The Adaptive Markets Hypothesis

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How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

Deep Reinforcement Learning: An Overview (2017, background): “A reconciliation is the adaptive markets hypothesis (Lo, 2004), which may be approached by reinforcement learning.”
Measuring the degree of time varying market inefficiency (2009, methodology): “Lo (2004) is an exception, as is described in section 2. In this paper, we realize an empirical study measuring a gradually time varying structure of market inefficiency.”
Econometric Measures of Systemic Risk in the Finance and Insurance Sectors (2010, background): “As this effect is amplified, the tighter are the connections and integration among financial institutions, heightening the severity of systemic events as shown by Castiglionesi, Periozzi, and Lorenzoni (2009) and Battiston et al.”
Stochastic and genetic neural network combinations in trading and hybrid time-varying leverage effects (2014, background): “Profitable trading strategies exist at any time but their strength and robustness is diminishing over time (Lo (2004)).”
A Forex trading system based on a genetic algorithm (2012, background): “1 EMH has been challenged by behavioral economists, who argue that markets are not rational, but are driven by fear and greed (Lo 2004).”
Applications of news analytics in finance: A review (2012, background): “Lo (2004) proposes a new framework—the Adaptive Market Hypothesis (AMH)—which seeks to reconcile market efficiency with behavioural alternatives.”