VOLUME 29 | NUMBER 4 | FALL 2017 Journal of APPLIED CORPORATE FINANCE In This Issue: Financial Regulation Has Financial Regulation Been a Flop? (or How to Reform Dodd-Frank) 8 Charles W. Calomiris, Columbia University Statement of the Financial Economists Roundtable 25 Charles W. Calomiris, Columbia University; Larry Harris, Uni- Bank Capital as a Substitute for Prudential Regulation versity of Southern California; Catherine Schrand, University of Pennsylvania; Roman L. Weil, University of Chicago High Frequency Trading and the New Stock Market: 30 Merritt B. Fox, Columbia Law School, Lawrence R. Glosten, Sense and Nonsense Columbia Business School, and Gabriel V. Rauterberg, Michigan Law School Shadow Banking, Risk Transfer, and Financial Stability 45 Christopher L. Culp, Johns Hopkins Institute for Applied Economics, and Andrea M. P. Neves, Seven Consulting Why European Banks Are Undercapitalized and What Should Be Done About It 65 John D. Finnerty, Fordham University, and Laura Gonzalez, California State University, Long Beach Bloomberg Intelligence Roundtable on 72 Participants: Clifford Smith, Gregory Milano, Joel Levington, The Theory and Practice of Capital Structure Management Asthika Goonewardene, Gina Martin Adams, Michael Holland, and Jonathan Palmer. Moderated by Don Chew. Leverage and Taxes: Evidence from the Real Estate Industry 86 Michael J. Barclay, University of Rochester, Shane M. Heitzman, University of Southern California, Clifford W. Smith, University of Rochester Formulaic Transparency: The Hidden Enabler of Exceptional U.S. Securitization 96 Amar Bhidé, Tufts University How Investment Opportunities Affect Optimal Capital Structure 112 Stanley Myint, BNP Paribas and University of Oxford, Antonio Lupi, BNP Paribas, and Dimitrios P. Tsomocos, University of Oxford How to Integrate ESG into Investment Decision-Making: 125 Robert G. Eccles, Arabesque Partners, and Results of a Global Survey of Institutional Investors Mirtha D. Kastrapeli, and Stephanie J. Potter, State Street Maximum Withdrawal Rates: A Novel and Useful Tool 134 Javier Estrada, IESE Business School Maximum Withdrawal Rates: A Novel and Useful Tool by Javier Estrada, IESE Business School* tandard evaluation of retirement strategies proportion of the portfolio that is withdrawn at the beginning involves the consideration of a large number of of retirement. Subsequent withdrawals are typically thought S simulated or historical retirement periods and of as being annually adjusted by inflation, thus enabling a the subsequent estimation of their failure rate; retiree to maintain his purchasing power constant during that is, the proportion of those periods in which the strategies retirement. In his seminal article,2 William Bengen suggested failed to sustain a withdrawal plan, thus depleting a portfolio that a strategy based on a 4% IWR was ‘safe’ in the sense before a retiree’s death. This failure rate, though ubiquitous that, historically, it never depleted a portfolio in less than 30 in retirement planning, has several flaws.1 years. The debate on the pros and cons of the ‘4% rule’ has For the purposes of the discussion here it suffices to been raging on since then. highlight that two strategies may have the same failure rate For the purposes of the discussion here, it is important and yet they may leave behind very different bequests. Put to highlight that some of the arguments in favor of the 4% differently, the failure rate may lead to an apples-to-oranges rule are based on its low failure rate in the U.S., at least comparison, which is where the novel tool discussed in this for relatively aggressive portfolios. Similarly, some of the article comes in: The maximum withdrawal rate predeter- arguments against it are based on its much higher failure rate mines a desired bequest, thus enabling an apples-to-apples in other countries. In my 2017 Journal of Retirement article, comparison of retirement strategies. I report historical failure rates for 11 asset allocations and 21 This maximum withdrawal rate has at least two applica- countries over the 1900-2014 period and also introduce the tions useful for retirees. First, it provides a comprehensive concept of shortfall years, which aims to refine and comple- way to evaluate retirement strategies, free from the flaw of ment the failure rate, and report its values for the same asset comparing strategies that leave very different bequests; and allocations, countries, and sample period. second, it provides a way to assess how likely is a retiree to To see how the failure rate provides an apples-to-oranges sustain a target sequence of inflation-adjusted withdrawals. comparison, consider Table 1, which reports evidence for the Given that depleting a portfolio too soon is one of the main U.S. market over the 1900-2014 period, for 11 asset alloca- risks faced by retirees, this tool may play the critical role of tions between 100-0 (all stocks) and 0-100 (all bonds), with assessing that risk. nine stock-bond allocations in between. All strategies are based on a starting portfolio of $1,000, a 4% IWR, subse- The Maximum Withdrawal Rate quent withdrawals annually adjusted by inflation, annual Retirement strategies can be classified as generating fixed rebalancing, and 86 rolling 30-year retirement periods or variable withdrawals during the retirement period. The between 1900-1929 and 1985-2014.3 former imply constant withdrawals, typically in real terms, The first row of Table 1 shows the failure rate for the and are related to the discussion here; the latter imply with- 11 asset allocations considered; for the four most aggressive drawals that vary over time depending on changing market strategies, the historical failure rate was 3.5%. These four conditions or life expectancy and are not the focus of this strategies, however, left substantially different bequests, article. regardless of whether they are measured with the mean or Strategies based on fixed withdrawals are fully charac- the median terminal wealth. The 100-0 and the 70-30 strate- terized by their initial withdrawal rate (IWR); that is, the gies left a median bequest of $2,881 and $1,460, a range over *I would like to thank Jack Rader and Vladimir Valenta for their comments. Patricia 2. William Bengen, “Determining Withdrawal Rates Using Historical Data.” Journal of Palgi provided valuable research assistance. IESE’s Center for International Finance (CIF) Financial Planning, 7, 4, 171-180, 1994. kindly provided support for this research. The views expressed below and any errors that 3. The data used throughout this article is from the Dimson-Marsh-Staunton (DMS) may remain are entirely my own. database for the U.S. market, described in detail in their book; see Elroy Dimson, Paul 1. For a discussion of these flaws, see Moshe Milevsky, “It’s Time to Retire Ruin (Prob- Marsh, and Mike Staunton, Triumph of the Optimists – 101 Years of Investment Re- abilities).” Financial Analysts Journal, 72, 2, 8-12, 2016; Javier Estrada, “Refining the turns, Princeton University Press, 2002 and, more recently, Elroy Dimson, Paul Marsh, Failure Rate,” Journal of Retirement, 4, 3, 63-76, 2017; Javier Estrada, “From Failure and Mike Staunton; Credit Suisse Global Investment Returns Sourcebook 2016. Credit to Success: Replacing the Failure Rate.” Journal of Retirement, forthcoming, 2018. Suisse Research Institute, Zurich. Annual returns for stocks and long-term government bonds are real and account for capital gains/losses and cash flows. 134 Journal of Applied Corporate Finance • Volume 29 Number 4 Fall 2017 Table 1 Failure Rates and Bequests This table shows failure rates (in %) for 11 static asset allocations with stock-bond proportions between 100-0 (all stocks) and 0-100 (all bonds), over 86 rolling 30-year retirement periods, beginning with 1900-1929 and ending with 1985-2014; it also shows the mean and median for the distribution of terminal wealth or bequest (in real $). All strategies are based on a starting portfolio of $1,000, a 4% IWR, subsequent annual withdraw- als adjusted by inflation, and annual rebalancing to the stock-bond allocations in the first row. Stocks-Bonds 100-0 90-10 80-20 70-30 60-40 50-50 40-60 30-70 20-80 10-90 0-100 Failure 3.5 3.5 3.5 3.5 4.7 8.1 15.1 25.6 40.7 64.0 65.1 Mean 3,232 2,789 2,383 2,009 1,667 1,356 1,082 848 665 536 433 Median 2,881 2,457 1,925 1,460 1,171 793 520 249 40 0 0 140% larger, in real terms, than the starting portfolio. Put Usefulness of the Maximum Withdrawal Rate differently, these two strategies can hardly be thought of as The MWR as presented above can only be calculated ex-post, having delivered similar performance just because they had once the returns of the portfolio during the retirement period the same failure rate; their mean and median bequests were become known; put differently, it is a measure of the best a dramatically different. retiree could have done had he known the future returns of Enter then the maximum withdrawal rate. Given a his portfolio. Obviously, in practice, nobody knows what the portfolio P0 at the beginning of retirement, a T-year retire- returns of a portfolio will be; still, the MWR is a useful tool ment period, a terminal wealth or desired bequest of $0, for retirees for at least two reasons. First, it provides a compre- and the goal of keeping purchasing power constant during hensive way to evaluate retirement strategies, free from the retirement, the maximum withdrawal rate (MWR) is formally flaw of comparing strategies that leave very different bequests; given by and second, it provides a way to assess how likely is a retiree to sustain a target sequence of inflation-adjusted withdraw- (1+R )(1+R )∙∙∙(1+R ) MWR= 1 2 T als.