Risks in Macroeconomic Fundamentals and Excess Bond Returns Predictability
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Credit Derivatives: Macro-Risk Issues
Credit Derivatives: Macro-Risk Issues Credit Derivatives, Macro Risks, and Systemic Risks by Tim Weithers University of Chicago April 20, 2007 Abstract In this paper, some of the “bigger picture” risks associated with credit derivatives are explored. After drawing a distinction between the market’s perception of credit and “real credit” as reflected in the formal definition of a “credit event”, an examination of the macro drivers of credit generally (which might then prove to be one of the catalysts for larger scale concerns with credit derivatives) is undertaken; these have been fairly well researched and documented. Next, the most frequently cited concerns with the modern credit derivative marketplace are enumerated: the exceedingly large notional traded in credit default swaps alone relative to (i.e., integer multiples of) the outstanding supply of debt (bonds and loans) in any single name, the increasing involvement of the hedge fund community in these products, and the operational concerns (lack of timely confirmations,…) which have come to light (and been publicly and roundly criticized) in the last year or two. The possibilities of associated systemic risk are subsequently considered. Credit derivatives deal with risk, involve the transfer of risk, and are, potentially, risky in and of themselves. As in any “new”market, there have been some “glitches”; some of these issues have already been addressed by the market participants and some of these entail the evolving modelling of these instruments. A brief look at the auto downgrade in March 2005 resulted in some “surprises”; part of the concern with these new (and sometimes complex) credit derivative instruments is their proper hedging, risk management, and valuation. -
Portfolio Structuring and the Value of Forecasting
Research Foundation Briefs PORTFOLIO STRUCTURING AND THE VALUE OF FORECASTING Jacques Lussier, PhD, CFA, Editor In partnership with CFA Montréal Named Endowments The CFA Institute Research Foundation acknowledges with sincere gratitude the gen- erous contributions of the Named Endowment participants listed below. Gifts of at least US$100,000 qualify donors for membership in the Named Endow- ment category, which recognizes in perpetuity the commitment toward unbiased, practitioner-oriented, relevant research that these firms and individuals have expressed through their generous support of the CFA Institute Research Foundation. Ameritech Meiji Mutual Life Insurance Company Anonymous Miller Anderson & Sherrerd, LLP Robert D. Arnott Nikko Securities Co., Ltd. Theodore R. Aronson, CFA Nippon Life Insurance Company of Japan Asahi Mutual Life Nomura Securities Co., Ltd. Batterymarch Financial Management Payden & Rygel Boston Company Provident National Bank Boston Partners Asset Management, L.P. Frank K. Reilly, CFA Gary P. Brinson, CFA Salomon Brothers Brinson Partners, Inc. Sassoon Holdings Pte. Ltd. Capital Group International, Inc. Scudder Stevens & Clark Concord Capital Management Security Analysts Association of Japan Dai-Ichi Life Company Shaw Data Securities, Inc. Daiwa Securities Sit Investment Associates, Inc. Mr. and Mrs. Jeffrey Diermeier Standish, Ayer & Wood, Inc. Gifford Fong Associates State Farm Insurance Company Investment Counsel Association Sumitomo Life America, Inc. of America, Inc. T. Rowe Price Associates, Inc. Jacobs Levy Equity Management Templeton Investment Counsel Inc. John A. Gunn, CFA Frank Trainer, CFA John B. Neff Travelers Insurance Co. Jon L. Hagler Foundation USF&G Companies Long-Term Credit Bank of Japan, Ltd. Yamaichi Securities Co., Ltd. Lynch, Jones & Ryan, LLC Senior Research Fellows Financial Services Analyst Association For more on upcoming Research Foundation publications and webcasts, please visit www.cfainstitute.org/learning/foundation. -
WWP Wolfsburg Working Papers No. 12-01
WWP Wolfsburg Working Papers No. 12-01 The improvement of annual economic forecasts by using non-annual indicators An empirical investigation for the G7 states Johannes Scheier, 2012 The improvement of annual economic forecasts by using non- annual indicators An Empirical Investigation for the G7 states Johannes Scheier Faculty of Business, Chair in Finance, Ostfalia University of Applied Sciences, D-38440 Wolfsburg, Germany Email: [email protected] Phone: +49 5361 8922 25450 Abstract A key demand made of business cycle forecasts is the efficient processing of freely available information. On the basis of two early indicators, this article shows that these opportunities are not being exploited. To this end, consensus forecasts for the economies of the G7 states from 1991-2009 were examined in this study. According to the present state of research, the forecasts are of moderate quality depending on the forecast horizon. The situation is different with regard to the early indicators which were examined. Both the results of a worldwide survey among experts by the Ifo Institute as well as the Composite Leading Indicators of the OECD exhibit a measurable correlation to the economic development considerably earlier for all countries. If viewed simultaneously, it can be seen that the forecast quality for most G7 states could be improved by taking the early indicators into consideration. Keywords: adjusting forecasts, business cycles, macroeconomic forecasts, evaluating forecasts, forecast accuracy, forecast efficiency, forecast monitoring, panel data, time series JEL classification: E17, E32, E37, E60 I. Introduction A wide range of demands are made of business cycle forecasts. The main demand is for them to be of good quality so that they can serve as a planning basis for states, companies and financial market participants. -
Essays on Empirical Asset Pricing
Essays on Empirical Asset Pricing A THESIS SUBMITTED TO THE FACULTY OF THE GRADUATE SCHOOL OF THE UNIVERSITY OF MINNESOTA BY Junyan Shen IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF DOCTOR OF PHILOSOPHY JIANFENG YU, HENGJIE AI May, 2016 c Junyan Shen 2016 ALL RIGHTS RESERVED Acknowledgements I am grateful to my advisors: Hengjie Ai and Jianfeng Yu for their valuable suggestions and continuous encouragement. I would also like to thank the rest of my committee members Frederico Belo and Erzo G.J. Luttmer. i Dedication This dissertation is dedicated to my wife and my parents - for their love, care and support. ii Abstract My dissertation investigates the interaction between macroeconomy and asset prices. On one hand, asset returns can be explained by the riskiness embedded in the economic variables; on the other hand, the aggregate economy is affected by the appropriate distri- bution of productive resources, arising from firm’s financing capability. My dissertation contains two chapters which study these two questions respectively. Chapter one explores the role of investor sentiment in the pricing of a broad set of macro-related risk factors. Economic theory suggests that pervasive factors (such as market returns and consumption growth) should be priced in the cross-section of stock returns. However, when we form portfolios based directly on their exposure to macro-related factors, we find that portfolios with higher risk exposure do not earn higher returns. More important, we discover a striking two-regime pattern for all 10 macro-related factors: high-risk portfolios earn significantly higher returns than low-risk portfolios following low-sentiment periods, whereas the exact opposite occurs following high-sentiment periods. -
Managing Functional Biases in Organizational Forecasts: a Case Study of Consensus Forecasting in Supply Chain Planning
07-024 Managing Functional Biases in Organizational Forecasts: A Case Study of Consensus Forecasting in Supply Chain Planning Rogelio Oliva Noel Watson Copyright © 2007 by Rogelio Oliva and Noel Watson. Working papers are in draft form. This working paper is distributed for purposes of comment and discussion only. It may not be reproduced without permission of the copyright holder. Copies of working papers are available from the author. Managing Functional Biases in Organizational Forecasts: A Case Study of Consensus Forecasting in Supply Chain Planning Rogelio Oliva Mays Business School Texas A&M University College Station, TX 77843-4217 Ph 979-862-3744 | Fx 979-845-5653 [email protected] Noel Watson Harvard Business School Soldiers Field Rd. Boston, MA 02163 Ph 617-495-6614 | Fx 617-496-4059 [email protected] Draft: December 14, 2007. Do not quote or cite without permission from the authors. Managing Functional Biases in Organizational Forecasts: A Case Study of Consensus Forecasting in Supply Chain Planning Abstract To date, little research has been done on managing the organizational and political dimensions of generating and improving forecasts in corporate settings. We examine the implementation of a supply chain planning process at a consumer electronics company, concentrating on the forecasting approach around which the process revolves. Our analysis focuses on the forecasting process and how it mediates and accommodates the functional biases that can impair the forecast accuracy. We categorize the sources of functional bias into intentional, driven by misalignment of incentives and the disposition of power within the organization, and unintentional, resulting from informational and procedural blind spots. -
Anchoring Bias in Consensus Forecasts and Its Effect on Market Prices
Finance and Economics Discussion Series Divisions of Research & Statistics and Monetary Affairs Federal Reserve Board, Washington, D.C. Anchoring Bias in Consensus Forecasts and its Effect on Market Prices Sean D. Campbell and Steven A. Sharpe 2007-12 NOTE: Staff working papers in the Finance and Economics Discussion Series (FEDS) are preliminary materials circulated to stimulate discussion and critical comment. The analysis and conclusions set forth are those of the authors and do not indicate concurrence by other members of the research staff or the Board of Governors. References in publications to the Finance and Economics Discussion Series (other than acknowledgement) should be cleared with the author(s) to protect the tentative character of these papers. ANCHORING BIAS IN CONSENSUS FORECASTS AND ITS EFFECT ON MARKET PRICES* Sean D. Campbell Steven A. Sharpe February 2007 Previous empirical studies that test for the “rationality” of economic and financial forecasts generally test for generic properties such as bias or autocorrelated errors, and provide limited insight into the behavior behind inefficient forecasts. In this paper we test for a specific behavioral bias -- the anchoring bias described by Tversky and Kahneman (1974). In particular, we examine whether expert consensus forecasts of monthly economic releases from Money Market Services surveys from 1990-2006 have a tendency to be systematically biased toward the value of previous months’ data releases. We find broad- based and significant evidence for the anchoring hypothesis; consensus forecasts are biased towards the values of previous months’ data releases, which in some cases results in sizable predictable forecast errors. Then, to investigate whether the market participants anticipate the bias, we examine the response of interest rates to economic news. -
Forecasting Spikes in Electricity Prices
NCER Working Paper Series Forecasting Spikes in Electricity Prices T M Christensen A S Hurn K A Lindsay Working Paper #70 January 2011 Forecasting Spikes in Electricity Prices T M Christensen Department of Economics, Yale University A S Hurn School of Economics and Finance, Queensland University of Technology K A Lindsay Department of Mathematics, University of Glasgow. Abstract In many electricity markets, retailers purchase electricity at an unregulated spot price and sell to consumers at a heavily regulated price. Consequently the occurrence of extreme movements in the spot price represents a major source of risk to retailers and the accu- rate forecasting of these extreme events or price spikes is an important aspect of effective risk management. Traditional approaches to modeling electricity prices are aimed primarily at predicting the trajectory of spot prices. By contrast, this paper focuses exclusively on the prediction of spikes in electricity prices. The time series of price spikes is treated as a realization of a discrete-time point process and a nonlinear variant of the autoregressive conditional hazard (ACH) model is used to model this process. The model is estimated using half-hourly data from the Australian electricity market for the sample period 1 March 2001 to 30 June 2007. The estimated model is then used to provide one-step-ahead forecasts of the probability of an extreme event for every half hour for the forecast period, 1 July 2007 to 30 September 2007, chosen to correspond to the duration of a typical forward contract. The forecasting performance of the model is then evaluated against a benchmark that is consistent with the assumptions of commonly-used electricity pricing models. -
Macro Risks and the Term Structure of Interest Rates∗
Macro Risks and the Term Structure of Interest Rates∗ Geert Bekaert, Columbia University and the National Bureau of Economic Research, Eric Engstrom, Board of Governors of the Federal Reserve System Andrey Ermolov, Gabelli School of Business, Fordham University May 31, 2018 Abstract We use non-Gaussian features in U.S. macroeconomic data to identify aggregate supply and demand shocks while imposing minimal economic assumptions. Recessions in the 1970s and 1980s were driven primarily by supply shocks; later recessions by demand shocks. We estimate macro risk factors that drive \bad" (negatively skewed) and \good" (positively skewed) variation for supply and demand shocks. We document that macro risks significantly contribute to the variation of yields, risk premiums and return variances for nominal bonds. While overall bond risk premiums are counter-cyclical, an increase in aggregate demand variance significantly lowers risk premiums. Keywords: macroeconomic volatility, business cycles, bond return predictability, term premium, Great Moderation JEL codes: E31, E32, E43, E44, G12, G13 ∗Contact information: Geert Bekaert - [email protected], Eric Engstrom - eric.c. [email protected], Andrey Ermolov - [email protected]. Authors thank Michael Bauer, Mikhail Chernov, Philipp Illeditsch, Andrea Vedolin, seminar participants at Baruch College, Bilkent University, University of British Columbia, Bundesbank, City University of London, Duke, Fordham, University of Illinois at Urbana-Champaign, Imperial College, Oxford, Riksbank, Sabanci Business School, Tulane, University of North Carolina at Chapel-Hill, and Stevens Institute of Technology and conference par- ticipants at 2015 Federal Reserve Bank of San Francisco and Bank of Canada Conference on Fixed Income Markets, 2016 NBER Summer Institute, 2016 Society of Financial Econometrics Meeting, 2017 European Finance Association Meeting, 2017 NBER-NSF Time Series Conference, Spring 2018 Midwest Macroeconomics Meetings, and 2018 SFS Cavalcade North America for useful comments. -
Macro Risks and the Term Structure of Interest Rates
NBER WORKING PAPER SERIES MACRO RISKS AND THE TERM STRUCTURE OF INTEREST RATES Geert Bekaert Eric Engstrom Andrey Ermolov Working Paper 22839 http://www.nber.org/papers/w22839 NATIONAL BUREAU OF ECONOMIC RESEARCH 1050 Massachusetts Avenue Cambridge, MA 02138 November 2016 Authors thank seminar participants at Baruch College, Bilkent University, University of British Columbia, Bundesbank, City University of London, Duke, Fordham, University of Illinois at Urbana-Champaign, Imperial College, Oxford, Riksbank, Sabanci Business School, Tulane, and University of North Carolina at Chapel-Hill and conference participants at 2015 Federal Reserve Bank of San Francisco and Bank of Canada Conference on Fixed Income Markets, 2016 NBER Summer Institute, and 2016 Society of Financial Econometrics Meeting for useful comments. All errors are the sole responsibility of the authors. The views expressed herein are those of the authors and do not necessarily reflect the views of the Federal Reserve System, its Board of Governors, or staff, nor those of the National Bureau of Economic Research. NBER working papers are circulated for discussion and comment purposes. They have not been peer-reviewed or been subject to the review by the NBER Board of Directors that accompanies official NBER publications. © 2016 by Geert Bekaert, Eric Engstrom, and Andrey Ermolov. All rights reserved. Short sections of text, not to exceed two paragraphs, may be quoted without explicit permission provided that full credit, including © notice, is given to the source. Macro Risks and the Term Structure of Interest Rates Geert Bekaert, Eric Engstrom, and Andrey Ermolov NBER Working Paper No. 22839 November 2016 JEL No. E31,E32,E43,E44,G12,G13 ABSTRACT We extract aggregate supply and aggregate demand shocks for the US economy from macroeconomic data on inflation, real GDP growth, core inflation and the unemployment gap. -
Exchange Rate Risks and Asset Prices in a Small Open Economy
WORKING PAPER SERIES NO. 314 / MARCH 2004 EXCHANGE RATE RISKS AND ASSET PRICES IN A SMALL OPEN ECONOMY by Alexis Derviz WORKING PAPER SERIES NO. 314 / MARCH 2004 EXCHANGE RATE RISKS AND ASSET PRICES IN A SMALL OPEN ECONOMY1 by Alexis Derviz 2 In 2004 all publications will carry This paper can be downloaded without charge from a motif taken http://www.ecb.int or from the Social Science Research Network from the €100 banknote. electronic library at http://ssrn.com/abstract_id=515078. 1 This research was conducted during the author’s fellowship at the ECB DG Research sponsored by the Accession Countries Central Banks’ Economist Visiting Programme. Comments and valuable advice by Carsten Detken,Vítor Gaspar, Philipp Hartmann and ananonymous referee are gratefully acknowledged.The usual disclaimer applies.The opinions expressed herein are those of the autor(s) and do not necessarily reflect those of the ECB. 2 Czech National Bank, Monetary and Statistics Dept., Na Prikope 28, CZ-115 03 Praha 1, Czech Republic, email:[email protected] and Institute for Information Theory and Automation, Pod vodarenskou vezi 4, CZ-182 08 Praha 8, Czech Republic, e-mail: [email protected]. © European Central Bank, 2004 Address Kaiserstrasse 29 60311 Frankfurt am Main, Germany Postal address Postfach 16 03 19 60066 Frankfurt am Main, Germany Telephone +49 69 1344 0 Internet http://www.ecb.int Fax +49 69 1344 6000 Telex 411 144 ecb d All rights reserved. Reproduction for educational and non- commercial purposes is permitted provided that the source is acknowledged. The views expressed in this paper do not necessarily reflect those of the European Central Bank. -
What Explains the Sovereign Credit Default Swap Spreads Changes in the GCC Region?
Journal of Risk and Financial Management Article What Explains the Sovereign Credit Default Swap Spreads Changes in the GCC Region? Nader Naifar College of Economics and Administrative Sciences, Imam Mohammad Ibn Saud Islamic University (IMSIU), P.O. Box 5701, Riyadh 11432, Saudi Arabia; [email protected] Received: 25 August 2020; Accepted: 14 October 2020; Published: 16 October 2020 Abstract: This paper aimed to investigate the drivers of sovereign credit risk spreads changes in the case of four Gulf Cooperation Council (GCC) countries, namely Kingdom of Saudi Arabia (KSA), the United Arab Emirates (UAE), Qatar, and Bahrain. Specifically, we explained the changes in sovereign credit default swap (hereafter SCDS) spreads at different locations of the spread distributions by three categories of explanatory variables: global uncertainty factors, local financial variables, and global financial market variables. Using weekly data from 5 April 2013, to 17 January 2020, and the quantile regression model, empirical results indicate that the global factors outperform the local factors. The most significant variables for all SCDS spreads are the global financial uncertainty embedded in the Chicago Board Options Exchange (CBOE) volatility index (VIX) and the global conventional bond market uncertainty embedded in the Merrill Lynch Option Volatility Estimate (MOVE) index. Moreover, the MOVE index affects the various SCDS spreads only when the CDS markets are bullish. Interestingly, the SCDS spreads are not affected by the global economic policy and the gold market uncertainties. Additionally, a weak dependence is observed between oil prices and SCDS spreads. For the country-specific factors, stock market returns are the most significant variable and impact the SCDS spreads at different market circumstances. -
Macro Risks and the Term Structure of Interest Rates∗
Macro Risks and the Term Structure of Interest Rates∗ Geert Bekaert, Columbia University and the National Bureau of Economic Research, Eric Engstrom, Board of Governors of the Federal Reserve System Andrey Ermolov, Gabelli School of Business, Fordham University September 9, 2019 Abstract We use non-Gaussian features in U.S. macroeconomic data to identify aggregate supply and demand shocks while imposing minimal economic assumptions. Macro risks represent the vari- ables that govern the time-varying variance, skewness and higher-order moments of these two shocks, with \good" (\bad") variance associated with positive (negative) skewness. We docu- ment that macro risks significantly contribute to the variation of yields and risk premiums for nominal bonds. While overall bond risk premiums are counter-cyclical, an increase in aggregate demand variance significantly lowers risk premiums. Macro risks also significantly predict future realized bond return variances. Keywords: bond return predictability, term premium, macroeconomic volatility, business cycles, macro risk factors JEL codes: E31, E32, E43, E44, G12, G13 ∗Contact information: Geert Bekaert - [email protected], Eric Engstrom - eric.c. [email protected], Andrey Ermolov - [email protected]. Authors thank Michael Bauer, Mikhail Chernov, Isaiah Hull, Philipp Illeditsch, Aaron Pancost, Andrea Vedolin, seminar participants at Baruch College, Bilkent University, University of British Columbia, Bundesbank, City University of London, Duke, Fordham, University of Illinois at Urbana-Champaign,