Abstract
This paper investigates if energy block chain based crypto currencies can help diversify equity portfolios consisting primarily of leading energy companies of the US S&P Composite 1500 energy index. Key contributions are in terms of assessing the importance of energy cryptos as alternative investments in portfolio management, and whether different volatility models such as autoregressive moving average – Generalized Autoregressive Heteroskedasticity (ARMA-GARCH) and machine learning (ML) can help investors make better investment decisions. The methodology utilizes the traditional Markowitz mean-variance framework to obtain optimized portfolio combinations. Volatility measures, derived from the Cornish-Fisher adjusted variance, ARMA family classes and ML models are used to compare efficient portfolios. The study also analyses the effect of adding cryptos to equity portfolios with non-positive excess returns. Different models are assessed using the Sharpe performance measure. Daily data is used, spanning from November 21, 2017 to January 31, 2019. Findings suggest that energy based cryptos do not have a significant impact on energy equity portfolios, despite the use of different risk measures. This is attributable to the relatively poor performance of energy cryptos which did not contribute in improving the excess return per unit of risk of efficient portfolios based on the leading US energy stocks.
Highlights
Cryptocurrency portfolio management is already a reality with names like Blockfolio and Delta, allowing investors or traders to manage their portfolios of cryptocurrencies and altcoins using different tools like advanced charting, order books, and portfolio tracking
A second, yet important question, which arises is how, using different measures of risk from different models such as Cornish-Fisher (CF) expansion, autoregressive moving average – generalized autoregressive heteroskedasticity (ARMA-generalized autoregressive conditional heteroskedasticity (GARCH)) and machine learning (ML), can help the investor or trader to make better informed decisions in how to allocate funds among the risky assets coming from different asset classes, and how well the portfolio performed using the Sharpe performance measure
This study fills the gap by being the first to evaluate whether energy based block chain cryptos can affect energy equity portfolios which consists of the leading US energy stocks
Summary
Cryptocurrency portfolio management is already a reality with names like Blockfolio and Delta, allowing investors or traders to manage their portfolios of cryptocurrencies and altcoins using different tools like advanced charting, order books, and portfolio tracking. As reported by IBM (2017), the prevalent benefits of adopting block chain technologies are associated with risk, time and cost savings. Various startups in the US energy sector have raised nearly $325 million in 2017 to implement block chain to energy related projects (Lacey, 2017). These projects range from facilitating peer to peer dealings without the necessity of a retailed based energy provider or central utility, to tracking low carbon impact energy production. While block chain aims to introduce decentralized energy trading in various energy sectors like the electric power
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