We empirically evaluate the predictive power of money growth measured by M2 for stock returns of the S&P 500 index. We use monthly US data and predict multiperiod returns over 1, 3, and 5 years with long-horizon regressions. In-sample regressions show that money growth is useful for predicting...

We empirically evaluate the predictive power of money growth measured by M2 for stock returns of the S&P 500 index. We use monthly US data and predict multiperiod returns over 1, 3, and 5 years with long-horizon regressions. In-sample regressions show that money growth is useful for predicting...

Understanding the pattern of stock market volatility is important to investors as well as for investment policy. Volatility is directly associated with risks and returns, higher the volatility the more financial market is unstable. The volatility of the Zimbabwean stock market is modeled using...

We examine the cross-section of international equity risk premia with machine learning methods. We identify, classify, and calculate 88 market characteristics and use them to forecast country returns with various machine learning techniques. While all algorithms produce substantial economic...

Using a modified DCC-MIDAS specification that allows the long-term correlation component to be a function of multiple explanatory variables, we show that the stock-bond correlation in the US, the UK, Germany, France, and Italy is mainly driven by inflation and interest rate expectations as well...

As a response to the Great Recession, many central banks resorted to unconventional monetary policies, in the form of a balance sheet expansion. Our research aims at analyzing the impact of the ECB policies on stock market volatility in four Eurozone countries (France, Germany, Italy, and Spain)...

This study sheds new light on the question of whether or not sentiment surveys, and the expectations derived from them, are relevant to forecasting economic growth and stock returns, and whether they contain information that is orthogonal to macroeconomic and financial data. I examine 16...

Purpose - The economic and administrative conditions of countries normatively have an effect on the economy and level of market development. Moreover, it is of great importance for a healthy economy whether the public institutions and organizations are transparent and functioning in accordance...

This study is an attempt to review the theory and applications of autoregressive fractionally integrated moving average (ARFIMA) and fractionally integrated generalized autoregressive conditional heteroskedasticity (FIGARCH) models, mainly for the purpose of the description of the observed...