hedging strategies, and assessing risk. Most investors estimate the stock-bond correlation simply by extrapolating the …Investors rely on the stock-bond correlation for a variety of tasks, such as forming optimal portfolios, designing … historical correlation of monthly returns and assume that this correlation best characterizes the correlation of future, annual …

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 … portfolios in terms of portfolio risk. While optimal daily weights minimize portfolio risk, we find that portfolio turnover and …

explain risk premium. Investigating whether these factors are useful in forecasting stock returns remains active research in …

. These seven scripts contain the Dynamic Conditional Correlation (DCC) framework, Instantaneous Frequency Forecasting (IFF …) framework, Regularised Covariance Regression (RCR) framework, Risk Premia Parity (RPP) weighting functions, Singular Spectrum … RCR framework to forecast covariance and correlation structures and finally apply portfolio weighting strategies based on …

interval representing the LSTM's parameter uncertainty. Finally, resulting death rates are showed through a back …

correlation predictions. The volatilities are here forecast using hybrid neural networks while correlations follow a traditional …

The correlation between stock markets and interest rates has been discussed in numerous studies in the past, with … which allow for time-variability and regime changes in correlation. All estimated models allowing for timevarying … correlation complement each other in identifying time-varying patterns found in the (co-)movement between the variables …