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Forecasting the market risk premium with artificial neural networks

Oikonomikou, Leoni Eleni - 2016 - Revised version: November 2015

This paper aims to forecast the Market Risk premium (MRP) in the US stock market by applying machine learning techniques, namely the Multilayer Perceptron Network (MLP), the Elman Network (EN) and the Higher Order Neural Network (HONN). Furthermore, Univariate ARMA and Exponential Smoothing...

Persistent link: https://www.econbiz.de/10011454074

Comparing the market risk premia forecasts in JSE and NYSE equity markets

Oikonomikou, Leoni Eleni - 2016 - Corrected version: March 2016

This paper examines the evidence regarding predictability in the market risk premium using artificial neural networks (ANNs), namely the Elman Network (EN) and the Higher Order Neural network (HONN), univariate ARMA and exponential smoothing techniques, such as Single Exponential Smoothing (SES)...

Persistent link: https://www.econbiz.de/10011454082

Economically-Linked Economies and Forecasting Chinese Stock Returns

Jordan, Steven J. - 2012

indices from countries that China net exports from can forecast the Chinese aggregate market return at the weekly time horizon …. Countries that China net exports to have no consistently significant OOS predictability.The economic intuition for our results … follows from the fact that China has positioned itself as a low-cost provider competing on price. As a low-cost provider China …

Persistent link: https://www.econbiz.de/10013098289

China Markets and Global Stock Return Predictability

Sun, Yulong - 2020

We have seen China's growing role in the past decades, and the world economy has become more exposed to the influence … of China. This paper explores emerging China's impact on the global equity market through the lens of asset pricing. We … study the predictive properties of the lagged China returns for global stock returns and find that the lagged China returns …

Persistent link: https://www.econbiz.de/10012824300

Predicting Stock Market Returns Using the Shiller CAPE — An Improvement Towards Traditional Value Indicators?

Keimling, Norbert - 2016

Existing research indicates that it is possible to forecast potential long-term returns in the S&P 500 for periods of more than 10 years using the cyclically adjusted price-to-earnings ratio (CAPE). This paper concludes that this relationship has also existed internationally in 17 MSCI Country...

Persistent link: https://www.econbiz.de/10012998360

Recession Prediction Using Yield Curve and Stock Market Liquidity Deviation Measures

Erdogan, Oral - 2016

This paper extends the benchmark Estrella and Hardouvelis (1991) term spread approach to recession forecasting by including the stock market macro liquidity deviation factor. We use a probit framework to predict US business cycles, as defined by the NBER between 1959Q1 and 2011Q4. We find that...

Persistent link: https://www.econbiz.de/10013007569

Does Investor Sentiment Predict Future Mexican Stock Market Returns?

Perez-Liston, Daniel - 2017

This paper studies whether investor sentiment can predict future Mexican stock market returns. Furthermore, we examine the dynamic correlation between sentiment and returns. Lastly, we examine whether sentiment innovations influence unexpected returns. We find that sentiment has significant...

Persistent link: https://www.econbiz.de/10012948714

Does the Bond-Stock Earning Yield Differential Model Predict Equity Market Corrections Better than High P/E Models?

Lleo, Sebastien - 2015

In this paper, we extend the literature on crash prediction models in three main ways. First, we explicitly relate crash prediction measures and asset pricing models. Second, we present a simple, effective statistical significance test for crash prediction models. Finally, we propose a...

Persistent link: https://www.econbiz.de/10013035325

Short-Term Predictability of Stock Market Indexes Following Large Drawdowns and Drawups

Ratton Brandi, Vinicius - 2018

The Efficient Market Hypothesis is one of the most popular subjects in the empirical finance literature. Previous studies in the stock markets, which are mostly based on fixed time price variations, do not provide conclusive findings, in which evidence of short-term predictability varies...

Persistent link: https://www.econbiz.de/10012914355

Forecasting Realized Intra-Day Volatility and Value at Risk : Evidence From a Fractional Integrated Asymmetric Power ARCH Skewed-T Model

Degiannakis, Stavros Antonios - 2018

Predicting the one-step-ahead volatility is of great importance in measuring and managing investment risk more accurately. Taking into consideration the main characteristics of the conditional volatility of asset returns, I estimate an asymmetric Autoregressive Conditional Heteroscedasticity...

Persistent link: https://www.econbiz.de/10012910129