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Predicting stock returns: A regime-switching combination approach and economic links.

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TLDR
In this paper, a regime-switching combination approach is proposed to predict excess stock returns, which explicitly incorporates model uncertainty, regime uncertainty, and parameter uncertainty to predict stock returns.
Abstract
This paper introduces a regime-switching combination approach to predict excess stock returns. The approach explicitly incorporates model uncertainty, regime uncertainty, and parameter uncertainty. The empirical findings reveal that the regime-switching combination forecasts of excess returns deliver consistent out-of-sample forecasting gains relative to the historical average and the Rapach et al. (2010) combination forecasts. The findings also reveal that two regimes are related to the business cycle. Based on the business cycle explanation of regimes, excess returns are found to be more predictable during economic contractions than during expansions. Finally, return forecasts are related to the real economy, thus providing insights on the economic sources of return predictability.

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Forecasting realized volatility in a changing world: A dynamic model averaging approach

TL;DR: In this article, a dynamic model averaging (DMA) approach is used to combine the forecasts of the individual models, which can generate more accurate forecasts than individual model in both statistical and economic senses.
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Forecasting crude oil prices with a large set of predictors: Can LASSO select powerful predictors?

TL;DR: The lasso and elastic net methods are found to select powerful predictors and the ones that can provide complementary information and the OLS regression models based on the selected predictors exhibit better out-of-sample performances than the competing models.
Journal ArticleDOI

Oil and the short-term predictability of stock return volatility

TL;DR: The authors showed that crude oil volatility is predictive of stock volatility in the short-term from both in-sample and out-of-sample perspectives, and the revealed predictability is also of economic significance.
Journal ArticleDOI

Forecasting oil price volatility: Forecast combination versus shrinkage method

TL;DR: In this paper, the predictive ability between forecast combination and shrinkage method in the prediction of oil price volatility was compared based on the heterogeneous autoregressive (HAR) framework, and it was shown that the elastic net and lasso have significantly better out-of-sample forecasting performance than not only the individual extended HAR models but also the combination approaches.
Journal ArticleDOI

Forecasting the prices of crude oil: An iterated combination approach

TL;DR: In this paper, the authors employ an iterated combination approach to examine oil price predictability with a large set of predictors, including 18 macroeconomic variables and 18 technical indicators.
References
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Journal ArticleDOI

An intertemporal capital asset pricing model

Robert C. Merton
- 01 Sep 1973 - 
TL;DR: In this article, an intertemporal model for the capital market is deduced from portfolio selection behavior by an arbitrary number of investors who aot so as to maximize the expected utility of lifetime consumption and who can trade continuously in time.
Journal ArticleDOI

Business conditions and expected returns on stocks and bonds

TL;DR: For example, this paper found that expected returns on common stocks and long-term bonds contain a term or maturity premium that has a clear business-cycle pattern (low near peaks, high near troughs).
Posted Content

By Force of Habit: A Consumption-Based Explanation of Aggregate Stock Market Behavior

TL;DR: In this paper, a consumption-based model is proposed to explain a wide variety of dynamic asset pricing phenomena, including the procyclical variation of stock prices, the long-term horizon predictability of excess stock returns, and the countercyclical variations of stock market volatility.
Journal ArticleDOI

By Force of Habit: A Consumption-Based Explanation of Aggregate Stock Market Behavior

TL;DR: This paper presented a consumption-based model that explains a wide variety of dynamic asset pricing phenomena, including the procyclical variation of stock prices, the long-horizon predictability of excess stock returns, and the countercyclical variations of stock market volatility.
Posted Content

The Impact of Uncertainty Shocks

TL;DR: In this paper, a model with a time varying second moment is proposed to simulate a macro uncertainty shock, which produces a rapid drop and rebound in aggregate output and employment, which occurs because higher uncertainty causes firms to temporarily pause their investment and hiring.
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