Advances in Economics, Management and Political Sciences
- The Open Access Proceedings Series for Conferences
Series Vol. 53 , 01 December 2023
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Utilizing Monte Carlo Simulation and annualized data, this paper investigates portfolio establishment with currency, comparing the performance of the portfolio with the performance of equity. Specially, we choose S&P 500 to represent equity, while choosing Gold futures, Bitcoin, and CHF to represent different types of currency. Firstly we use Python to help us do the initial simulation of one million portfolios, analyzing the result of the simulation based on sharp ratio with Excel. We find that there are some regular patterns in the asset allocation of the portfolio and explain the appearance of the strange angle in our simulation. Then to increase the market shares of currency, we advocate adding an extra yield to the currency's annualized return and doing another two simulations on the four assets with a new annual rate of return. We then compare the results of new simulations with the performance of the initial simulation and S&P 500, finding that with extra yield it will be more easier for the portfolio including currency and equity to perform better than initial portfolios. We also find that the regular pattern of asset allocation which is discovered from the initial simulation is inapplicable in new simulations.
currency, portfolio analysis, extra yield, portfolio construction
1. Guangxi C, Wenhao X. Cryptocurrency Investment Portfolio from a Fractal Perspective: Comparison of Bull and Bear Market Effects[J].Management Review,2023,35(03):39-48.DOI:10.14120/j.cnki.cn11-5057/f.2023.03.007.
2. Jiaming J. Research on Digital Currency Investment Portfolio Strategy Based on Machine Learning [D]. Dongbei University of Finance and Economics,2021.DOI:10.27006/d.cnki.gdbcu.2021.000697.
3. Platanakis E,Urquhart A. Should investors include Bitcoin in their portfolios? A portfolio theory approach[J]. The British Accounting Review,2020,52(4).
4. Liu W. Portfolio diversification across cryptocurrencies[J]. Finance Research Letters,2019,29(C).
5. Guesmi K,Saadi S,Abid I, et al. Portfolio diversification with virtual currency: Evidence from bitcoin[J]. International Review of Financial Analysis,2019,63(C).
6. Yong T, Pengfei Z. Investment Portfolio Strategy for Shanghai and Hong Kong Stock Markets from a Fractal Perspective [J]. System Engineering Theory and Practice,2018,38(09):2188-2201.
7. Klein T,Thu P H,Walther T. Bitcoin is not the New Gold – A comparison of volatility, correlation, and portfolio performance[J]. International Review of Financial Analysis,2018,59.
8. Yu L, Min X, Ruixing M. Minimum variance investment portfolio based on high-frequency high-dimensional covariance matrix contraction estimation [J]. Business Economics and Management,2023(03):94-108.DOI:10.14134/j.cnki.cn33-1336/f.2023.03.007.
9. Ledoit O,Wolf M. Honey, I Shrunk the Sample Covariance Matrix[J]. Journal of portfolio management,2004,30(4).
10. Jagannathan R,Ma T. Risk Reduction in Large Portfolios: Why Imposing the Wrong Constraints Helps[J]. The Journal of Finance,2003,58(4).
11. Ledoit O,Wolf M. Improved estimation of the covariance matrix of stock returns with an application to portfolio selection[J]. Journal of Empirical Finance,2003,10(5).
The datasets used and/or analyzed during the current study will be available from the authors upon reasonable request.
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