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Large Time-Varying Parameter Vars : A Non-Parametric Approach

Kapetanios, George - 2017

In this paper we introduce a non-parametric estimation method for a large Vector Autoregression (VAR) with time-varying parameters. The estimators and their asymptotic distributions are available in closed form. This makes the method computationally efficient and capable of handling information...

Persistent link: https://www.econbiz.de/10012949026

Common cycles in volatility and cross section of stock returns

Barunik, Jozef; Kraicova, Lucie - 2017

We study the relationship between conditional quantiles of returns and the long-, medium- and short-term volatility in … the volatility time series provides us with new insights into the pricing of risk and increases the accuracy of our …

Persistent link: https://www.econbiz.de/10011722181

Macroeconomic forecasting in times of crises

Guerrón-Quintana, Pablo A.; Zhong, Molin - 2017

We propose a parsimonious semiparametric method for macroeconomic forecasting during episodes of sudden changes. Based on the notion of clustering and similarity, we partition the time series into blocks, search for the closest blocks to the most recent block of observations, and with the...

Persistent link: https://www.econbiz.de/10011708260

A probit model for the state of the Greek GDP growth

Degiannakis, Stavros - In: International Journal of Financial Studies : open … 3 (2015) 3, pp. 381-392

evaluates the performance of the models. The probit model with the industrial production index and the realized volatility as …

Persistent link: https://www.econbiz.de/10011312197

A Survey of Alternative Measures of Macroeconomic Uncertainty : Which Measures Forecast Real Variables and Explain Fluctuations in Asset Volatilities Better?

David, Alexander; Veronesi, Pietro - 2022

creation, as well as in explaining fluctuations in stock-market and Treasury bond market volatility. In general, we find that …'s stock market volatility performing the best on several (but not all) dimensions. Their learning-based model's volatility … volatile than the David and Veronesi (2013) stock market volatility …

Persistent link: https://www.econbiz.de/10013294567

Nonparametric Impulse Response Analysis in Changing Macroeconomic Conditions

Nyberg, Henri; Lanne, Markku - 2021

We introduce a simple nonparametric approach to compute impulse response functions. We first search for clusters of recurrent patterns of observations resembling two sets of given initial conditions, one of which contains the impact effect of the structural shock of interest. Then, to trace out...

Persistent link: https://www.econbiz.de/10013216683

Specification tests for non-Gaussian maximum likelihood estimators

Fiorentini, Gabriele; Sentana, Enrique - In: Quantitative economics : QE ; journal of the … 12 (2021) 3, pp. 683-742

We propose generalized DWH specification tests which simultaneously compare three or more likelihood-based estimators in multivariate conditionally heteroskedastic dynamic regression models. Our tests are useful for Garch models and in many empirically relevant macro and finance applications...

Persistent link: https://www.econbiz.de/10012598494

Predicting US Recessions : A Dynamic Time Warping Exercise in Economics

Raihan, Tasneem - 2017

Dynamic Time Warping (DTW) is a widely used algorithm in speech recognition for measuring similarity between two time series. This non-parametric technique overcomes the problems associated with Pearson's correlation coefficient by allowing a non-linear mapping of one sequence to another...

Persistent link: https://www.econbiz.de/10012946331

Machine Learning for Recession Prediction and Dynamic Asset Allocation

James, Alex - 2019

We introduce a novel application of support vector machines (SVM), an important machine learning algorithm, to determine the beginning and end of recessions in real time. Nowcasting, forecasting a condition in the present time because the full information will not be available until later, is...

Persistent link: https://www.econbiz.de/10012894791

Kuntze, Visa; Nyberg, Henri; Rauhala, Samuel - 2022

We develop a flexible nonparametric similarity-based approach to predict the state of the business cycle in different interest rate environments. Our approach provides methodological advantages over parametric logit and probit models and new empirical perspectives on the usefulness of the term...

Persistent link: https://www.econbiz.de/10013404263