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Causal discovery of gene regulation with incomplete data

Foraita, Ronja; Friemel, Juliane; Günther, Kathrin; … - In: Journal of the Royal Statistical Society: Series A … 183 (2020) 4, pp. 1747-1775

Causal discovery algorithms aim to identify causal relations from observational data and have become a popular tool for analysing genetic regulatory systems. In this work, we applied causal discovery to obtain novel insights into the genetic regulation underlying head-and-neck squamous cell...

Persistent link: https://www.econbiz.de/10012428705

Lasso maximum likelihood estimation of parametric models with singular information matrices

Jin, Fei; Lee, Lung-Fei - In: Econometrics 6 (2018) 1, pp. 1-24

regular case. We propose to estimate such models by the adaptive lasso maximum likelihood and propose an information criterion …

Persistent link: https://www.econbiz.de/10011995209

Building news measures from textual data and an application to volatility forecasting

Caporin, Massimiliano; Poli, Francesco - In: Econometrics 5 (2017) 3, pp. 1-46

We retrieve news stories and earnings announcements of the S&P 100 constituents from two professional news providers, along with ten macroeconomic indicators. We also gather data from Google Trends about these firms' assets as an index of retail investors' attention. Thus, we create an extensive...

Persistent link: https://www.econbiz.de/10011995242

Two-step Lasso estimation of the spatial weights matrix

Ahrens, Achim; Bhattacharjee, Arnab - In: Econometrics 3 (2015) 1, pp. 128-155

sparsity of the spatial weights matrix. The proposed estimation methodology exploits the Lasso estimator and mimics two … larger than the number of observations. We derive convergence rates for the two-step Lasso estimator. Our Monte Carlo …

Persistent link: https://www.econbiz.de/10011755274

International Inflation Synchronization and Implications

Chon, Sora - In: KDI Journal of Economic Policy 42 (2020) 2, pp. 57-84

This study analyzes global inflation synchronization and derives policy implications for the Korean economy. Unlike previous studies that assume a single global inflation factor, this study investigates if inflation in Korea can be explained further by other global inflation factors. Our...

Persistent link: https://www.econbiz.de/10012298159

S&P 500 index price spillovers around the COVID-19 market meltdown

Lento, Camillo; Gradojevic, Nikola - In: Journal of Risk and Financial Management 14 (2021) 7, pp. 1-13

This paper explores price spillover effects around the COVID-19 pandemic market meltdown between the S&P 500 index, five other financial markets, and the VIX. Frequency domain causalities are estimated for the January-May 2020 time period on a high-frequency data set at five-minute intervals....

Persistent link: https://www.econbiz.de/10013201014

Dimension reduction via penalized GLMs for non-Gaussian response: Application to stock market volatility

Li, Tao; Desmond, Anthony F.; Stengos, Thanasēs - In: Journal of Risk and Financial Management 14 (2021) 12, pp. 1-26

Gaussian LASSO model and an IG GLM LASSO model as dimension reduction techniques and we attempted to identify some common … Box-Cox transformation Gaussian LASSO model, a three-phase iterative grid search Box-Cox transformation Gaussian LASSO … model, and both canonical link and optimal link IG GLM LASSO models. The latter two models assume an approximately IG …

Persistent link: https://www.econbiz.de/10013201266

The effect of index option trading on stock market volatility in China: An empirical investigation

Wu, Kai; Liu, Yi; Feng, Weiyang - In: Journal of Risk and Financial Management 15 (2022) 4, pp. 1-19

, including principal component analysis, GARCH-family model, and LASSO regression. The results of this paper suggest that the …

Persistent link: https://www.econbiz.de/10013201453

A statistical learning approach for stock selection in the Chinese stock market

Wu, Wenbo; Chen, Jiaqi; Xu, Liang; He, Qingyun; … - In: Financial Innovation 5 (2019) 1, pp. 1-18

Forecasting stock returns is extremely challenging in general, and this task becomes even more difficult given the turbulent nature of the Chinese stock market. We address the stock selection process as a statistical learning problem and build cross-sectional forecast models to select individual...

Persistent link: https://www.econbiz.de/10012602815

A principal component-guided sparse regression approach for the determination of bitcoin returns

Panagiōtidēs, Theodōros; Stengos, Thanasēs; … - In: Journal of Risk and Financial Management 13 (2020) 2, pp. 1-10

We examine the significance of fourty-one potential covariates of bitcoin returns for the period 2010-2018 (2872 daily observations). The recently introduced principal component-guided sparse regression is employed. We reveal that economic policy uncertainty and stock market volatility are among...

Persistent link: https://www.econbiz.de/10012611251