scholarly journals Evaluating Firm-Level Expected-Return Proxies: Implications for Estimating Treatment Effects

2020 ◽  
Author(s):  
Charles M C Lee ◽  
Eric C So ◽  
Charles C Y Wang
Keyword(s):  
Time Series ◽  
Measurement Error ◽  
Cross Section ◽  
Treatment Effects ◽  
Relative Performance ◽  
Expected Return ◽  
Firm Level ◽  
Ex Ante ◽  
The Cross ◽  
New Evidence

Abstract We introduce a parsimonious framework for choosing among alternative expected-return proxies (ERPs) when estimating treatment effects. By comparing ERPs’ measurement error variances in the cross-section and in the time series, we provide new evidence on the relative performance of firm-level ERPs nominated by recent studies. Generally, “implied-costs-of-capital” metrics perform best in the time series, whereas “characteristic-based” proxies perform best in the cross-section. Factor-based ERPs, even the latest renditions, perform poorly. We revisit four prior studies that use ex ante ERPs and illustrate how this framework can potentially alter either the sign or the magnitude of prior inferences.

The Determinants of Idiosyncratic Volatility

2017 ◽  
Vol 25 (4) ◽  
pp. 509-545
Author(s):  
Jaeuk Khil ◽  
Song Hee Kim ◽  
Eun Jung Lee
Keyword(s):  
Growth Rate ◽  
Time Series ◽  
Cross Section ◽  
Growth Rates ◽  
Idiosyncratic Volatility ◽  
Return Volatility ◽  
Firm Level ◽  
Cross Sectional ◽  
Asset Growth ◽  
The Cross

We investigate the cross-sectional and time-series determinants of idiosyncratic volatility in the Korean market. In particular, we focus on the empirical relation between firms’ asset growth rate and idiosyncratic stock return volatility. We find that, in the cross-section, companies with high idiosyncratic volatility tend to be small and highly leveraged, have high variance of ROE and Market to Book ratio, high turnover rate, and pay no dividends. Furthermore, firms with extreme (either high positive or negative) asset growth rates have high idiosyncratic return volatility than firms with moderate growth rates, suggesting the V-shaped relation between asset growth rate and idiosyncratic return volatility. We find that the V-shaped relation is robust even after controlling for other factors. In time-series, we find that firm-level idiosyncratic volatility is positively related to the dispersion of the cross-sectional asset growth rates. As a result, this study is contributed to show that the asset growth is the most important predictor of firm-level idiosyncratic return volatility in both the cross-section and the time-series in the Korean stock market. In addition, we show how the effect of risk factors varies with industries.

Dissecting Investment Strategies in the Cross Section and Time Series

2015 ◽  
Author(s):  
Jamil Baz ◽  
Nicolas M Granger ◽  
Campbell R. Harvey ◽  
Nicolas Le Roux ◽  
Sandy Rattray
Keyword(s):  
Time Series ◽  
Cross Section ◽  
Investment Strategies ◽  
The Cross

scholarly journals Measuring creative capacity of Visegrad Four countries’ economies

Region Direct ◽  
2014 ◽  
Vol 7 (1) ◽  
pp. 77-104
Author(s):  
Martin Alexy ◽  
Marek Káčer
Keyword(s):  
Time Series ◽  
Czech Republic ◽  
Open Source ◽  
Cross Section ◽  
Empirical Results ◽  
The Cross ◽  
Creative Capacity

Abstract In this paper we study creative capacity of economies of Visegrad Four countries in the period 2000-2011. Creativity index is constructed based on the 3Ts concept of talent, technology and tolerance being the key components of the creativity. Creativity index is measured and calculated with both the cross-section and the time series dimensions. The paper provides index as an open source with the description of variables and their respective weights. Comparison of the creative capacity of economies is based on the empirical results of the Creativity index and its components. Czech Republic is the first and Hungary is the second in the ranking continuously during the examined period. Talent and technology areas are the main reasons for differences between the two leading countries and the rest.

scholarly journals Forecasting using cross-section average–augmented time series regressions

2020 ◽  
Author(s):  
Hande Karabiyik ◽  
Joakim Westerlund
Keyword(s):  
Time Series ◽  
Cross Section ◽  
Regression Models ◽  
Common Factor ◽  
Principal Component ◽  
Small Sample ◽  
Interactive Effects ◽  
Cross Sectional ◽  
Second Development ◽  
The Cross

Summary There is a large and growing body of literature concerned with forecasting time series variables by the use of factor-augmented regression models. The workhorse of this literature is a two-step approach in which the factors are first estimated by applying the principal components method to a large panel of variables, and the forecast regression is then estimated, conditional on the first-step factor estimates. Another stream of research that has attracted much attention is concerned with the use of cross-section averages as common factor estimates in interactive effects panel regression models. The main justification for this second development is the simplicity and good performance of the cross-section averages when compared with estimated principal component factors. In view of this, it is quite surprising that no one has yet considered the use of cross-section averages for forecasting. Indeed, given the purpose to forecast the conditional mean, the use of the cross-sectional average to estimate the factors is only natural. The present paper can be seen as a reaction to this. The purpose is to investigate the asymptotic and small-sample properties of forecasts based on cross-section average–augmented regressions. In contrast to most existing studies, the investigation is carried out while allowing the number of factors to be unknown.

scholarly journals Unemployement and Labour Force Participation : The Canadian Experience

2005 ◽  
Vol 28 (1) ◽  
pp. 56-75
Author(s):  
Robert Swidinsky
Keyword(s):  
Time Series ◽  
Cross Section ◽  
Labour Force ◽  
Labour Force Participation ◽  
Negative Response ◽  
Time Series Regression ◽  
Canadian Experience ◽  
Short Run ◽  
The Cross ◽  
Force Time

In an analysis of the short-run sensitivity of the Canadian labour force time series regression results appear inconclusive whereas cross-section regression results suggest a strong negative response to unemployment. Generally, the findings from the cross-section are comparable neither qualitatively nor quantitatively with those from the time series.

scholarly journals A SIMPLE EFFICIENT INSTRUMENTAL VARIABLE ESTIMATOR FOR PANEL AR(p) MODELS WHEN BOTHNANDTARE LARGE

2009 ◽  
Vol 25 (3) ◽  
pp. 873-890 ◽  
Author(s):  
Kazuhiko Hayakawa
Keyword(s):  
Time Series ◽  
Lower Bound ◽  
Asymptotic Distribution ◽  
Cross Section ◽  
Simulation Study ◽  
Instrumental Variable ◽  
Asymptotic Variance ◽  
The Cross ◽  
Instrumental Variable Estimator ◽  
Normally Distributed

In this paper, we show that for panel AR(p) models, an instrumental variable (IV) estimator with instruments deviated from past means has the same asymptotic distribution as the infeasible optimal IV estimator when bothNandT, the dimensions of the cross section and time series, are large. If we assume that the errors are normally distributed, the asymptotic variance of the proposed IV estimator is shown to attain the lower bound when bothNandTare large. A simulation study is conducted to assess the estimator.

The Determinants of Corporate CDS Spreads: Do Equity Liquidity and Jump Matter?

2014 ◽  
Vol 22 (3) ◽  
pp. 565-595
Author(s):  
Yuen Jung Park ◽  
Jungmu Kim
Keyword(s):  
Time Series ◽  
Stock Return ◽  
Global Financial Crisis ◽  
Explanatory Power ◽  
Firm Level ◽  
Cross Sectional ◽  
Stock Return Volatility ◽  
The Cross ◽  
Market Variables ◽  
The Global Financial Crisis

This paper investigates whether equity liquidity and stock return jump are important determinants for the Korean corporate CDS spreads. The previous studies mainly have examined the determinants of CDS spread time series levels, whereas this study focuses on the determinants of changes or differences of CDS spread time series as well as the effecting factors of cross-sectional variations. Using monthly averaged CDS quotes for 29 firms from Jan. 2005 to Nov. 2012, we first demonstrate that the explanatory power for CDS spread changes is improved to about 39% by adding both credit risk-related market variables and firm-level jump variables, contrary to the low explanatory power (approximately 21%) reported by the previous study. However, since the principle component analysis for residuals from the regression shows that a common risk factor exists, it is possible that additional important factor remains. In addition, we demonstrate that stock return volatility is a robust variable to explain the cross-sectional differences in CDS spreads. We also find that the equity liquidity is a robust and significant factor for the cross-sectional differences in CDS spreads after the global financial crisis period. The result implies that, after the recent crisis, investors more actively considered equity illiquidity costs when they hedged their CDS exposures by stocks.

Sign in / Sign up

Export Citation Format

Share Document