the potential to become more than Sociopath: a fully sovereign actor who is anti-fragile (Nassim Nicholas Taleb).

Dissecting Steve A. Cohen’s Edge

One of my discarded PhD chapter outlines was on the hedge fund SAC Capital and the insider trading case involving former SAC trader Matthew J. Martoma and the firms Elan and Wyeth. I had hypothesised that SAC founder Steve A. Cohen had developed a specific organisational strategic subculture. Recently, I read and analysed Cohen’s legal defence. Now, The New Yorker‘s Patrick Radden Keefe has written a lengthy article on SAC, Cohen, Martoma, and the insider case’s legal outcomes. I reflected on how Cohen developed his edge:

 

1. Cohen had ignition experiences early on in his career. Keefe and the PBS Frontline ‘To Catch A Trader‘ point to Cohen’s formative trading experiences with the investment bank Gruntal & Company as a likely first encounter with insider trading. Possibly more important to Cohen’s creative psychobiography are his early experiences in learning to perceive fluctuations in stockmarket prices, as told to Jack Schwager. This tape-reading ability has been part of trading education since Jesse Livermore and is echoed in the Market Wizards series interviews that Jack Schwager did with Michael Marcus and Paul Tudor Jones II. Cohen’s early experiences also parallel the role of ignition experiences in the literature on genius and creativity. They also meant that Cohen did not adopt the dominant approaches of fundamental and technical analysis. Instead, he anticipated behavioural finance in looking for catalysts that moved stocks and that led to rational herding and overconfidence behaviours he could trade against.

 

2. Cohen hired a performance psychologist. Keefe mentions but does not name the late Ari Kiev as the performance psychologist who Cohen hired to mentor his traders. Kiev’s books notably The Mental Strategies of Top Traders (Hoboken, NJ: John Wiley & Sons, 2009) draw on his SAC experiences and detail his personal synthesis of elite sports training, game theory, portfolio management, and leadership frameworks. Kiev foreshadowed other performance psychologists such as Brett N. Steenbarger who have worked with hedge funds. In doing so, Kiev and Steenbarger became de facto strategic foresight practitioners, albeit with a different knowledge base to futures studies.

 

3. Cohen created a specific organisational strategic culture. Keefe and PBS Frontline‘s narratives focus on SAC’s competitive culture between rival portfolio managers; the inside discussion of “black edge” as material non-public information; how Cohen ran his trading floor; and how Cohen got the best trading ideas from portfolio managers whilst also insulating himself from their information sources. There are observations here worthy of the third generation literature on strategic culture, and how specific organisations have developed ways to hedge risk and volatility. If Keefe had been familiar with the sociology of finance literature then he might have focused on this more. Now that SAC has transformed into Point 72 Asset Management – to manage Cohen’s estimated $9 billion wealth – we may never really know what went on inside SAC, unless there is further operational disclosure in civil cases, or in trader memoirs.

 

4. Cohen was pro anti-fragile. Keefe tells an anecdote about how Cohen would ask job applicants: “Tell me some of the riskiest things you’ve ever done in your life.” Keefe segues from this into an anecdote about insider trader Richard Lee. But there are several other possible ways to interpret Cohen’s question and why he would pose it to SAC job applicants. Cohen may have wanted to assess how the job applicant conceptualised risk; how they made decisions; and what specific decisions they made when faced by risk. As Kiev identified these are crucial aspects to successful trading. The anecdote also suggests to me that Cohen was pro anti-fragile: options trader and philosopher Nassim Nicholas Taleb’s term for phenomena that become stronger due to volatility exposure. Being pro anti-fragile – and taking considered risks – was in part how Cohen turned an initial $US25 million in the early 1990s into his fortune – as a possible successful example also of the Kelly Criterion risk management strategy.

 

5. Cohen factored in transaction and execution costs. Keefe alludes in passing to how SAC used dark pools – private exchanges that hedge funds use to trade their positions – in order to exit Martoma’s Elan and Wyeth trades. Kiev’s game theoretic reasoning about catalysts and other market participants provided one rationale that was influential in SAC’s organisational strategic subculture. Awareness of transaction and execution costs – and their impact on a trade’s profitability – provide another rationale. In one of the few public statements by SAC staff, Neil Chriss emphasised the importance of considering transaction and execution costs in his introduction to Robert Kissell and Morton Glantz’s book Optimal Trading Strategies (New York: AMACOM, 2003), pp. viii – x. Chriss suggested there was “an efficient frontier of trading strategies . . . Each strategy has a certain transaction cost and a certain risk” (emphasis original) (p. x). He then stated: “no institutional manager can afford not to understand transaction costs” (emphasis original) (p. x). In doing so Cohen anticipated the impact that dark pools, and algorithmic / high frequency trading have had on contemporary market microstructure.

 

There is thus far more to Cohen’s hedge fund success with SAC Capital – his sustained edge over two decades – than what the Martoma insider trading case has revealed to-date. Keefe’s New Yorker profile reveals aspects – but more trading knowledge is needed to piece together Cohen’s secrets from public information sources.

What I’m Reading: Momentum Investing & Hedge Fund Strategies

This week I did some research program planning on hedge funds as strategic subcultures. Some recent material:

 

1. AQR Capital Management focuses on the momentum anomaly as an investment strategy (PDF).

 

2. The investor information for Goldman Sachs Asset Management LP contains some useful information (PDF).

 

3. AQR’s Cliff Asness and index fund pioneer Jack Bogle have a great discussion on active / passive management and pension fund investing.

 

4. BlackRock’s guide to Absolute Return investment strategies (PDF).

 

5. Nassim Nicholas Taleb talks with James Altucher about anti-fragility and uncertainty.

 

6. Slate’s John Swansburg dissects the American myth of the self-made man.

 

7. Wagner Award 2014 submissions to the National Association of Active Index Managers.

 

8. Trend-follower Michael Covel asks: Does momentum investing work?

 

9. Patrick O’Shaughnessy on two ways to improve the momentum strategy.

Wealth Secrets of Financial Elites

How do financial elites gain effortful power? What are their wealth management secrets?

 

Chrystia Freeland’s book Plutocrats: The Rise of the New Global Super-Rich (New York: Penguin Group, 2012) suggests three factors:

 

1. Anti-fragility or positive growth from the interaction of volatility and time. Freeland focuses on forces like entrepreneurship, globalisation, technology and political change. The “anti-fragility premia” is perhaps best discussed in Nassim Nicholas Taleb’s options trading and philosophy work.

 

2. Capital Accumulation as inter-generational wealth creation. Pick a famous dynastic family like the Carnegies or the Rothschilds. Capital Accumulation can be expressed as the positive growth of wealth over time expressed as a Present Value to Future Value cashflow. This process can also be considered in terms of the financial decisions that we make over our lifespan: decisions today set-up the potential favourable conditions for tomorrow. Warren Buffett’s official biographer came up with a memorable image to describe this process: The Snowball.

 

3. Rent-Seeking: Rent-seeking is control of financial / real assets that allow for Capital Accumulation to occur (as an extraction premia). Gordon Gekko exemplifies this in the Oliver Stone film Wall Street. Rent-seeking may be done via entity structures (such as a pass-through vehicle like a limited liability partnership) and through wealth management strategies (such as funds management and legal tax minimisation).

 

Freeland and others suggest that Superstars are able to use these three factors to gain cumulative career and financial advantages.

 

This leads to the following equation for elites: rent-seeking control of PV and FV cashflows + anti-fragility + volatility (where the first two are stronger than volatility, which in the case of events like the 2007-09 global financial crisis, can still lead to significant drawdowns).

 

An example from my own life: the 1998-2008 period of work with The Disinformation Company Ltd (now TDC Entertainment):

 

1. Pick an anti-fragile trend – such as pre-millennialist conspiracy theories in the mid-late 1990s and a web portal platform during the 1995-2000 dotcom speculative bubble.

 

2. Set-up a structure for capital accumulation: TDC as a Delaware-registered company that engaged in book, television, DVD, web, and conference projects and that built an audience.

 

3. Rent-seeking over time via the free cash-flows from the project portfolio.

 

You can find and understand examples from your own life.

Price Signals and Publishing

Today, I received notification that Contemporary Security Policy has accepted an academic article on Australian defence and national security policy I coauthored with Deakin University’s Ben Eltham.

 

Eltham also wrote for Australia’s New Matilda on the late economist Gary Becker and price signals:

 

Becker’s idea of “human capital” has been among his most influential. This is the notion that getting an education is, in a very real sense, investing in yourself. “If you’re in an environment where knowledge counts for so much, then if you don’t have much knowledge, you’re gonna be a loser,” he once said.

Attitudes like this make Becker the patron saint of neoliberalism. As no less a thinker than Michel Foucault observed, Becker saw the rational individual as an “entrepreneur of himself, being for himself his own capital, being for himself his own producer, being for himself the source of his earnings.

 

Juxtaposing what we wrote with Eltham’s analysis offers insights about academic publishing.

 

Research managers have adopted Becker’s advocacy of human capital. This means that academic publishing is often judged on three output measures: (1) journal rankings; (2) academic citations; and (3) the government income a university receives for each academic’s publication.

 

This has some subtle effects on academic publishing. Fields like anthropology or political science — which require fieldwork or extensive modelling — have different publication rates than some laboratory-based science. The latter enables researchers to publish more papers. This creates a Matthew Effect or Winner-Takes-All dynamic: more income is generated and hopefully more academic citations will occur. These outcomes are examples of Becker’s pricing signals: each publication becomes an output of workload activities (for cost and business process management) and a monetisable income stream (for J-curve patterns in entrepreneurial venture capital: an academic will generate more value as their career unfolds).

 

These price signals have anchoring, disposition, and representativeness biases that can lead some research managers to potentially misjudge the effort involved in getting a paper published. This is where Nassim Nicholas Taleb’s heuristic of having ‘skin in the game’ as a published academic author can be important to facilitate judgments. In our case, Eltham and I spent 18 months writing at least three drafts. We had to rewrite sections for two changes in Australia’s federal government. We had to address new literature. Our special issue editor also edited the paper. I edited the endnotes twice. We got extensive, critical, and helpful comments from three knowledgeable reviewers. I also got feedback during an international conference panel — where I met the journal editor — and from seeing other panels on parallel research programs.

 

This also involved a lot of effort and coordination that formal workload models often do not capture.

 

Narrow interpretations of these price signals can also ignore cumulative learning effects. Eltham and I learned several things in writing our just accepted paper. We self-funded the research as academic entrepreneurs. An earlier article draft had a comparison of United States, United Kingdom, and Australian defence and national security exercises that might become a separate article. We started to co-develop a microfoundations model of strategic culture that first arose when Eltham recommended I read Dan Little’s Microfoundations, Methods, and Causation: On the Philosophy of the Social Sciences (Transaction Publishers, 1998). I learned a lot about national security and recent Australian policymaking innovations: a socialisation process.  These are just some examples of what occurred over an 18 month period.

 

Often, research managers bring up price signals in terms of value creation. However, can be in the narrow sense above of a journal ranking; citation metric; or a dollar value for income generated. Whilst these are important they are only part of the full spectrum of potential value creation that can occur when academic coauthors collaborate on a research article or a project. Yet the conversation is often as if tools like Real Options valuation or Balanced Scorecard reporting (which acknowledges learning) were never created. The problem isn’t the use of managerial frameworks: it’s that they can be used in a shallow and superficial way for less-optimal outcomes.

 

Collectively, these challenges mean that academics and institutions alike never realise the full spectrum of potential value creation from an academic publication. Becker saw investment. Foucault saw entrepreneurship. I see the potential for knowledge commons arbitrage. Perhaps that’s why academics enjoy the international conference circuit so much. Sometimes the potential value creation can be more like work-life balance: Taleb wrote Antifragile: Things That Gain From Disorder (New York: Penguin Press, 2012) in solitude, to distill his life experience as an options trader and his love of classical philosophy. Read it on your next study leave period.

The Toronto-Dominion Centre Working

2:30pm – 3:30pm, 30th March 2014

Toronto-Dominion Centre and Bay St financial district, Toronto, Canada

 

Preparation material: Francis James Chan’s The Prop Trader’s Chronicles: Short-Term Proprietary Trading Strategies for Both Bull and Bear Markets (Hoboken, NJ: John Wiley & Sons, 2013).

 

Aims:

 

(i) Understand the geography of Toronto’s financial district.

(ii) Make a psychological connection to Toronto’s bank prop traders.

 

Results:

 

Chan’s book on intraday trading at a Toronto-based proprietary trading firm alludes to inter-firm competition amongst Bay St trading firms. On arrival in Bay St it became clear that Canada’s five major banks — Bank of Montreal, Scotiabank, the Canadian Imperial Bank of Commerce, the Toronto-Dominion Bank, and the Royal Bank of Canada — dominate the area.

 

The dominance of bank proprietary trading desks explains several aspects that Chan had omitted from his description of intraday trading strategies. Chan and others relied on contracts for difference without overnight holdings. They attempted to understand the order flow of market microstructure using Level II quotes from the NYSE and NASDAQ exchanges rather than technical analysis charts. In game theory terms this was Chan’s attempt to use the best available dominated strategies in a predator-prey ecosystem that the banks dominated.

 

The Toronto-Dominion Centre evokes this institutional banking power in Ludwig van der Rohe’s modernist, international architecture. The TD Bank Pavilion, TD North, and TD West buildings impose themselves on the surrounding area. Their tenants include banking, financial services, investment banking, investment brokerage, and private equity firms.

 

On 11th October 2011, I had visited the Tokyo Stock Exchange and formally began a personal research program “to develop a private, low-key, personal vehicle for long-term self-sufficiency.” The Toronto Stock Exchange was closed so I was unable to repeat the experience. Instead, I stood in the TD Bank Pavilion and grasped the essence of institutional banking power evoked in Adam Smith’s satirical book The Money Game (London: Michael Joseph, 1968).

 

Later that afternoon I visited the Toronto Eaton Centre and the Indigo Books & Music store. Indigo’s business and investment book section was a mix of inspirational biographies; retail investor primers; and technical analysis books. Much of this is outdated information from an institutional banking perspective which relies on non-public trade secrets. I bought a paperback copy of Nassim Nicholas Taleb’s Antifragile: Things That Gain From Disorder (New York: Penguin, 2012) as a reminder of the tacit knowledge that a trader may create through personal experience, research, and reflection.

 

The next day I read the new Michael Lewis book Flash Boys: A Wall Street Revolt (New York: W.W. Norton & Co., 2014) which features former Royal Bank of Canada trader Brad Katsuyama – founder of the IEX Group dark pool – and critic of high-frequency trading. Lewis describes RBC as a sleepy backwater compared to Wall Street but this wasn’t my sense when walking past the RBC Centre in Wellington Street West, Toronto.

 

Several days later I learned of a new University of Toronto study (PDF) on how retail traders and high-frequency traders interacted on the Toronto Stock Exchange in 2012. The study felt like a research counterpoint to the Lewis book. The study found that retail investors largely benefited from the market microstructure of high-frequency trading firms.

 

I resolved to do two things over the next five years:

 

1. To develop a greater awareness of how bank proprietary trading desks affect market microstructure using dominant trading strategies in a predator-prey ecosystem.

 

2. To continue to develop a personal knowledge base and decision heuristics akin to Nassim Nicholas Taleb’s published work.

Thriving On Chaos

Thriving On Chaos (1987)
Thriving On Chaos (1987)

 

One of my mid-term career goals is to understand and implement enterprise value management. I’ve started with Tom Peters‘ Thriving On Chaos (New York: Alfred A. Knopf, 1987), an artifact of the late 1980s: United States fears of Japan’s quality revolution; a mergers wave; corporate raiders and leveraged buyouts; middle management restructures; vision; innovation; decentralised information; and urgent change management. In some ways not much has changed in management books: these are still important themes for the higher education sector. I spent 1996 to 2001 reading Peters’ various books, and after a decade’s experience I can appreciate some of his insights, alongside the post-McKinsey thought leadership. Thriving On Chaos anticipates Nassim Nicholas Taleb’s antifragility and barbell strategy.

The Long Gamma Working

The Long Gamma Working

7th September 2013

 

Background

 

On 11th October 2011, I “resolved to develop a private, low-key, personal vehicle for long-term self-sufficiency” in the Nihonbashi Working, held at the Tokyo Stock Exchange in Japan.

 

I had started to trade in Australian financial markets on 8th October 2011. Standard & Poors had downgraded US debt from its AAA rating on 5th October 2011. Over the next several months the European Union’s bond markets also faced a debt crisis which led to austerity policies and intermarket volatility. Simultaneously, my university employer went through a year-long organisational restructure with several rounds of redundancies. I spent this time gathering resources; doing due diligence on early, failed trades; and researching financial markets using the ThomsonReuters Datastream information system.

 

On 30th July 2013 as part of the Sirius XI Working in the Esoteric Order of Beelzebub, I isolated two specific strategies that provided illustrative LBM insights. I was familiar with Charles Mackay’s influential reportage on the behavioural and sociological dynamics of speculative bubbles (Extraordinary Popular Delusions and the Madness of Crowds). In Arnold Van Gennep’s framework (The Rites of Passage), this can involve creating the conditions for rational herding (indirect, contagious, and negative taboo) that leads to crowded trades (identified by Richard D. Wyckoff and others). Alternatively, this can involve active management (animistic, direct, and sympathetic). I found evidence of the first strategy in the Drexel Burnham Lambert, Galleon, and SAC insider trading cases; and for the second strategy in Bill Ackman and David Einhorn’s hedge fund activism.

 

Long Gamma is a long-term illustrative GBM Working to create a preferred financial future, which builds on these insights, past Workings, and on-going practice-based research. The Working title refers to the key strategy that Nassim Nicholas Taleb articulates in his book Antifragile: Things That Gain From Disorder (New York: Penguin, 2012) (TS-5), from his experience with the Greeks (key sensitivities) as an options trader.

 

Goals

 

1. Utilisation of current research on expertise, skills building, and performance psychology.

 

William Chase, Anders Ericsson, Michael Howe and others have popularised strategies for expertise and skills building using cognitive engineering, deliberate practice, and fluid intelligences (from the Cattell-Horn-Carroll model of human intelligence). Chase, Ericsson and Howe’s research provides a more rigorous framework for cognitive modelling than the Neuro-linguistic Programming approach of Richard Bandler, John Grinder, and Robert Dilts. Brett N. Steenbarger, Ari Kiev, Mark Douglas and Doug Hirschorn have adapted these insights to traders’ use of performance psychology. My illustrative GBM immersion in this material builds on my Fluid Intelligence Working (30th June and 1st July 2012).

 

2. Development of a Long Gamma personal trading capability.

 

Long Gamma involves time (theta), volatility (vega), and nonlinear rates of change (gamma). Hedge fund managers use the two strategies mentioned above as an operative LBM strategy to create Long Gamma dynamics that they can profit from at others’ expense. This part of the Working builds on the Oligarchy Working of 30th January 2013. The development of a personal trading capability involves several stages:

 

Stage 1: 2013 – 2015

 

This period coincides with on-going PhD research which may involve a possible chapter on the Department of Justice and Securities & Exchange Commission’s criminal and civil cases against Steve A. Cohen and SAC. I will use this period to codify the two strategies mentioned above, and to develop case based reasoning from Wall Street biographies, history, and contemporary journalistic reportage, in order to make causal, probabilistic inferences from. I will start to develop a trading playbook of insights during this period which can be used for the later development of trading strategies.

 

Stage 2: 2015 – 2017

 

Using the case based reasoning as a starting point, more in-depth analysis of specific filter and trading rules using a Bayesian belief network to model financial markets as a complex adaptive system. Possible areas of analysis might include: (1) the impact of high-frequency trading; (2) the contributions of behavioural finance and market microstructure literature; and (3) predatory trading approaches that target the retail and institutional trader use of technical analysis. The result will be Bayesian decision rules that can be tested in live trading.

 

Stage 3: 2018 – 2020

 

Codify the Bayesian decision rules into cognitive task protocols for discretionary trade and portfolio management processes. Two more long-term options that will be explored for possible quantitative trading include: (1) the use of Markov Chain Monte Carlo simulation to test market data; and (2) the possible development of proprietary trading strategy algorithms. This may be done using a commercial platform like MetaTrader or TradeStation for retail traders; the possible emergence or the reverse engineering of a retail trader accessible option for alpha discovery comparable to Deltix’s QuantOffice for institutional traders; or using the Matlab programming language as an interface to Interactive Brokers or a similar trade execution platform. This will require an understanding of agile software development; machine learning; quantitative strategies; and test driven development.