Testing and comparing conditional risk‐return relationship with a new approach in the cross‐sectional framework

Messis, Petros; Alexandridis, Antonis; Zapranis, Achilleas

doi:10.1002/ijfe.1786

Cited by 6 publications

(4 citation statements)

References 77 publications

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“…Fama and French (2015), for instance, argue that their five-factor model performs better than their three-factor model (FF, 1993) but still shows alphas that are jointly significantly different from zero. Similarly, Harvey and Siddique (2000), Dittmar (2002), Messis, Alexandridis, and Zapranis (2021), Lewellen and Nagel (2006), and Maio and Santa-Clara (2012), present studies respectively on the conditional three-moment CAPM, four-moment CAPM, CAPM with asymmetric and constant systemic risk, conditional consumption CAPM, CCAPM, and ICAPM, finding similar results in terms of the significance of the intercepts.…”

Section: Introductionsupporting

confidence: 64%

Explaining Abnormal Returns in Stock Markets: An Alpha-Neutral Version of the CAPM

Rocciolo¹,

Gheno

Brooks

2018

SSRN Journal

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Section: Introductionsupporting

confidence: 64%

Explaining Abnormal Returns in Stock Markets: An Alpha-Neutral Version of the CAPM

Rocciolo¹,

Gheno

Brooks

2018

SSRN Journal

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“…The hypotheses are assessed using a t-Student test for average value with a one or two-sided critical area according to the formula (Messis et al, 2021).…”

Section: Unconditional Relationships Of Modifications Of Capm In Conv...mentioning

confidence: 99%

Conventional and downside CAPM with higher-order moments: Evidence from emerging markets

Markowski

2024

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Research background: Conventional CAPM is a well-known and tested theory on various capital markets. It was also repeatedly rejected as a model of capital pricing. This article proposes a different approach to both CAPM testing and the use of other risk measures. In addition, research is global, including emerging countries. Purpose of the article: This paper investigates the standard CAPM, and this model is based on higher moments of the return distribution for the global emerging market. In addition, this paper aims to compare the conventional and downside CAPM versions using the beta coefficient and co-moments. Methods: Contrary to the classical unconditional tests for the risk premium, conditional relationships are also estimated considering the market portfolio condition. Moreover, the studies considered conventional and downside approaches to risk measures. The cross-sectional regressions are based on the Fama-MacBeth (F-M) procedure and panel models. Findings & value added: The findings contribute to the debate on whether beta coefficient and higher order co-moments in conventional and downside approaches can explain the cross-sectional emerging indices returns. The unconditional models using all measures do not significantly describe the cross-sectional volatility of returns. The cross-sectional regressions in up and down-market based on both the classic F-M procedure and panel models show that the beta and co-kurtosis risk premium is significant and depends on market conditions. The risk premium for co-skewness is not valid, and the direction of the relationships is opposite than expected. Research also demonstrates that the test results of CAPM relationships are not robust to the presence of outliers and shocks resulting from the Covid-19 pandemic in the context of risk-return space. Research provides strong support for the importance of downside risk in the context of standard CAPM and, above all, higher co-moments.

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“…Multicollinearity refers to a state in which several independent variables exhibit a high level of linear correlation, which can affect model fit and results (Khan et al, 2016). Additionally, the choice of macroeconomic variables analyzed are often guided by an underlying subjective approach (Messis et al, 2019). This suggests a bias in the chosen macroeconomic fundamentals in explaining the risk-return relationship (Park et al, 2017) [16] .…”

Section: Empirical Reviewmentioning

confidence: 99%

A solution to the risk-return conundrum: Return exposure and the nonparametric Bayesian approach

Dwarika

2023

IJMRGE

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The topic of the risk-return relationship is of broad importance in the fields of finance and economics. It has been widely investigated on an international scale, especially by developed markets from as early as the 1950's, with the primary motive being to help market participants optimize their chance to earn higher returns. According to conventional economic theory, the relationship between risk and return is a positive and linear relationship – the higher the risk, the higher the return. However, there are many studies documented in literature which show a positive or negative or no relationship at all. As a result, due to the magnitude of conflicting results over the years, this has caused an ongoing debate to arise regarding the risk-return relationship. International studies have explored a number of theories and models to attempt resolving the inconclusive empirical backing of the risk-return relationship. A valuable contribution of this study is the introduction of the novel concept “returns exposure” which refers to the risk that arises from the asymmetric nature of returns. This measure has a certain level of uncertainty attached to it due to its latent and stochastic nature. As a result, it may be ineffectively accounted for by existing parametric methods such as regression analysis and GARCH type models which are prone to model misspecification. This motivates the use of a more robust method, namely, the nonparametric Bayesian approach. The Bayesian approach has the ability to average out sources of uncertainty and measurement errors and thus effectively account for “return risk” or “returns exposure.” The Bayesian approach can be modelled within a parametric or nonparametric framework. The nonparametric approach is considered more robust as it relaxes modelling assumptions such as normality. Thus, in combination with the nonparametric approach, this provides a more robust estimation of the risk-return relationship.

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Testing and comparing conditional risk‐return relationship with a new approach in the cross‐sectional framework

Cited by 6 publications

References 77 publications

Explaining Abnormal Returns in Stock Markets: An Alpha-Neutral Version of the CAPM

Explaining Abnormal Returns in Stock Markets: An Alpha-Neutral Version of the CAPM

Conventional and downside CAPM with higher-order moments: Evidence from emerging markets

A solution to the risk-return conundrum: Return exposure and the nonparametric Bayesian approach

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