Results 111 to 120 of about 30,733 (250)
Journal of Economic Surveys, EarlyView.ABSTRACT There is an increased proportion of studies using quantile‐based regression methodology (QR) in economics. They offer a robust alternative to classical mean regressions, which can estimate non‐normal variables with distributional heterogeneity in the dependent variable.
Shajara Ul‐Durar +4 more
wiley +1 more source
Econometrics at the Extreme: From Quantile Regression to QFAVAR1
Journal of Economic Surveys, EarlyView.ABSTRACT This paper surveys quantile modelling from its theoretical origins to current advances. We organize the literature and present core econometric formulations and estimation methods for: (i) cross‐sectional quantile regression; (ii) quantile time series models and their time series properties; (iii) quantile vector autoregressions for ...
Stéphane Goutte +4 more
wiley +1 more source
Calorie and Nutrient Consumption as a Function of Income: A Cross-Country Analysis [PDF]
The relationship between calorie and nutrient (fat, protein, and carbohydrates) intake as a function of income is explored using data for 171 countries over two time periods 1990-1992 and 2003-2005. Three types of analysis are employed: i) nonparametric,
Balcombe, Kelvin +2 more
core +1 more source
Size, Returns, and Value: Do Private Equity Firms Allocate Capital According to Manager Skill?
The Journal of Finance, EarlyView.ABSTRACT Using a novel data set linking private equity (PE) deals to individual managers, we document evidence of manager skill in terms of generating net present value (NPV), a performance measure that captures both scale and returns. PE firms have strong economic incentives to raise larger funds and execute larger deals.
REINER BRAUN +3 more
wiley +1 more source
The Journal of Finance, EarlyView.ABSTRACT Using information in returns, we identify the stochastic process of consumption. We find that aggregate consumption reacts over multiple quarters to innovations spanned by financial markets. This persistent component accounts for over a quarter of consumption variation. These shocks command a large and significant risk premium, driving a large
SVETLANA BRYZGALOVA +2 more
wiley +1 more source
Pointwise adaptive estimation for robust and quantile regression
, 2009 A nonparametric procedure for robust regression estimation and for quantile regression is proposed which is completely data-driven and adapts locally to the regularity of the regression function. This is achieved by considering in each point M-estimators
Cuenod, Charles-Andre +2 more
core +1 more source
Journal of Time Series Analysis, EarlyView.ABSTRACT Expectile is a coherent and elicitable law‐invariant risk measure widely applied in risk management. Existing methods based on iteratively reweighted least squares (IWLS) are not computationally efficient for large‐scale sample sizes. To overcome the issue, we develop a direct nonparametric conditional expectile function estimator by inverting
Feipeng Zhang, Ping‐Shou Zhong
wiley +1 more source
Nauki o FinansachAim: This study examines how management reports affect stock liquidity and compares the responses of stocks with low, medium, and high liquidity. Methodology: Stocks were classified into three liquidity groups based on the median Amihud (ILLIQ) ratio ...
Tohid Zeinali, Jan Makary Fryczak
doaj +1 more source
Density‐Valued ARMA Models by Spline Mixtures
Journal of Time Series Analysis, EarlyView.ABSTRACT This paper proposes a novel framework for modeling time series of probability density functions by extending autoregressive moving average (ARMA) models to density‐valued data. The method is based on a transformation approach, wherein each density function on a compact domain [0,1]d$$ {\left[0,1\right]}^d $$ is approximated by a B‐spline ...
Yasumasa Matsuda, Rei Iwafuchi
wiley +1 more source
Pointwise adaptive estimation for quantile regression [PDF]
A nonparametric procedure for quantile regression, or more generally nonparametric M-estimation, is proposed which is completely data-driven and adapts locally to the regularity of the regression function.
Charles A. Cuenod +2 more
core