Results 11 to 20 of about 10,568,970 (294)
SSRN Electronic Journal, 2020 Quantile factor models (QFM) represent a new class of factor models for high‐dimensional panel data. Unlike approximate factor models (AFM), which only extract mean factors, QFM also allow unobserved factors to shift other relevant parts of the distributions of observables.
Chen, Liang +2 more
openaire +4 more sources
Dynamic Hierarchical Factor Models [PDF]
SSRN Electronic Journal, 2011 AbstractThis paper uses multilevel factor models to characterize within- and between-block variations as well as idiosyncratic noise in large dynamic panels. Block-level shocks are distinguished from genuinely common shocks, and the estimated block-level factors are easy to interpret. The framework achieves dimension reduction and yet explicitly allows
Emanuel Moench +2 more
openaire +4 more sources
Generalized infinite factorization models [PDF]
Biometrika, 2022 SummaryFactorization models express a statistical object of interest in terms of a collection of simpler objects. For example, a matrix or tensor can be expressed as a sum of rank-one components. In practice, however, it can be challenging to infer the number of components and the relative impact of the different components.
Schiavon, L, Canale, A, Dunson, D B
openaire +5 more sources
Учёт. Анализ. Аудит, 2018 The method of private investigations is probably the most appropriate basis for the implementation of independent external control of commercial enterprises.
A. E. Krioni
doaj +1 more source
Cryptoasset factor models [PDF]
Algorithmic Finance, 2018 We propose factor models for the cross-section of daily cryptoasset returns and provide source code for data downloads, computing risk factors and backtesting them out-of-sample. In “cryptoassets” we include all cryptocurrencies and a host of various other digital assets (coins and tokens) for which exchange market data is available.
openaire +2 more sources
Single-Cell Differential Network Analysis with Sparse Bayesian Factor Models
Frontiers in Genetics, 2022 Differential network analysis plays an important role in learning how gene interactions change under different biological conditions, and the high resolution of single-cell RNA (scRNA-seq) sequencing provides new opportunities to explore these changing ...
Michael Sekula +2 more
doaj +1 more source
Risk-sensitive investment in a finite-factor model [PDF]
, 2016 A new jump diffusion regime-switching model is introduced, which allows for linking jumps in asset prices with regime changes. We prove the existence and uniqueness of the solution to the risk-sensitive asset management criterion maximisation problem in ...
Andruszkiewicz, Grzegorz +2 more
core +2 more sources
Hierarchical confirmatory factor analysis of the flow state scale in exercise [PDF]
, 2000 In this study, we examined the factor structure and internal consistency of the Flow State Scale using responses of exercise participants.This self-report questionnaire consists of nine subscales designed to assess flow in sport and physical activity. It
Karageorghis, CI +2 more
core +3 more sources
Factor‐augmented Error Correction Models* [PDF]
, 2009 This paper brings together several important strands of the econometrics literature: errorcorrection, cointegration and dynamic factor models. It introduces the Factor-augmented Error Correction Model (FECM), where the factors estimated from a large set of variables in levels are jointly modelled with a few key economic variables of interest.
MARCELLINO, MASSIMILIANO, A. Banerjee
openaire +6 more sources
Comparison of Different Methods of Predicting Iran\'s Economic Growth with an Emphasis on Dynamic Model Selection and Dynamic Model Averaging [PDF]
پژوهشهای اقتصادی, 2020 In recent decades, due to the importance of future values of macroeconomic variables, a range of predicting methods and models has been studied and evaluated.
Teymour Mohammadi +3 more
doaj