Generalized financial ratios to predict the equity premium

Algaba, Andres; Boudt, Kris

doi:10.1016/j.econmod.2017.07.009

Cited by 9 publications

(4 citation statements)

References 45 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…3 With regards to macro variables, Cooper andPriestley (2009, 2013) use the output gap and the world business cycle, respectively, Favero, Gozluklu, and Tamoni (2011) consider a demographic variable (the proportion of middle-aged to young population), Li, Ng, and Swaminathan (2013) study the aggregate implied cost of capital, Chava, Gallmeyer, and Park (2015) study the predictive power of bank lending standards, and Moller andRangvid (2015, 2018) study dierent US-based macroeconomic variables and global economic growth, respectively, by focusing on their fourth-quarter growth rate. Financial market variables include the variance risk premium (Bollerslev, Tauchen, and Zhou, 2009), lagged US market returns for the OOS predictability of stock returns of other industrialized countries (Rapach, Strauss, and Zhou, 2013), the stockbond yield gap (Maio, 2013), technical indicators (Neely, Rapach, Tu, and Zhou, 2014), the government bond volatility index (Pan and Chan, 2017), option-implied state prices (Metaxoglou and Smith, 2017), risk neutral variance of the equity market return measured from index option prices (Martin, 2017), and generalized nancial ratios (Algaba and Boudt, 2017). Behavioral-related variables include the investment sentiment indexes (Huang, Jiang, Tu, and Zhou, 2015) and information on short-interest positions (Rapach, Ringgenberg, and Zhou, 2016).…”

Section: Related Literaturementioning

confidence: 99%

The Equity Risk Premium and the Low Frequency of the Term Spread

Faria

Verona

2017

SSRN Journal

View full text Add to dashboard Cite

Michael Weber, as well as of participants at the Católica Porto Business School seminar, the HECER time series econometrics seminar, the Bank of Finland seminar, the Bank of England seminar, the 17 th SAET Conference on Current Trends in Economics (Faro), the 11 th Annual Meeting of the Portuguese Economic Journal (Vila Real), the 25 th Finance Forum (Barcelona), the II Workshop on Financial Mathematics Models and Statistical Methods at the FCT/UNL (Lisbon), the 5 th Applied Macroeconometric Workshop (Labex MME-DII, CEPN and INFER network), the ECB WGEM November 2017 meeting, the IV Christmas Workshop in Accounting and Finance (Universidade do Porto) and the Inquire Europe 2018 Spring conference (Dresden). The views expressed are those of the authors and do not necessarily reect those of the Bank of Finland. Faria gratefully acknowledge nancial support from Fundação para a Ciência e Tecnologia through project UID/GES/00731/2016.

show abstract

Section: Related Literaturementioning

confidence: 99%

The Equity Risk Premium and the Low Frequency of the Term Spread

Faria

Verona

2017

SSRN Journal

View full text Add to dashboard Cite

show abstract

“…This analysis was conducted by establishing the Pearson's coefficient for these variables and the results thereof, tabled for discussion in the form of a heatmap again. Several other authors use correlations to test the relationships between similar variables, including Kenourgios et al (2021), Jivraj & Shiller (2017) and Algaba & Boudt (2017).…”

Section:  Consumer Price Inflation Index (Cpi)mentioning

confidence: 99%

“…There is a collection of well-known financial ratios and tools which are used to measure the relative value of equity (Algaba & Boudt, 2017). Among the collection of these financial models and ratios is the price-earnings ratio (PER), price-dividend ratio or dividend yield, price-earnings to growth ratio (PEG), price-to-book ratio, price-tosales ratio, and free cash flow amongst others (Algaba & Boudt, 2017, p. 245).…”

Section: Introductionmentioning

confidence: 99%

A modified Shiller's cyclically adjusted price-to-earnings (CAPE) ratio for stock market index valuation in a zero-interest rate environment

Catanho

Saville

2022

Investment Analysts Journal

View full text Add to dashboard Cite

The cyclically adjusted price-earnings ratio (CAPE) is a tool that has become widely used to predict market returns. However, recently, deterioration in its forecast strength has surfaced. At the same time, global long-term interest rates have declined and are expected to remain at record lows, which the CAPE fails to consider, and which represents a gap in knowledge. This study uses a modified CAPE to account for interest rates, known as the excess CAPE yield (ECY), to offer an alternative -and potentially improved -model for predicting global stock market returns. We find that CAPEs peak when real interest rates are between 3% and 5%, while the ECY fails to improve on the predictive abilities of the CAPE.

show abstract

“…(2) parsimonious ARIMA models; (3) disaggregated-accrual, time-series regression models; and (4) parsimonious ARIMA models with both adjacent and seasonal characteristics. Algaba and Boudt [3] used financial ratios to predict the equity premium over a horizon of 1 to 12 months for corporations. They found that transformations of the financial ratios that properly account for the time-varying relationship between the variables at stake are more suitable for predicting the equity premium over the intra-year horizon than the original financial ratios.…”

Section: Introductionmentioning

confidence: 99%

Financial Forecasting With Multivariate Adaptive Regression Splines and Queen Genetic Algorithm-Support Vector Regression

Chen

Lin

2019

IEEE Access

View full text Add to dashboard Cite

In consideration of the financial indicators of financial structure, solvency, operating ability, profitability, and cash flow as well as the non-financial indicators of firm size and corporate governance, the algorithms of multivariate adaptive regression splines (MARS) and queen genetic algorithm-support vector regression (QGA-SVR) are used in this study to create a comprehensive financial forecast of operating revenue, earnings per share, free cash flow, and net working capital to help enterprises forecast their future financial situation and offer investors and creditors a reference for investment decision-making. This study's objectives are achieved through the following steps: (i) establishment of feature indicators for financial forecasting, (ii) development of a financial forecasting method, and (iii) demonstration of the proposed method and comparison with existing methods.INDEX TERMS Financial forecasting, multivariate adaptive regression splines (MARS), queen genetic algorithm (QGA), support vector regression (SVR).

show abstract

Generalized financial ratios to predict the equity premium

Cited by 9 publications

References 45 publications

The Equity Risk Premium and the Low Frequency of the Term Spread

The Equity Risk Premium and the Low Frequency of the Term Spread

A modified Shiller's cyclically adjusted price-to-earnings (CAPE) ratio for stock market index valuation in a zero-interest rate environment

Financial Forecasting With Multivariate Adaptive Regression Splines and Queen Genetic Algorithm-Support Vector Regression

Contact Info

Product

Resources

About