Risk, Time-Varying Second Moments and Market Efficiency

1991 ◽  
Vol 58 (3) ◽  
pp. 479 ◽  
Author(s):  
Orazio P. Attanasio
Keyword(s):  
Market Efficiency ◽  
Time Varying ◽  
Second Moments

Evolving time-varying market efficiency of energy stock market

2020 ◽  
Vol 27 (36) ◽  
pp. 45539-45554
Author(s):  
Negar Fazlollahi ◽  
Nesrin Ozatac ◽  
Korhan K. Gokmenoglu
Keyword(s):  
Stock Market ◽  
Market Efficiency ◽  
Time Varying

scholarly journals Time-Varying Price–Volume Relationship and Adaptive Market Efficiency: A Survey of the Empirical Literature

2019 ◽  
Vol 12 (2) ◽  
pp. 105 ◽  
Author(s):  
Ashok Chanabasangouda Patil ◽  
Shailesh Rastogi
Keyword(s):  
Market Efficiency ◽  
Cross Correlation ◽  
Efficient Market Hypothesis ◽  
Return Predictability ◽  
Empirical Literature ◽  
Fluctuation Analysis ◽  
Time Varying ◽  
Review Of The Literature ◽  
Volume Relationship ◽  
Detrended Fluctuation

This paper conducts a review of the literature on the price–volume relationship and its relation with the implications of the adaptive market hypothesis. The literature on market efficiency is classified as efficient market hypothesis (EMH) studies or adaptive market hypothesis (AMH) studies. Under each class, studies are categorized either as return predictability studies or price–volume relationship studies. Finally, review in each category is analyzed based on the methodology used. Our review shows that the literature on return predictability and price–volume relationship in classical EMH approach is extensive while studies in return predictability in the AMH approach have gained increased attention in the last decade. However, the studies in price–volume relationship under adaptive approach are limited, and there is a scope for studies in this area. Authors did not find any literature review on time-varying price–volume relationship. Authors find that there is a scope to study the nonlinear cross–correlation between price and volume using detrended fluctuation analysis (DFA)-detrended cross–correlational analysis (DXA) in the AMH domain. Further, it would be interesting to investigate whether the same cross–correlation holds across different measures of stock indices within a country and across different time scales.

FORECASTING NATIONAL FOOTBALL LEAGUE GAME OUTCOMES RELATIVE TO BETTING SPREADS

2013 ◽  
Vol 6 (3) ◽  
pp. 1-16
Author(s):  
William Mallios
Keyword(s):  
Risk Assessment ◽  
New York ◽  
Market Efficiency ◽  
National Football League ◽  
Time Varying ◽  
Volatility Risk ◽  
Varying Coefficients ◽  
Time Varying Coefficients ◽  
Linear Regressions

Cointegrated time processes measuring NFL playoff game performances relative to the betting spreads are graphed in terms of candlestick charts and forecast in terms of autoregressive systems with time varying coefficients. Coefficients are modeled in terms of linear regressions on lagged shocks. Estimation is non Bayesian. Forecasts provide measures of market efficiency/inefficiency and outcome volatility. Risk assessment utilizes GARCH-type modeling in estimating volatility. Applications are presented for the New York Giants 2012 playoff games based on a data backlog of three years.

Time Varying Behavior of Share Returns in Australia: 1988–2004

2016 ◽  
Vol 19 (01) ◽  
pp. 1650004
Author(s):  
Yew-Choe Lum ◽  
Sardar M. N. Islam
Keyword(s):  
Stock Returns ◽  
Future Research ◽  
Practical Reasons ◽  
Time Varying ◽  
Asymmetric Effect ◽  
Conditional Capm ◽  
Conditional Mean ◽  
Second Moments ◽  
Statistical Sense ◽  
Capm Model

The model in this paper is similar to Brailsford and Faff (1997), using a conditional CAPM model with the GARCH-M framework, but with a significant additional dummy term (in the conditional mean of the share return) that will help explain the models better in both economic and statistical sense. The relatively simpler asymmetric model in this paper is compatible to other more complex asymmetric models and hence should be easier to model and explain for practical purposes. The model in this paper is also a more effective model, in both economical and statistical terms, as compared to some other models in the GARCH family as it captures the asymmetric effect in the modeling process in both the conditional first and second moments. The findings in this paper have contributed in re-evaluating the nature and process of time varying behavior of time series of stock returns and will provide researchers and practitioners additional options and incentives to explore for future research. We have also provided statistical and practical reasons to support these findings.

scholarly journals International stock market efficiency: a non-Bayesian time-varying model approach

2014 ◽  
Vol 46 (23) ◽  
pp. 2744-2754 ◽  
Author(s):  
Mikio Ito ◽  
Akihiko Noda ◽  
Tatsuma Wada
Keyword(s):  
Stock Market ◽  
Market Efficiency ◽  
Time Varying ◽  
Stock Market Efficiency ◽  
Model Approach

Market efficiency in Indian soybean futures markets

2014 ◽  
Vol 9 (4) ◽  
pp. 520-534 ◽  
Author(s):  
Thiagu Ranganathan ◽  
Usha Ananthakumar
Keyword(s):  
Market Efficiency ◽  
Risk Premium ◽  
Futures Markets ◽  
Structural Breaks ◽  
Time Varying ◽  
Content Type ◽  
Futures Contract ◽  
Long Run ◽  
Short Run ◽  
Commodity Derivatives

Purpose – The National commodity exchanges were established in India in the year 2003-2004 to perform the functions of price discovery and price risk management in the economy. The derivatives market can perform these functions properly only if they are efficient and unbiased. So, there is a need to properly evaluate these aspects of the Indian commodity derivatives market. The purpose of this paper is to test the market efficiency and unbiasedness of the Indian soybean futures markets. Design/methodology/approach – The paper uses cointegration and a QARCH-M-ECM-based framework to test the market efficiency and unbiasedness in the soybean futures contract traded in the National Commodity Derivatives Exchange (NCDEX). The cointegration test is used to test the long-run unbiasedness and market efficiency of the contract, while the QARCH-M-ECM model is used to test the short-run market efficiency and unbiasedness of the contract by allowing for a time-varying risk premium. The price data is also tested for presence of structural breaks using a Zivot and Andrews unit root test. Findings – The soybean contract is unbiased in the long run, but there are short-run market inefficiencies and also a presence of a time-varying risk premium. Though the weak form of market efficiency is rejected in the short run, the semi-strong market efficiency is not rejected based on the forecasts. Originality/value – This is the first paper to consider time-varying risk premium while performing the tests of market efficiency and unbiasedness on Indian commodity markets.

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