What I’m Reading

Disinformation alumnus Roy Christopher kindly included me in his annual Summer Reading List. It’s become a kind of snapshot over the past 15 years of different periods of my life. What else I’m reading at the moment:


Old Gods, New Enigmas: Marx’s Lost Theory by Mike Davis (New York: Verso, 2018). 21C and World Art former publisher and editor Ashley Crawford turned me onto Davis in the mid-1990s. I’m just into this new book and Davis already frames Karl Marx’s political economy theories and 19th century reportage in new ways.


Turning To Political Violence: The Emergence of Terrorism by Marc Sageman (Philadelphia, PA: The University of Pennsylvania Press, 2017). Sageman is a forensic psychiatrist and an incisive critic of terrorism studies research. In this book he uses process tracing to document the social identity formation of terrorists in the late 19th and early 20th century. I’m reading this book as a model of how to do process tracing in terrorism studies: the research methodology of my in-progress PhD dissertation.


Return Of The BarbariansConfronting Non-State Actors from Ancient Rome to the Present by Jakub J. Grygiel (Cambridge: Cambridge University Press, 2018). One of the major themes to what I call (post-2002) fourth generation scholarship on strategic culture is the re-emergence in a multipolar world of violent and persistent non-state actors. Although not strictly part of the strategic culture camp Grygiel has emerged as an important scholar on emerging security threats.


Dead Right: How Neoliberalism Ate Itself And What Comes Next by Richard Denniss (Carlton, Australia: Black Inc, 2018). An incisive long-form essay on the troubled state of Australia’s political economy in 2018.

ACT and PhD Work

Last year, I started working with Acceptance and Commitment Therapy material. ACT provides a way to examine and prioritise human values that differ from previous work I have done on this.


Below is a brief diary note on six aspects of ACT and how I approach in-progress PhD work:


1. Cognitive defusion: I am distinct from my PhD thesis, which is an artifact of my personal learning, reflection, and research.


2. Experiential acceptance: My PhD thesis reflects the institutional and personal circumstances that I am in, and the networks / resources that I have access to. There are some goals that will inform future research after the PhD thesis is completed. There are also some goals that I may not be able to achieve.


3. Present-moment awareness: I develop the PhD thesis in the present moment and cumulatively over time. I have approximately 28 months left until final submission.


4. Self-as-context: The PhD thesis involves mastery of strategic studies, terrorism studies, and process tracing. These choices reflect personal experiences such as a formative trip to New York City on 20th-25th September 2001.


5. Committed action: I commit to working each day on my PhD thesis and research program. For now, this means that I need to write every day.


6. Chosen values: The PhD thesis work I do reflects values that I manifest in the world.

Red Teaming Clinton

On 9th November 2016, I awoke expecting Hillary Clinton to have a large lead in the electoral college votes for the United States election. Instead, CNN was focusing on Donald Trump’s red states. Disbelief and panic flooded my social media feeds for the next 48 hours.


I had been writing the first draft of my PhD conclusion chapter. One section dealt with red teams: adopting an enemy or adversary’s viewpoint during a war game or strategic planning. Did I live in a bubble? I wondered. Why did Clinton not have a red team to understand Trump?


I retreated to think more about who had foreseen Trump’s electoral win. Michael Moore had foreseen Trump’s strategy in advance. Dilbert creator Scott Adams had lobbied Twitter for Trump to win. SkyBridge Capital’s Anthony Scaramucci and PayPal founder Peter Thiel had advocated for Trump’s innovation agenda.


But the dominant theme was the rise of white working class voters.


I had been thinking about this group for awhile but had not made the connection. In 2013, I read George Packer’s book The Unwinding as a model of individual decision-making in the face of structural change. In 2014 whilst at an International Studies Association conference in Toronto, Canada, I bought paperback copies of The Unwinding and Nassim Nicholas Taleb’s Antifragile. Months before the election outcome I was reading sociologist Justin Gest’s The New Minority and J.D. Vance’s memoir Hillbilly Elegy. I had also bought Trump and Tony Schwartz’s The Art of the Deal during business development training.


But this reading wasn’t done as some red team prescience. Instead, I was trying to understand my own blue collar family and working class childhood. I had finished a university contract and had moved cities. The decompression time made me reflect on the end of Australia’s mining boom and the socioeconomic changes I was seeing play out.


I had expected Hillary Clinton to win. There were red team signals I had seen but not integrated which showed Trump would win. Jane Mayer’s book Dark Money had documented the Koch Brothers’ funding of Charles Murray’s research and the alt.right. I had skimmed Murray’s book Coming Apart on white America at the start of 2016. J.D. Vance’s Hillbilly Elegy had become an Amazon.com bestseller. Trump had hired UKIP proponent Nigel Farage. These were all red team signals that Michael Moore, Scott Adams, and others had integrated into their worldview.


In her campaign’s last few days Hillary Clinton campaigned on the aspirational goal of becoming the first female President of the United States. This is an important and now missed historical opportunity. In contrast, Gest, Murray, Packer, and Vance remind us that the power of aspirational goals are muted when survival goals are more paramount to the individual’s life circumstances. I had also forgotten this insight from psychologist Clare W. Graves’ work on human values.


The red team signals of Trump’s strategy and election win were visible in advance. I had seen some of them. But I took the Clinton campaign and election polls at their face value. I wanted Hillary Clinton to win and for the United States to embrace the historical opportunity it faced. I felt Clinton was the more experienced candidate in terms of governance and her performance during the three televised debates.


This analytic misperception illustrates why red team work can be important. An enemy, adversary or competitor may work out your cognitive biases and decision preferences. Your filter bubble may not realise this until it is too late – even if you had the background to correctly see the situation. Consequently, the world is going to be a different place now that Trump is President-elect. A Hillary Clinton Administration will now be a counterfactual scenario for political scientists to consider.




In the past several years I’ve collected memoirs on hedge fund managers. These include asset class histories (More Money Than God), the Galleon case (The Billionaire’s Apprentice and The Buy Side), insider trading cases (Circle of Friends and the forthcoming Black Edge), interviews (Inside the House of Money), academic studies (Hedge Funds: An Analytic Perspective), and reflections (Diary of a Hedge Fund ManagerDiary of a Very Bad Year, and Money Mavericks).


These books gave several insights. Hedge fund capabilities embody what I researched 12-14 years ago on institutional strategic foresight. They are actively managed vehicles for extractive capital accumulation. Most hedge fund managers have an ethic of chaotic good versus the chaotic evil of terrorist group leaders. Their intellectual property is know how or trade secrets.


These books informed several decisions. First, I will be mindful of the finance-terrorism and economic statecraft nexus in future research. Second, HFM-style active management illustrates what a focused and committed life can achieve. Third, I will continue a trajectory in the Nihonbashi and Toronto-Dominion reflections of private research into discretionary and electronic execution services.

On Trump

The size of Donald Trump’s election gains came as a little surprise to me on Wednesday morning, Australian time. I then reflected on Justin Gest, J.D. Vance, George Packer, and other writers I had read who have documented the lives of Trump’s white working class voters. The New York Times has a good reading list here.


I grew up in an Australian rural, working class neighbourhood. I have experienced downward mobility at times in my life. I have seen dotcom era, early Web 2.0, and university deal-making culture that heeds Trump and biographer Tony Schwartz’s Art of the Deal. I’ve had dinner with Listen, Liberal author Thomas Frank (and used his book One Market Under God to understand the 1995-2000 speculative bubble). I’ve studied the sociology of class and inequality. I’ve followed Russian disinformation operations.


So, I can understand why some people voted for Trump.


Trump’s election for me consolidates likely post-thesis research on economic statecraft. Phenomena like Trump, Vladimir Putin, Brexit, Islamic State, Julian Assange, Edward Snowden and postcapitalist re-evaluation of neoliberalism all fit a Kondratieff Winter outlook. I’ll be watching the next four years closely and gathering data for possible Post-Doctoral and ARC DECRA applications.

17th June 2013: Becoming Heisenberg



I’m a late-comer to Vince Gilligan’s television series Breaking Bad. Most people are waiting for Season 5’s second half in August. I’m at the end of Season 1. Walter White’s (Bryan Cranston) transformation from “Mr. Chips into Scarface” (Gilligan) might find its way into a PhD chapter.


A pivotal scene from Season 1 occurs during the finale of episode 6 ‘Crazy Handful of Nothin’‘. White has just shaved his hair due to chemotherapy. He confronts crystal methamphetamine dealer Tuco Salamanca (Raymond Cruz) who beat up White’s partner Jesse Pinkman (Aaron Paul). White’s bargaining leverage is the fulminated mercury he has bought with him as a small incendiary explosive, and which the episode foreshadowed in a high school chemistry class. The scene is a great negotiation clip that illustrates the madman theory in grand strategy and nuclear deterrence.


More significantly, it is the moment that White takes Action, and first transforms from a mild-mannered chemistry teacher (and former graduate student researcher) into his alter ego, Heisenberg. It’s a moment of Metic intelligence (craft, cunning, skill, wisdom). I’m looking forward to how White evolves, and what the consequences of his decisions are, in the remainder of Breaking Bad.

1st June 2013: My First Trading System

My First Trading System
My First Trading System


In August 2011, I started trading Australian equities after over a decade of watching financial markets as a journalist, website editor, and university-based researcher. I developed a pulse for event arbitrage. In October 2011, I visited the Tokyo Stock Exchange where I vowed “to develop a private, low-key, personal vehicle for long-term self-sufficiency, drawing on insights from active management, event-based arbitrage, tick data analysis of market trading and volatility, and money management.”


In the past few days this applied research program has metamorphosed into a new phase.


I also mapped out how the trading literature has evolved over the past 30 years.


I am developing my first trading system: Bayesian, risk-weighted, algorithmic and quantitative trading rules.


I’m using the following development process (with the books above and other resources):


1. Identify possible Alpha Opportunities, Arbitrage Factors, and Trading Catalysts using a systematic review of hedge fund, risk, and quantitative trading literature. These are Bayesian pre-observed outcomes or inputs.


2. Iteratively develop a Trading System with careful attention to probable market exposures, decision-action loops, and transaction/execution costs. Consider what correlations and joint probabilities might arise.


3. Code the Trading System as algorithms and quantitative screens. Back-test them in a variety of market conditions. Check the back-test data for potential curve-fitting. Update Bayesian beliefs.


4. Do an After Action Review with careful attention to risk/money management lessons.