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Early 2017 Reading Pile

The following books will be on my reading pile for early 2017:

 

  1. Sheelah Kolhatkar’s Black Edge: Inside Information, Dirty Money, and the Quest to Bring Down the Most Wanted Man on Wall Street (New York: Random House, 2017). Kolhatkar is a staff writer at The New Yorker. I followed the insider trading case against Steve A. Cohen and his hedge fund SAC Capital for several years. I thought about writing a PhD chapter on it — but getting access to the court records was going to be expensive and it was out-of-scope to my main focus. Kolhatkar has saved me the trouble — and illustrates why investigative journalism is important.
  2. Ed Thorp’s A Man For All Markets: From Las Vegas to Wall Street, How I Beat the Dealer and the Market (New York: Random House, 2017). Thorp is a giant in quantitative investing and card counting in poker. There’s a lengthy interview with Thorp in Jack D. Schwager’s book Hedge Fund Market Wizards, and this book promises more revelations. Features a foreward by Nassim Nicholas Taleb.
  3. Andrew W. Lo’s Adaptive Markets: Financial Evolution at the Speed of Thought (Princeton, NJ: Princeton University Press, 2017). Lo is the Charles E. and Susan T. Harris Professor, a Professor in Finance, and the Director of the Laboratory for Financial Engineering at the MIT Sloan School of Management. This book outlines Lo’s Adaptive Markets Hypothesis – a challenger to the Efficient Markets Hypothesis – and offers a conceptual basis for why some hedge fund trading works.
  4. Siva Vaidyanathan’s Intellectual Property: A Very Short Introduction (New York: Oxford University Press, 2017). Vaidyanathan is Professor of Media Studies at the University of Virginia. Intellectual Property (IP) is an intangible asset class that includes copyrights (works of creative expression), trademarks (logos and symbols that differentiate a company in the marketplace), patents (know how and processes), and trade secrets (confidential and secret information). Vaidyanathan explains how IP works and examines its legal / cultural debates. A good primer for content creators.
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Roy Christopher’s Summer Reading List 2015 + Bonus Material

I have some book suggestions in Disinformation alumnus Roy Christopher’s Summer Reading List 2015.

 

The emergent theme in my list this year is: the wealth extraction strategies of oligarchical elites and how to Become them.

 

Here is some bonus material I wrote that you might find useful:

 

Lasse Heje Pedersen Efficiently Inefficient: How Smart Money Invests & Market Prices Are Determined (Princeton University Press, 2015). Lasse Heje Pederson is the John A. Paulson Professor of Finance and Alternative Investments at the New York University Stern School of Business. Perdersen’s “efficiently inefficient” theory of financial markets focuses on active investors who have a comparative advantage. This book examines six economically motivated investment styles and eight hedge fund strategies. It contains one of the best descriptions I have read of how active management works. Pedersen also interviews influential hedge fund managers and investment managers including James Chanos, Cliff Asness, George Soros, Myron Scholes, Ken Griffin, and John A. Paulson. For a history of hedge funds see Sebastian Mallaby’s More Money Than God: Hedge Funds and the Making of a New Elite (Bloomsbury, 2010).

 

Han Smit and Thras Moraitis Playing At Acquisitions: Behavioral Option Games (Princeton University Press, 2015). Han Smit is a Professor in the Faculty of Economics at the Erasmus University Rotterdam. Thras Moraitis was Group Head of Strategy and Corporate Affairs at Xstrata. Playing At Acquisitions offers a synthesis of three business strategy methodologies: behavioural economics, game theory, and real options. An in-depth case study on the company Xstrata is also provided. Smit and Moraitis provide a personal synthesis that will enable you to perceive your own cognitive biases, to understand others, and to make more effective decisions under uncertainty. For a conceptual understanding of business strategy see J.C. Spenders Business Strategy: Managing Uncertainty, Opportunity, and Enterprise (Oxford University Press, 2014).

 

Lauren A Rivera Pedigree: How Elite Students Get Elite Jobs (Princeton University Press, 2015). Lauren Rivera is Associate Professor of Management & Organizations at Northwestern University’s Kellogg School of Management. Pedigreefollows in the footsteps of Vilfredo Pareto and Gaetano Mosca in examining how the processes of elite reproduction and social stratification occur in elite firms who hire students from elite schools into entry-level jobs. Rivera uses interviews and participant observation to discover how employers use a range of filtering mechanisms to reproduce elites in a way that is reminiscent of ancestral heritage and cultural transmission. This book also offers novel insights on the sociological study of contemporary elites and elite circulation. For a micro-study on elites, non-elites and economic stratification see Robert D. Putnam’s Our Kids: The American Dream in Crisis (Simon & Schuster, 2015).

 

Karen Dawisha Putin’s Kleptocracy: Who Owns Russia? (Simon & Schuster, 2014). Karen Dawisha is the Director of the Havighurst Center for Russian and Post-Soviet Studies at Miami University. Putin’s Kleptocracy was originally under contract at Cambridge University Press before potential libel concerns led to Simon & Schuster publishing the book. Dawisha uses archival, internet, interview, and other sources to show how Putin rose to power and how he and a small oligarchical elite succeeded in extracting economic wealth from post-Soviet Russia. Dawisha’s research informed the PBS Frontline documentary Putin’s Way (13th January 2015). Putin’s success at wealth extraction can be compared with Thor Bjorgolfsson’s Billions to Bust – and Back (Profile Books 2014) and Bill Browder’s Red Notice (Simon & Schuster, 2015) in which self-styled ‘adventure capitalists’ and emerging market financiers were not so lucky. On Putin’s use of sociological propaganda to restructure post-Soviet Russia see Peter Pomerantsev’s Nothing Is True And Everything Is Possible (PublicAffairs, 2014) and Jason Stanley’s How Propaganda Works (Princeton University Press, 2015).

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Active Management Reading List

Asset Management

 

Asset Management: A Systematic Approach to Factor Investing by Andrew Ang (New York: Oxford University Press, 2014). Presents an asset management model including factor risk premiums for different asset classes.

 

Expected Returns: An Investor’s Guide to Harvesting Market Rewards by Antti Ilmanen (Hoboken, NJ: John Wiley & Sons, 2011). The return drivers of the major asset classes.

 

Funds: Private Equity, Hedge, and All Core Structures by Matthew Hudson (Hoboken, NJ: John Wiley & Sons, 2014).  The types and structures of major investment funds.

 

Manias, Panics and Crashes: A History of Financial Crises (6th edition) by Charles P. Kindleberger and Robert Z. Aliber (New York: Palgrave Macmillan, 2011). The historical lessons and structure of speculative bubbles.

 

Hedge Funds

 

The Alpha Masters: Unlocking the Genius of the World’s Top Hedge Funds by Maneet Ahuja (Hoboken, NJ: John Wiley & Sons, 2012). Profiles of activist and global macro hedge fund managers.

 

The Big Short: Inside the Doomsday Machine by Michael Lewis (New York: W.W. Norton & Company, 2010). How hedge fund managers extracted alpha from the 2007-09 global financial crisis.

 

The Billionaire’s Apprentice: The Rise of the Indian-American Elite and the Fall of the Galleon Hedge Fund by Anita Raghavan (New York: Business Plus, 2013). Hedge fund manager Raj Rajaratnam and the demise of the Galleon hedge fund.

 

Confidence Game: How A Hedge Fund Manager Called Wall Street’s Bluff by Christine S. Richard (Hoboken, NJ: John Wiley & Sons, 2010). Hedge fund manager Bill Ackman and the MBIA fraud investigation.

 

Efficiently Inefficient: How Smart Money Invests and Market Prices Are Determined by Lasse Heje Perdersen (Princeton, NJ: Princeton University Press, 2015). Presents a framework for how hedge funds extract alpha (excess returns above a benchmark) using active management.

 

Fooling Some of the People All of the Time (rev. edition) by David Einhorn (Hoboken, NJ: John Wiley & Sons, 2010). The fallout from hedge fund manager Einhorn’s decision to ‘short’ Allied Capital.

 

The Fundamentals of Hedge Fund Management: How to Successfully Launch and Operate a Hedge Fund (2nd edition) by Daniel A. Strachman (Hoboken, NJ: John Wiley & Sons, 2012). The operational structure of hedge funds.

 

Hedge Fund Market Wizards: How Winning Traders Win by Jack D. Schwager (Hoboken, NJ: John Wiley & Sons, 2012). Interviews with successful hedge fund managers and traders.

 

Hedge Fund Masters: How Top Hedge Fund Traders Set Goals, Overcome Barriers, and Achieve Peak Performance by Ari Kiev (Hoboken, NJ: John Wiley & Sons, 2005). The performance psychology of hedge fund traders.

 

Hedge Funds: An Analytic Perspective by Andrew W. Lo (New Haven, CT: Princeton University Press, 2010). A quantitative finance model of how hedge funds work.

 

Hedge Hogs: The Cowboy Traders Behind Wall Street’s Largest Hedge Fund Disaster by Barbara T. Dreyfuss (New York: Random House, 2013). The demise of the Amaranth hedge fund.

 

Inside The House of Money: Top Hedge Fund Traders on Profiting in the Global Markets (rev. edition) by Steven Drobny (Hoboken, NJ: John Wiley & Sons, 2009). How hedge fund traders profited during the 2003-08 speculative bubble.

 

Investment Strategies of Hedge Funds by Filippo Stefanini (Hoboken, NJ: John Wiley & Sons, 2006). Common investment strategies of major hedge funds.

 

The Invisible Hands: Top Hedge Fund Traders on Bubbles, Crashes, and Real Money by Steven Drobny (Hoboken, NJ: John Wiley & Sons, 2011). How hedge fund traders risk hedged the 2007-09 global financial crisis.

 

The Little Book of Hedge Funds: What You Need to Know About Hedge Funds but the Managers Won’t Tell You by Anthony Scaramucci (Hoboken, NJ: John Wiley & Sons, 2012). An introduction by a hedge fund manager to hedge funds as an active management vehicle to extract alpha from financial markets.

 

More Money Than God: Hedge Funds and the Making of a New Elite by Sebastian Mallaby (New York: The Penguin Press, 2010). The history of hedge funds as an active management structure and biographies of hedge fund managers.

 

Risk Management in Trading: Techniques to Drive Profitability of Hedge Funds and Trading Desks by Davis W. Edwards (Hoboken, NJ: John Wiley & Sons, 2014). Risk management strategies used by major banks and hedge funds.

 

Trade Like a Hedge Fund: 20 Successful Uncorrelated Strategies & Techniques to Winning Profits by James Altucher (Hoboken, NJ: John Wiley & Sons, 2004). The strategies and techniques that Altucher developed whilst trading for Victor Niederhoffer.

 

Visual Guide to Hedge Funds by Richard C. Wilson (Hoboken, NJ: John Wiley & Sons, 2014). An introduction to hedge funds as an active management vehicle.

 

When Genius Failed: The Rise and Fall of Long-Term Capital Management by Roger Lowenstein (New York: Random House, 2001). The demise of the hedge fund Long-Term Capital Management.

 

Private Equity

 

Barbarians At The Gate: The Fall of RJR Nabisco by Bryan Burrough and John Helyar (New York: HarperBusiness, 2008). The market for corporate control of RJR Nabisco and the takeover’s ‘winners curse’.

 

The Fissured Workplace: Why Work Became So Bad For So Many and What Can Be Done to Improve It (Boston, MA: Harvard University Press, 2014). A labour / union critique of the asset management / private equity model and its impact on workers.

 

The Masters of Private Equity and Venture Capital: Management Lessons from the Pioneers of Private Investing by Robert A. Finkel with David Greising (New York: McGraw-Hill, 2010). Anecdotes about private equity and venture capital deals.

 

Private Equity: Fund Types, Risks and Returns, and Regulation edited by Douglas Cumming (Hoboken, NJ: John Wiley & Sons, 2010). Private equity’s investment fund and legal structure as a form of active management.

 

Private Equity At Work: When Wall Street Manages Main Street by Eileen Appellbaum and Rosemary Batt (New York: Russell Sage Foundation, 2014). Presents a justification for and evaluation of private equity as a form of active management.

 

The Private Equity Edge by Arthur B. Laffer, William J. Hass and Shepherd G. Pryor IV (New York: McGraw-Hill, 2009). A justification for private equity as a form of experimental innovation.

 

Private Equity Operational Due Diligence: Tools to Evaluate Liquidity, Valuation, and Documentation by Jason Scharfman (Hoboken, NJ: John Wiley & Sons, 2012). Presents a framework for operational due diligence of private equity as active management.

 

Private Equity Unchained: Strategy Insights for the Institutional Investor by Thomas Meyer (New York: Palgrave Macmillan, 2014). Presents a strategic model for private equity as arbitrage.

 

Sovereign Wealth Funds

 

Sovereign Wealth Funds: Legitimacy, Governance and Global Power by Gordon L. Clark, Adam D. Dixon, and Ashby H.B. Monk (Princeton, NJ: Princeton University Press, 2013). The fund structure and investment strategies of sovereign wealth funds.

 

Value Creation

 

The Alchemy of Finance: Reading the Mind of the Market by George Soros (New York: Simon & Schuster, 1987). Presents Soros’ theory of reflexivity about financial markets, influenced by philosopher Karl Popper.

 

Antifragile: Things That Gain From Disorder by Nassim Nicholas Taleb (New York: Random House, 2012). An optionality-based philosophy of how to actively deal with luck, risk, and uncertainty.

 

Den of Thieves by James B. Stewart (New York: Touchstone, 1992). How financier Michael Milken helped to create the high yield bond / junk bond trade and caused the downfall of Drexel Burnham Lambert.

 

Learn Or Die: Using Science to Build a Leading-Edge Learning Organization by Edward D. Hess (New York: Columbia University Press, 2014). How the hedge fund Bridgewater creates a Radical Transparency culture for value creation.

 

Moneyball: The Art of Winning an Unfair Game by Michael Lewis (New York: W.W. Norton & Company, 2003). How baseball coach Billy Beane used Bill James’ sabermetrics – the statistical study of baseball performance – to transform the Oakland A’s team.

 

More Than You Know: Finding Financial Wisdom In Unconventional Places (rev. edition) by Michael J. Mauboussin (New York: Columbia University Press, 2008). How to find and extract alpha from financial markets using lessons from psychology and science.

 

The Nature of Value: How to Invest in an Adaptive Economy by Nick Gogerty (New York: Columbia University Press, 2014). Presents a value creation model used by the hedge fund Bridgewater.

 

Plutocrats: The Rise of the Global Rich and the Fall of Everyone Else by Chrystia Freeland (New York: The Free Press, 2012). The geopolitical worldview of contemporary business and financial elites.

 

The Predators’ Ball: The Inside Story of Drexel Burnham and the Rise of the Junk Bond Traders by Connie Bruck (New York: Penguin Books, 1989). How financier Michael Milken’s deal flow enabled him to take control of Drexel Burnham Lambert.

 

Putin’s Kleptocracy: Who Owns Russia? by Karen Dawisha (New York: Simon & Schuster, 2014). How Putin’s regime in Russia dealt with the oligarchs, and engaged in institutional capture and value appropriation of Russian state assets for private gain.

 

The Snowball: Warren Buffet and the Business of Life by Alice Schroeder (New York: Bantam Books, 2008). The authorised biography of value investor Warren Buffett.

 

Security Analysis (6th edition) by Benjamin Graham and David Dodd (New York: McGraw-Hill, 2008). The influential primer on value investing.

 

Steve Jobs by Walter Isaacson (New York: Simon & Schuster, 2011). The authorised biography of Apple’s co-founder Steve Jobs.

 

Why Moats Matter: The Morningstar Approach to Stock Investing by Heather Brilliant and Elizabeth Collins (Hoboken, NJ: John Wiley & Sons, 2014). Morningstar’s ‘economic moats’ framework for value creation.

 

Venture Capital

 

The Business of Venture Capital: Insights from Leading Practitioners on the Art of Raising a Fund, Deal Structuring, Value Creation, and Exit Strategies (2nd edition) by Mahendra Ramsinghani (Hoboken, NJ: John Wiley & Sons, 2014). Interviews with venture capital practitioners on deals and term sheets.

 

Deal Terms: The Finer Points of Venture Capital Deal Structures, Valuations, Term Sheets, Stock Options, and Getting Deals Done by Alex Wilmerding (Eagan, MN: Thomson Reuters / Aspatore, 2005). Term sheets, deal structures, raising capital, and legal structures for private equity and venture capital deals.

 

Term Sheets & Valuations: A Line by Line Look at the Intricacies of Term Sheets & Valuations by Alex Wilmerding (Eagan, MN: Thomson Reuters / Aspatore, 2006).

 

Venture Capital: Investment Strategies, Structures, and Policies edited by Douglas Cumming (Hoboken, NJ: John Wiley & Sons, 2010). Venture capital’s investment fund and legal structure as a form of active management.

 

Venture Deals: Be Smarter Than Your Lawyer and Venture Capitalist (2nd edition) by Brad Feld and Jason Mendelson (Hoboken, NJ: John Wiley & Sons, 2012). The legal structure and term sheets for venture capital deals.

 

Zero to One: Notes on Startups, or How to Build the Future by Peter Thiel with Blake Masters (London: Virgin Books, 2014). The PayPal co-founder and Facebook / SpaceX investor presents a venture capital model of value creation.

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On Jim Simons, String Theory, and Quantitative Hedge Funds

Renaissance Technologies founder and mathematics professor Jim Simons is an enigma in quantitative hedge funds.

 

Simons rarely gives interviews. One of the best is an Institutional Investor interview he gave in 2000 (PDF). One insight is that Renaissance makes trades in specific time periods using pattern recognition to model volatility.

 

Simons has done important work in differential geometry and the theoretical physics subdiscipline of string theory. I recently looked at some academic journal articles by Lars Brink (Sweden’s Chalmers University of Technology) and Leonard Susskind (Stanford University) to try and understand how Simons views financial markets.

 

String theory proposes one-dimensional objects called strings as particle-like objects that have quantum states. String theory and cosmology has progressed over the past 35 years to describe this phenomena but still lacks some key insights.

 

How might Simons use string theory to understand financial markets? Two possibilities:

 

(1) The mathematical language of couplings, phase transitions, perturbations, rotational states, and supersymmetries provides a scientific way to describe financial market  data and price time-series. It does so in a different way to fundamental analysis, technical analysis, and behavioural finance: Simons uses string theory to understand the structure of information in financial markets. (Ed Thorp pursued a similar insight with Claude Shannon using probability theory.) String theory-oriented trading may be falsifiable in Karl Popper’s philosophy of science.

 

(2) String theory provides a topological model that can be applied to money flows between mutual funds, hedge funds, and bank trading desks over short periods of time. This might enable Simons’ traders to forecast the likely catalysts for changes in stock prices in the short-term and to trade accordingly. This might involve using string theory to forecast how price trajectories might change if portfolio managers at other funds alter their portfolio weights for a stock. In doing so, Simons is trading in a similar way to SAC’s Steve Cohen (who uses game theory) and D.E. Shaw’s David Shaw but uses different methods of pattern recognition to do so.

 

I have made a list of popular science books and Springer academic monographs to keep an eye on string theory. Simons’ success also illustrates how insights from one knowledge domain (string theory, astrophysics, computational linguistics, and voice recognition) can be transferred to another domain (financial markets trading).

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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.

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Reading Steve A. Cohen’s White Paper in the SAC Insider Trading Case

I’ve followed hedge funds – pooled fund structures that engage in active management often uncorrelated with financial markets – for about a decade.

 

Almost 12 years ago I wrote a Masters paper on Long-Term Capital Management (PDF) in Swinburne University’s Strategic Foresight program. I read Sebastian Mallaby’s history More Money Than God (PDF) and MIT’s Andrew Lo. Hedge funds appeared to be exemplars of Richard Slaughter‘s Institutes of Foresight thesis. More recently, I have thought of hedge funds as possible examples of meso-level, organisational strategic subcultures.

 

Today, I re-watched the PBS Frontline documentary ‘To Catch A Trader‘ (2014) and read the white paper (PDF) from SAC founder Steve A. Cohen’s lawyers in the now-notorious Elan and Wyeth insider trading case. Cohen’s portfolio manager Matthew Martoma was convicted of insider trading and sentenced to jail. Cohen’s SAC was fined millions and is now basically a family office.

 

I’ve had the white paper for over a year but only today got a chance to have a close read of it with an eye on how Cohen’s lawyers describe his trading strategies. I learned to do this when studying strategic foresight methodologies.

 

Some of my summary notes from the white paper:

  • Back of envelope estimate of Steve Cohen’s trading portfolio size in July 2013: $US1,253,000,000.
  • Cohen trades over 80 individual securities a day.
  • Algorithms, direct market access, and dark pools are routinely used for trade execution.
  • The PBS Frontline documentary describes Edge as an informational advantage about market activity.
  • The white paper describes the following as Events: (1) corporate access (competitor announcements; adverse developments); (2) market moving (catalysts, technical analysis); (3) analyst convergence (broker-deal reports; ratings such as downgrades); and (4) market rumours (false market).
  • SAC portfolio managers develop a Company Investment Thesis. This may involve: (1) trimming positions whilst going into earnings announcements; (2) using option hedges to offset long/short positions using a market neutral strategy; (3) anticipating slippage: incremental shifts in share prices due to the timing of executed trades; and (4) responding to risk reviews of large positions.
  • Market price-psychology patterns that Cohen has identified: (1) increases in individual share prices versus S&P 500 declines (deteriorating market) over specific time periods; (2) tests of if positive market reaction is sustainable (possible mean reversion); (3) company news that is ambiguous or less-than-spectacular information that will trigger a decline; and (4) rapid stock appreciation that creates high expectations and the probability of a price decline.

 

The Steve A. Cohen white paper illustrates how to potentially reverse engineer a hedge fund’s trading strategy – as a strategic foresight example – and to not be a Muppet-like naive retail trader.

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Sebastian Mallaby @ CFR on Hedge Funds

 

Sebastian Mallaby’s More Money Than God: Hedge Funds and the Making of a New Elite (New York: The Penguin Press, 2010) is an informative history and defence of hedge funds as an alternative investment vehicle. Mallaby’s 2010 talk at the Council on Foreign Relations captures the book’s major talking points and illustrates how policymakers talk to each-other. Author Chrystia Freeland handles the Q&A giving an early glimpse of themes from her book Plutocrats: The Rise of the New Global Super-Rich and the Fall of Everyone Else (New York: Penguin Press, 2013). The Mallaby-Freeland exchange suggests a possible invisible college or citation network around 1% socio-economic elites. This work informs post-PhD research into the possible strategic subcultures of specific hedge funds and hedge fund managers.

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Thematic Analysis of a Reading List on Investment Alpha

I recently did a thematic analysis of a reading list on investment alpha, which involves:

 

1. Excess return.

2. Active management.

3. Adjusted risk.

 

The following themes emerged from the reading list, and from also checking the rankings of several hundred books at Amazon.com:

 

1. Excess return: fund type (hedge fund, private equity, venture capital); return drivers (including asset class); and quantitative models.

 

2. Active management: discretionary (human trading, portfolio composition and rebalancing, options, technical analysis) and algorithmic (algorithmic trading; complex event / stream processing; computational intelligence; genetic algorithms; machine learning; neural nets; and software agents).

 

3. Adjusted risk: Bayesian probabilities; investor psychology; market microstructure; and risk management models (such as Monte Carlo simulation, Value at Risk, and systematic risk)

 

This core work suggests the following query line:

 

SELECT return drivers (Bayesian belief network) (multi-asset) (portfolio) (fund)

 

 

WHERE risk (Bayesian probability) (exposures) (exposures – investor decisions) (exposures – market microstructure) AND trade (algorithms)

 

ORDER BY Bayesian (belief network, probability); return drivers (multi-asset); risk (exposures); and trading (algorithms).

 

This thematic analysis will help to focus my post-PhD research on the sociology of finance into the following initial research questions:

 

1. What is the spectrum of possible return drivers in a multi-asset world?

 

A good model for this is David Swensen’s Yale endowment portfolio detailed in Pioneering Portfolio Management: An Unconventional Approach to Institutional Investment (New York: The Free Press, 2009). Antti Ilmanen’s magisterial Expected Returns: An Investor’s Guide to Harvesting Market Rewards (Hoboken, NJ: John Wiley & Sons, 2011) has information on the return drivers of specific asset classes. Matthew Hudson’s recent Funds: Private Equity, Hedge Funds, and All Core Structures (Hoboken, NJ: John Wiley & Sons, 2014) deals with global fund structures.

 

2. What specific risk exposures might these multi-assets face, and under what conditions?

 

Richard C. Grinold and Ronald Kahn’s Active Portfolio Management: A Quantitative Approach for Producing Superior Returns and Controlling Risk (New York: McGraw-Hill, 1999) is the classic book on institutional portfolio models. Morton Glantz and Robert Kissell’s Multi-Asset Risk Modeling: Techniques for a Global Economy in an Electronic and Algorithmic Trading Era (San Diego, CA: Academic Press, 2014) is a recent book I will look at. Charles Albert-Lehalle and Sophie Larulle’s Market Microstructure in Practice (Singapore: World Scientific Publishing Company, 2014), and Thierry Foucault, Marco Pagano, and Ailsa Roell’s Market Liquidity: Theory, Evidence, and Policy (New York: Oxford University Press, 2013) deal respectively with the practice and theory of contemporary financial markets. There are many books on behavioural finance and investor psychology: two recent ones are H. Kent Baker and Victor Ricciardi’s collection Investor Behavior: The Psychology of Financial Planning and Investing (Hoboken, NJ: John Wiley & Sons, 2014), and Tim Richards’ Investing Psychology: The Effects of Behavioral Finance on Investment Choice and Bias (Hoboken, NJ: John Wiley & Sons, 2014).

 

3. How can algorithmic trading and computational techniques model the risk-return dynamics of alpha generation?

 

Despite its flaws Rishi K. Narang’s Inside the Black Box: A Simple Guide to Quantitative and High Frequency Trading (New York: John Wiley & Sons, 2013) opened my eyes to the structures needed for alpha generation. The Bayesian approach is detailed in David Barber’s Bayesian Reasoning and Machine Learning (New York: Cambridge University Press, 2012). Barry Johnson’s Algorithmic Trading and DMA: An Introduction to Direct Access Trading Strategies (London: 4Myeloma Press, 2010) and Robert Kissell’s The Science of Algorithmic Trading and Portfolio Management (San Diego, CA: Academic Press, 2013) deal with order types in algorithmic trading. Christian Dunis, Spiros Likothanassis, Andreas Karathanasopoulos, Georgios Sermpinis, and Konstantinos Theofilatos have edited a recent collection on Computational Intelligence Techniques for Trading and Investment (New York: Routledge, 2014). Eugene A. Durenard’s Professional Automated Trading: Theory and Practice (New York: John Wiley & Sons, 2013) covers software agents. For retail trader-oriented applications of data mining, machine learning, and Monte Carlo simulations there is Kevin Davey’s Building Algorithmic Trading Systems: A Trader’s Journey from Data Mining to Monte Carlo Simulation to Live Trading (New York: John Wiley & Sons, 2014), and David Aronson and Timothy Masters’ Statistically Sound Machine Learning for Algorithmic Trading of Financial Instruments: Developing Predictive-Model-Based Trading Systems Using TSSB (CreateSpace, 2013).

 

What this means is that for an investment of about $US1,000 a new researcher can gain some of the core books on institutional, quantitative portfolio and risk management; behavioural finance and market microstructure as potential sources for edges; and some recent practitioner-oriented literature on algorithmic / automated trading that uses computational intelligence.

 

In deference to Mao and McKenzie Wark’s vectoralist class:

 

Let a thousand algorithmic / quantitative micro-funds bloom.

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Hedge Fund Secret Source

The New Yorker‘s John Cassidy recently asked why some hedge funds make so much money.

 

Cassidy like hedge fund critic Les Leopold focuses on two primary reasons: (1) the ‘2 and 20’ fees that hedge fund managers charge investors where the funds charge a 2% administration fee and take 20% of the profits; and (2) carried interest loopholes in United States tax laws that hedge funds are structured to take advantage of.

 

Yet the other reason Cassidy does not explore is the hedge fund secret source: their trading strategies and transaction execution capabilities.

 

The vanilla version of hedge fund strategies is well known. For instance, ‘long / short’ funds take a long (upside) position in financial securities whilst ‘shorting’ (downside) others. Global macro funds profit from geopolitical risk and central bank monetary policy. Distressed debt and special event funds make profits from turnarounds or from creating situations where there are crowded trades and rational herding among investors.

 

The secret source is how a vanilla strategy is transformed into one where there is an edge or positive expectancy that is in the hedge fund’s favour. Some pre-quant hedge fund managers learned this from formative childhood experiences playing backgammon and poker. The quants studied Andrey Kolmogorov‘s probability work, and applied it to market microstructure patterns of the order book, and price / volume dynamics. Others benefited from geopolitical events: the 1973-74 growth of offshore Eurodollar markets (Paul Tudor Jones); the European Union’s Exchange Rate Mechanism and Black Wednesday (George Soros); or understanding bubble dynamics in the 1995-2000 dotcom bubble (trader Dan Zanger) and 2007-09 global financial crisis (John Paulson).

 

One of the keys to this is having a transaction execution capability. It means having a prime broker relationship with more favourable terms than retail traders get. It means having the complex event processing / stream processing capabilities to identify edges / positive expectancy and to trade them in many different financial instruments, markets, and timeframes. This is why some retail traders look at Edwards & Magee-style technical analysis and signals software; successful proprietary traders use trading psychology and market microstructure theory; and quantitative hedge funds use computational intelligence, machine learning, and software agents.

 

Cassidy and Leopold rail against hedge fund managers as a financialisation symbol of extreme income inequality. Their arguments resonate with many people who are legitimately angry about how much money some hedge funds make – even though there is survivorship bias. But what Cassidy and Leopold may obscure is the fact that – to quote the mid-1990s television show The X-Files – the information to create hedge fund-like capabilities is out there, scattered, waiting to be identified and reassembled into new forms. William Gibson, Bruce Sterling, and Charles Stross have already given fictional hints in their novels about what this proto-cyberpunk world might resemble.

 

When these hedge fund capabilities ‘cross the chasm’ from the hedge fund managers (1%) to the multitudes (90%) then things will get even more interesting.

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Ray Dalio’s How The Economic Machine Works

 

Ray Dalio is the legendary founder of the Bridgewater hedge fund which manages $US150 billion for the World Bank and pension fund clients. Dalio is influential for sharing his management principles that inform Bridgewater’s strategic subculture (PDF). He has now shared a 30-minute video on his personal model of global macro dynamics.

 

Maneet Ahuja has a chapter-length interview with Dalio in her book The Alpha Masters (Hoboken, NJ: John Wiley & Sons, 2012) in which he talks about how to learn; how he founded and built Bridgewater; dealing with the World Bank; and how to deal with crises:

 

If you’re limiting yourself to what you experienced, you are going to be in trouble. . . . I studied the Great Depression. I studied the Weimar Republic. I studied important events that didn’t happen to me. (p. 12).

 

Dalio says if you have 15 or more good, uncorrelated bets, you will improve your return to risk ratio by a factor of five. He calls this the holy grail of investing. “If you can do this thing successfully, you will make a fortune,” he says. “You’ll get the pot of gold at the end of the rainbow.” (p. 17).