Examining Simple Joint Macroeconomic and Term-Structure Models: A Practitioner's Perspective

Bolder, David Jamieson; Liu, Shudan

doi:10.2139/ssrn.1082831

Cited by 6 publications

(4 citation statements)

References 51 publications

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“…For the full sample, the correlation with the term spread is −0.39 while the correlations with the implied volatilities (median value across cap rates) are negative but close to zero. Around days with monetary policy decisions, the correlations with the term spread and the 5-year implied volatility are Bolder and LIU (2007) argue that imposing no-arbitrage restrictions might hurt the empirical performance (for instance, in forecasting) compared to more agnostic models like Diebold and Li (2003). much more negative (−0.71 and −0.42, respectively).…”

Section: Datamentioning

confidence: 99%

Reaction of Swiss term premia to monetary policy surprises

Söderlind

2010

Swiss J Economics Statistics

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Summary An affine yield curve model is estimated on daily Swiss data 2002–2009. The market price of risk is modelled in terms of proxies for uncertainty, which are estimated from interest rate options. The estimated model generates innovations in the 3-month rate that are similar to external evidence of monetary policy surprises — as well as term premia that are consistent with survey data. The results indicate that a surprise increase in the policy rate gives a reasonably sized decrease (−0.25%) in term premia for longer maturities.

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Section: Datamentioning

confidence: 99%

Reaction of Swiss term premia to monetary policy surprises

Söderlind

2010

Swiss J Economics Statistics

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“…The models used in this work are empirically motivated from previous work in this area. In particular, Bolder (2006) and Bolder and Liu (2007) investigate a number of models, including affine (see, for example, Dai and Singleton (2000), Duffie, Filipovic and Schachermayer (2003), Ang and Piazzesi (2003)), in which pure-discount bond prices are exponential-affine functions 1 of the state variables, and empirical-based (such as those in Bolder and Gusba (2002) and the extension of the Nelson-Siegel model by Diebold and Li (2003)). The results indicate that forecasts of affine termstructure models are inferior to those of empirically-motivated models.…”

Section: Modelsmentioning

confidence: 99%

“…We augment the factors with three macroeconomic variables-the output gap x t , consumer price inflation π t , and the overnight rate r t -and collect these to form a time series. This procedure and the estimation of modelspecific parameters for the NS, ES and FS models are given in Bolder and Liu (2007) and the references therein. In the SS model, we simply regress the vector of zero-coupon rates Z t on the first three principal components, extracted from the observed term structure up to time t, and the three contemporaneous macro variables.…”

Section: Modelsmentioning

confidence: 99%

Combining Canadian Interest Rate Forecasts

Bolder¹,

Romanyuk²

2010

Interest Rate Models, Asset Allocation and Quantitative Techniques for Central Banks and Sovereign Wealth Funds

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Model risk is a constant danger for financial economists using interest-rate forecasts for the purposes of monetary policy analysis, portfolio allocations, or risk-management decisions. Use of multiple models does not necessarily solve the problem as it greatly increases the work required and still leaves the question "which model forecast should one use?" Simply put, structural shifts or regime changes (not to mention possible model misspecifications) make it difficult for any single model to capture all trends in the data and to dominate all alternative approaches. To address this issue, we examine various techniques for combining or averaging alternative models in the context of forecasting the Canadian term structure of interest rates using both yield and macroeconomic data. Following Bolder and Liu (2007), we study alternative implementations of four empirical term structure models: this includes the Diebold and Li (2003) approach and three associated generalizations. The analysis is performed using more than 400 months of data ranging from January 1973 to July 2007. We examine a number of model-averaging schemes in both frequentist and Bayesian settings, both following the literature in this field (such as de Pooter, Ravazzolo and van Dijk (2007)) in addition to introducing some new combination approaches. The forecasts from individual models and combination schemes are evaluated in a number of ways; preliminary results show that model averaging generally assists in mitigating model risk, and that simple combination schemes tend to outperform their more complex counterparts. Such findings carry significant implications for central-banking analysis: a unified approach towards accounting for model uncertainty can lead to improved forecasts and, consequently, better decisions.

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“…However,Bolder and Liu (2007) argue that imposing no-arbitrage restrictions might hurt the empirical performance (for instance, in forecasting) compared to more agnostic models likeDiebold and Li (2003).…”

mentioning

confidence: 99%

Reaction of Swiss Term Premia to Monetary Policy Surprises

Söderlind

2009

SSRN Journal

View full text Add to dashboard Cite

An affine yield curve model is estimated on daily Swiss data 2002-2009. The market price of risk is modelled in terms of proxies for uncertainty, which are estimated from interest rate options. The estimated model generates innovations in the 3-month rate that are similar to external evidence of monetary policy surprises-as well as term premia that are consistent with survey data. The results indicate that a surprise increase in the policy rate gives a reasonably sized decrease (-0.25%) in term premia for longer maturities.

show abstract

Examining Simple Joint Macroeconomic and Term-Structure Models: A Practitioner's Perspective

Cited by 6 publications

References 51 publications

Reaction of Swiss term premia to monetary policy surprises

Reaction of Swiss term premia to monetary policy surprises

Combining Canadian Interest Rate Forecasts

Reaction of Swiss Term Premia to Monetary Policy Surprises

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