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

Abstract

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.

A comparative study of the CAPM and extended models in the Indian stock market

“…Using data from the Pakistan Stock Exchange (PSX-100), they argued that the momentum factor was only rejected in the beta-based 6-factor model, suggesting that the downside beta 6-factor model was a more suitable option for investors in the context of asset pricing models. Hoque & Low (2020) suggested that investors were penalized for their downside exposure to these risk factors, aligning with the risk preference explanation of prospect theory. Downside risk measures are widely utilized in portfolio optimization problems to construct investment portfolios with minimized downside risk.…”

Numerical Simulation of Natural Gas Hydrate Exploitation in Complex Structure Wells: Productivity Improvement Analysis

“…When the pressure drop is the same, the more hydrates that are decomposed when the NGH is produced under a pressure drop in complex structure wells, the better the gas production and the longer the gas production time. In particular, CHW can significantly improve production efficiency, and if a more substantial step-down can be achieved, it is very likely to break the threshold [27,28].…”

Asymmetric and Lag Effects of Industry Risk Factors on the Malaysian Oil and Gas Stocks

“…OIL represents oil return, LNG represents gas returns, and FOREX represents exchange rate return. This table was published in our previous paper (Hoque & Low, 2020). * Statistical significance at 10% level. ** Statistical significance at 5% level. *** Statistical significance at 1% level. …”

“…OIL represents oil return, LNG represents gas returns, and FOREX represents exchange rate return. This table was published in our previous paper(Hoque & Low, 2020).…”