31st August 2012: Ryan, Rand & Traders

TNR‘s Leon Wieseltier observes about US vice presidential candidate Paul Ryan:

 

“The moral symbol of respect for human beings is the trader,” as John Galt instructs. Self-reliance, which Ryan falsely construed as the trader’s most essential characteristic, became Ryan’s supreme ideal. . . . The splendid isolation of the trader, the builder, the innovator, the entrepreneur, the superman, does not exist. It is one of the many flattering legends that successful people in this country devise about themselves. (Like the legend that success is a proof of personal virtue.) The individual—even the individualist individual—is always situated densely in the customs and the conventions of society.

 

The trader’s key skill is arbitrage: finding mispricings in the market and taking advantage of investor psychology, macroeconomic conditions, timing, and volatility. This requires an intense awareness of who else is on the other side of the trade. It involves Other People’s Money. The cumulative actions of others can change a security’s valuation and market dynamics. Effective trading involves thinking several steps ahead — knowing that other fund managers and traders will be doing the same. This involves both immersion in society’s financial markets and the trader’s cultivation of self-sovereignty as a separateness from it: standing apart to evaluate the probable market dynamics, risks, and arbitrage opportunities. It is why many traders begin with Gustave Le Bon, Charles Mackay, Jessie Livermore, and Charles P. Kindleberger. The ‘isolation’ ideal evolved from Ayn Rand via the 1980s Masters of the Universe to contemporary hedge funds, quantitative funds, and high-frequency trading firms.

Trading Chaos

Williams, Bill & Justine Gregory-Williams.  Trading Chaos: Maximise Profits With Proven Technical Techniques (2nd ed.), John Wiley & Sons, New York, 2004.

The father-daughter authors summarise a personal methodology based primarily on: (1) the technical analysis of oscillations in market securities; and (2) the opportunities for day traders and swing traders to appropriate value from institutional funds through ‘countertrend’ signals which occur in commodities futures and currency/foreign exchange (forex) markets.  The first (1995) and second (2004) editions coincided with the IT and subprime bubbles which created day trading subcultures and market volatility, so it would be interesting to see how the authors have fared during the 2007-08 global financial crisis.

The book’s first half synthesises various ideas on formulating a trading plan and the psychology of market trading.  The ideas include a social constructionist view of money as a holder of value (John Searle); crowd psychology and rational herds in markets (Gustave Le Bon, Charles Mackay); the new paradigm of chaos theory in markets and how fractals and self-similarity create new trading perceptions about pricing and signals (Benoit Mandelbrot), and the popularity of Eastern belief systems amongst traders as models for skills acquisition and stress management (notably Western popularisations of Zen and Taoism).  Thus an awareness of broader intellectual trends can be useful to unpack the building blocks of a system and for comparative analysis with other theorists and models.

Ben Williams’ original contribution is to explain how his background as a psychologist informs his trading approach.  Chapter 7 outlines a generic model of skills acquisition — novice, advance beginner, competent, proficient and expert — that was explored in the book’s first edition, and can be integrated with Agile, CMMI and other frameworks for integrating operations and strategy.  Williams summarises exercises from autogenic training for stress control in the face of market volatility, symbolic interactionist approaches to align the trader’s individual psyche with the market, and cognitive psychology techniques such as cognitive chaining for surfacing deeply held beliefs which lead to self-sabotage and trying to trade out of a losing position without stop losses.  The cognitive psychology approach reminds me of physician John Lilly‘s mid-career work on meta-beliefs and it also parallels recent work in behavioural finance.  However, some descriptions — such as a section on Taoism, Zen and visualising the market as a river which follows the path of least resistance — seem to be closer to New Age beliefs about zero point fields which integrate consciousness and matter than the original metaphysical systems.  I agree these systems can be applied to training however they need far more grounding than detailed here.

From the earlier material on trading approaches, the book’s second half develops a trading system to anticipate the price movements in market securities through fractals and self-similarity which occur in volatility.  It’s always interesting to see how traders justify their approaches and the example trades given.  I’m closer to the adaptive markets, event arbitrage and behavioural finance schools of investing and remain to be convinced about the validity of technical analysis that the Williams propose, beyond the obvious role of pattern recognition.  Actually perceiving nonlinear dynamics and turbulence can be very different to the language and paradigmatic thought that makes chaos theory a popular explanation.

I did experience some perception changes after reading Trading Chaos: (1) charts might be interpreted in a different psychological frame using fractal, self-similarity and volatility metaphors; (2) viewing charts at different timescales (e.g. 1 hour, 1 day, 1 week) might develop the cognition skills to quickly scan signals in a real-time environment; and (3) the juxtaposition of lead and lag signals for trading decisions and triggers has potential, particularly if combined with game theoretic modelling of the market and volatility effects from institutional investors, monetary policy and rational herds.  It remains to be seen if these perceptions are sustainable and verifiable in trading conditions, and not just subjective reactions based on past research about chaos theory models.

That said, the trading system may also have several criticisms and weaknesses. Finding signals in oscillations and nonlinear dynamics may be difficult in a volatile market.  Analysts can be subjective particularly if de-leveraging and other actions by institutional investors are not factored in.  Swing traders may be exposed to market sensitivities (aka the Greeks): Gamma (the rate of change in the underlying security’s price), Vega (sensitivity to volatility), Theta (time-decay) and Rho (time-decay of interest rates).  Finally, modelling turbulence and uncertainty in a grey or white box system remains a major challenge for financial engineers in new market environments.

Threaded throughout Trading Chaos are the mix of useful insights and shibboleths in day trading subcultures.  CNBC, investment experts, and the plethora of courses and newsletters thrive on investor insecurity yet create noise (pp. 34, 42, 56).  Trading decisions, trading volume, and speed and type of momentum may be lead indicators of price volatility (p. 126).  Broad market knowledge purports to trump expert/specialist understanding (p. 135).  Market facts must be distinguished from opinions and beliefs (pp. 8-11).  Trader personalities shape risk tolerance, time horizon, the asset allocation process and types of controls (pp. 92, 155), a factor relevant to human resources consultants and the ‘transition in’ process for trading desks in investment banks.  Analysis risk involves emotions and perceptions of a signal (pp. 52-53).  The interest in Fibonacci numbers and Golden ratios are partly because they are iterative, geometric structures applicable to price movement forecasting (pp. 22-23).  Grey and white box systems with transparent, programmable rules are preferable to expensive, high-end black box systems which use artificial intelligence and neural net algorithms (pp. 53, 56).  A useful bibliography highlights the Santa Fe Institute‘s influence on chaos theory applications in finance and macroeconomics.  It suggests this area needs far more research to verify the claims and provisional findings in this book, to separate the gold from the dross.

Perhaps the most pivotal insight of Trading Chaos is buried in the text.  “We all trade our belief systems.  When some of you think about this, it produces a crisis,” the authors assert.
  Now that could be the basis for a ‘contrarian’ trading system — probably the one that hedge funds with a short/event arbitrage approach use to scalp day traders in currency/forex and commodities futures markets.

Duelling Web 2.0 Scenarios: Boom/Bust

Has Tim O’Reilly’s Web 2.0 meme become a high-tech bubble about to burst?

Origins of the Web 2.0 Boom

O’Reilly’s vision of a new Web platform originally fused two developments.

The first development: C, Smalltalk and object oriented programmers devised design patterns in the early 1990s to reuse software code and workaround solutions across projects.  A 1995 catalog catapulted its four authors to software engineering fame.  To capture the rapidly growing number of design patterns programmer Ward Cunningham created the first wiki: the Portland Patterns Repository.

The second development: a re-evaluation of dotcom era business models to encompass new technologies that enhanced the end-user experience including the site interface and information architecture.  Industry buzz around News Corporation’s acquisition of MySpace (18th July 2005), Yahoo!’s purchase of Flickr (21st March 2005) and del.ico.us (9th December 2005), and Google’s stock-for-stock deal for YouTube (9th October 2006) made O’Reilly’s vision the ‘default’ vision for Web pundits and investors.

The media’s buzz cycle soon went into warp speed as Facebook frenzy replaced MySpace mania.  In a move that exemplified the pivotal role of complementors O’Reilly & Associates morphed into the juggernaut O’Reilly Media.  Ajax and Ruby Rails soon replaced Java and C# as the languages for new programmers to learn.  For activists in community-based media, angel investors investing in scalable programming prototypes and international conglomerates seeking to control their industry white-spaces Web 2.0 provided an all-encompassing answer to venture capitalists on how they would change the world.

Two Scenarios: Web 2.0 Boom & Bust

For industry pundits Google’s decision in October 2008 not to acquire Digg may signal the Web 2.0 boom has become a bubble.  If true Google’s decision could be the mirror of News Corporation and Yahoo!’s acquisitions in 2005.  Slate‘s Chris Anderson points to several factors: no tech IPOs in the second quarter of 2008, the cyclical nature of the digital consumer market, the exit of Yahoo! as a potential buyer due to internal problems, market noise due to low barriers of entry for startups, and a smaller “window of opportunity in which startups can think of a new neat trick, generate buzz, and cash out.”  YouTube’s co-founder Jawed Karim adamently believes that Silicon Valley is in a bubble.

Twitter is the latest startup in the duelling scenarios of Web 2.0 boom versus bust. New York Times journalist Adam Lashinsky experiences a similar euphoria to Facebook and YouTube when he visits Twitter’s co-founder Jack Dorsey.  Sceptics counter that Facebook and YouTube have not ‘monetised’ their business models into profitable revenues.  Portfolio‘s Sam Gustin raises the ‘monetisation’ problem with Twitter co-founder Biz Stone who believes that service reliability is a priority over the “distraction” of revenue pressures.  In support of Stone’s position Anderson observes that cloud computing and open source software are lowering the operational costs and slowing the burn rates of startups.

Yet monetisation remains a primary concern for Sand Hill Road entrepreneurs and other venture capitalists.  They differ in their decision-making criteria to Web 2.0 pundits and high-tech futurists: for angel investors and first round VC funding the entrepreneurs will demand a solid management team, the execution ability to control an industry whitespace, and viable sources of future revenue growth.  This is the realm of financial ratios and mark-to-market valuation rather than normative beliefs and ideals which probably influenced the acquiring firm’s decisions and valuation models in 2005-06.

Furthermore, if a Web 2.0 bust scenario is in play, the ‘contrarian’ sceptics will look to Charles Mackay, Charles P. Kindleberger, Joseph Stiglitz and other chroniclers of past bubbles, contagion and manias for guidance.  With different frames and time horizons the Web 2.0 pundits, high-tech futurists and venture capitalists will continue to talk past each other, creating still more Twitter microblogging, blog posts and media coverage.

Several preliminary conclusions can be drawn from the Web 2.0 boom/bust debate.  In a powerful case of futures thinking O’Reilly’s original Web 2.0 definition envisioned the conceptual frontier which enabled the social network or user-generated site of your choice to come into being.  The successful Web 2.0 startups in Silicon Valley have a distinctive strategy comparable to their dotcom era counterparts in Los Angeles and New York’s Silicon Alley.  Web 2.0 advocates who justify their stance with MySpace, YouTube and del.icio.us are still vulnerable to hindsight and survivorship biases. There’s a middle ground here to integrate the deep conceptual insights
of high-tech futurists with the quantitative precision of valuation
models.

It’s possible that the high-visibility Web 2.0 acquisitions in 2005-06 were due to a consolidation wave and strategic moves/counter-moves by their acquirers in a larger competitive game.  There are two precedents for this view.  Industry deregulation sparked a mergers and acquisitions boom in Europe’s telecommunications sector in the late 1990s comparable to the mid-1980s leveraged buyout wave in the United States.  Several factors including pension fund managers, day trading culture and the 1999 repeal of the US Glass-Steagall Act combined to accelerate the 1995-2000 dotcom bubble.  Thus, analysts who want to understand the boom/bust dynamics need to combine elements and factors from Web 2.0 pundits, high tech futurists and venture capitalists.

If the Web 2.0 boom has become a bubble then all is not lost.  Future entrepreneurs can take their cue from Newsweek journalist Daniel Gross and his book Pop! Why Bubbles Are Great for the Economy (Collins, New York, 2007): the wreckage from near-future busts may become the foundation of future bubbles.  Web 3.0 debates are already in play and will soon be eclipsed by Ray Kurzweil‘s Transhumanist agenda for Web 23.0.