In this paper we focus on analyzing the predictive accuracy of three different types of forecasting techniques, Autoregressive Integrated Moving Average (ARIMA), Artificial Neural Network (ANN), and Singular Spectral Analysis (SSA), used for predicting chaotic time series data. These techniques...

The study reports empirical evidence that artificial neural network based models are applicable to forecasting of stock market returns. The Nigerian stock market logarithmic returns time series was tested for the presence of memory using the Hurst coefficient before the models were trained. The...

This study investigates the cross-country impact of U.S. equity market skewness risk. We find that a large decrease in the U.S. market skewness significantly predicts high future returns on international equity markets. The predictability remains significant after controlling for a set of U.S....

According to present-value models, a financial valuation ratio should predict future stock returns or cash flows but empirically shows little power. This paper develops insights about stock return predictability and reconciles the contradicting findings. We decompose a financial ratio into (1) a...

We propose a new predictor - the innovation in the daily return minimum in the U.S. stock market () - for predicting international stock market returns. Using monthly data for a wide range of 17 MSCI international stock markets during the period spanning over half a century from January 1972 to...

Empirical financial literature documents the evidence of mean reversion in stock prices and the absence of out-of-sample return predictability over periods shorter than 10 years. The goal of this paper is to test the random walk hypothesis in stock prices and return predictability over periods...

While numerous studies have analyzed the asset allocation issue of US stock market from various angles, much less attention has been paid to the asset allocation issue of Chinese stock market. This article investigates the asset allocation in Chinese stock market from a perspective of...

Movements in the stock market should reflect expectations regarding future economic conditions and lead the macroeconomy. However, evidence for stock returns providing such predictive power is mixed. We argue this arises as stock returns are noisy and consider the predictive ability of derived...

This paper examines the ability of bond and stock markets to predict subsequent GDP growth over a range of horizons for twelve international countries. The results, using linear, probit, time- and regime-varying in-sample regressions and out-of-sample forecasting, confirm the view that both...