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Financial Markets as Massively Multiplayer Gambling

Posted in Animal Spirits, Big Ideas

Are financial markets best viewed as massively multiplayer gambling? In his March 2017 paper entitled “Why Markets Are Inefficient: A Gambling ‘Theory’ of Financial Markets for Practitioners and Theorists”, Steven Moffitt presents a model of financial markets based on the perspective of an analytical/enlightened gambler. The gambler believes that: (1) actions of many players (some astute, some mediocre and some fools) drive prices; and, (2) markets adapt such that all static trading systems eventually fail. The gambler combines fundamental laws of gambling, knowledge of trading strategies of other market participants and data analysis to identify and exploit trading opportunities. The gambler translates this general strategy into a specific plan that algorithmically generate trades. Key aspects of the model are, as proposed:

  • The fundamental laws of gambling are:
    1. Bet only when you believe you have an edge.
    2. Limit bets to a fraction of capital consistent with: an estimate of the size of the edge; a minimum return requirement; and, a bearable drawdown. Fractional Kelly betting offers approximately optimal portfolio growth given a drawdown constraint.
  • Opportunities evolve through four phases:
    1. Eureka!
    2. Early copycat, with contagion likely only if competing strategies link via some network.
    3. Late copycat, commonly with high return volatility near the end as many traders scale back or liquidate. The longer this phase lasts, the greater the likelihood of a crash.
    4. Crash, always with a reduction in liquidity and associated large price moves that large traders cannot escape.
  • Sources of gambling opportunities include:
    • Others (i.e., mutual funds) revealing information about their strategies, offering the advantage of second move.
    • Human biases that foster partly predictable strategic behavior of others.
    • Price distorters based on news, constraints on trading, widely held beliefs, widely used strategies or cyclic market behaviors.
  • Strategic analysis of markets involves six steps systematically applied based on a good working knowledge of market history and market ecology:
    1. Select potential price distorters.
    2. Assemble data to investigate the price impacts of these distorters.
    3. Formulate strategic plans for material price impacts from step 2. 
    4. Convert each strategic plan into a trading algorithm.
    5. Backtest each trading algorithm and iterate steps 3, 4 and 5 as necessary.
    6. For each promising backtest, locate the position of the opportunity within the four-phase life cycle and exploit future phases.

In summary, retrospection suggests that investors can reasonably view financial markets as massively multiplayer gambling.

Cautions regarding conclusions include:

  • The model is explanatory only. The author does not derive and test any new trading opportunities or strategies.
  • This different perspective on markets does not relieve the endemic issue of specific and aggregate snooping bias in backtests.
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