Why Should We Invest in CoCos Than Stocks? An Optimal Growth Portfolio Approach

The European Journal of Finance

27 Pages Posted: 5 Feb 2019 Last revised: 6 May 2020

See all articles by Hyun Jin Jang

Hyun Jin Jang

Ulsan National Institute of Science and Technology (UNIST)

Longjie Jia

affiliation not provided to SSRN

Harry Zheng

Imperial College London - Mathematical Finance

Date Written: January 22, 2019

Abstract

We investigate an optimal growth portfolio problem with contingent convertible bonds (CoCos). As the conversion risk in CoCos is closely associated with the issuer's capital structure and the stock price at conversion, we model both equity and credit risk to frame this optimisation problem. This study aims to answer two questions that (i) how investors should optimally allocate their financial wealth between a CoCo and a risk-free bond; and (ii) which approach -- investing in a CoCo or in a stock issued by the same bank -- could result in higher expected returns. First, we derive the dynamic of a coupon-paying CoCo price under a reduced-form approach. We then decompose the problem into pre- and post-conversion regimes to obtain closed-form optimal strategies. A comparative simulation leads us to conclude that, under various market conditions, investing in a CoCo with a risk-free bond provides a higher expected growth than investing in stock.

Keywords: Growth Portfolio Optimisation; Contingent Convertible Bond; Statistical Comparisons; Sensitivity Analysis

JEL Classification: G11; G13

Suggested Citation

Jang, Hyun Jin and Jia, Longjie and Zheng, Harry, Why Should We Invest in CoCos Than Stocks? An Optimal Growth Portfolio Approach (January 22, 2019). The European Journal of Finance, Available at SSRN: https://ssrn.com/abstract=3320264 or http://dx.doi.org/10.2139/ssrn.3320264

Hyun Jin Jang (Contact Author)

Ulsan National Institute of Science and Technology (UNIST) ( email )

gil 50
Ulsan, 689-798
Korea, Republic of (South Korea)

Longjie Jia

affiliation not provided to SSRN

Harry Zheng

Imperial College London - Mathematical Finance ( email )

United Kingdom

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