Macroeconomic and financial leading indicators of economic activity and sovereign bond yields: a practitioners' perspective

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dc.contributor.advisor Ryan, Geraldine en
dc.contributor.advisor Kavanagh, Ella en
dc.contributor.author Brady, Austin T.
dc.date.accessioned 2021-09-27T14:58:20Z
dc.date.available 2021-09-27T14:58:20Z
dc.date.issued 2021-09-01
dc.date.submitted 2021-09-01
dc.identifier.citation Brady, A. T. 2021 Macroeconomic and financial leading indicators of economic activity and sovereign bond yields: a practitioners' perspective. PhD Thesis, University College Cork. en
dc.identifier.endpage 737 en
dc.identifier.uri http://hdl.handle.net/10468/12019
dc.description.abstract This thesis examines how effective practitioners are at selecting leading indicators of economic activity and sovereign bond yields. The research is conducted prior to and in the aftermath of the Global Financial Crisis (GFC) in three countries: Germany, the United Kingdom (UK) and the United States (US). Empirical research such as Stock and Watson (1989, 2002a, 2002b, 2004, 2007), Artis et al (2005), Schumacher (2007), Ludvigson and Ng (2007, 2009) forecast economic activity and sovereign bond yields in the three countries. The aforementioned research has the following features: (i) use large datasets; (ii) use similar indicators across countries and time periods; (iii) have datasets that cover periods prior to the GFC and (iv) datasets that are not pre-screened for leading properties. This thesis focuses on more refined datasets, selected by two sets of practitioners: economist practitioners and fixed income practitioners. We address any potential changes impacting economic activity and sovereign bond yields by creating datasets for the period in the aftermath of the GFC. In addition, the datasets selected by economist and fixed income practitioners are pre-screened for leading properties, with only leading indicators used in the analysis. To examine the effectiveness of practitioners, this thesis develops a unique primary dataset for the three countries, based on the input of financial market practitioners, employed professionally by financial institutions. Face-to-face structured interviews with a total of 35 practitioners working in the International Financial Services Centre (IFSC) located in Dublin, Ireland, shows that whilst both sets of practitioners have access to large databases, they use smaller refined datasets when forecasting, compared to those previously examined in the literature. Practitioners operate within high-paced environments where fast decision making is key. Two types of practitioners are identified to create two distinct datasets for economic activity and sovereign bond yields: economist practitioners and fixed income practitioners. Economist practitioners use a variety of information to make forecasts of economic activity and fixed income practitioners use the latter and market-specific information to forecast sovereign bond yields. Both types of practitioners operate in real time, high-paced environments, often on behalf of clients. Economist practitioner and fixed income practitioner datasets are examined for leading properties in three time periods: the period prior to the GFC, the period during the GFC and the aftermath of the GFC. The objective is to determine whether both sets of practitioners are successful at selecting leading indicators; whether practitioners react to changes in the business cycle when selecting additional leading indicators; whether specific indicators lead for certain periods and whether commonalities exist among leading properties selected in the three countries under examination. Our findings find evidence of the following: economist and fixed income practitioners are better at selecting leading indicators in periods of more certainty; both sets of practitioners react to changes in the business cycle when selecting leading indicators; indicators lead for specific periods; there is a small amount of indicators that do not lead economic activity and sovereign bond yields and there is no common set of indicators that lead either economic activity or sovereign bond yields across the three countries. Given that we know economist and fixed income practitioners select leading indicators, we need to determine how accurate they are when forecasting economic activity and sovereign bond yields. In order to determine this, we must create leading composite indices for each period. We create a composite index based on the leading indicators selected by both economist practitioners and fixed income practitioners, and we test the out-of-sample forecasting capacity of this index. For each country, a total of two composites are created for the 2005-2008 period, two (one composite is created for the fixed income practitioner dataset) for the 2008-2013 and one composite for the 2013-2018 period. Our results are compared to a series of benchmarks. The benchmarks used are the Autoregressive (AR) and Random Walk (RW) models. However, we include two additional composites for economic activity (the OECD and the Conference Board (CB)) and one additional index for sovereign bond yields (the Barclays bond index). The results show that the economist and fixed income practitioner composites, for Germany and the UK in particular, have equal predictive ability relative to the Barclays benchmarks in the pre-Lehman and recovery periods. The results from this thesis show that practitioners add considerable value in their indicator selection. The results from this thesis have a number of important implications going forward for practitioners. The first is that the datasets selected by both economist and fixed income practitioners should statistically examine the leading properties of their datasets, prior to forecasting economic activity and sovereign bond yields. The results show that practitioners should periodically evaluate whether the indicators practitioners use are leading instead of making the assumption that they lead. Secondly, given the robustness of the static composites constructed using PCA, practitioners should use the steps outlined by the OECD (2008) to construct leading indicator composites. Thirdly, practitioners may improve economic activity and sovereign bond yield forecasts by using the static PCA approach to construct composites. en
dc.format.mimetype application/pdf en
dc.language.iso en en
dc.publisher University College Cork en
dc.rights © 2021, Austin T. Brady. en
dc.rights.uri https://creativecommons.org/licenses/by-nc/4.0/ en
dc.subject Practitioner en
dc.subject Out-of-sample forecasting en
dc.subject Leading indicator composites en
dc.subject Principal components en
dc.subject Practitioner surveys en
dc.title Macroeconomic and financial leading indicators of economic activity and sovereign bond yields: a practitioners' perspective en
dc.type Doctoral thesis en
dc.type.qualificationlevel Doctoral en
dc.type.qualificationname PhD - Doctor of Philosophy en
dc.internal.availability Full text not available en
dc.description.version Accepted Version en
dc.description.status Not peer reviewed en
dc.internal.school Economics en
dc.internal.conferring Autumn 2021 en
dc.availability.bitstream controlled


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