Asset pricing and downside risk in the Australian share market

Alles, Lakshman; Murray, Louis

doi:10.1080/00036846.2017.1282143

Cited by 17 publications

(20 citation statements)

References 35 publications

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“…The study period runs from 2 January 2020 to 30 April 2020, or 83 trading days for each company. 2 Following Alles and Murray (2017) , firms with no trading data on more than 50% of trading days in the given period have been removed. Hence, the final sample consists of 134 companies.…”

Section: Datamentioning

confidence: 99%

The impact of policy responses to COVID-19 on U.S. travel and leisure companies

Chen

Demir

García-Gómez

et al. 2020

Annals of Tourism Research Empirical Insights

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This paper analyzes the impact of government restrictions arising from the COVID-19 pandemic on stock returns of U.S. travel and leisure companies. We demonstrate that the stringency of government restrictions has a negative impact on stock returns even after controlling for the pandemic itself. Moreover, stock prices of travel and leisure firms with a smaller size, less tangibility, and higher cash reserves are more resilient to the COVID-19 related government restrictions. Restrictions have the highest impact on airlines, followed by travel and tourism and casinos and gambling sectors. Our empirical findings provide valuable policy implications for travel and leisure firm managers, financial investors, and policymakers.

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Section: Datamentioning

confidence: 99%

The impact of policy responses to COVID-19 on U.S. travel and leisure companies

Chen

Demir

García-Gómez

et al. 2020

Annals of Tourism Research Empirical Insights

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“…Similarly, for calculating the cost of equity, Foong and Goh (2012) compared various CAPM measures for an emerging market and concluded that downside beta is the most relevant measure. Recently, many researches have tested DCAPM in asset pricing like Alles and Murray (2017) tested downside, upside beta and co-skewness in the Australian equities market and found that they are priced in Australian stock market, however, downside and upside beta are not related to each other. In Pakistan, Raza (2018) and Rashid and Mehmood (2018) conducted researches on Pakistan stock market and financial institutions and provide evidence of a positive and statistically significant risk-return relationship.…”

Section: Downside Beta Capm (Dcapm)mentioning

confidence: 99%

Higher Co-Moments and Downside Beta in Asset Pricing

Chhapra¹,

Kashif²

2019

AAMJAF

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The Capital Asset Pricing Model (CAPM) assumes a linear relationship between an asset's return and financial market. However, empirical invalidity of linearity of returns has given birth to other CAPM models. Therefore, this study aims to examine the implication of preference by a risk-averse investor for higher moments and downside risk as investors are assumed to be prudent, temperate and cautious and prefer firms with negative coskewness, positive co-kurtosis, and downside risk as they yield higher risk premium. To empirically test these theoretical assumptions data of all 901 firms (listed and delisted) in Pakistan Stock Exchange (PSX) from 2000 to 2016 have been used. Decile portfolios are constructed for cross-sectional and time series analysis. Generalized Method of Moments (GMM) and Wald Test are applied to check the robustness of results. The results indicate that co-skewness, co-kurtosis and downside beta are important risk factors but only downside beta is genuinely priced over and above what co-variance risk can explain and CAPM does not significantly capture market risk premium indicating the existence of other risk measures in PSX. The findings can help investors in formulating investment strategies for constructing well-diversified and efficient portfolios and can enable firm managers to take appropriate capital budgeting decisions by appropriately costing equities.

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“…These circumstances have led financial economists and academic practitioners to develop new pricing theory/framework for asset pricing and managing risk, in the form of downside risk measures. These theories include the lower-partial moment framework of Bawa and Lindenberg [17], the loss aversion of Kahneman and Tversky [29] in their prospect theory, the disappointment aversion of Gul [17], and the mean semi-variance framework of Estrada [15,20,40].…”

Section: Mean Semi-variance Frameworkmentioning

confidence: 99%

“…Most past oil-related studies employ standard multifactor asset pricing models, which implicitly assume that the underlying distribution of returns is normal or symmetrical (e.g., [11,14,18,19], among others). While numerous prior studies recognize that stock returns are non-normally distributed especially within the context of emerging markets, at best, these studies only include additional risk measures to proxy for downside risk such as skewness and kurtosis in the analysis modelled using standard asset pricing model [2,20]. In those studies, the asset pricing framework and factor are still based on co-movements, and the inclusion of co-skewness and co-kurtosis are just non-linear effects of risk factors.…”

Section: Introductionmentioning

confidence: 99%

“…Our findings for oil and gas companies draw attention to the importance of the downside in oil-related risk factors, as we evidence that downside risk exposures to risk factors are negatively priced in the Malaysian oil and gas stocks, apart from the gas (LNG) risk factor. The negative risk-return relationship was observed in numerous past studies that employ downside risk measures in the standard asset pricing models [20,22,23,28]. The findings of negative risk-return relationships in those studies have so far been regarded as "anomalies", as it is assumed that investors are risk-averse, and thus demand compensation for bearing risk, which implicitly indicates a positive risk-return relationship.…”

Section: Introductionmentioning

confidence: 99%

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Industry Risk Factors and Stock Returns of Malaysian Oil and Gas Industry: A New Look with Mean Semi-Variance Asset Pricing Framework

Hoque

Low

2020

Mathematics

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This study employs a mean semi-variance asset pricing framework to examine the influence of risk factors on stock returns of oil and gas companies. This study also examines how downside risk is priced in stock performance. The time-series estimations expose that market, size, momentum, oil, gas, and exchange rate have significant impacts on oil and gas stock returns, but effects are heterogeneous depending on an individual stock. The two-stage cross-section estimations provide new insights about investors’ risk-return trade-off when facing downside risks. The results show that downside risk exposures to market, momentum, oil, and exchange rate factors are negatively priced in the Malaysian oil and gas stocks. This implies that investors are penalized for their downside exposure to these risk factors, and such inference is consistent with the risk preference explanation of prospect theory. Liquefied natural gas (LNG) is the only risk factor found to be positively priced in the returns of oil and gas stocks. Additionally, we find a negative relationship between LNG factor and total risk. This suggests that as the risk exposure to LNG increases, the total risk decreases, implying that the LNG risk factor is an idiosyncratic risk and not a systematic risk factor. Such interpretation is consistent with the correlation result, which shows no association between LNG and the market risk factor.

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Asset pricing and downside risk in the Australian share market

Cited by 17 publications

References 35 publications

The impact of policy responses to COVID-19 on U.S. travel and leisure companies

The impact of policy responses to COVID-19 on U.S. travel and leisure companies

Higher Co-Moments and Downside Beta in Asset Pricing

Industry Risk Factors and Stock Returns of Malaysian Oil and Gas Industry: A New Look with Mean Semi-Variance Asset Pricing Framework

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