Personal Goals for 2015

Some personal goals for 2015:


1. Complete a full PhD draft (two chapters plus rewrites). Model the rewrites on the chapter / structure / paragraph format used for the Princeton Studies in International History and Politics and using the methodology insights of the Cambridge Series in Political Science Research Methods. Submit PhD-related presentation proposals to International Studies Association for possible inclusion in the 2016 annual convention.


2. Develop an Academic Moneyball framework (one page) for business development / contract management / research management activities. Draw on asset management, hedge fund, private equity, and value creation domains – for active management – in order to develop the Academic Moneyball framework. Note relevant insights in one paragraph (the Aramchek model) from Russia’s Putin regime on leadership and value appropriation in bureaucracies that also face volatility from international capital markets (some potential background reading: Putin vs. Putin; Putin’s KleptocracyHow Russia Really WorksThe Social Construction of Russia’s Resurgence; The Man Without A Face, and Nothing Is True and Everything Is Possible). Distill into a rolling 100-day action plan (one page) and work breakdown structure (Work Breakdown Structures: The Foundation for Project Management Excellence).


3. Continue to keep a reflective diary on trading systems development. Develop one-page algorithm pseudo-code for momentum, trend-following, and value-based strategies – decomposed from the relevant academic research and practitioner literature – with awareness of stream-based processing methods (Fundamentals of Stream Processing).


4. Complete a personal program of Cognitive Behavioural Therapy and attend a Mindfulness meditation group.

Speculative Bias: Young, Male, Poor, Overconfident

Since 2012, whilst holidaying overseas, I visit the finance / investment section of bookstores as a barometer on their business climate. This year in Toronto, Canada, I visited Indigo Books in Fairview Mall. It had a number of books on technical analysis: reading price / volume charts to make investment and trading decisions.


TA was popular from the mid-1970s until the 1987 stockmarket crash and regained popularity during the 1995-2000 dotcom crash. Since about 2003 it’s been a dead methodology — at least in its vanilla, popular treatments — due to high-frequency trading. TA books however continue to sell to uninformed retail investors.


Arvid O.I. Hoffmann and Hersh Shefrin’s new study of 5,500 trader accounts at a Dutch discount brokerage between 2000 and 2006 has some sobering insights on TA and retail traders:


  • The study period coincides with the 2000-01 dotcom crash and the mark-up period of the 2003-07 speculative bubble in real estate.
  • TA appeals to young, male, poor, overconfident traders who want to speculate or who treat trading as a hobby.
  • TA traders had more concentrated portfolios than those who used fundamental analysis or professional advice.
  • TA traders had higher turnover; personal ambition; a short-term timeframe; and often did not consider transaction costs or taxation implications.
  • The average portfolio size in this study was $60,589 and the median age of traders was 49.79 years of age.
  • The 95th percentile included traders aged 70; who turned over their portfolios 98.19% per month; who did 43.06 trades per year (mean of 10.66 trades per year); who had 72 months experience or 6 years experience (mean of 40.21 months experience or 3.35 years); and whose portfolio was valued at EUR166,840 compared with a median of EUR15,234 and a mean of EUR45,915.


Hoffmann and Shefrin’s study suggests several things to me:


  • There are at least two identifiable sub-populations: (1) young traders who try to compound their risk capital to get rich; and (2) older investors using savings and retirement money.
  • Most traders last less than 3 years. Many over-trade or blow-up their accounts within 10-to-15 trades – in part due to very small trading accounts.
  • TA appeals to new retail traders who are really trading on rumours that can be traced back to Martin Zweig (“The trend is your friend”), Jesse Livermore, and the Edwards / Magee school of TA.
  • Interest in trading occurs at distinctive life stages: early twenties (get rich); late forties (save for retirement); and post-retirement (create a financial buffer for future spending).
  • Some trader success is due to the hot hand effect of winning streaks – which may in a social network influence a new cohort of traders – for what was more luck than skill.
  • TA traders attempt to mix indicators / signals and psychology (state management). Yet the real gap for retail traders is an understanding of transaction / execution costs.


Hoffmann and Shefrin’s study suggests several things to me about myself:


  • I’m in what Paul Fussell calls the High-Proletarian level of the middle class: university educated; but without the financial security of Fussell’s Upper Middle class.
  • I had encounters with financial markets from my early teens to my early twenties, but was not an investor in early life due in part to the adverse experiences of recessions and stockmarket crashes.
  • My serious interest in financial markets emerged after formative experiences around the 1995-2000 dotcom crash; the 1998 collapse of Long-Term Capital Management; and an encounter with Sir James Goldsmith’s life philosophy in 1995, re-explored in 2010.
  • I began research in 2009 and first traded on 5th August 2011 – days after a ratings agency downgrade in United States sovereign debt and into a Eurozone financial crisis.
  • I started with an account size in the 25th-30th percentile of the study – about $A5,600 to trade. I soon ran into psychological barriers about getting out of trades in a deteriorating market situation where I had hoped a market retracement might occur. I continued to hold positions despite passing my stop-loss limit.
  • This loss aversion led me later to more closely study the research on behavioural finance. I found that my initial trading hypothesis was correct — but the reason why was that it was also being ‘gamed by convertible arbitrageurs, prop desk traders, and high-frequency trading firms. I lost several thousand dollars before I exited the trade. In October 2011, whilst in Tokyo, Japan, I put the pieces together involving a series of trades by the Mitsubishi UFJ Bank which was warehousing trades for foreign hedge funds. This involved a Gurdjieffian shock – I knew what to do but emotionally I was unable to Act at the appropriate time to exit the trades. I sat in the Starbucks above the Shibuya Crossing and considered the implications.
  • This initial experience in live trading led me to pull back and examine what I knew about financial markets; what algorithmic and high-frequency trading was; why retail traders fail; and how professional traders work.
  • From 2011 to 2013, I bought most of the core literature on finance, wealth management, funds management, trading, behavioural finance, and market psychology to fill in some major knowledge gaps. This led to what will possibly be a post-PhD strand in my research program on the sociology of finance, and hedge funds / private equity funds as strategic subcultures.
  • From 2011 to 2014, I made a series of personal oath-promises to myself about personal self-sufficiency (Nihonbashi), long-run gains (Long Gamma), and shifting from a naive retail trader to understanding the institutional mindset (Toronto-Dominion).
  • Rather than trade I dealt with saving for retirement via employer defined contribution plans, employer co-payments, and legal tax minimisation strategies.
  • Rather than TA signals I began to study market microstructure (the study of price dynamics in order book flows) and money market flows between funds. Recently, I have downloaded several Springer books on high-frequency econometrics from a university database.
  • I found the major lesson about trading was about the psychology of decision-making and money management. These are skills I Needed to learn yet lacked.


In conclusion I fit one of Hoffmann and Shefrin’s sub-populations and past trading strategies. Reading their study is an important ‘reality check’ that helps me to identify what I can change to build a more resilient financial future. At least, I didn’t lose a million dollars.

Trading Lineages

For about three years I have been looking at financial markets as part of a practice-based research program. This past week I honed in on some specific material for a longer-term project. I then realised that much of the research material is traceable to several key sources.


In the 1980s, Stephen Brill’s American Lawyer Magazine helped develop the careers of several financial investigative journalists. Connie Bruck (The Predators Ball) and James B. Stewart (Den of Thieves) documented the insider trading scandals involving Ivan Boesky and Michael Milken, who both influenced Michael Douglas’ portrayal of Gordon Gekko in Oliver Stone’s film Wall Street. I recently discovered that Jim Cramer (Confessions of a Street Addict) was briefly at American Lawyer Magazine at the same time as Bruck and Stewart: Cramer founded a hedge fund, was involved in, and is now a high-profile CNBC presenter. Bruck and Stewart’s detailed reportage foreshadowed the recent insider trading cases involving the Galleon and SAC hedge funds. Cramer’s experience is far more cautionary.


Another personal influence is the work of performance psychologists who have worked with traders. Ari Kiev (The Mental Strategies of Top Traders) worked with SAC’s Steve A. Cohen. Brett N. Steenbarger (The Psychology of TradingEnhancing Trader Performance) has worked with several firms including SMB Capital, where Mike Bellafiore (One Good TradeThe Playbook) and Adam H. Grimes (The Art and Science of Technical Analysis) have influenced proprietary trading firms. I have found that performance psychology insights can be applied to other areas of my life.


Finally, I have picked up specific insights from Market Wizards traders like Linda RaschkeMichael Steinhardt, and Larry Williams, who each have lineages of hedge fund and trading students.


Collectively, this work from American Lawyer Magazine, performance psychologists, and specific traders continues to shape my on-going, practice-based research.

The Long Gamma Working

The Long Gamma Working

7th September 2013




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.




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.

On Informal Research Collaboration


This week on the plane trip to ARMS 2013 — the Australasian Research Management Association‘s annual conference — I came across this passage on the value of informal research collaboration in John Coates‘ award-winning book The Hour Between Dog And Wolf: Risk-Taking, Gut Feelings, and the Biology of Boom and Bust (London: Fourth Estate, 2012):


I came across a likely suspect purely by chance. During the later years of the era I was fortunate enough to observe some fascinating research being conducted in a neuroscience lab at Rockefeller University, a research institution hidden on the Upper East Side of Manhattan, where a friend, Linda Wilbrecht, was doing a Ph.D. I was not at Rockefeller in any formal capacity, but when the markets were slow I would jump in a taxi and run up to the lab to observe the experiments taking place, or to listen to afternoon lectures in Caspary Auditorium, a geodesic dome set in the middle of that vine-clad campus. Scientists in Linda’s lab were working on what is called ‘neurogenesis’, the growth of new neurons. Understanding neurogenesis is in some ways the Holy Grail of the brain sciences, for if neurologists could figure out how to regenerate neurons they could perhaps cure or reverse the damage of neuro-degenerative diseases such as Alzheimer’s and Parkinson’s. Many of the breakthroughs in the study of neurogenesis have taken place at Rockefeller. (pp. 20-21).


Wilbrecht now runs the Wilbrecht Laboratory at University of California, Berkeley. Coates’ exposure to Rockefeller University’s research environment deepened Coates’ perspective on the financial trading he oversaw at Goldman Sachs and Deutsche Bank. This experience likely also influenced Coates’ research program at Cambridge University on the interaction of human physiology and financial markets. The Wellcome Trust, the UK Financial Times, and others shortlisted Coates’ book for 2012 book awards. The Economist and Financial Times both praised Coates’ research. Informal research collaborations can lead to ‘ignition’ or ‘shaping’ experiences that develop researchers, and that combine insights from several domains: Wall Street trading and neuroscience research for Coates.

17th July 2013: NEO-PI-R Personality Test Results

I took the NEO-PI-R personality test again recently (here), on the Big 5 personality  traits, whilst reading Jason Williams’ book The Mental Edge In Trading (New York: McGraw-Hill, 2012).


The individual weights have changed slightly over the past two decades, but are broadly similar to personal results from the Myers-Briggs, Enneagram, and McQuaig Survey tests. As with any test there are anchoring/representativeness biases and life experience factors that affected the weighted scores.


The NEO-PI-R test describes me as active, independent; an outsider; intellectual with artistic interests; fact-oriented; disciplined; achievement-striving (work-obsessed); cautious; friendly; have high self-efficacy; can be altruistic; aware of emotions; and politically liberal.


(This fits a trading style that is research/trading system focused, with an emphasis on distressed debt/value and event arbitrage approaches.)


Using Williams’ descriptions, the NEO-PI-R reveals my Personality Style as:


Style of Well-Being: E- N- (Low Keyed).

Style of Defense: O+ N- (Adaptive).

Style of Interests: O+ E- (Introspectors).

Style of Anger Control: A- N- (Cold-Blooded).

Style of Impulse Control: C+ N- (Directed).

Style of Interactions: A- N- (Competitors).

Style of Activity: C+ E- (Plodders).

Style of Attitude: A- O+ (Free-Thinkers).

Style of Learning: C+ O+ (Good Students).

Style of Character: C+ A- (Self-Promoters).

16th June 2013: My First Trade

My First Trade
My First Trade (click to enlarge)


Foreign Policy‘s Dan Drezner asks: “Hey, remember when Standard & Poor’s downgraded U.S. sovereign debt back in 2011?”


I sure do.


S&P downgraded US debt on 5th August 2011. I placed my first trade on 8th August 2011: 1041 ASX:LYC @$1.92 ($2003.31 including $15 brokerage fee).


(ASX:LYC closed Friday +4.44% @$0.47. I caught the tail end of the 2008-10 speculative bubble in rare earths. Lynas Corporation has since faced project delays in Malaysia; activist lawsuits; headline risk; and regular ‘shorting’ due to convertible bond arbitrageurs and exchange traded funds. I entered the market on a distribution phase — expecting a further rise — and instead faced a markdown, in terms of Richard D. Wyckoff‘s technical analysis methodology.)


The next five or so months got very interesting regarding market volatility and contagion effects. I read up again on international political economy. I also learned more about transmission shocks; political risk; hedge fund activism; and share ‘warehousing’. In October 2011, I did some further research whilst on holiday in Tokyo, Japan, including an eventful visit to the Tokyo Stock Exchange.


Drezner and I are both political scientists. One book I turned to was Timothy J. Sinclair’s The New Masters of Capital: American Bond Rating Agencies and the Politics of Creditworthiness (Ithaca, NY: Cornell University Press, 2005). A gem I discovered by accident in Sinclair’s book was about how Victoria’s conservative Kennett Government used S&P and Moodys ratings downgrades in 1993 to cut $A730 million “from Victoria’s education, health, and other programs” (Sinclair 2005: 103). In 1992, my father had co-founded Victoria’s nursing agency Psychiatric Care Consultants, which responded to the new competitive market environment. So, the S&P and Moodys downgrades had deeper personal and familial significance.


These examples illustrate how research can change the researcher.

6th January 2013: The Failure Test Entry Working

The Failure Test Entry Working

3:30-8:30pm, Saturday 5th January 2013

Melbourne, Australia


Preparation Material: Adam H. GrimesThe Art and Science of Technical Analysis (New York: John Wiley & Sons, 2012); Margery Mayall’s University of Queensland sociological research on technical analysis; BusinessSource database search on academic research into technical analysis, and trader development and learning; and behavioural finance and psychological tests.




(i) Identification of trading personal goals for 2013.

(ii) Illustrative understanding of technical analysis as a trading methodology for alpha generation.

(iii) Consideration of learning barriers to trader development.


Technical analysis (TA) is the study of group psychology in financial market using price, sentiment, and volume indicators, and pattern recognition. It arose in a modern context due to Charles H. Dow and Richard Schabacker’s study of market patterns in the late 1800s-early 1900s. Robert D. Edwards and John Magee’s Technical Analysis of Stock Trends became the TA bible of market patterns later promulgated in variations by Martin Pring and others. Richard D. Wyckoff (the Wyckoff Method), Robert Prechter (Elliott wave theory), and other TA theoreticians have made influential contributions. TA focuses on identification of trends, retracements, breakouts, pullbacks, support and resistance. It anticipated some aspects of current academic research programs on behavioural finance and market microstructure but from a trader or practitioner viewpoint.


Academics and traders remain divided on TA’s efficacy. In 1934, Alfred Cowles contended that a ‘buy and hold’ strategy beat Dow Theory trading. Early studies from 1966 to 1970 by Eugene Fama and his University of Chicago colleagues found that TA filter rules were unprofitable once transaction and execution costs were considered. Fama’s finding led academics to focus on the Efficient Markets Hypothesis, and, ultimately, mutual fund and passive index fund products. In contrast, TA became popular in the mid-late 1970s amongst trend-following Commodity Trading Advisors on volatile commodities and foreign exchange markets. The ‘housewives of Tokyo’ who speculated on currency movements now challenged the ‘gnomes of Zurich’ or institutional investment managers. Victor Sperandeo who traded for George Soros used Dow Theory. The bootlegged PBS documentary ‘Trader’ (1987) shows Paul Tudor Jones II and Peter Borish using Elliot wave theory and 1929 price data to predict a stockmarket crash in early-mid 1988. Finance theories in academic journals and hedge fund manager practices diverged into parallel universes.


Recent academic research has shed new light on this academic-practitioner divide. In a review of 95 academic studies on TA from 1960 to 2004, Cheol-Ho Park and Scott H. Irwin found that “56 studies find positive results regarding technical trading strategies” (“What Do We Know About the Profitability of Technical Analysis?, Journal of Economic Studies 21:4 2007, p. 786). They note data snooping problems with Edwards & Magee-style pattern recognition which other academic researchers have also identified. Importantly, Park and Irwin found that TA was profitable in spot foreign exchange and futures contracts “from the late 1970s to the early 1990s” involving “unlevered annual net returns of 2-10%” (Park & Irwin 2007, p. 795). This finding reflects the period when Sperandeo, Jones, Borish, and other non-TA traders like Martin Zweig were ascendant in financial markets. It contradicts the earlier findings of Cowles and Fama that TA has always been unprofitable.


Park and Irwin’s finding about TA’s period of profitability is also mirrored in other post-1988 academic studies. These find that the traders used arbitrage on anomalies; the transmission shocks of central bank monetary policies; the anchoring, crowded exits and rational herding of institutional investors; and changes to the international monetary system and political economy. However, these studies often fail to link their finding to the practitioner literature which offers independent confirmation, such as Jones II’s interview in Sebastian Mallaby’s More Money Than God: Hedge Funds and the Making of a New Elite (London: Bloomsbury Publishing, 2010). TA practitioners like Jones II were also often aware of the speculative bubble literature—Charles Mackay, Gustave Le Bon, Charles P. Kindleberger, John Kenneth Galbraith, and Hyman Minsky—which has inspired contemporary research in behavioural finance. This is why Gordon Gekko’s apartment in Wall Street: Money Never Sleeps (2010) had pictures from the Dutch Tulip bubble (1636-37). The conceptual gap between TA and behavioural finance is perhaps not as large for financial market practitioners as some academic researchers believe.


The decline in TA profitability after the early 1990s can be attributed to changes in central bank policy coordination, market microstructure, and the growth of algorithmic trading. For instance, the Wyckoff Method identifies institutional trading and market patterns also found in Robert Shiller’s study of ‘irrational exuberance’ and speculative bubbles. But the growth of new trading—options, futures, and high-frequency systems—have altered what the Wyckoff Method found in pre-World War II financial markets.  Collectively, the above developments over the past two decades have changed markets and volatility from trending to more range-bound dynamics. Edwards & Magee’s TA indicators, and support and resistance levels, can now be programmed into algorithms that actively trade against institutional and retail traders who still use traditional TA methods. This Darwinian-like evolution has led to the demise of dotcom era day traders (1995-2000), and trend followers who benefited from asset price valuations due to housing and commodities speculative bubbles (2003-2008).


Academic researchers rarely refer to the TA practitioner literature beyond introductory books by Alexander Elder, Van Tharp, and other authors. Academics often state incorrectly that TA remains unstructured as a knowledge domain: Edwards & Magee, the Wyckoff Method, Elliott wave, Fibonacci, Japanese Candlesticks, and other major TA methods and schools each have their exponents and adherents. Instead, TA now involves an industry of books, consultants and custom indicators targeted at the retail investor. University of Queensland sociologist Margery Mayall found that TA indicators shaped the self-beliefs, mindsets, and decisions of the Australian retail traders who she interviewed. Some of Mayall’s retail traders became focused on the never-ending Holy Grail Quest to find the ‘right’ TA indicator or system.


In contrast, proprietary trading desks now combine TA with behavioural finance, game theory, and market microstructure. Professional traders seek what Michael Steinhardt called contrarian ‘variant perception’ in financial markets compared with the ‘consensus perception’ of retail traders. There is always someone else on the other side of the trade even if it is a market-making algorithm. Academic researchers could bridge the gap with TA practitioners if the popular models were evaluated and back-tested in a more rigorous manner. However, recent work by Andrew Lo and other authors on rehabilitating TA remains at the interview or memoir stage, rather than using a robust empirical research design. Recent TA practitioner work by Adam H. Grimes, Xin Xie, Charles D. Kirkpatrick II, Julie R. Dahlquist, L.A. Little, David R. Aronson, and others looks promising. Grimes links TA and trader development to George Leonard’s Aikido model of self-mastery; to Daniel Kahneman’s prospect theory and behavioural finance study of cognitive biases; and to Mihaly Csikzentmihalyi’s study of creativity, flow, and optimal experience. This augments earlier work by the late Ari Kiev, Brett N. Steenbarger, and Mark Douglas on trading and performance psychology.


Since circa 1992, a subset of TA academic research has also used genetic algorithms and high-frequency tick data analysis to identify trading rules. The findings from this research often either remain proprietary or reflect mathematical and quantitative models. Hedge fund managers who use TA are closer to Aaron C. Brown’s Bayesian risk managers who revise and update their beliefs. Such hedge fund managers are often aware of confirmation bias, the disposition effect, overconfidence, model risk, and other cognitive biases identified in the behavioural finance literature. Hedge fund managers and professional traders now use TA in a mixed methods approach – if they have not already been replaced by algorithmic trading systems. Another problem with the genetic algorithms research is that whilst it identifies trading rules it often does not include trader learning, risk and money management practices. These are what Sperandeo, Jones II, Borish and other TA traders use, and thus these practices modify the efficacy of the trading rules identified. For instance, the PBS ‘Trader’ documentary (1987) shows Jones II using deception and rumour – closer to the Chinese 36 Strategies – to mask his order size and to influence other traders. Academic researchers using genetic algorithms and other methods have often overlooked this cunning or metic intelligence.


I resolved in 2013 to integrate TA’s relevant insights into a personal knowledge base and bespoke trading system for alpha generation. Academic research rigour can be combined with professional trading insights whilst retail trading myths promulgated by the TA industry and self-styled trading coaches can be avoided. A mixed methods research approach looks promising: where TA sees trends and retracements – a market microstructure researcher may see the interaction of strategic traders, order flow, and order types – and a behavioural finance proponent may find specific cognitive biases and decision heuristics. All three approaches look at the same market data via different lenses and vantage points. I took several tests to identify and to understand personal cognitive biases and psychological preferences. Once identified, I then compared the personal cognitive biases with past trades using an after action review approach. This illustrative research will inform operative action research to improve decision heuristics, mental models, and risk preferences for future alpha generation.

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.