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Do U.S. economic conditions at the state level predict the realized volatility of oil-price returns? A quantile machine-learning approach
Because the U.S. is a major player in the international oil market, it is interesting to study whether aggregate and state-level economic conditions...
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Forecasting VaR and ES by using deep quantile regression, GANs-based scenario generation, and heterogeneous market hypothesis
Value at risk (VaR) and expected shortfall (ES) have emerged as standard measures for detecting the market risk of financial assets and play...
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Penalized Averaging of Quantile Forecasts from GARCH Models with Many Exogenous Predictors
This study explores the multi-step ahead forecasting performance of a so-called hybrid conditional quantile method, which combines relevant...
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Market Resilience Unveiled: Insights from Quantile Time Frequency Connectedness into Emerging Countries Stock Indices
This study provides an in-depth analysis of the dynamic connectedness among BRICS-plus stock indices, focusing on three distinct periods:...
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What Really Drives Economic Growth in Sub-Saharan Africa? Evidence from the Lasso Regularization and Inferential Techniques
The question of what really drives economic growth in sub-Saharan Africa (SSA) has been debated for many decades now. However, there is still a lack...
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Modelling systemic risk using neural network quantile regression
We propose a novel approach to calibrate the conditional value-at-risk (CoVaR) of financial institutions based on neural network quantile regression....
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Inferring Causal Interactions in Financial Markets Using Conditional Granger Causality Based on Quantile Regression
Granger causality analysis emerges as a typical method for inferring causal interactions in economics variables. Yet the traditional pairwise...
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Gender wage inequality: new evidence from penalized expectile regression
The Machado-Mata decomposition building on quantile regression has been extensively analyzed in the literature focusing on gender wage inequality. In...
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Variable selection with group structure: exiting employment at retirement age—a competing risks quantile regression analysis
We consider the exit routes of older employees out of employment around retirement age. Our administrative data cover weekly information about the...
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Allometric evolution between economic growth and carbon emissions and its driving factors in the Yangtze River Delta region
Balancing economic growth and carbon emissions reduction is crucial for achieving integrated development in the Yangtze River Delta (YRD) region and...
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Penalised Quantile Regression Analysis of the Land Price in Japan by Using GIS Data
Land price analysis remains one of the active research fields where new methods, in order to quantify the effect of economic and noneconomic...
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Labor market tightness and individual wage growth: evidence from Germany
It is often stated that certain occupations in Germany, because of “ Demographic Change “, are dwindling, implying a labor shortage. We investigate...
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Safe Havens, Machine Learning, and the Sources of Geopolitical Risk: A Forecasting Analysis Using Over a Century of Data
We use monthly data covering a century-long sample period (1915–2021) to study whether geopolitical risk helps to forecast subsequent gold...
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Local Walsh-average-based Estimation and Variable Selection for Spatial Single-index Autoregressive Models
This paper is concerned with spatial single-index autoregressive model (SSIM), where the spatial lag effect enters the model linearly and the...
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Robust Identification of Gene-Environment Interactions Under High-Dimensional Accelerated Failure Time Models
For complex diseases, beyond the main effects of genetic (G) and environmental (E) factors, gene-environment (G-E) interactions also play an...
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Housing, imputed rent, and household welfare
Housing is the most important durable good consumed by households. This paper assesses the distributional effects of including the value of the flow...
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Explaining Exchange Rate Forecasts with Macroeconomic Fundamentals Using Interpretive Machine Learning
The complexity and ambiguity of financial and economic systems, along with frequent changes in the economic environment, have made it difficult to...
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Machine Learning Based Quantitative Pricing for US Airbnb Renting Program
In this paper, price analysis and prediction are carried out for shared homes in the Boston area on Airbnb, and price performance is tested through...