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Financial Markets and Portfolio Management

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27-11-2017

International asset allocation using the market implied cost of capital

Author: Patrick Bielstein

Published in: Financial Markets and Portfolio Management | Issue 1/2018

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Abstract

The Black and Litterman (Financ Anal J 48(5):28–43, 1992) (BL) approach to portfolio optimization requires investor views on expected asset returns as an input. I demonstrate that the market implied cost of capital (ICC) is ideal for quantifying those views on a country level. I benchmark this approach against a BL optimization using time-series models as investor views, the equally weighted portfolio, and allocation methods based on stock market capitalization and GDP. I find that the ICC portfolio offers an increase in average return of 2.1 percentage points (yearly) as compared to the value-weighted portfolio, while having a similar standard deviation. The resulting difference in Sharpe ratios is statistically significant and robust to the inclusion of transaction costs, varying BL parameters, and a less strictly defined investment universe.

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The study by Becker and Gürtler (2010) is closely related to this paper as they show that the BL portfolio with views derived from ICC estimates performs well in the German stock market. However, they do not implement a short-sale constraint in their main analysis, and they completely ignore transaction costs, thus limiting the practical applicability of their results.

Claus and Thomas (2001) include the same six countries in their analysis.

I thank two anonymous referees for suggesting these tests.

I need IBES reported earnings to compute the forecast error, which is an input in the earnings forecast adjustment (Guay et al. 2011). For that purpose, I cannot use earnings from Compustat or Worldscope as the calculation method differs in several aspects (Livnat and Mendenhall 2006).

If the return (r) in t or \(t-1\) is larger than 300% and \((1 + r_t) (1 + r_{t-1}) - 1\) is less than 50% then \(r_t\) and \(r_{t-1}\) are set to missing.

I aggregate winsorized firm-level payout ratios (instead of computing the payout ratio with aggregated dividends and earnings) as these figures are more robust to data errors because of the firm-level winsorization.

This assumption is somewhat arbitrary; however, Claus and Thomas (2001) find that their model is robust to other values of the long-term growth rate.

In the robustness section, I run the optimization for different values of c to confirm that the results are not driven by the choice of \(c=5\).

https://doi.org/mba.tuck.dartmouth.edu/pages/faculty/ken.french/data_library.html, visited on September 22, 2016.

I thank Michael Wolf for making the R code freely available on his website.

Eling (2008) studies numerous performance metrics applied to mutual fund returns and arrives at a similar conclusion.

NBER make their business cycle data available on their Web site: https://doi.org/www.nber.org/cycles/cyclesmain.html. Contractions are defined as the months between the peak of the business cycle and the trough. Expansions are the months between the trough of the business cycle and the peak.

The EGARCH strategy now has a Sharpe ratio of 0.098 versus 0.107 for the BL optimization, ICC_ADJ now has a Sharpe ratio of 0.136 versus 0.150 for the BL optimization, ICC_RAW now has a Sharpe ratio of 0.142 versus 0.154 for the BL optimization, and MA now has a Sharpe ratio of 0.102 versus 0.122 for the BL optimization.

EW: 0.107 vs. 0.112 before; GDP: 0.106 vs. 0.112 before; VW: 0.102 vs. 0.113 before; MA: 0.113 vs. 0.122 before.

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Title: International asset allocation using the market implied cost of capital
Author: Patrick Bielstein
Publication date: 27-11-2017
Publisher: Springer US
Published in: Financial Markets and Portfolio Management / Issue 1/2018
Print ISSN: 1934-4554
Electronic ISSN: 2373-8529
DOI: https://doi.org/10.1007/s11408-017-0302-3

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