Portfolio Optimization Using Novel Intelligent Probabilistic Forecasts of Risk Measures

Intelligent Probabilistic Risk Forecasting With Applications to Algorithmic Trading and Portfolio Optimization

“…In that case, the corresponding degrees of freedom (d.f.) ν can be computed by solving the following equation [1]:…”

“…For example, the given basket could be the SP500, and the goal would be to find the optimal weights for each asset using the sharp ratio. In [1] optimal portfolio weights are obtained by minimizing the corresponding risk forecasts of portfolio volatility. Some of the common risk forecast metrics are the mean absolute deviation (MAD), Value-at-Risk (VaR), and conditional Value-at-Risk (CVaR).…”

“…It is essential to understand that these risk forecast metrics depend on the variance of the portfolio; estimating the portfolio variance using a forecasting model will improve our risk forecast metrics. In [1], the data-driven portfolio volatility forecasting models: DD-EWMA is investigated. Besides the portfolio volatility, the commonly used portfolio risk measures such as MAD, VaR, and CVaR are based on forecasting portfolio volatility.…”

“…The volatility forecasting models are used to study the generalized dynamic portfolio optimization using intelligent probabilistic forecasts based on the data-driven t distribution of the portfolio returns distribution. [1]. Chapter I -Introduction…”