Central Bank Journal of Law and Finance L Year II, no. 1, 2015 The Central Bank Journal of Law and Finance is coordinated by the National Bank of Romania – Legal Department, Director Alexandru-Nicolae Păunescu, PhD 1. SCIENTIFIC BOARD Mugur ISĂRESCU Academician, Romanian Academy, Corresponding member of Real Academia de Ciencias Económicas y Financieras, Barcelona, Spain Moisă ALTĂR Professor, DoFIN, Academy of Economic Studies, Bucharest, Romania, Romanian-American University, Bucharest, Romania Lucian BERCEA Professor, West University of Timişoara, Romania Radu CATANĂ Professor, Babeş Bolyai University, Cluj, Romania James Ming CHEN Professor, Justin Smith Morrill Chair in Law, Michigan State University, USA Ionuţ DUMITRU Professor, DoFIN, Academy of Economic Studies, Bucharest, Romania Ovidiu FOLCUŢ Professor, Romanian-American University, Bucharest, Romania M. Peter van der HOEK Professor, Academy of Economic Studies, Bucharest, Romania, Erasmus University (EM), Rotterdam, Netherlands Iftekhar HASAN Professor, E. Gerald Corrigan Chair in International Business and Finance, Fordham University’s Schools of Business, New York, USA Dumitru MIRON Professor, Academy of Economic Studies, Bucharest, Romania Ion STANCU Professor, Academy of Economic Studies, Bucharest, Romania Brânduşa ŞTEFĂNESCU Professor Emeritus Paul WACHTEL Professor, Stern School of Business, New York University, USA 2. EDITORIAL BOARD Tudor CIUMARA PhD, Researcher, Centre of Financial and Monetary Research, Bucharest, Romania Adrian - Ionuţ PhD, Associate Professor, Academy of Economic Studies, CODIRLAŞU Bucharest, Romania Bogdan-Octavian PhD, Senior Lecturer, Academy of Economic Studies, COZMÂNCĂ Bucharest, Romania Adina CRISTE PhD, Researcher, Centre of Financial and Monetary Research, Bucharest, Romania Constantin MARIN PhD, Researcher, Centre of Financial and Monetary Research, Bucharest, Romania Beatrice POPESCU Adviser to the Deputy Governor of the National Bank of Romania Radu RIZOIU PhD, Lecturer, Faculty of Law, University of Bucharest, Romania iii Cover by Romeo Cȋrjan, PhD DISCLAIMER The opinions expressed in this publication are those of the authors and do not necessarily reflect the views of the National Bank of Romania, nor do they engage it in any way. © 2015 National Bank of Romania. All rights reserved. Published by the National Bank of Romania, 25 Lipscani Street, 030031 Bucharest | www.bnro.ro ISSN 2392 – 9723 ISSN-L 2392 – 9723 iv CONTENTS James Ming Chen The Promise and the Peril of Parametric Value at-Risk (VaR) Analysis 1 Andreas Guericke, Jochen Sprung Designing Macroprudential Mandates and Institutional Frameworks: The German Approach 43 Lucian Croitoru Monetary Policy and the Global Imbalances (the Euro, the Dollar, the Yen and the Yuan) 57 Ianfred Silberstein The Essential Characteristic of a Central Bank – Independence 69 Mirela Iovu The Effects of Implementing European Commission Recommendation (EC) No. 135/2014 on a New Approach to Business Failure and Insolvency 89 Irina Mihai, Alina Tarţa The Role of the Insolvency Framework in Strengthening the Payment Discipline and in Developing the Credit Market in Romania 107 Dan Pălăngean The Evolution of GDP in Romania and the Consequences from the Purchasing Power Perspective 133 v AUTHOR GUIDELINES for CENTRAL BANK JOURNAL OF LAW AND FINANCE The future contributors of the Central Bank Journal of Law and Finance, published under the auspices of the National Bank of Romania, are requested to consider the guidelines below. DRAFTING GUIDELINES Manuscript Formatting. Prepare the manuscript in English, using Georgia 10 pt. for the body text and 9 pt. for footnotes and legends, 1.2 line spacing, A4 paper size and submit it as doc, docx or rtf. Do not use bold, underline or ALL CAPS. Use italics sparingly, for emphasis only. Do not use tabs or indents. Manuscript Structure. Structure the manuscript as follows: the manuscript title in capital letters, an abstract that should not exceed 100 words, keywords, JEL classification, main text, acknowledgements, appendices, references. Divide your manuscript into clearly defined and numbered sections. Tables, Graphics and Schemes. Provide numbered captions for all tables and figures. Citations. Use endnotes to cite sources. Citations should follow the format: author’s last name, author’s first name, full title of the cited paper, publisher, place of publication, year, cited page(s). References. Submit each manuscript with a full list of references. The list should be numbered, delimited by semicolons and each reference should follow the format: author’s last name, author’s first name, full title (do not use abbreviations), publisher, place of publication, year, cited page(s). SUBMISSION Submit your manuscript to the e-mail address: [email protected]. vi The Promise and the Peril of Parametric Value-at-Risk (VaR) Analysis James Ming Chen* Abstract Leptokurtosis, or the risk lurking in “fat tails,” poses the deepest epistemic threat to economic forecasting. Parametric value-at-risk (VaR) models are vulnerable to kurtosis in excess of the levels associated with a Gaussian distribution. Careful application of Student’s t-distribution can enhance the statistical robustness of VaR forecasts. For degrees of freedom greater than 4, Student’s t-distribution can emulate any level of excess kurtosis. Observed levels of kurtosis guide the use of Student’s t-distribution to measure VaR. Parametric VaR according to the number of degrees of freedom implied by historical levels of kurtosis also yields the corresponding value of expected shortfall. This parametric technique not only exploits the elicitability of VaR from historical data, but also informs the computation of expected shortfall as a coherent risk measure. Keywords kurtosis, value-at-risk, VaR, expected shortfall, Basel accords, Student’s t-distribution JEL Classification: C58, G17, G21 * Justin Smith Morrill Chair in Law, Michigan State University. I presented this paper on June 24, 2015, to the Faculty of Economics of the University of Zagreb (Ekonomski Fakultet Sveučilišta u Zagrebu). I have benefited from scholarly interactions with Anna Agrapetidou, Moisa Altar, Chris Brummer, Adam Candeub, Robert Dubois, John F. Duffy, Santanu Ganguli, Tomislav Gelo, Periklis Gogas, Jagoda Kaszowska, Daniel Martin Katz, Yuri Katz, Imre Kondor, Othmar Lehner, Milivoj Marković, José María Montero Lorenzo, Vivian Okere, Merav Ozair, Carol Royal, Jeffrey A. Sexton, Jurica Šimurina, Nika Sokol Šimurina, Robert Sonora, Benjamin Walther, Gal Zahavi, and Johanna F. Ziegel. Christian Diego Alcocer Argüello, Emily Strickler, and Michael Joseph Yassay provided very capable research assistance. Special thanks to Heather Elaine Worland Chen. Central Bank Journal of Law and Finance, No. 1/2015 1 The Promise and the Peril of Parametric Value-at-Risk (VaR) Analysis T.S. Eliot, the celebrated Anglo-American poet, called history “a pattern/ Of timeless moments.”1 In projecting forward rather than backward over time, economic forecasting cannot escape moments of a different sort: the mathematical moments of the distribution of financial returns. Of the four moments of greatest interest to financial institutions and their regulators2 — mean, variance, skewness, and kurtosis — it is the fourth moment, kurtosis, that should pose the deepest epistemic concern. Kurtosis eludes detection where it counts most — in its fat tails. Our expectations and perceptions may underestimate the most extreme risks by a significant margin. The overarching goal in financial responses to leptokurtosis and “fat tails” is the accurate forecasting of extreme events. Simple accuracy in description, if attainable and attained, would be a fantastic accomplishment. This article will describe one approach for managing kurtosis in financial returns. Despite its flaws, conventional value-at-risk (VaR) analysis remains a vital tool in financial risk management. VaR and related risk management techniques have been embraced by the Basel Committee on Banking Supervision and codified in the accords known as Basel II, 2.5, and III. But parametric VaR models are extremely vulnerable to kurtosis in excess of the levels associated with a normal, Gaussian distribution. Using a systematically leptokurtic distribution to forecast extreme losses provides a workable response to the model risk that haunts VaR analysis. This article provides step-by-step guidance on the use of Student’s t-distribution as an easily implemented model for enhancing the robustness of VaR forecasts. Although the distribution and quantile functions of Student’s t-distribution lack simple, closed-form representations,3 the distribution’s even-numbered moments are extremely tractable. For degrees of freedom greater than 4, Student’s t-distribution can emulate any level of kurtosis exceeding that of a Gaussian distribution. The elicitability of VaR from historical data invites the use of observed kurtosis as a credible theoretical basis for enhancing the robustness of VaR measurements. Part I of this article provides background on kurtosis. Mindful of the ongoing significance of conventional VaR in financial risk management, Part II describes parametric VaR on a Gaussian model. Part III implements an alternative approach to parametric VaR according to Student’s t-distribution. The pivotal question is determining the number of degrees of freedom. As an admonition to heed the shape as well as the scale of a statistical distribution, part IV will compare Student’s t-distribution to the logistic distribution,