Size, Value, and Momentum in Polish Equity Returns: Local or International Factors?

Zaremba, Adam; Konieczka, Przemysław

doi:10.1515/ijme-2017-0017

Cited by 8 publications

(6 citation statements)

References 61 publications

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“…This argument is in line with [13]. Likewise, Zaremba and Konieczka [41] reported that the value factor performs poorly on the Polish market. Barillas and Shanken [42] compared different asset pricing models, and they reported that the model containing the value factor performs the best.…”

Section: Regression Results Of β and Dβsix-factor Model For The Period 2012-2018supporting

confidence: 73%

Downside Risk-Based Six-Factor Capital Asset Pricing Model (CAPM): A New Paradigm in Asset Pricing

et al. 2020

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The importance of downside risk cannot be denied. In this study, we have replaced beta in the five-factor model of using downside beta and have added a momentum factor to suggest a new six-factor downside beta capital asset pricing model (CAPM). Two models are tested—a beta- and momentum-based six-factor model and a downside-beta- (proxy of downside risk) and momentum-based six-factor model. Beta and downside beta are highly correlated; therefore, portfolios are double-sorted to disentangle the correlation. Factor loadings, i.e., size, value, momentum, profitability, and investment, are constructed. The standard methodologies are applied. Data for sample stocks from different non-financial sectors listed in the Pakistan Stock Exchange (PSX) are taken from January 2000 to December 2018. The PSX-100 index and three-month T-bills are taken as proxies for market and risk-free returns. The study uses three subsamples for robustness—period of very high volatility, period of stability, and period of stability and growth with volatility. The results show that the value factor is redundant in both models. The momentum factor is rejected in the beta-based six-factor model only. The beta-based six-factor model shows very low R2 in periods of highly volatility. The R2 is high for the other periods. In contrast, the downside beta six-factor model captures the downside trend of the market in an effective manner with a relatively high R2. The risk–return relationship is stronger for the downside beta model. These reasons lead us to believe that, overall, the downside beta six-factor model is a better option for investors as compared to the beta-based six-factor model in the area of asset pricing models.

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Section: Regression Results Of β and Dβsix-factor Model For The Period 2012-2018supporting

confidence: 73%

Downside Risk-Based Six-Factor Capital Asset Pricing Model (CAPM): A New Paradigm in Asset Pricing

et al. 2020

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“…Here the study built on the line of research indicating that Carhart four-factor model outperforms capital asset pricing model (Sharpe, 1964), the Fama and French (1993) three-factor model, Carhart’s (1997) four-factor model and the Fama and French (2015) five-factor model and is best suited to explain the cross-section of stock returns (Balakrishnan, 2015; Lobao and Fernandez, 2017; Zaremba and Konieczka, 2017; Zaremba et al , 2019).…”

Section: Methodsmentioning

confidence: 99%

The impact of eco-innovation on the stock returns of technology-based KIBS: role of eco-innovation type and its degree of novelty

Szutowski

2020

SAMPJ

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Purpose The purpose of this paper is to determine the role of eco-innovation type and its degree of novelty in increasing the stock returns of technology-based knowledge-intensive business service companies (T-KIBS), to advance the development of the concept of eco-innovation within the literature on the effects of innovation. Design/methodology/approach The effects of four eco-innovation types were examined across three degrees of novelty involved. The event study methodology was applied to the sample of 238 eco-innovation announcements released during the period of January 2016–June 2019 (inclusive) by European T-KIBS. Findings While the implementation of product and organisational eco-innovation was the most beneficial, the results indicated that a high degree of novelty resulted in larger increase of stock returns in the case of all the four eco-innovation types. Research limitations/implications The eco-innovation announcements were gathered from specialised databases. However, it could be the case that companies may have used different communication channels (e.g. social media) to communicate innovation. Furthermore, a certain amount of bias undoubtedly exists, as the data came only from the European Union. Expanding the spatial scope to include the North American (especially the USA) and Asian economies appears necessary. Practical implications The practical insights into the role that the degree of novelty plays in eco-innovation announcements were formulated, which may be used to increase the market valuation of the firm. Social implications Strategies supporting eco-innovation are crucial for business development as the value created for the stakeholders involved transmits in time into the enterprise value. Originality/value The paper attempts to fill the research gap concerning the impact of eco-innovation on the stock returns of T-KIBS.

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“…Later on, Drew and Veeraraghavan (2003) affirm the findings of Halliwell and Sawicki (1999) and find a significant impact of size and value premiums on stocks return. Zaremba (2017) has reported that four factor model of Carhat (2007) perform poorly in explaining in stock returns on the Polish market. Fraz and Hassan (2016) Hameed, Qarni, and Shafi (2018) investigate the applicability of Fama and French's three-factor model for four Asian(Karachi, Bombay, Dhaka, Colombo) stock markets.…”

Section: Literature Reviewmentioning

confidence: 99%

Financial Distress premium in Pakistan’s Banking Stocks

Khan

Fraz

Ali³

2020

NRJSS

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This paper examines the role of financial distress premium in explaining the stock returns of banking sector in Pakistan using the sample of twenty listed banks for the period of 2008 to 2018. The study has used two methodologies. Firstly, multifactor model approach of Fama and French (1992) is used to test the financial distress premium (additional risk factor) where portfolio returns are regressed with factor premiums in time series framework. Fama and French (1993) argue that the relationship between the stock return and the selected characteristics occur for that reason these characteristics are proxies for non-diversifiable factor risk. So, the characteristic based model approach of Huang (2009) is used in cross-sectional regression framework where stock returns are regressed with the characteristics. The results indicate that the proposed four factor model is applicable in the banking sector of Pakistan where financial distress premium is priced by the market. The characteristic based model shows insignificant impact of distress proxy of Altman Z score on the banking returns. It suggests that the cross-sectional returns are explained on the covariance structure of returns not the characteristics in the Pakistani banking stocks. The findings of the study suggests that the financial distress is important and consider while forming their portfolios.

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Size, Value, and Momentum in Polish Equity Returns: Local or International Factors?

Cited by 8 publications

References 61 publications

Downside Risk-Based Six-Factor Capital Asset Pricing Model (CAPM): A New Paradigm in Asset Pricing

Downside Risk-Based Six-Factor Capital Asset Pricing Model (CAPM): A New Paradigm in Asset Pricing

The impact of eco-innovation on the stock returns of technology-based KIBS: role of eco-innovation type and its degree of novelty

Financial Distress premium in Pakistan’s Banking Stocks

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