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Value Matters : Predictability of Stock Index Returns

Angelini, Natascia - 2013

We present a simple dynamical model of stock index returns which is grounded on the ability of the Cyclically Adjusted Price Earning (CAPE) valuation ratio devised by Robert Shiller to predict long-horizon performances of the market. More precisely, we discuss a discrete time dynamics in which...

Persistent link: https://www.econbiz.de/10013091244

Two-Stage Model Averaging : An Application to Forecasting Stock Returns

Lutz, Chandler - 2013

incorporate economic theory or prior economic information into their forecasts. By using prior economic information, 2SMA …

Persistent link: https://www.econbiz.de/10013072247

Time Series Momentum and Reversal : Intraday Information from Realized Semivariance

Liu, Zhenya - 2020

The presence of time series momentum effect has been widely documented in the financial markets across asset classes and countries. We find a predictable pattern of the realized semi-variance to the future individual asset return, especially during the stressed states of time series momentum...

Persistent link: https://www.econbiz.de/10012836027

Consumption Fluctuations and Expected Returns

Atanasov, Victoria - 2019

This paper introduces a novel consumption-based variable, cyclical consumption, and examines its predictive properties for stock returns. Future expected stock returns are high (low) when aggregate consumption falls (rises) relative to its trend and marginal utility from current consumption is...

Persistent link: https://www.econbiz.de/10012900308

Forecasting Stock Returns with Model Uncertainty and Parameter Instability

Zhang, Hongwei - 2019

We compare several representative sophisticated model averaging and variable selection techniques of forecasting stock returns. When estimated traditionally, our results confirm that the simple combination of individual predictors is superior. However, sophisticated models improve dramatically...

Persistent link: https://www.econbiz.de/10012901029

Valuation Ratios and Shape Predictability in the Distribution of Stock Returns

Giordani, Paolo - 2019

While a large literature on return predictability has shown a link between valuation levels and expected rates of aggregate returns in-sample, we document a link between valuation levels and the shape of the distribution of cumulative (for example, over 12 and 24 months) total returns. Return...

Persistent link: https://www.econbiz.de/10012902527

Nonparametric Tail Risk, Stock Returns and the Macroeconomy

Almeida, Caio - 2016

This paper introduces a new tail risk measure based on the risk-neutral excess expected shortfall of a cross-section of stock returns. We propose a novel way to risk neutralize the returns without relying on option price information. Empirically, we illustrate our methodology by estimating a...

Persistent link: https://www.econbiz.de/10012993993

That Is Not My Dog : Why Doesn't the Log Dividend-Price Ratio Seem to Predict Future Log Returns or Log Dividend Growths?

Dybvig, Philip H.; Zhang, Huacheng - 2021

Campbell and Shiller’s “accounting identity” implies that the log dividend-price ratio (LDPR) predicts either returns or dividend growths, but neither is significantly predictable, a well-known puzzle. Existence of the long-term mean LDPR is an important assumption behind the accounting...

Persistent link: https://www.econbiz.de/10013223114

Long-Horizon Predictability and Information Decay in Equity Markets

Geertsema, Paul; Lu, Helen - 2022

We use machine learning to predict stock returns at forward horizons from 1 month ahead to 120 months ahead. Stock return predictability declines with the forecast horizon; it follows an asymptotic exponential decay process consisting of a permanent component (c. 20 bp/month) and a transient...

Persistent link: https://www.econbiz.de/10013314271

Diverging roads: theory-based vs. machine learning-implied stock risk premia

Grammig, Joachim; Hanenberg, Constantin; Schlag, Christian - 2020

We assess financial theory-based and machine learning-implied measurements of stock risk premia by comparing the … preferable to rely on a theory-based approach instead of engaging in the computerintensive hyper-parameter tuning of statistical … models. The theory-based approach also delivers a solid performance at the one year horizon, at which only one machine …

Persistent link: https://www.econbiz.de/10012163064