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Does the Current State of the Business Cycle matter for Real-Time Forecasting? A Mixed-Frequency Threshold VAR approach.

Heinrich, Markus - 2020

Macroeconomic forecasting in recessions is not easy due to the inherent asymmetry of business cycle phases and the …-frequency setting. A real-time forecasting experiment highlights the advantage of including the threshold feature for the asymmetry as … well as the common stochastic volatility in mean in MF-VARs of different size for US GDP, inflation and unemployment. The …

Persistent link: https://www.econbiz.de/10012229214

Predicting the global minimum variance portfolio

Reh, Laura; Krüger, Fabian; Liesenfeld, Roman - 2020

We propose a novel dynamic approach to forecast the weights of the global minimum variance portfolio (GMVP). The GMVP weights are the population coefficients of a linear regression of a benchmark return on a vector of return differences. This representation enables us to derive a consistent loss...

Persistent link: https://www.econbiz.de/10012250683

COVID-19 outbreak and beyond: The information content of registered short-time workers for GDP now- and forecasting

Kaufmann, Sylvia - In: Swiss Journal of Economics and Statistics 156 (2020) 1, pp. 1-12

The number of short-time workers from January to April 2020 is used to now- and forecast quarterly GDP growth. We purge the monthly log level series from the systematic component to extract unexpected changes or shocks to log short-time workers. These monthly shocks are included in a univariate...

Persistent link: https://www.econbiz.de/10013205796

Employing Machine Learning Algorithms to build Trading Strategies with higher than Risk-Free Returns

Uzunlu, Baris Yalin; Hussain, Syed Muzammil - In: International Econometric Review (IER) 12 (2020) 2, pp. 112-138

This research aims at exploring whether simple trading strategies developed using state-ofthe-art Machine Learning (ML) algorithms can guarantee more than the risk-free rate of return or not. For this purpose, the direction of S&P 500 Index returns on every 6th day (SPYRETDIR6) and magnitude of...

Persistent link: https://www.econbiz.de/10012610982

Automatic time series modeling and forecasting: a replication case study of forecasting real GDP, the unemployment rate and the impact of leading economic indicators

Guerard, John Baynard; Thomakos, Dimitrios D.; Kyriazi, … - In: Cogent Economics & Finance 8 (2020) 1, pp. 1-20

We test and report on time series modelling and forecasting using several US. Leading economic indicators (LEI) as an … input to forecasting real US. GDP and the unemployment rate. These time series have been addressed before, but our results … unemployment rate series. We tested the forecasting ability of best univariate and best bivariate models over 60- and 120-period …

Persistent link: https://www.econbiz.de/10012657604

Covid-19 outbreak and beyond: The information content of registered short-time workers for GDP now- and forecasting

Kaufmann, Sylvia - 2020

The number of employees historically filed and registered from January to April 2020 for short-time compensation is used to obtain a nowcast for GDP growth in the first quarter and an outlook until the third quarter 2021. We purge the monthly log level series from the systematic component to...

Persistent link: https://www.econbiz.de/10012671248

Bivariate volatility modeling with high-frequency data

Matei, Marius; Rovira, Xari; Agell, Núria - In: Econometrics 7 (2019) 3, pp. 1-15

volatility information improves the day volatility estimation. The results indicate a forecasting improvement using bivariate …

Persistent link: https://www.econbiz.de/10012696256

Antecipação fiscal, não fundamentalidade e não causalidade no Brasil

Borelli, Luan; Vonbun, Christian; Góes, Geraldo Sandoval - 2021

So far, there are very few papers concerning the problems of non causality and non-fundamentalness in fiscal studies. This is even truer for Brazil. Non causality and non fundamentalness are econometric problems that are specially relevant in fiscal studies, as they are relate to fiscal...

Persistent link: https://www.econbiz.de/10012802817

Improving inference and forecasting in VAR models using cross-sectional information

Prüser, Jan; Blagov, Boris - 2022

We propose a prior for VAR models that exploits the panel structure of macroeconomic time series while also providing shrinkage towards zero to address overfitting concerns. The prior is flexible as it detects shared dynamics of individual variables across endogenously determined groups of...

Persistent link: https://www.econbiz.de/10013366009

New forecasting methods for an old problem: Predicting 147 years of systemic financial crises

du Plessis, Emile; Fritsche, Ulrich - 2022

forecasting solutions. In this context, the paper develops new forecasting methods for an old problem by employing 13 machine … important variable. GDP per capita and consumer inflation have increased in prominence whereas debt-to-GDP, stock market and …

Persistent link: https://www.econbiz.de/10013368847