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Article
Publication date: 7 June 2018

Jörg Döpke and Lars Tegtmeier

The purpose of this paper is, to study macroeconomic risk factors driving the expected stock returns of listed private equity (LPE). The authors use LPE indices divided…

Abstract

Purpose

The purpose of this paper is, to study macroeconomic risk factors driving the expected stock returns of listed private equity (LPE). The authors use LPE indices divided into different styles and regions from January 2004 to December 2016 and a set of country stock indices to estimate the macroeconomic risk profiles and corresponding risk premiums. Using a seemingly unrelated regressions (SUR) model to estimate factor sensitivities, the authors document that LPE indices exhibit stock market βs that are greater than 1. A one-factor asset pricing model using world stock market returns as the only possible risk factor is rejected on the basis of generalized method of moments (GMM) orthogonality conditions. In contrast, using the change in a currency basket, the G-7 industrial production, the G-7 term spread, the G-7 inflation rate and a recently proposed indicator of economic policy uncertainty as additional risk factors, this multifactor model is able to price a cross-section of expected LPE returns. The risk-return profile of LPE differs from country equity indices. Consequently, LPE should be treated as a separate asset class.

Design/methodology/approach

Following Ferson and Harvey (1994), the authors use an unconditional asset pricing model to capture the structure of returns across LPE. The authors use 11 LPE indices divided into different styles and regions from January 2004 to December 2016, and a set of country stock indices as spanning assets to estimate the macroeconomic risk profiles and corresponding risk premiums.

Findings

Using a seemingly unrelated regressions (SUR) model to estimate factor sensitivities, the authors document that LPE indices exhibit stock market ßs that are greater than 1. The authors estimate a one-factor asset pricing model using world stock market returns as the only possible risk factor by GMM. This model is rejected on the basis of the GMM orthogonality conditions. By contrast, a multifactor model built on the change in a currency basket, the G-7 industrial production, the G-7 term spread, the G-7 inflation rate and a recently proposed indicator of global economic policy uncertainty as additional risk factors is able to price a cross-section of expected LPE returns.

Research limitations/implications

Given data availability, the authors’ sample is strongly influenced by the financial crisis and its aftermath.

Practical implications

Information about the risk profile of LPE is important for asset allocation decisions. In particular, it may help to optimally react to contemporaneous changes in economy-wide risk factors.

Originality/value

To the best of authors’ knowledge, this is the first LPE study which investigates whether a set of macroeconomic factors is actually priced and, therefore, associated with a non-zero risk premium in the cross-section of returns.

Details

Studies in Economics and Finance, vol. 35 no. 2
Type: Research Article
ISSN: 1086-7376

Keywords

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Article
Publication date: 1 August 2008

Claudia Buch and Joerg Doepke

Purpose – The purpose of this paper is two‐fold. First, it studies whether output volatility and growth are linked at the firm‐level, using data for German firms. Second…

Abstract

Purpose – The purpose of this paper is two‐fold. First, it studies whether output volatility and growth are linked at the firm‐level, using data for German firms. Second, it explores whether the link between volatility and growth depends on the degree of credit market imperfections. Design/methodology/approach – The authors use a novel firm‐level dataset provided by the Deutsche Bundesbank, the so‐called Financial Statements Data Pool. The dataset has time series observations for German firms for the period 1997‐2004, and the authors use information on the debt‐to‐assets or leverage ratio of firms to proxy for credit‐constraints at the firm‐level. As additional proxies for the importance of credit market imperfections, we use information on the size and on the legal status of firms. Findings – The authors find that higher volatility has a negative impact on growth for small and a positive impact for larger firms. Higher leverage is associated with higher growth. At the same time, there is heterogeneity in the determinants of growth across firms from different sectors and across firms with a different legal status. Practical implications – While most traditional macroeconomic models assume that growth and volatility are uncorrelated, a number of microeconomic models suggest that the two may be linked. However, it is unclear whether the link is positive or negative. The paper presents additional evidence regarding this question. Moreover, understanding whether credit market conditions affect the link between volatility and growth is of importance for policy makers since it suggests a channel through which the credit market can have long‐run welfare implications. The results stress the importance of firm‐level heterogeneity for the effects and effectiveness of economic policy measures. Originality/value – The paper has two main novel features. First, it uses a novel firm‐level dataset to analyze the determinants of firm‐level growth. Second, it analyzes the growth‐volatility nexus using firm‐level data. To the best of the authors' knowledge, this is the first paper, which addresses the link between volatility, growth, and credit market imperfections using firm‐level data.

Details

Journal of Economic Studies, vol. 35 no. 3
Type: Research Article
ISSN: 0144-3585

Keywords

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