Robust optimization takes into account the uncertainty in expected returns to address the
shortcomings of portfolio mean-variance optimization, namely the sensitivity of the optimal …

This paper examines which safe haven assets should be used when improving out-of-
sample portfolio performance. We define a market state with recurrent neural network (RNN) …

We forecast portfolio risk for managing dynamic tail risk protection strategies, based on
extreme value theory, expectile regression, copula‐GARCH and dynamic generalized …

Implemented in corporate strategies, the concept of sustainability with its synthesis between
economical, social and ecological objectives can have a strong business case. In …

ABSTRACT A challenge to developing data-driven approaches in finance and trading is the
limited availability of data because periods of instability, such as during financial market …

We present dynamic trading strategies that target a predefined level of risk measured by
volatility, Value-at-Risk (VaR) or Conditional-Value-at-Risk (CVaR). Recent studies have …

Motivated by the recent market turbulence triggered by the COVID‐19 pandemic and the
changing interest rate environment, we propose an improved investment strategy for …

Over the last few decades, exten-sive econometric research has convincingly demonstrated
that financial asset returns exhibit heteroskedasticity with volatility clustering. This empirical …

This article examines whether volatility targeting can improve returns, decrease tail loss, and
deliver a more stable risk profile for risk assets using the example of US equities. The author …

This paper attempts to extend the approach of quantitative investment and provide investors
with suggestions about volatility timing. Based on the volatility-managed portfolios strategy …