07269oam 22011534 450 991082053450332120240402045534.01-4755-1037-31-4755-1431-X(CKB)2670000000278836(EBL)1606956(SSID)ssj0000949447(PQKBManifestationID)11958267(PQKBTitleCode)TC0000949447(PQKBWorkID)11014320(PQKB)11314871(MiAaPQ)EBC1606956(Au-PeEL)EBL1606956(CaPaEBR)ebr10627057(OCoLC)870244999(IMF)WPIEE2012212(IMF)WPIEA2012212(EXLCZ)99267000000027883620020129d2012 uf 0engur|n|---|||||txtccrEmerging Market Sovereign Bond Spreads : Estimation and Back-testing /Fabio Comelli1st ed.Washington, D.C. :International Monetary Fund,2012.1 online resource (44 p.)IMF Working PapersDescription based upon print version of record.1-4755-4252-6 1-4755-0562-0 Includes bibliographical references.Cover; Contents; I. Introduction; II. Literature; III. The data; A. Emerging Market Sovereign Bond Spreads Data; B. Pull Factors Data; Political Risk Rating (PRR); Economic Risk Rating (ERR); Financial Risk Rating (FRR); C. Push Factors Data; IV. The Model; V. Regression Results; A. Baseline regression; B. Global Abundant Liquidity and Global Financial Crisis; Tables; Table 1. Sovereign Bond Spreads: Coefficient Estimates, All Emerging Market Economies; C. Regional Subgroups; D. How Do Fitted Bond Spreads Compare With Actual Bond Spreads?Table 2. Sovereign Bond Spreads: Coefficient Estimates Across EM Regions.Figures; Panel 1. Actual and Fitted Sovereign Bond Spreads (basis points); Panel 2. Actual and Fitted Sovereign Bond Spreads: (basis points); E. Robustness Checks; Table 3. Sovereign Bond Spreads: Coefficient Estimates, Robustness Checks; Panel 3. Actual and Fitted Sovereign Bond Spreads (Basis points); F. Simulating an Improvement in Country-specific Variables on Bond Spreads; Table 4. Impact of one-standard deviation change on the model spread (Percent)Panel 4. Impact on the Model Spread Provoked by a One-standard Deviation ChangeVI. Back-testing the Model; A. Linear Prediction Method; B. Rolling Regression Method; Table 5. Probabilities that the linear prediction method correctly predicts (i) the; Table 6. Probabilities that the rolling regression (RR1) method correctly predicts; C. Comparing Competing Forecasts; Table 7. Measuring the accuracy of bond spread forecasts with the Diebold-Mariano; VII. Concluding Remarks; References; Appendixes; A. Tables; Appendix TablesTable A1. Probabilities that the rolling regression (RR2) method correctly predictsTable A2. Comparing rolling regression and linear prediction forecasts with the Diebold- Mariano test; Table A3. Mean Square Error, Mean Absolute Error and Theil's U Statistics for the rolling regression (RR1) method; Table A4. Mean Square Error, Mean Absolute Error and Theil's U Statistics for the rolling regression (RR2) method; B. Charts; Panel A1. Emerging Market Sovereign Bond Spreads: Actual, Fitted and Residuals; Panel A2: Emerging Markets Sovereign Bond Spread Tracker: January 1998 - December 2001Panel A3: Emerging Markets Sovereign Bond Spread Tracker: January 2002 - December 2005Panel A4: Emerging Markets Sovereign Bond Spread Tracker: January 2006 - December 2009; Panel A5: Emerging Markets Sovereign Bond Spread Tracker: January 2010 - December 2011We estimate sovereign bond spreads of 28 emerging economies over the period January 1998-December 2011 and test the ability of the model in generating accurate in-sample predictions for emerging economies bond spreads. The impact and significance of country-specific and global explanatory variables on bond spreads varies across regions, as well as economic periods. During crisis times, good macroeconomic fundamentals are helpful in containing bond spreads, but less than in non-crisis times, possibly reflecting the impact of extra-economic forces on bond spreads when a financial crisis occurs. For some emerging economies, in-sample predictions of the monthly changes in bond spreads obtained with rolling regression routines are significantly more accurate than forecasts obtained with a random walk. Rolling regression-based bond spread predictions appear to convey more information than those obtained with a linear prediction method. By contrast, bond spreads forecasts obtained with a linear prediction method are less accurate than those obtained with random guessing.IMF Working Papers; Working Paper ;No. 2012/212State bondsEconometric modelsGovernment securitiesEconometric modelsBanks and BankingimfFinance: GeneralimfInvestments: BondsimfInternational Finance Forecasting and SimulationimfFinancial Forecasting and SimulationimfInterest Rates: Determination, Term Structure, and EffectsimfGeneral Financial Markets: General (includes Measurement and Data)imfFinanceimfInvestment & securitiesimfYield curveimfSovereign bondsimfEmerging and frontier financial marketsimfBond yieldsimfSecurities marketsimfFinancial servicesimfFinancial institutionsimfFinancial marketsimfInterest ratesimfBondsimfFinancial services industryimfCapital marketimfUnited StatesimfState bondsEconometric models.Government securitiesEconometric models.Banks and BankingFinance: GeneralInvestments: BondsInternational Finance Forecasting and SimulationFinancial Forecasting and SimulationInterest Rates: Determination, Term Structure, and EffectsGeneral Financial Markets: General (includes Measurement and Data)FinanceInvestment & securitiesYield curveSovereign bondsEmerging and frontier financial marketsBond yieldsSecurities marketsFinancial servicesFinancial institutionsFinancial marketsInterest ratesBondsFinancial services industryCapital market332.1/52Comelli Fabio1082917DcWaIMFBOOK9910820534503321Emerging Market Sovereign Bond Spreads4110856UNINA