| 1. |
- Kiss, Tamás, 1988-, et al.
(författare)
-
Modelling the Relation between the US Real Economy and the Corporate Bond-Yield Spread in Bayesian VARs with non-Gaussian Disturbances
- 2021
-
Rapport (övrigt vetenskapligt/konstnärligt)abstract
- In this paper we analyze how skewness and heavy tails affect the estimated relationship between the real economy and the corporate bond-yield spread, a popular predictor of rea lactivity. We use quarterly US data to estimate Bayesian VAR models with stochastic volatility and various distributional assumptions regarding the disturbances. In-sample, we find that – after controlling for stochastic volatility – innovations in GDP growth can be well-described by a Gaussian distribution. In contrast, both the unemployment rate and the yield spread appear to benefit from being modelled using non-Gaussian innovations. When it comes to real-time forecasting performance, we find that the yield spread is an important predictor of GDP growth, and that accounting for stochastic volatility matters, mainly for density forecasts. Incremental improvements from non-Gaussian innovations are limited to forecasts of the unemployment rate. Our results suggest that stochastic volatility is of first order importance when modelling the relationship between yield spread and real variables; allowing for non-Gaussian innovations is less important.
|
|
| 2. |
|
|
| 3. |
- Kiss, Tamás, 1988-, et al.
(författare)
-
Predicting returns and dividend growth - The role of non-Gaussian innovations
- 2022
-
Ingår i: Finance Research Letters. - : Elsevier. - 1544-6123 .- 1544-6131. ; 46:Part A
-
Tidskriftsartikel (refereegranskat)abstract
- In this paper we assess whether flexible modelling of innovations impact the predictive performance of the dividend price ratio for returns and dividend growth. Using Bayesian vector autoregressions we allow for stochastic volatility, heavy tails and skewness in the innovations. Our results suggest that point forecasts are barely affected by these features, suggesting that workhorse models on predictability are sufficient. For density forecasts, however, we find that stochastic volatility substantially improves the forecasting performance.
|
|
| 4. |
- Hjalmarsson, Erik, 1975, et al.
(författare)
-
Dividend Growth Does Not Help Predict Returns Compared To Likelihood-Based Tests: An Anatomy of the Dog
- 2021
-
Ingår i: Critical Finance Review. - : Now Publishers. - 2164-5744 .- 2164-5760. ; 10:3, s. 445-464
-
Tidskriftsartikel (refereegranskat)abstract
- The dividend-growth based test of return predictability, proposed by Cochrane (2008), is similar to a likelihood-based test of the standard return-predictability model, treating the autoregressive (AR) parameter of the dividend-price ratio as known. In comparison to standard OLS-based inference, both tests can achieve power gains by using restrictions or prior information on the value of the AR parameter. When compared to the likelihood-based test, there are no power advantages for the dividend-growth based test. In common implementations, with the AR parameter set equal to the corresponding OLS estimate, Cochrane's test suffers from severe size distortions.
|
|
| 5. |
- Hjalmarsson, Erik, 1975, et al.
(författare)
-
Long-run predictability tests are even worse than you thought
- 2022
-
Ingår i: Journal of Applied Econometrics. - : Wiley. - 0883-7252 .- 1099-1255. ; 37:7, s. 1334-1355
-
Tidskriftsartikel (refereegranskat)abstract
- We derive asymptotic results for the long-horizon ordinary least squares (OLS) estimator and corresponding t$$ t $$-statistic for stationary autoregressive predictors. The t$$ t $$-statistic-formed using the correct asymptotic variance-together with standard-normal critical values result in a correctly-sized test for exogenous predictors. For endogenous predictors, the test is size distorted regardless of the persistence in the predictor and adjusted critical values are necessary. The endogeneity problem stems from the long-run estimation and is distinct from the ordinary persistence-dependent "Stambaugh" bias. The bias for fully stationary predictors appears not to have been previously noted and adds further difficulty to inference in long-run predictive regressions.
|
|
| 6. |
|
|
| 7. |
- Javed, Farrukh, 1984-, et al.
(författare)
-
Performance analysis of nowcasting of GDP growth when allowing for conditional heteroscedasticity and non-Gaussianity
- 2022
-
Ingår i: Applied Economics. - : Routledge. - 0003-6846 .- 1466-4283. ; 54:58, s. 6669-6686
-
Tidskriftsartikel (refereegranskat)abstract
- The nowcasting performance of autoregressive models for GDP growth are analysed in a setting where the error term is allowed to be characterized both by conditional heteroscedasticity and non-Gaussianity. Standard, publicly available, quarterly data on GDP growth from 1979 to 2019 for six countries are employed: Australia, Canada, France, Japan, the United Kingdom and the United States. In-sample analysis suggests that when homoscedasticity is assumed, support is provided for non-Gaussian error terms; the estimated degrees of freedom of the t-distribution lie between two and seven for all countries. However, allowing for both conditional heteroscedasticity and t-distributed innovations, results indicate that conditional heteroscedasticity captures the fat-tailed behaviour of the data to a large extent. Results from out-of-sample analysis show that point nowcasts are hardly affected by taking conditional heteroscedasticity and/or non-Gaussianity into account. For the density nowcasts, it is found that accounting for conditional heteroscedasticity leads to improvements for Australia, Canada, Japan, the United Kingdom and the United States; allowing for non-Gaussianity seems less important though. This result is robust to which measure is used for assessing density nowcasting performance.
|
|
| 8. |
- Karlsson, Sune, Professor, 1960-, et al.
(författare)
-
Svensk ekonomi är inte normal (och oberoende) – fakta om makroekonomiska variablers tidsserieegenskaper
- 2023
-
Ingår i: Ekonomisk Debatt. - Stockholm : Nationalekonomiska föreningen. - 0345-2646. ; 51:1, s. 42-54
-
Tidskriftsartikel (refereegranskat)abstract
- Att de störningar som drabbar makroekonomin är normalfördelade och har konstant varians är två antaganden som allt oftare har övergivits i den inter-nationella forskningslitteraturen under de senaste två decennierna. I denna artikel undersöks om detta är relevant för ett antal nyckelvariabler i svensk mak-roekonomi. Sammantaget tyder våra resultat på att forskare och policyekonomer som modellerar svenska makroekonomiska variabler – t ex i syfte att beskriva riskbilden kring dem – har påtaglig anledning att åtminstone överge antagandet om konstant störningsvarians. Ett konkret problem som annars kan uppstå är att prognososäkerhet överskattas i lugna tider och underskattas i turbulenta tider.
|
|
| 9. |
- Kiss, Tamás, 1988-, et al.
(författare)
-
Corona, Crisis and Conditional Heteroscedasticity
- 2021
-
Ingår i: Applied Economics Letters. - : Routledge. - 1350-4851 .- 1466-4291. ; 28:9, s. 755-759
-
Tidskriftsartikel (refereegranskat)abstract
- In this paper, we illustrate the macroeconomic risk associated with the early stage of the corona- virus outbreak. Using monthly data ranging from July 1991 to March 2020 on a recently developed coincidence indicator of global output growth, we estimate an autoregressive model with GARCH effects and non-Gaussian disturbances. Our results indicate that i) accounting for conditional heteroscedasticity is important and ii) risk, measured as the volatility of the shocks to the process, is at a very high level – largely on par with that experienced around the financial crisis of 2008–2009.
|
|
| 10. |
- Kiss, Tamás, 1988-, et al.
(författare)
-
Fat tails in leading indicators
- 2020
-
Ingår i: Economics Letters. - : Elsevier. - 0165-1765 .- 1873-7374. ; 193
-
Tidskriftsartikel (refereegranskat)abstract
- We analyse four leading indicators in the US economy using autoregressive models and find strong evidence in favour of GARCH effects. All series remain fat-tailed after controlling for GARCH effects, suggesting that non-Gaussianity of the innovations should be accounted for.
|
|
