Adaptive market hypothesis

About: Adaptive market hypothesis is a research topic. Over the lifetime, 193 publications have been published within this topic receiving 15969 citations.

Does the Stock Market Overreact

Abstract: Research in experimental psychology suggests that, in violation of Bayes' rule, most people tend to "overreact" to unexpected and dramatic news events. This study of market efficiency investigates whether such behavior affects stock prices. The empirical evidence, based on CRSP monthly return data, is consistent with the overreaction hypothesis. Substantial weak form market inefficiencies are discovered. The results also shed new light on the January returns earned by prior "winners" and "losers." Portfolios of losers experience exceptionally large January returns as late as five years after portfolio formation. As ECONOMISTS INTERESTED IN both market behavior and the psychology of individual decision making, we have been struck by the similarity of two sets of empirical findings. Both classes of behavior can be characterized as displaying overreaction. This study was undertaken to investigate the possibility that these phenomena are related by more than just appearance. We begin by describing briefly the individual and market behavior that piqued our interest. The term overreaction carries with it an implicit comparison to some degree of reaction that is considered to be appropriate. What is an appropriate reaction? One class,,of tasks which have a well-established norm are probability revision problems for which Bayes' rule prescribes the correct reaction to new information. It has now been well-established that Bayes' rule is not an apt characterization of how individuals actually respond to new data (Kahneman et al. [14]). In revising their beliefs, individuals tend to overweight recent information and underweight prior (or base rate) data. People seem to make predictions according to a simple matching rule: "The predicted value is selected so that the standing of the case in the distribution of outcomes matches its standing in the distribution of impressions" (Kahneman and Tversky [14, p. 416]). This rule-of-thumb, an instance of what Kahneman and Tversky call the representativeness heuristic, violates the basic statistical principal that the extremeness of predictions must be moderated by considerations of predictability. Grether [12] has replicated this finding under incentive compatible conditions. There is also considerable evidence that the actual expectations of professional security analysts and economic forecasters display the same overreaction bias (for a review, see De Bondt [7]). One of the earliest observations about overreaction in markets was made by J. M. Keynes:"... day-to-day fluctuations in the profits of existing investments,

Stock Market Prices Do Not Follow Random Walks: Evidence from a Simple Specification Test

Abstract: In this article we test the random walk hypothesis for weekly stock market returns by comparing variance estimators derived from data sampled at different frequencies. The random walk model is strongly rejected for the entire sampleperiod (1962-1985) and for all subperiods for a variety of aggregate returns indexes and size-sorted porfolios. Although the rejections are due largely to the behavior of small stocks, they cannot be attributed completely to the effects of infrequent trading or timevarying volatilities. Moreover, the rejection of the random walk for weekly returns does not support a mean-reverting model of assetprices.

The Efficient Market Hypothesis and Its Critics

Abstract: Ageneration ago, the efe cient market hypothesis was widely accepted by academic e nancial economists; for example, see Eugene Fama’ s (1970) ine uential survey article, “ Efe cient Capital Markets.” It was generally believed that securities markets were extremely efe cient in ree ecting information about individual stocks and about the stock market as a whole. The accepted view was that when information arises, the news spreads very quickly and is incorporated into the prices of securities without delay. Thus, neither technical analysis, which is the study of past stock prices in an attempt to predict future prices, nor even fundamental analysis, which is the analysis of e nancial information such as company earnings and asset values to help investors select “ undervalued” stocks, would enable an investor to achieve returns greater than those that could be obtained by holding a randomly selected portfolio of individual stocks, at least not with comparable risk. The efe cient market hypothesis is associated with the idea of a “ random walk,” which is a term loosely used in the e nance literature to characterize a price series where all subsequent price changes represent random departures from previous prices. The logic of the random walk idea is that if the e ow of information is unimpeded and information is immediately ree ected in stock prices, then tomorrow’ s price change will ree ect only tomorrow’ s news and will be independent of the price changes today. But news is by dee nition unpredictable, and, thus, resulting price changes must be unpredictable and random. As a result, prices fully ree ect all known information, and even uninformed investors buying a diversie ed portfolio at the tableau of prices given by the market will obtain a rate of return as generous as that achieved by the experts.

The Adaptive Markets Hypothesis

Abstract: One of the most influential ideas in the past 30 years is the efficient markets hypothesis, the idea that market prices incorporate all information rationally and instantaneously. The emerging discipline of behavioral economics and finance has challenged the EMH, arguing that markets are not rational, but rather driven by fear and greed. Research in the cognitive neurosciences suggests these two perspectives are opposite sides of the same coin. An adaptive markets hypothesis that reconciles market efficiency with behavioral alternatives applies the principles of evolution?competition, adaptation, and natural selection?to financial interactions. Extending Simon9s notion of ?satisficing? with evolutionary dynamics, the author argues that much of what behaviorists cite as counter-examples to economic rationality?loss aversion, overconfidence, overreaction, mental accounting, and other behavioral biases?is in fact consistent with an evolutionary model of individual adaptation to a changing environment via simple heuristics. The adaptive markets hypothesis offers a number of surprisingly concrete implications for portfolio management.

Reconciling Efficient Markets with Behavioral Finance: The Adaptive Markets Hypothesis

Abstract: The battle between proponents of the Efficient Markets Hypothesis and champions of behavioral finance has never been more pitched, and there is little consensus as to which side is winning or what the implications are for investment management and consulting. In this article, I review the case for and against the Efficient Markets Hypothesis, and describe a new framework - the Adaptive Markets Hypothesis - in which the traditional models of modern financial economics can co-exist alongside behavioral models in an intellectually consistent manner. Based on evolutionary principles, the Adaptive Markets Hypothesis implies that the degree of market efficiency is related to environmental factors characterizing market ecology such as the number of competitors in the market, the magnitude of profit opportunities available, and the adaptability of the market participants. Many of the examples that behavioralists cite as violations of rationality that are inconsistent with market efficiency - loss aversion, overconfidence, overreaction, mental accounting, and other behavioral biases - are, in fact, consistent with an evolutionary model of individuals adapting to a changing environment via simple heuristics. Despite the qualitative nature of this new paradigm, I show that the Adaptive Markets Hypothesis yields a number of surprisingly concrete applications for both investment managers and consultants.