Diversifying portfolios of U.S. stocks with crude oil and natural gas: A regime-dependent optimization with several risk measures

Gatfaoui, Hayette

doi:10.1016/j.eneco.2018.12.013

Cited by 34 publications

(6 citation statements)

References 84 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…She highlighted that the three markets have time-dependent structural changes while studying the data on returns for the three markets from January 1997 to January 2013 and concludes that it is difficult to forecast future prices and dependency due to the unstable dependency. She further extended the study (Gatfaoui, 2019 ) by implementing portfolio optimization for different variance regimes by minimizing risk metrics. She argued that such a regime dependency analysis was required for an active portfolio management strategy given the dependence structure of the three markets (US Stocks, Oil, and Gas).…”

Section: Literature Reviewmentioning

confidence: 99%

“…Ex-post portfolios provide better results than naively weighted portfolios and suggest further exploration Bessler and Wolff ( 2015 ) S&P 500, Barclays US aggregate govt bond index, S&P GSCI index, S&P GSCI light energy index, self-constructed-equally weighted commodity index excluding agriculture and livestock January 1986–December 2013 Out of sample benefits of commodities are much lower than previously stated. Most asset allocation strategies preferred aggregate commodity index and industrial metals for performance enhancement followed by energy Kang et al ( 2017 ) Gold, Silver, WTI Crude oil, corn, wheat, and rice January 4, 2002, to July 28, 2016 Positive equicorrelation level jumps during financial and economic turmoil, return and volatility spillover indexes have a bidirectional behavior across commodity markets, and gold and silver are net information transmitter to the other four commodity futures Gatfaoui ( 2019 ) US Natural gas, crude oil, S&P 500, S&P1500, S&P Midcap 400, S&P SmallCap 600 January 8, 1997–October 30, 2017 Regime specific dependence structure for portfolio optimization is being studied. The authors concluded that diversification through power commodities is a function of risk measures used and dependence structure between the three (gas, oil, and S&P indices) Rehman et al ( 2019 ) Crude oil, gas, coal, gold, silver, copper, platinum, palladium, and wheat (weekly) January 2010−December 2018 Short- and long-term asymmetric relationship between energy and non-energy futures is investigated.…”

Section: Literature Reviewmentioning

confidence: 99%

See 1 more Smart Citation

Portfolio optimization of financial commodities with energy futures

et al. 2021

View full text Add to dashboard Cite

The recent growth in economic and financial markets has brought the focus on energy derivatives as an alternative investment class for investors, financial analysts, and portfolio managers. The financial modeling and risk management of portfolios using the energy derivatives instrument is a requirement and challenge for researchers in the field. The energy and other commodity futures force the expert investors to investigate the broader investment spectrum and consequently diversify their portfolios using the futures instruments. Going beyond the conventional portfolios and developing out-of-the-box strategies that comply with the changing financial and economic advancements are the keys to long-term sustainability in the financial world. This study investigates the impact of diversification with five energy futures from January 2011 to July 2020 on three traditional commodity futures portfolios. The results show that diversification increased the returns while simultaneously reducing the portfolio volatility in all portfolios. The diversified portfolios provided higher returns than the traditional portfolios for the same level of risk. This study also revealed that the results might improve when a short position in the futures contracts is allowed. Moreover, we conclude that adding multiple energy futures in a portfolio provides enhanced diversification results, whereas the WTI crude oil futures fail to diversify any portfolio considered in the study.

show abstract

Section: Literature Reviewmentioning

confidence: 99%

Section: Literature Reviewmentioning

confidence: 99%

Portfolio optimization of financial commodities with energy futures

et al. 2021

View full text Add to dashboard Cite

show abstract

“…Andriosopoulos, Doumpos, Papapostolou, and Pouliasis studied portfolio optimization about the shipping stocks and the freight markets [2]. Gatfaou studied portfolio optimization by trying to diversify the portfolio with crude oil and natural gas [3]. Wood also studied portfolio optimization about trying to predict the value and risk of oil and gas stocks [4].…”

Section: Introductionmentioning

confidence: 99%

Portfolio Optimization for Six Companies in Different Industries

Han¹,

Li²

2023

BCPBM

View full text Add to dashboard Cite

Portfolio optimization is an essential step in the process of asset management. Studying portfolio can help people gain greater benefits after investing their assets. This paper makes a subjective analysis of the stocks in the American stock market, and finally selects six stocks from different fields, including health care, finance, public utilities, Internet software and services, non-energy minerals, and industry for portfolio analysis. This paper uses mean-variance analysis, CAPM model and Fama-French model to get the best portfolios, and analyses portfolio performance under different methods. The results show that, in the CAPM model, "GS" gets the largest weight in the maximum Sharpe ratio portfolio and "AWK" gains the largest weights in the minimum variance portfolio. At the same time, in the Fama-French model, "GS" and "AWK" still get the largest weight in the maximum Sharpe ratio portfolio and minimum variance portfolio, respectively. This paper will be helpful to investors who pay attention to the six areas involved in this paper.

show abstract

“…The results are then applied to a portfolio optimization problem. Copula models have recently been applied in portfolio optimization (see, for example, Gatfaoui (2019); Bekiros et al (2015); Sahamkhadam et al (2018); Low et al (2013); de Melo Mendes and Marques ( 2012)).…”

Section: Introductionmentioning

confidence: 99%

Assessing Market Risk in BRICS and Oil Markets: An Application of Markov Switching and Vine Copula

Mwamba¹,

Mwambi²

2021

IJFS

View full text Add to dashboard Cite

This paper investigates the dynamic tail dependence risk between BRICS economies and the world energy market, in the context of the COVID-19 financial crisis of 2020, in order to determine optimal investment decisions based on risk metrics. For this purpose, we employ a combination of novel statistical techniques, including Vector Autoregressive (VAR), Markov-switching GJR-GARCH, and vine copula methods. Using a data set consisting of daily stock and world crude oil prices, we find evidence of a structure break in the volatility process, consisting of high and low persistence volatility processes, with a high persistence in the probabilities of transition between lower and higher volatility regimes, as well as the presence of leverage effects. Furthermore, our results based on the C-vine copula confirm the existence of two types of tail dependence: symmetric tail dependence between South Africa and China, South Africa and Russia, and South Africa and India, and asymmetric lower tail dependence between South Africa and Brazil, and South Africa and crude oil. For the purpose of diversification in these markets, we formulate an asset allocation problem using raw returns, MS GARCH returns, and C-vine and R-vine copula-based returns, and optimize it using a Particle Swarm optimization algorithm with a rebalancing strategy. The results demonstrate an inverse relationship between the risk contribution and asset allocation of South Africa and the crude oil market, supporting the existence of a lower tail dependence between them. This suggests that, when South African stocks are in distress, investors tend to shift their holdings in the oil market. Similar results are found between Russia and crude oil, as well as Brazil and crude oil. In the symmetric tail, South African asset allocation is found to have a well-diversified relationship with that of China, Russia, and India, suggesting that these three markets might be good investment destinations when things are not good in South Africa, and vice versa.

show abstract

Diversifying portfolios of U.S. stocks with crude oil and natural gas: A regime-dependent optimization with several risk measures

Cited by 34 publications

References 84 publications

Portfolio optimization of financial commodities with energy futures

Portfolio optimization of financial commodities with energy futures

Portfolio Optimization for Six Companies in Different Industries

Assessing Market Risk in BRICS and Oil Markets: An Application of Markov Switching and Vine Copula

Contact Info

Product

Resources

About