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The Financial Risk Meter (FRM) is an established mechanism that, based on conditional Value at Risk (VaR) ideas, yields insight into the dynamics of network risk. Originally, the FRM has been composed via Lasso based quantile regression, but we here extend it by incorporating the idea of...
Persistent link: https://www.econbiz.de/10013235490
This paper considers smooth principle component analysis for high dimensional data with very large dimensional observations p and moderate number of individuals N. Our setting is similar to traditional PCA, but we assume the factors are smooth and design a new approach to estimate them. By...
Persistent link: https://www.econbiz.de/10011714498
The Financial Risk Meter (FRM) is an established mechanism that, based on conditional Value at Risk (VaR) ideas, yields insight into the dynamics of network risk. Originally, the FRM has been composed via Lasso based quantile regression, but we here extend it by incorporating the idea of...
Persistent link: https://www.econbiz.de/10012500095
K-means clustering is one of the most widely-used partitioning algorithm in cluster analysis due to its simplicity and computational efficiency, but it may not provide ideal clustering results when applying to data with non-spherically shaped clusters. By considering the asymmetrically weighted...
Persistent link: https://www.econbiz.de/10012500154
This study proposes a novel nonparametric estimation approach to solving asset-pricing models. Our method is robust to misspecification errors and it inherits a closed-form solution that facilitates ease of implementation. By transforming the Euler equation, our estimate is fully identified, and...
Persistent link: https://www.econbiz.de/10012849548
This textbook emphasizes the applications of statistics and probability to finance. Students are assumed to have had a prior course in statistics, but no background in finance or economics. The basics of probability and statistics are reviewed and more advanced topics in statistics, such as...
Persistent link: https://www.econbiz.de/10001805902
This paper considers a fast and effective algorithm for conducting functional principle component analysis with multivariate factors. Compared with the univariate case, our approach could be more powerful in revealing spatial connections or extracting important features in images. To facilitate...
Persistent link: https://www.econbiz.de/10012941577
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