Preference for dividends and stock returns around the world
Allaudeen Hameed (National University of Singapore), et al.
November 2022
We find strong international evidence favoring dividend payout as a salient stock characteristic affecting expected stock returns. We find that dividend-paying stocks outperform non-payers by 0.54% per month in 44 countries, adjusting for exposures to global and regional risk factors. The majority of the dividend premium is earned during the ex-dividend months. The dividend premium is higher following bad market states and co-varies across countries. Dividend payers’ outperformance is stronger in countries with poor governance but is unrelated to local tax rates on dividends. The evidence emphasizes the importance of (time-varying) preference for dividends in driving average stock returns and global return comovement.
The Optimal Stock Valuation Ratio
Sebastian Hillenbrand (Harvard U.) and Odhrain McCarthy (New York U.)
November 2022
Stock valuation ratios contain expectations of returns, yet, their performance in predicting returns
has been rather dismal. This is because of an omitted variable problem: valuation ratios also contain expectations of cash flow growth. Time-variation in cash flow volatility and a structural shift towards repurchases have magnified this omitted variable problem. We show theoretically and empirically that scaling prices by forward measures of cash flows can overcome this problem yielding optimal return predictors. We construct a new measure of the forward price-to-earnings ratio for the S&P index based on earnings forecasts using machine learning techniques. The out-of-sample explanatory power for predicting one-year aggregate returns with our forward price-to-earnings ratio ranges from 7% to 11%, thereby beating all other predictors and helping to resolve the out-of-sample predictability debate (Goyal and Welch, 2008).
The Return of Return Dominance: Decomposing the Cross-section of Prices
Ricardo De la O (University of Southern California), et al.
November 2022
Are stock valuation ratios mainly informative about future earnings growth or future returns? Using a variance decomposition, we find that over 70% of cross-sectional variation in price-earnings ratios is reflected in cross-sectional differences in future returns, while less than 30% is reflected in cross-sectional differences in future earnings growth. This is because, empirically, valuation ratios primarily predict future returns and only modestly predict future earnings growth. Additionally, changes in predicted future returns are more important than changes in predicted future earnings growth for explaining innovations in price-earnings ratios and current realized returns. We reconcile these results with previous literature which has found a strong relation between prices and future profitability. These results are consistent with models in which the cross-section of stock valuation ratios is driven mainly by discount rates or mispricing rather than differences in future earnings growth.
Equity Duration: Theoretical and Practical Analysis
Dennis Marco Montagna and Luca Bianchi (University of Pavia)
September 2022
Duration is an important parameter used by investors to choose between different investment opportunities in financial economics. While the concept of duration is usually associated with fixed-income assets, its expansion to the equity assets is becoming more relevant in the recent period, due to extraordinary measures by central banks. The Quantitative Easing and other related programs are relevant to risk-free rates and, consequently, discount factors and expected returns. The article aims to provide a first complete overview of Equity Duration, calculating and comparing different types, investigating the changes in prices and equity values, and identifying whether there is a relationship between duration fluctuations and enterprise values. The models are applied to the dataset covering roughly 30 years of data until 2021. The analysed equity indexes belong to the US market; four of them refer to the general US market, while the others refer to the first-level and second-level sectors, with the price of S&P500 used as the benchmark for beta computation in the CAPM discount factor formula. The analysis uses several methods to calculate the duration between 21/12/2007 and 01/10/2021, each one aiming to find the most accurate and consistent. The first method is the benchmark for the subsequent computations and uses the dividend discount model; the second method uses the discounted cash flow model over four years; the last one implements an H-Model to the discounted cash flow over nine years. Finally, we analyse the relationship between debt and duration fluctuations: data show a close relationship which could help investors’ decisions in asset allocation.
Interest Rate Uncertainty and Vulnerabilities in Stock Market Valuation
Thiago Ramos Almeida (Petrobras)
October 2022
This paper proposes a direct and robust method to quantify economic uncertainty. Cap and floor options are empirically used to gauge uncertainty about future interest rates. The developed measure is shown to be counter-cyclical, precedes bad macroeconomic states, and its increases are associated with a lower stock market valuation. I also examine the conditional distribution of the cyclically adjusted price-to-earnings ratio (CAPE ratio) as function of economic and uncertainty conditions. Increases in uncertainty are related to rises in conditional volatility and a fall in the conditional median of CAPE ratio growth.
Valuation When Disaster Risks Increase at an Increasing Rate
Ravi Joshi (Louisiana State University), et al.
November 2022
Atmospheric CO2 been growing at an increasing rate for many years and this suggests that investments may face an increasing rate of future disaster risk. We provide a simple variation of the Gordon Growth model that accounts for potential increasing disaster risks and provides a closedform bound to the reduction in value.
Learn To Use R For Portfolio Analysis
Quantitative Investment Portfolio Analytics In R:
An Introduction To R For Modeling Portfolio Risk and Return
By James Picerno
Pingback: Quantocracy's Daily Wrap for 12/11/2022 - Quantocracy