Developing a Measure of Sequence Risk

27 Pages Posted: 27 Jan 2020

See all articles by Andrew Clare

Andrew Clare

City, University of London - Bayes Business School

Simon Glover

affiliation not provided to SSRN

James Seaton

City University London - The Business School

Peter N. Smith

University of York - Department of Economics and Related Studies; Australian National University (ANU) - Centre for Applied Macroeconomic Analysis (CAMA)

Steve Thomas

City University London - The Business School

Date Written: December 27, 2019

Abstract

We discuss the nature and importance of the concept of Sequence Risk, the risk that a bad return occurs at a particularly unfortunate time, such as around the point of maximum accumulation or the start of decumulation. This is especially relevant in the context of retirement savings, where the implications for withdrawal rates of a bad return can be particularly severe. We show how the popular ‘glidepath’ or target date savings’ products are very exposed to such risk. Three different measures of Sequence Risk are proposed, each of which is intended to inform investors of the probability that a chosen investment strategy may not deliver desired withdrawal rates and hence these measures are intended to aid investment choices; conventional performance measures such as Sharpe or Sortino ratios are only indirectly related to this ability to achieve a given withdrawal experience. Finally, we note that, using US data, very simple portfolios comprising equities and bonds can achieve very low probabilities of failure to achieve popular desired withdrawal rates such as 5% p.a. providing the equity component is ‘smoothed’ by switching in and out of cash using a simple trend following rule.

Keywords: Glidepath Investing, Sequence Risk, Perfect Withdrawal Rates, Trend Following

JEL Classification: G10, G11

Suggested Citation

Clare, Andrew D. and Glover, Simon and Seaton, James and Smith, Peter N. and Thomas, Stephen H., Developing a Measure of Sequence Risk (December 27, 2019). Available at SSRN: https://ssrn.com/abstract=3513546 or http://dx.doi.org/10.2139/ssrn.3513546

Andrew D. Clare (Contact Author)

City, University of London - Bayes Business School ( email )

106, Bunhill Row
London, EC1Y 8TZ
United Kingdom

Simon Glover

affiliation not provided to SSRN

James Seaton

City University London - The Business School ( email )

106 Bunhill Row
London, EC1Y 8TZ
United Kingdom

Peter N. Smith

University of York - Department of Economics and Related Studies ( email )

Heslington
York 010 5DD
United Kingdom
+44 1904 433 765 (Phone)
+44 1904 433 759 (Fax)

Australian National University (ANU) - Centre for Applied Macroeconomic Analysis (CAMA) ( email )

ANU College of Business and Economics
Canberra, Australian Capital Territory 0200
Australia

Stephen H. Thomas

City University London - The Business School ( email )

106 Bunhill Row
London, EC1Y 8TZ
United Kingdom
+44 (0) 20 7040 5271 (Phone)
+44 (0) 20 7040 8881 (Fax)

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