Efficient Capital Markets: A Review of Theory and Empirical Work

By A. Laffer. 2017

Subfields: Economics & Operations Research

How researchers see this paper

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

In Economics & Operations Research

Citations in the corpus

Autoregressive Convolutional Neural Networks for Asynchronous Time Series (2017, background): “A common situation with ﬁnancial data is that the same signal (e.g. value of an asset) is observed from different sources (e.g. ﬁnancial news, analysts, portfolio managers in hedge funds, market-makers in investment banks) in asynchronous moments of time.”
Long short‐term memory networks for CSI300 volatility prediction with Baidu search volume (2018, background): “Prediction tasks on financial time series are notoriously difficult, primarily driven by the high degree of noise and the generally accepted, semi-strong form of market efficiency [3].”
Assessing the Efficacy of Adjustable Moving Averages Using ASEAN-5 Currencies (2016, background): “Even though the efficient market and random walk hypotheses contradict this approach by affirming that all public information in the market is immediately reflected in prices, and that abnormal returns can never be made with only knowledge of historical data [16], empirical evidence however, indicat”
Application of the Fractional Diffusion Equation for Predicting Market Behaviour (2010, methodology): “(i) The DFT is taken to generate an output in standard form where the zero frequency component of the power spectrum is taken to be P [1].”
On stock return prediction with LSTM networks (2017, background): “Gencay (1996) and Gencay & Stengos (1998) examine how simple feedforward networks performs compared to an ARMA(1,1)-GARCH(1,1) model.”
Are there exploitable inefficiencies in the futures market for oil (2007, background): “If historical price patterns can indeed be used to predict future prices, the market would not fit the strict definition of efficient markets laid out by Fama (1970).”
Annual report readability and corporate agency costs (2018, background): “, annual reports) is quickly reflected in the stock price, which may lead investors’ trading behavior and thus optimize the resource allocation in capital markets (Malkiel and Fama, 1970).”
The Corporate Headquarters in the Contemporary Corporation: Advancing a Multimarket Firm Perspective (2015, background): “These studies build on transaction cost theory (Coase, 1937; Williamson, 1975, 1981), agency theory (Berle & Means, 1932; Jensen & Meckling, 1976), and the efficient market hypothesis (Fama, 1970), which is a pillar of financial economics (Markovitz, 1952; Modigliani & Miller, 1958) to explain how e”
Commodity futures and market efficiency (2013, background): “Efficient market hypothesis (EMH) has been a cornerstone of financial economics for decades and it has been brought to the forefront by the influential paper of Fama (1970), summarizing the empirical findings based on efficient market hypotheses by Fama (1965) and Samuelson (1965).”
Asymmetric causality tests with an application (2012, background): “10 Fama (1970) promoted the EMH and described three forms of this hypothesis.”
Some stylized facts of the Bitcoin market (2017, background): “Following [26], informational efficiency can be divided into three categories: (i) weak efficiency, if prices reflect the information contained in the past series of prices, (ii) semi-strong efficiency, if prices reflect all public information and (iii) strong efficiency, if prices reflect all publi”