A random walk approach to predicting US 30-year home mortgage rates

Baghestani, Hamid

doi:10.1016/j.jhe.2008.06.001

Cited by 3 publications

(2 citation statements)

References 16 publications

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“…4. For instance, in line with Reichenstein (2006), Baghestani (2008a) shows that the random walk forecasts of the US 30-year mortgage rate for 1987-2006 are rational. Baghestani (2009a) reaches a similar conclusion for the random walk forecasts of the dollar/euro for 1999-2007 and the dollar/pound for 1971-2007.…”

Section: Discussionmentioning

confidence: 84%

Long-term interest rate predictability: Exploring the usefulness of survey forecasts of growth and inflation

Baghestani

2019

Cogent Economics & Finance

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This study focuses on the consensus forecasts from the Survey of Professional Forecasters (SPF) for 1993-2017. These include the SPF forecasts of US 10-year Treasury rate (TBR), Moody's Aaa corporate bond rate (Aaa), CPI inflation, and real GDP growth. We show that both SPF and random walk forecasts of TBR and Aaa generally fail to be orthogonal to changes in SPF inflation (but not growth) forecasts. Such findings point to the potential usefulness of SPF inflation forecasts in improving the accuracy of SPF and random walk forecasts of TBR and Aaa. Further results indicate that changes in SPF inflation forecasts accurately predict directional change in both TBR and Aaa at longer forecast horizons for 2008-2017 (but not for 1993-2007). These latter results raise the question of whether long-term interest rates have become easier to predict, which deserves subsequent research.

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Section: Discussionmentioning

confidence: 84%

Long-term interest rate predictability: Exploring the usefulness of survey forecasts of growth and inflation

Baghestani

2019

Cogent Economics & Finance

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“…Research indicates that, for many economic and financial variables, a random walk is not necessarily a naïve forecast (Diebold and Lopez, 1996). This is especially true for exchange rates (Baghestani, 2009; Rossi, 2013), long‐term interest rates (Pesando, 1979; Reichenstein, 2006; Baghestani, 2008a) and stock prices (Fama, 1995). Existing evidence indicates that it is difficult for both model‐ and survey‐based forecasts of such indicators to outperform a simple random walk forecast (Meese and Rogoff, 1983; Frankel and Froot, 1987; Mitchell and Pearce, 2007; Baghestani, 2008b).…”

Section: Introductionmentioning

confidence: 99%

Gasoline price predictability: insights from consumer vehicle‐buying assessments

Baghestani

2021

OPEC Energy Review

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This study employs the random walk forecasts of US retail gasoline prices for 2001–2020 in order to investigate the potential usefulness of consumer vehicle‐buying assessments for predicting gasoline prices. We show that the random walk forecasts are free of systematic bias and imply symmetric loss, but they do not fully contain the information on consumer vehicle‐buying assessments. For instance, the random walk forecast errors fail to be orthogonal to the difference of opinion of consumers about whether the next 12 months or so will be a good time or a bad time to buy a new vehicle, and to the difference of opinion of consumers about vehicle prices (but not interest rates). In addition, the random walk forecast errors fail to be orthogonal to the change in consumer opinion about gasoline prices, fuel efficiency and poor selections (quality). Such findings remain unchanged when we use the ‘weakly’ rational forecasts of gasoline prices instead of the random walk benchmark. Put together, our results provide new insights into the potential usefulness of consumer vehicle‐buying assessments for predicting gasoline prices. We recommend forecasters pay special attention to such assessments when forecasting retail gasoline prices, since they can potentially help produce forecasts that are superior to both the random walk and ‘weakly’ rational forecasts.

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Do US consumer survey data help beat the random walk in forecasting mortgage rates?

Baghestani

2017

Cogent Economics & Finance

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A random walk approach to predicting US 30-year home mortgage rates

Cited by 3 publications

References 16 publications

Long-term interest rate predictability: Exploring the usefulness of survey forecasts of growth and inflation

Long-term interest rate predictability: Exploring the usefulness of survey forecasts of growth and inflation

Gasoline price predictability: insights from consumer vehicle‐buying assessments

Do US consumer survey data help beat the random walk in forecasting mortgage rates?

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