19th June 2013: The SmallCap Value Premia

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Richard C. Marston‘s Portfolio Design: A Modern Approach to Asset Allocation (Hoboken, NJ: John Wiley & Sons, 2011) is my work commute read for this week. Wiley has excerpts here.

 

Portfolio Design focuses on return drivers and risk premia for the major asset classes used to allocate assets in diversified portfolios. The ‘modern approach’ includes a focus on data analytics and the available evidence base; a review of recent (Fama-French-influenced) quantitative finance studies; and insights on index benchmarks and portfolio construction.

 

I’m a couple of chapters in: Marston focuses on smallcap and value return drivers, in contrast to largecap and growth stocks. Although he doesn’t explore this Marston’s insights in his opening chapters are also relevant to two other areas:

 

  • Penny stick promoters rely on ‘crowded trades’ and rational herding: this is often what the ‘free’ investment newsletters and watchlists are for, to create drawdown market dynamics in relatively illiquid stocks.
  • Venture capital’s asymmetric returns can have large payoffs if opportunity evaluation screening works, and if stage one financing backs a break-out company that creates a new, large market or is a successful disruptive entrant into existing markets.

 

It’s interesting to see how an experienced, endowment investment adviser handles index benchmarks, portfolio construction, and specific return drivers. Since he is also on Yale’s investment committee Portfolio Design also makes an interesting counterpart to the influential Yale Swensen model detailed in Swensen’s Pioneering Portfolio Management: An Unconventional Approach to Institutional Investment (rev ed.) (New York: The Free Press, 2009).

19th June 2013: ANAO Audit of AUSTRAC

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The Australian Transaction Reports and Analysis Centre (AUSTRAC) has an important role in financial intelligence and anti-money laundering initiatives in Australia.

 

Monash University’s Andrew Zammit tipped me off to an Australian National Audit Office audit of AUSTRAC, available here.

 

ANAO’s audit opinion has some interesting reflections on AUSTRAC’s financial intelligence function:

  • Partner agency access to AUSTRAC data should be regularly reviewed by AUSTRAC personnel.
  • Processing time targets and processing backlogs for financial intelligence assessment should be monitored by AUSTRAC management.
  • Key Performance Indicators and structured feedback from partner agencies should be developed for financial intelligence.

 

These are a mix of high-level strategic planning; operational review; and partner corporate governance. The ANAO audit opinion is an interesting read on AUSTRAC’s organisational evolution — its financial intelligence methodologies remain confidential.

 

For some possible answers, we can look to the current literature in intelligence studies on structured analytic techniques and methodologies. The US-based Central Intelligence Agency released A Tradecraft Primer in 2009 (PDF). Ricahrd J. Heuer Jr and Randolph H. Pherson’s Structured Analytic Techniques for Intelligence Analysis (Washington DC: CQ Press College, 2010), and Sarah Miller Beebe and Randolph H. Pherson’s Cases in Intelligence Analysis: Structured Analytic Techniques in Action (Washington DC: CQ Press College, 2011) are also excellent tradecraft primers.

18th June 2013: Algorithmic Trading Goes Retail

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Fortune Magazine reports that EquaMetrics is now selling a cloud-based app that creates Technical Analysis-based algorithmic trading strategies for retail trading subscribers:

 

EquaMetrics’ app is simply designed and since its software firepower comes from the cloud, it doesn’t require anything more than the typical PC. You can drag and drop colored tiles to assemble your own algorithm. Day traders can choose between 30 variables to build their formulas. The options are built on so-called technical indicators, metrics that reflect trading patterns as opposed to stock fundamentals such as the price-earnings ratio. After you’re done, you run the program to buy and sell stocks and currencies.

 

The web application is relatively inexpensive: it costs $99 a month or $250 a month, depending on how many algorithms you want to run. That’s a steal compared to the alternative of hiring a quantitative programmer for $200,000 a year. EquaMetrics gives you the stuff a programmer could produce. Then it’s up to you to assemble your own strategy.

 

I have been expecting apps like this for several months, and have been monitoring other initiatives like the Quantopian community. The popular literature on algorithmic trading strategies evolved from Technical Analysis mechanical systems (Tushar S. Chande’s Beyond Technical Analysis) to back-testing (Robert Pardo’s The Evaluation and Optimization of Trading Strategies) and then to algo trading using Matlab software (Ernie Chan’s Quantitative Trading and his new Algorithmic Trading; and Barry Johnson’s Algorithmic Trading & DMA). This period spans the post-dotcom collapse; the 2003-08 speculative bubble in real estate and asset-backed securitisation; and institutional experimentation with high-frequency trading platforms, and transaction and execution costs.

 

EquaMetrics’ strategy reflects this decade-long evolution:

  • Its initial offering is Technical Analysis strategies: at a time when: (a) high-frequency trading has ‘broken’ many trend-following and momentum indicators; and (b) hedge funds and proprietary trading desks use predatory trading to clean out TA-oriented retail traders.
  • The model is subscription-based software as a service — which could eventually disrupt or change the economics of agile software programming if this offering scales up in a significant way. Will the $US99-250 per month price point remain? Or will another platform develop a lower-priced offering and trigger a ‘race to the bottom’ competitive dynamic?
  • It opens the way for the licensing of specific TA indicators and proprietary methods as ancillary revenue streams, and as a way to build a market around the core product offering (which NinjaTrader, MetaStation, and ESignal have all done with their respective platforms).
  • The quality and scope of the back-tested data is important: quantitative hedge funds like Jim Simons’ Renaissance and David Shaw’s D.E. Shaw & Co each clean their own data.
  • EquaMetrics’ move into fundamental indicators reflects some recently published work on the quantitative analysis of these strategies (notably, Richard Tortoriello’s Quantitative Strategies for Achieving Alpha, and Wesley Gray and Tobias Carlisle’s Quantitative Value).
  • EquaMetrics’ choice of FXCM and Interactive Brokers as prime brokers to process client trades is significant: brokerage transaction and execution costs can mean a potential, new trading strategy is actually unprofitable to execute, or that its profit-taking ability declines over time, especially in correlated and ‘crowded trade’ markets.
  • The focus on TA and fundamental indicators does not address some of the quantitative, statistical or machine learning strategies that quantitative hedge funds use to develop algorithms; how correlation testing of model variables might occur; and what might happen to retail investors once several different competing firms have back-tested and issued dueling algorithms (a factor in high-frequency markets where scalping and order front-running occurs).

 

Still, the EquaMetrics offering has me interested: I’ve been waiting for algorithmic trading to ‘value migrate’ (Adrian Slywotzky) to retail traders, for awhile. It’s a first step towards post-human trading (Charles Stross’s novel Accelerando).

18th June 2013: The Wolf of Wall Street Trailer

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There are two kinds of Wall Street films: the techno-science thriller involving financial risk management and VaR (The Bank; Margin Call; Arbitrage); and the elite trader’s excessive lifestyle (Wall Street; Boiler Room; Wall Street: Money Never Sleeps). Martin Scorsese’s forthcoming film adaptation of Jordan Belfort’s ‘pump and dump’ memoir The Wolf of Wall Street (New York: Bantam, 2007) goes for the latter, because it appeals to a far broader audience. The trailer benefits from Kanye West’s pulsating new song ‘Black Skinhead’ (from Yeezus).

 

Belfort’s friends got him the film deal with Scorsese and actor Leonardo DiCaprio whilst Belfort was resurrecting his sales career on the Australian seminar circuit (PDF). In just a few years Belfort transformed his Straight Line Sales technique from free MP3 interviews into slick website and seminar circuit presentations on sales psychology. Josh Brown outlines in his book Backstage Wall Street: An Insider’s Guide to Knowing Who to Trust, Who to Run From, and How to Maximize Your Investments (New York: McGraw-Hill, 2012) how pitch books like Befort’s Straight Line works. Maybe Belfort’s seminar clients in Australia need to read Brown’s book and blog. It all reminds me of telemarketing stints I had in the mid-late 1990s, whilst reading Tom Hopkins and Zig Ziglar, and watching friends get recruited into Amway’s multi-level marketing schemes. Maybe Belfort will be able to pay back his clients, after all, if his deal includes a share of Scorsese’s film residuals.

 

The elite trader image of ‘conspicuous consumption’ has its roots in Thorstein Veblen‘s leisure class economics, and Reagan era money managers like Henry Kravis, Peter Lynch, Victor Sperandeo, and Martin Zweig. The traders I know enjoy the Hollywood media imagery. But they also know it is a myth that artificially inflates the subjective expectations of how trading actually works and what it is really like. The ‘excessive lifestyle’ myth actually serves as an entry barrier. Most novice and retail traders will more likely ‘blow up’ their trading accounts.

17th June 2013: Becoming Heisenberg

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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.

17th June 2013: Esoteric Order of Beelzebub

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For the past few months, I have been corresponding with Houston-based EBM/darkwave musician Paul Frederic (Asmodeus X).

 

We share some common interests that were a major part of my life in the 199os, and whilst writing for and editing the Disinformation website: the Gurdjieff Work; the Temple of Set; Spiral Dynamics; Neuro-linguistic Programming; futures studies and strategic foresight (which I studied in a Masters program at Australia’s Swinburne University); and the metaprogramming approaches of John C. Lilly and Robert Anton Wilson. The deep theme running through these different currents, organisations and methods is willed, sovereign, self-change and creative Action in the world.

 

I recently joined the Esoteric Order of Beelzebub: a confederation of independent artist-entrepreneurs (James Altucher), which Frederic made me aware of. The EOB’s mission statements is “leveraging conscious evolution!” Its public imagery draws on diverse sources: astrobiological space imagery; comparative religion and historical daemonology/goetia; libertarian economics; and the contemporary techno-sciences.

 

Many of my EOB contributions will be posted to this personal blog.

16th June 2013: My First Trade

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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.

16th June 2013: ICIJ’s Offshore Tax Havens Database

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For the past few months the International Consortium of Investigative Journalists (ICIJ) has been releasing information about offshore tax havens. ICIJ’s database was leaked from two wealth management firms: Portcullis TrustNet (Singapore) and Commonwealth Trust Limited (British Virgin Islands). The ICIJ chose La Nación de Costa Rica to analyse the data which reveals how offshore companies and trusts are used for tax minimisation, tax avoidance, and possible money laundering.

Now, the ICIJ has released the database for public analysis.

 

The ICIJ’s database arrived with perfect timing for me: I was thinking about some PhD-related new chapters. In 2005, I wrote a Masters essay (PDF) on international governance for anti-money laundering initiatives. I was re-reading Nick Kochan’s The Washing Machine: Money, Crime & Terror In The Offshore System (London: Gerald Duckworth & Co., 2006), and eyeing off my copy of Jeffrey Robinson’s The Sink: How Banks, Lawyers and Accountants Finance Terrorism and Crime – And Why Governments Can’t Stop Them (London: Constable & Robinson, 2003).

 

Now, thanks to the ICIJ, I have some data on offshore tax havens to examine.

15th June 2013: HFT, Disruptive Innovation & Theta Arbitrage

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23rd July 2009 was perhaps the day that retail investors became aware of high-frequency trading (HFT).

 

That was the day that New York Times journalist Charles Duhigg published an article on HFT and market microstructure changes. Duhigg’s article sparked a public controversy about HFT and changes to United States financial markets.

 

Then on 6th May 2010 came the Flash Crash. HFT was again the villain.

 

For the past few years HFT has inspired both pro and con books from publishers. HFT has changed how some retail investors and portfolio managers at mutual and pension funds view financial markets. Now, Matthew Philips of Bloomberg Businessweek reports that 2009-10 may have been HFT’s high-point in terms of being a profitable strategy.

 

Philips’ findings illustrate several often overlooked aspects of Clayton Christensen‘s Disruptive Innovation Theory. Scott Patterson notes in his book Dark Pools (New York: Crown Business, 2012) that HFT arose due to a combination of entrepreneurial innovation; technological advances in computer processing power; and changes to US Securities and Exchanges Commission regulations. Combined, these advances enabled HFT firms to trade differently to other dotcom era and post-dotcom firms that still used human traders or mechanical trading systems. This trading arbitrage fits Christensen’s Disruptive Innovation Theory as a deductive, explanatory framework.

 

The usually overlooked aspect of Disruptive Innovation Theory is that this entrepreneurial investment and experimentation gave HFT firms a time advantage: theta arbitrage. HFT firms were able to engage for about a decade in predatory trading against mutual and pension funds. HFT also disrupted momentum traders, trend-followers, scalping day traders, statistical arbitrage, and some volatility trading strategies. This disruption of trading strategies led Brian R. Brown to focus on algorithmic and quantitative black boxes in his book Chasing The Same Signals (Hoboken, NJ: John Wiley & Sons, 2010).

 

Paradoxically, by the time Duhigg wrote his New York Times article, HFT had begun to lose its profitability as a trading strategy. Sociologist of finance Donald MacKenzie noted that HFT both required significant capex and opex investment for low-latency, and this entry barrier increased competition fueled ‘winner-takes-all’ and ‘race to the bottom’ competitive dynamics. HFT’s ‘early adopters’ got the theta arbitrage that the late-comers did not have, in a more visible and now hypercompetitive market.  Duhigg’s New York Times article wording and the May 2010 Flash crash also sparked an SEC regulatory debate:

 

  • On the pro side were The Wall Street Journal’s Scott Patterson; author Rishi K. Narang (Inside The Black Box); and industry exponent Edgar Perez (The Speed Traders).
  • On the con side were Haim Bodek of Decimus Capital Markets (The Problem With HFT), and Sal L. Arnuk and Joseph C. Saluzzi of Themis Trading (Broken Markets) which specialises in equities investment for mutual and pension fund clients.
  • The winner from the 2009-12 debate about HFT regulation appears to be Tradeworx‘s Manoj Narang who was both pro HFT yet who also licensed his firm’s systems to the SEC for market surveillance, as a regulatory arbitrage move. The SEC now uses Tradworx’ systems as part of the Market Information Data Analytics System (MIDAS, Philips reports.

 

Philips announced that HFT firms now have new targets: CTAs, momentum traders, swing traders, and news sentiment analytics. That might explain some recent changes I have seen whilst trading the Australian equities market. Christensen’s Disruptive Innovation Theory and theta arbitrage both mean that a trading strategy will be profitable for a time before changes in market microstructure, technology platforms, and transaction and execution costs mean that it is no longer profitable.