In this article, we consider the Tunisia InterBank Offered Rate (TUNIBOR) which is the interest rate at which Tunisian banks lend and borrow liquidity in the Tunisian interbank market which is the arithmetic average of the interest rates fixed and submitted by the Tunisian most active banks (ranking is determined by the Banque Centrale de Tunisie). Then, it is given as an indication for lending and borrowing operations carried out between Tunisian banks. This study focuses on exploring the dependencies of the TUNIBOR with external factors. The first part presents the approach used by the authors to collect the dataset. In the second part, we will explore the dependencies of the TUNIBOR and look for potential correlations. Finally, we present the computation results that lead to the choice of the optimal parameters for the models proposed.
{"title":"Market Analysis and Dependencies Exploration of the Tunisia Interbank Offered Rate","authors":"Iheb Hajji, A. Rebai","doi":"10.2139/ssrn.3917540","DOIUrl":"https://doi.org/10.2139/ssrn.3917540","url":null,"abstract":"In this article, we consider the Tunisia InterBank Offered Rate (TUNIBOR) which is the interest rate at which Tunisian banks lend and borrow liquidity in the Tunisian interbank market which is the arithmetic average of the interest rates fixed and submitted by the Tunisian most active banks (ranking is determined by the Banque Centrale de Tunisie). Then, it is given as an indication for lending and borrowing operations carried out between Tunisian banks. This study focuses on exploring the dependencies of the TUNIBOR with external factors. The first part presents the approach used by the authors to collect the dataset. In the second part, we will explore the dependencies of the TUNIBOR and look for potential correlations. Finally, we present the computation results that lead to the choice of the optimal parameters for the models proposed.","PeriodicalId":112822,"journal":{"name":"ERN: Interest Rate Forecasts (Topic)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128544266","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Following the 2008 financial crisis, interest rate market experienced major changes in the ways Libor rate was treated. Since Libor is not a risk free rate, the dual curve bootstrapping (Libor-OIS) has been introduced. The term risk premium (e.g., 3m6m Libor basis) has been handled via newly introduced multi-curve framework. The discovery of the Libor rate manipulations back in 2007 broke Libor's back. Citigroup introduced Nybor in 2008 as an alternative to Libor. Following the Libor crisis, the Alternative Reference Rates Committee (ARRC) has been established to "ensure a successful transition from U.S. dollar (USD) Libor to a more robust reference rate, its recommended alternative, the Secured Overnight Financing Rate (SOFR)." This rippled through other countries with introductions of SONIA (for GBP Libor), ESTER (for Euribor), etc. Although there are a lot of modeling similarities between Libor and SOFR rate bootstrapping, there are a number of differences. In this paper we discuss bootstrapping methodologies along with some modeling differences and new modeling considerations.
{"title":"SOFR Bootstrapping Modeling Methodologies and Issues (w/Python and Excel Replicas of Bloomberg SOFR @ GitHub)","authors":"V. Abramov, Xianwen Zhou, Zhengye Bian","doi":"10.2139/ssrn.3654466","DOIUrl":"https://doi.org/10.2139/ssrn.3654466","url":null,"abstract":"Following the 2008 financial crisis, interest rate market experienced major changes in the ways Libor rate was treated. Since Libor is not a risk free rate, the dual curve bootstrapping (Libor-OIS) has been introduced. The term risk premium (e.g., 3m6m Libor basis) has been handled via newly introduced multi-curve framework. The discovery of the Libor rate manipulations back in 2007 broke Libor's back. Citigroup introduced Nybor in 2008 as an alternative to Libor. Following the Libor crisis, the Alternative Reference Rates Committee (ARRC) has been established to \"ensure a successful transition from U.S. dollar (USD) Libor to a more robust reference rate, its recommended alternative, the Secured Overnight Financing Rate (SOFR).\" This rippled through other countries with introductions of SONIA (for GBP Libor), ESTER (for Euribor), etc. Although there are a lot of modeling similarities between Libor and SOFR rate bootstrapping, there are a number of differences. In this paper we discuss bootstrapping methodologies along with some modeling differences and new modeling considerations.","PeriodicalId":112822,"journal":{"name":"ERN: Interest Rate Forecasts (Topic)","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-07-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129243268","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This paper proposes an evaluative study of the predictive capabilities of the yield spread on economic performance in India. While literature on the subject is vast, studies so far have centered primarily on the U.S. and other developed European economies. In line with previous literature, we choose the spread between the 3-month and 10-year treasury bonds to conduct our analysis, using data from the beginning of 1995 till the end of 2019. We use the probit model to check whether curve inversions predict recessions within the country, finding the spread to be a significant determinant either immediately or 2-quarters ahead. However, in terms of predicting economic performance, the spread shows much weaker capabilities, containing minimal information on changes in real GDP, inflation rates or industrial production. With the yield curve being an easy to track monetary policy indicator, proving its forecasting potential should prove an aid to policymakers and sheds light on the importance of monetary policy for developing countries, establishing the need for further academic research on the subject in the developing and underdeveloped countries of the global east.
{"title":"An Evaluation of the Predictive Capabilities of the Yield Curve in India","authors":"M. Chaudhuri","doi":"10.2139/ssrn.3580931","DOIUrl":"https://doi.org/10.2139/ssrn.3580931","url":null,"abstract":"This paper proposes an evaluative study of the predictive capabilities of the yield spread on economic performance in India. While literature on the subject is vast, studies so far have centered primarily on the U.S. and other developed European economies. In line with previous literature, we choose the spread between the 3-month and 10-year treasury bonds to conduct our analysis, using data from the beginning of 1995 till the end of 2019. We use the probit model to check whether curve inversions predict recessions within the country, finding the spread to be a significant determinant either immediately or 2-quarters ahead. However, in terms of predicting economic performance, the spread shows much weaker capabilities, containing minimal information on changes in real GDP, inflation rates or industrial production. With the yield curve being an easy to track monetary policy indicator, proving its forecasting potential should prove an aid to policymakers and sheds light on the importance of monetary policy for developing countries, establishing the need for further academic research on the subject in the developing and underdeveloped countries of the global east.","PeriodicalId":112822,"journal":{"name":"ERN: Interest Rate Forecasts (Topic)","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-04-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121248624","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
We use survey data on expectations about future monetary policy to decompose excess returns to fed funds (FF) futures and overnight index swaps (OIS) into a term premium and an expectation error component. We find that excess returns are almost entirely driven by expectation errors, while term premia are slightly negative and economically small. We show that most of the expectation errors stem from market participants underestimating how aggressively the Federal Reserve has eased policy during the last three decades. Our evidence suggests that market participants at the time were unaware of changes in the central bank's reaction function, in particular the importance attributed to deteriorating financial conditions and falling stock market returns. We confirm our main results in an international sample of six major currency areas.
{"title":"Monetary Policy Expectation Errors","authors":"Maik Schmeling, A. Schrimpf, Sigurd Steffensen","doi":"10.2139/ssrn.3553496","DOIUrl":"https://doi.org/10.2139/ssrn.3553496","url":null,"abstract":"We use survey data on expectations about future monetary policy to decompose excess returns to fed funds (FF) futures and overnight index swaps (OIS) into a term premium and an expectation error component. We find that excess returns are almost entirely driven by expectation errors, while term premia are slightly negative and economically small. We show that most of the expectation errors stem from market participants underestimating how aggressively the Federal Reserve has eased policy during the last three decades. Our evidence suggests that market participants at the time were unaware of changes in the central bank's reaction function, in particular the importance attributed to deteriorating financial conditions and falling stock market returns. We confirm our main results in an international sample of six major currency areas.","PeriodicalId":112822,"journal":{"name":"ERN: Interest Rate Forecasts (Topic)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-03-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115811386","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In this paper, I introduce and define interest rate models for pricing interest rate derivatives in ibor fallback environment. July 2017 Andrew Bailey, the CEO of the U.K. Financial Conduct Authority (FCA), speech on "The future of LIBOR" contains that there is an increased expectation that some IBOR benchmarks will be discontinued in the near future. On July 12, 2018, ISDA published a consultation on benchmark fallbacks to market participants, and on the end of 2018, published the final results of new benchmark fallbacks for interest rate derivatives contracts that reference certain IBORs. As a result, quantitative analysts, risk managers and financial system engineers have been forced to develop fallback rate dynamics that model new benchmark fallbacks of the final results published by ISDA and evaluate interest rate derivatives corresponding to the fallback rate. Furthermore, they have to evaluate both ibor based interest rate derivatives contracted before ibor fallback and ones after it for ibor fallback environment. I show that fallback rate dynamics can be described with extending the classic interest rate models, and the dynamics can be available for pricing interest rate derivatives in ibor fallback environment.
{"title":"Pricing Interest Rate Derivatives after Ibor Fallback","authors":"Takahiro Hasegawa","doi":"10.2139/ssrn.3677012","DOIUrl":"https://doi.org/10.2139/ssrn.3677012","url":null,"abstract":"In this paper, I introduce and define interest rate models for pricing interest rate derivatives in ibor fallback environment. July 2017 Andrew Bailey, the CEO of the U.K. Financial Conduct Authority (FCA), speech on \"The future of LIBOR\" contains that there is an increased expectation that some IBOR benchmarks will be discontinued in the near future. On July 12, 2018, ISDA published a consultation on benchmark fallbacks to market participants, and on the end of 2018, published the final results of new benchmark fallbacks for interest rate derivatives contracts that reference certain IBORs. As a result, quantitative analysts, risk managers and financial system engineers have been forced to develop fallback rate dynamics that model new benchmark fallbacks of the final results published by ISDA and evaluate interest rate derivatives corresponding to the fallback rate. Furthermore, they have to evaluate both ibor based interest rate derivatives contracted before ibor fallback and ones after it for ibor fallback environment. I show that fallback rate dynamics can be described with extending the classic interest rate models, and the dynamics can be available for pricing interest rate derivatives in ibor fallback environment.","PeriodicalId":112822,"journal":{"name":"ERN: Interest Rate Forecasts (Topic)","volume":"38 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124580031","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
We assess the ability of yield curve factors to predict risk premia in short-term interest rates and exchange rates across a large sample of major advanced economies. We find that the same tick-shaped linear combination of (relative) bond yields predicts risk premia in both short-term interest rates and exchange rates at returnforecasting horizons of up to six months for all (but one) countries and currencies in our sample. Our single forecasting factor loads positively on the short and long end of the curve and negatively on the medium-term and is therefore inversely related to Nelson-Siegel’s curvature factor. In line with recent interpretations of the yield curve factors, our findings suggest that the hump of the yield curve bears important information about future short-term interest rates. A relatively high curvature predicts a surprise rise in short-term interest rates beyond expectations and, coincidentally, an appreciation of the home currency in line with uncovered interest rate parity. JEL Classification: C23, C53, G11
{"title":"Predicting Risk Premia in Short-Term Interest Rates and Exchange Rates","authors":"J. Gräb, T. Kostka","doi":"10.2139/ssrn.3130604","DOIUrl":"https://doi.org/10.2139/ssrn.3130604","url":null,"abstract":"We assess the ability of yield curve factors to predict risk premia in short-term interest rates and exchange rates across a large sample of major advanced economies. We find that the same tick-shaped linear combination of (relative) bond yields predicts risk premia in both short-term interest rates and exchange rates at returnforecasting horizons of up to six months for all (but one) countries and currencies in our sample. Our single forecasting factor loads positively on the short and long end of the curve and negatively on the medium-term and is therefore inversely related to Nelson-Siegel’s curvature factor. In line with recent interpretations of the yield curve factors, our findings suggest that the hump of the yield curve bears important information about future short-term interest rates. A relatively high curvature predicts a surprise rise in short-term interest rates beyond expectations and, coincidentally, an appreciation of the home currency in line with uncovered interest rate parity. JEL Classification: C23, C53, G11","PeriodicalId":112822,"journal":{"name":"ERN: Interest Rate Forecasts (Topic)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-02-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115588173","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Negative interest rates are present in various marketplaces since mid-2014, following the negative interest rate policy (NIRP) adopted by the European Central Bank in order to lift the economic growth (and, therefore, the inflation). However, this policy involves difficulties for market practitioners as there is no model that enables to forecast negative interest rates in a coherent and sounding theoretical manner. Facing this lack of reliable models, the well-known Historical Approach (HA) appears to be a good resource. By tweaking the HA, we derive a data-driven and very tractable tool that allows practitioners to generate yield-curve distribution at future discrete time horizons. So, we provide a robust and easy-to-understand forecasting model, suitable for the NIRP context, allowing to appreciate its prediction power. Besides the methodology development that we present in this work, various numerical illustrations are reported in order to shed light on the benefit (and the limit) of our forecasting approach.
{"title":"Forecasting Negative Yield-Curve Distributions","authors":"Jae-Yun Jun, Victor Lebreton, Y. Rakotondratsimba","doi":"10.2139/ssrn.3034358","DOIUrl":"https://doi.org/10.2139/ssrn.3034358","url":null,"abstract":"Negative interest rates are present in various marketplaces since mid-2014, following the negative interest rate policy (NIRP) adopted by the European Central Bank in order to lift the economic growth (and, therefore, the inflation). However, this policy involves difficulties for market practitioners as there is no model that enables to forecast negative interest rates in a coherent and sounding theoretical manner. Facing this lack of reliable models, the well-known Historical Approach (HA) appears to be a good resource. By tweaking the HA, we derive a data-driven and very tractable tool that allows practitioners to generate yield-curve distribution at future discrete time horizons. So, we provide a robust and easy-to-understand forecasting model, suitable for the NIRP context, allowing to appreciate its prediction power. Besides the methodology development that we present in this work, various numerical illustrations are reported in order to shed light on the benefit (and the limit) of our forecasting approach.","PeriodicalId":112822,"journal":{"name":"ERN: Interest Rate Forecasts (Topic)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129344172","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This paper undertakes an empirical inquiry concerning the determinants of long-term interest rates on US Treasury securities. It applies the bounds testing procedure to cointegration and error correction models within the autoregressive distributive lag (ARDL) framework, using monthly data and estimating a wide range of Keynesian models of long-term interest rates. While previous studies have mainly relied on quarterly data, the use of monthly data substantially expands the number of observations. This in turn enables the calibration of a wide range of models to test various hypotheses. The short-term interest rate is the key determinant of the longterm interest rate, while the rate of core inflation and the pace of economic activity also influence the long-term interest rate. A rise in the ratio of the federal fiscal balance (government net lending/borrowing as a share of nominal GDP) lowers yields on long-term US Treasury securities. The short- and long-run effects of short-term interest rates, the rate of inflation, the pace of economic activity, and the fiscal balance ratio on long-term interest rates on US Treasury securities are estimated. The findings reinforce Keynes’s prescient insights on the determinants of government bond yields.
{"title":"An Inquiry Concerning Long-Term US Interest Rates Using Monthly Data","authors":"Tanweer Akram, Huiqing Li","doi":"10.2139/ssrn.3015348","DOIUrl":"https://doi.org/10.2139/ssrn.3015348","url":null,"abstract":"This paper undertakes an empirical inquiry concerning the determinants of long-term interest rates on US Treasury securities. It applies the bounds testing procedure to cointegration and error correction models within the autoregressive distributive lag (ARDL) framework, using monthly data and estimating a wide range of Keynesian models of long-term interest rates. While previous studies have mainly relied on quarterly data, the use of monthly data substantially expands the number of observations. This in turn enables the calibration of a wide range of models to test various hypotheses. The short-term interest rate is the key determinant of the longterm interest rate, while the rate of core inflation and the pace of economic activity also influence the long-term interest rate. A rise in the ratio of the federal fiscal balance (government net lending/borrowing as a share of nominal GDP) lowers yields on long-term US Treasury securities. The short- and long-run effects of short-term interest rates, the rate of inflation, the pace of economic activity, and the fiscal balance ratio on long-term interest rates on US Treasury securities are estimated. The findings reinforce Keynes’s prescient insights on the determinants of government bond yields.","PeriodicalId":112822,"journal":{"name":"ERN: Interest Rate Forecasts (Topic)","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-08-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125140144","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This paper presents an application of stochastic risk factor approach to model the non-maturing deposits and it sketches a benchmark framework to assess the related expected profitability and the liquidity and duration risks of a bank compared with the rest of the economic system it works within. More specifically, we calibrate the model to system data for sight deposits of the Italian banking industry, available from the public statistical data base of Banca d'Italia, spanning over a long period of time that includes the Euro Crisis. The approach is applied to both retail and corporate customers, and it considers their different behaviour based on the size of their deposit. It allows for i) an integrated modelling of the market interest rates, creditworthiness of the bank and evolution of the deposits' volume; ii) stochastic risk factors driving deposits' rates and volume; iii) unified and consistent measurement of the interest rate risk and the liquidity; iv) negative interest rates, both at inception and in the future; v) the evaluation of optionalities such as the zero floor on the deposits rates; vi) stress testing for ALM purposes.
{"title":"A Benchmark Framework for Non Maturing Deposits: An Application to Public Data Available from Banca d'Italia","authors":"A. Castagna, Antonio Scaravaggi","doi":"10.2139/ssrn.3090427","DOIUrl":"https://doi.org/10.2139/ssrn.3090427","url":null,"abstract":"This paper presents an application of stochastic risk factor approach to model the non-maturing deposits and it sketches a benchmark framework to assess the related expected profitability and the liquidity and duration risks of a bank compared with the rest of the economic system it works within. More specifically, we calibrate the model to system data for sight deposits of the Italian banking industry, available from the public statistical data base of Banca d'Italia, spanning over a long period of time that includes the Euro Crisis. The approach is applied to both retail and corporate customers, and it considers their different behaviour based on the size of their deposit. It allows for i) an integrated modelling of the market interest rates, creditworthiness of the bank and evolution of the deposits' volume; ii) stochastic risk factors driving deposits' rates and volume; iii) unified and consistent measurement of the interest rate risk and the liquidity; iv) negative interest rates, both at inception and in the future; v) the evaluation of optionalities such as the zero floor on the deposits rates; vi) stress testing for ALM purposes.","PeriodicalId":112822,"journal":{"name":"ERN: Interest Rate Forecasts (Topic)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130355428","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Based on high-frequency data for Norway and Sweden, we investigate to what extent explicit forward guidance from monetary policy makers, by means of publishing the path of expected future policy rates, affects the market yield curve. We summarise movements in the yield curve by two latent factors (the 'target factor' and 'market path factor'), which capture market participants' assessment of all relevant monetary policy communication made available on announcement days. We then show that information contained in the published interest rate path has a signi cant effect on the market path, and can explain up to 47% of the market path factor. Hence, we conclude that 'explicit' forward guidance in the form of publishing the interest rate path succeeds in moving markets in the desired direction. Furthermore, our results show that central bank and market revisions of interest rate expectations are strongly correlated. This suggests that market participants to a large extent understand the monetary policy reaction pattern.
{"title":"Forward Guidance Through Interest Rate Projections: Does It Work?","authors":"Leif Brubakk, Saskia ter Ellen, Hong Xu","doi":"10.2139/ssrn.2955662","DOIUrl":"https://doi.org/10.2139/ssrn.2955662","url":null,"abstract":"Based on high-frequency data for Norway and Sweden, we investigate to what extent explicit forward guidance from monetary policy makers, by means of publishing the path of expected future policy rates, affects the market yield curve. We summarise movements in the yield curve by two latent factors (the 'target factor' and 'market path factor'), which capture market participants' assessment of all relevant monetary policy communication made available on announcement days. We then show that information contained in the published interest rate path has a signi cant effect on the market path, and can explain up to 47% of the market path factor. Hence, we conclude that 'explicit' forward guidance in the form of publishing the interest rate path succeeds in moving markets in the desired direction. Furthermore, our results show that central bank and market revisions of interest rate expectations are strongly correlated. This suggests that market participants to a large extent understand the monetary policy reaction pattern.","PeriodicalId":112822,"journal":{"name":"ERN: Interest Rate Forecasts (Topic)","volume":"46 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-04-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128116318","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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