Dominik Schneller’s research while affiliated with University of Augsburg and other places

This research note is an excerpt of our paper “With a pinch of stop loss: A Real Vision trading recipe”. The paper analyses the sentiment and compares the performance of trade ideas extracted from 292 interviews of professional investors and money managers, which where streamed on the “Netflix of Finance” - Real Vision between January 2018 and March 2020. This short note gives unique insights into the performance of the trade ideas and analyzes the usefulness of using defined targets and risk limits in trade specifications.

Employing a nonlinear multi-criteria optimization approach, sentiment-based disagreement is incorporated into portfolio optimization as additional risk factor. A multi-criteria trading strategy outperforms several benchmarks regarding various performance measures. Applying the strategy over a long time period including downturns and upswings, disagreement proves itself especially valuable in bear markets as it is an indicator for future volatility.

The information contained in investor sentiment has up to now hardly been used for portfolio optimization, although theoretical works demonstrate that it should not be neglected and it has already been shown to contain exploitable information on future returns and volatility. Employing the approach of Copula Opinion Pooling, we explore how sentiment information regarding international stock markets can be directly incorporated into the portfolio optimization procedure. We subsequently show that sentiment information can be exploited by a trading strategy that takes into account a medium-term reversal effect of sentiment on returns. This sentiment-based strategy outperforms several benchmark strategies in terms of different performance and downside risk measures. More importantly, the results remain robust to changes in the parameter specification.

Using a new variable to measure investor sentiment we show that the sentiment of German and European investors matters for return volatility in local stock markets. A flexible empirical similarity (ES) approach is used to emulate the dynamics of the volatility process by a time-varying parameter that is created via the similarity of realized volatility and investor sentiment. Out-of-sample results show that the ES model produces significantly better volatility forecasts than various benchmark models for DAX and EUROSTOXX. Regarding other international markets no significant difference between the forecasts can be observed.