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Balancing cryptoassets and gold: a weighted-risk-contribution index for the alternative asset space
File | Description | Size | Format | |
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MARBLE_2019_CRC.pdf | Accepted version | 626.6 kB | Adobe PDF | View/Open |
Title: | Balancing cryptoassets and gold: a weighted-risk-contribution index for the alternative asset space |
Authors: | Koutsouri, A Poli, F Alfieri, E Petch, M Distaso, W Knottenbelt, W |
Item Type: | Conference Paper |
Abstract: | Bitcoin is foremost amongst the emerging asset class knownas cryptoassets. Two noteworthy characteristics of the returns of non-stablecoin cryptoassets are their high volatility, which brings with it ahigh level of risk, and their high intraclass correlation, which limits thebenefits that can be had by diversifying across multiple cryptoassets. Yetcryptoassets exhibit no correlation with gold, a highly-liquid yet scarceasset which has proved to function as a safe haven during crises affectingtraditional financial systems. As exemplified by Shannon’s Demon, a lackof correlation between assets opens the door to principled risk controlthrough so-called volatility harvesting involving periodic rebalancing.In this paper we propose an index which combines a basket of five cryp-toassets with an investment in gold in a way that aims to improve therisk profile of the resulting portfolio while preserving its independencefrom mainstream financial asset classes such as stocks, bonds and fiatcurrencies. We generalise the theory of Equal Risk Contribution to allowfor weighting according to a desired level of contribution to volatility. Wefind a crypto–gold weighting based on Weighted Risk Contribution to behistorically more effective in terms of Sharpe Ratio than several alterna-tive asset allocation strategies including Shannon’s Demon. Within thecrypto-basket, whose constituents are selected and rebalanced monthly,we find an Equal Weighting scheme to be more effective in terms of thesame metric than a market capitalisation weighting. |
Issue Date: | 14-Feb-2020 |
Date of Acceptance: | 22-Mar-2019 |
URI: | http://hdl.handle.net/10044/1/69962 |
DOI: | 10.1007/978-3-030-37110-4_15 |
ISBN: | 9783030371098 |
ISSN: | 0302-9743 |
Publisher: | Springer Verlag |
Start Page: | 217 |
End Page: | 232 |
Journal / Book Title: | Lecture Notes in Computer Science |
Copyright Statement: | © Springer Nature Switzerland AG 2020. The final publication is available at Springer via https://doi.org/10.1007/978-3-030-37110-4_15. |
Sponsor/Funder: | CoinShares (Jersey) Limited |
Funder's Grant Number: | PO 4550183036 |
Conference Name: | 1st International Conference on Mathematical Research for Blockchain Economy |
Keywords: | Artificial Intelligence & Image Processing |
Publication Status: | Published |
Start Date: | 2019-05-06 |
Finish Date: | 2019-05-09 |
Conference Place: | Santorini, Greece |
Online Publication Date: | 2020-02-14 |
Appears in Collections: | Imperial College Business School Computing Grantham Institute for Climate Change Faculty of Natural Sciences Faculty of Engineering |