Short- and Long-Horizon Behavioral Anomalies and Institutional Investors’ Nudge Behavior: Based on the Data of Listed Chinese Tobacco Companies

2021 ◽  
Vol 7 (5) ◽  
pp. 1904-1922
Author(s):  
Liu Yue ◽  
Liu Tianming
Keyword(s):  
Asset Pricing ◽  
Institutional Investors ◽  
Regulatory Agencies ◽  
Pricing Models ◽  
Healthy Development ◽  
Limits To Arbitrage ◽  
Asset Pricing Models ◽  
Pricing Factors ◽  
The Impact

We use the data of listed tobacco companies in China to study the existence of short- and long-horizon behavioral anomalies and the impact of institutional investors’ behavior on them. We found that the existing asset pricing models cannot explain the short- and long-horizon behavioral anomalies based on tobacco enterprise data. Conversely, the short- and long-horizon behavioral anomalies can explain the exciting asset pricing factors. Compared with existing asset pricing models, behavioral anomalies have a stronger ability to explain anomalies. Behavioral anomalies could pass the cross-sectionally test and strengthened over time. The above results indicate that behavioral anomalies exist in China tobacco enterprisest significantly and are time-varying. We found that the limits to arbitrage and cognitive bias lead to the existence of behavioral anomalies through mechanism tests. Institutional investors did not play the role of price discovery. Instead, their nudge behavior strengthens the short- and long-horizon behavioral anomalies. Therefore, tobacco regulatory agencies should guide listed tobacco companies to broaden information channels to reduce information asymmetry in the market through relevant policies, strengthen the supervision of institutional investors’ bubble riding behavior, and promote the healthy development of the tobacco market.

Nonrevealing Equilibria and Consumption-Based Asset Pricing Models

2006 ◽  
Vol 6 (1) ◽  
Author(s):  
James E Gunderson
Keyword(s):  
Asset Pricing ◽  
Private Information ◽  
Rational Expectations ◽  
Investment Risk ◽  
Conditional Distributions ◽  
Pricing Models ◽  
Asset Pricing Models ◽  
Empirical Tests ◽  
The Impact ◽  
Investment Choices

In the rational expectations equilibrium of this paper, agents have private information and differing information partitions and therefore assign differing conditional distributions to asset payoffs and other economic variables relevant to their investment choices. Standard asset pricing models typically do not recognize the impact of these differing information partitions, and empirical tests based on these models thus measure asset riskiness in a way that may not be relevant to any of the agents' decisions. I show how this can lead to distorted estimates of investment risk and how it can make the equity premium appear difficult to explain.

scholarly journals Identifying outliers in asset pricing data with a new weighted forward search estimator

2020 ◽  
Vol 31 (84) ◽  
pp. 458-472
Author(s):  
Alexandre Aronne ◽  
Luigi Grossi ◽  
Aureliano Angel Bressan
Keyword(s):  
Asset Pricing ◽  
Factor Model ◽  
The United States ◽  
Estimation Methods ◽  
Annual Data ◽  
Forward Search ◽  
Pricing Models ◽  
Asset Pricing Models ◽  
The Impact ◽  
Three Factor

ABSTRACT The purpose of this work is to present the Weighted Forward Search (FSW) method for the detection of outliers in asset pricing data. This new estimator, which is based on an algorithm that downweights the most anomalous observations of the dataset, is tested using both simulated and empirical asset pricing data. The impact of outliers on the estimation of asset pricing models is assessed under different scenarios, and the results are evaluated with associated statistical tests based on this new approach. Our proposal generates an alternative procedure for robust estimation of portfolio betas, allowing for the comparison between concurrent asset pricing models. The algorithm, which is both efficient and robust to outliers, is used to provide robust estimates of the models’ parameters in a comparison with traditional econometric estimation methods usually used in the literature. In particular, the precision of the alphas is highly increased when the Forward Search (FS) method is used. We use Monte Carlo simulations, and also the well-known dataset of equity factor returns provided by Prof. Kenneth French, consisting of the 25 Fama-French portfolios on the United States of America equity market using single and three-factor models, on monthly and annual basis. Our results indicate that the marginal rejection of the Fama-French three-factor model is influenced by the presence of outliers in the portfolios, when using monthly returns. In annual data, the use of robust methods increases the rejection level of null alphas in the Capital Asset Pricing Model (CAPM) and the Fama-French three-factor model, with more efficient estimates in the absence of outliers and consistent alphas when outliers are present.

Models or Stars: The Role of Asset Pricing Models and Heuristics in Investor Risk Adjustment

2020 ◽  
Vol 34 (1) ◽  
pp. 67-107 ◽  
Author(s):  
Richard B Evans ◽  
Yang Sun
Keyword(s):  
Asset Pricing ◽  
Risk Adjustment ◽  
Factor Models ◽  
Strongly Correlated ◽  
Pricing Models ◽  
Asset Pricing Models ◽  
Retail Investors ◽  
Before And After ◽  
Sector Funds

Abstract We examine the role of factor models and simple performance heuristics in investor decision-making using Morningstar’s 2002 rating methodology change. Before the change, flows strongly correlated with CAPM alphas. After, when funds are ranked by size and book-to-market groups, flows become more sensitive to 3-factor alphas (FF3). Flows to a matched institutional sample (same managers/strategies) follow FF3 before and after the change but are unrelated to the CAPM. Placebo tests with sector funds and other factor loadings show no effects. Our results imply that improvements in simple performance heuristics can result in more sophisticated risk adjustment by retail investors.

The role of sorting portfolios in asset-pricing models

2011 ◽  
Vol 21 (18) ◽  
pp. 1381-1396 ◽  
Author(s):  
J. Ernstberger ◽  
H. Haupt ◽  
O. Vogler
Keyword(s):  
Asset Pricing ◽  
Pricing Models ◽  
Asset Pricing Models

scholarly journals Neoclassical Asset Pricing Tests in Sri Lanka: A Structural Empirical Review

2020 ◽  
Vol 12 (2) ◽  
pp. 39
Author(s):  
Neelangie Sulochana Nanayakkara ◽  
P. D. Nimal ◽  
Y. K. Weerakoon
Keyword(s):  
Asset Pricing ◽  
Sri Lanka ◽  
Stock Returns ◽  
Pricing Models ◽  
Cross Sectional ◽  
Holistic View ◽  
Asset Pricing Models ◽  
Fama And French ◽  
The Impact ◽  
Empirical Investigations

Neoclassical asset pricing models try to explain cross sectional variation in stock returns. This study critically reviews the findings of empirical investigations on neoclassical asset pricing models in the Colombo Stock Exchange (CSE), Sri Lanka. The study uses the structural empirical review (SER) methodology to capture a holistic view of empirical investigations carried out in the CSE from the year 1997 to 2017.The pioneering Capital Asset Pricing Model (CAPM) (Sharpe, 1964; Lintner, 1965: Black, 1972) (SLB) states that market betas of stocks are sufficient to explain the cross sectional variation of stock returns. Alternatively there are multifactor models (Ross, 1976; Chen, 1986; Fama and French, 1993, 2015; Cahart, 1997) that state stock returns are driven by multiple risk factors. Similar to other markets the findings on the SLB model are not consistent in the CSE. The Fama and French (1993) and the Cahart (1997) models are supported in the CSE which is consistent with other markets, but the explanatory powers of them are substantially low in the Sri Lankan context. Contrasting the findings of a significant impact of macroeconomic factors on stock returns in developed markets, the impact of them in the CSE are temporary.The overall findings of the applicability of neoclassical asset pricing models in the CSE are inconsistent and inconclusive and the study identifies two reasons that may have contributed to such results. Firstly, it recognises that the inherent limitations of neoclassical asset pricing models may have affected the findings in the CSE. Secondly, it supports the argument that neoclassical models, as they are may not be applicable in emerging or frontier markets, thus they may need to be augmented with characteristics of such markets to make them more applicable.

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