Quoniam

Quoniam Asset Management – Strategic Partnership

Since September 2016, Joerg Osterrieder has served as a strategic partner to Quoniam Asset Management, focusing on traditional quantitative research and systematic investment strategies. Primary contributions centre on multi-asset and cross-asset momentum and trend-following models, with strong emphasis on statistical validation and risk-management integration so that the research outputs align with Quoniam’s systematic investment process, operational controls, and regulatory commitments.

Multi-Asset Momentum and Trend-Following Frameworks

The multi-asset momentum and trend-following frameworks are designed to capture medium- to long-term momentum and trend signals across global equities, government bonds, commodities, and currencies. Time-series methods — exponential moving averages, simple moving averages, and rolling regression models — estimate trend strength and persistence, while price-based filters such as breakout models and Bollinger bands identify entry and exit points in the systematic trend strategies. Combining these techniques across asset classes produces diversified trend exposures that pool signals which would be noisier in any single market, and that respond at horizons short enough for practical portfolio management while long enough to avoid excessive turnover.

Cross-Asset Signal Integration

Cross-asset signal integration rests on standardised momentum indicators — relative strength and rate of change — that allow momentum signals to be compared across asset classes on a normalised scale. Z-score normalisation and cross-sectional ranking then integrate these signals into a unified cross-asset allocation model, giving the portfolio a single view of which exposures look attractive relative to the opportunity set. Allocation rules rebalance positions dynamically based on relative momentum rankings and volatility-adjusted weights, so that the portfolio concentrates in the strongest signals while respecting risk budgets and avoiding concentration in a single asset class.

Statistical Validation and Robustness Testing

Statistical validation and robustness testing guard against the overfitting that quantitative trend strategies are particularly prone to. Out-of-sample backtesting on rolling and expanding windows tests the stability and predictive power of momentum signals across time, and bootstrap resampling assesses parameter stability and model robustness across different market regimes. Autocorrelation structures and drawdown profiles are analysed to verify the risk-management and diversification benefits that the design aims to achieve, so that claims about the strategy’s behaviour rest on evidence rather than on the particular sample period used in the original study.

Risk-Management Integration

Risk-management integration translates the research outputs into a trading strategy that can be run through real market conditions. Dynamic position sizing uses risk-budgeting frameworks based on rolling volatility estimates and Value-at-Risk (VaR) constraints, while correlation analysis and principal-component decomposition manage cross-asset exposures and guard against concentration risk in combinations that look independent in normal conditions but co-move sharply during stress. Portfolio-level drawdown controls then apply historical stress scenarios and tail-risk measures — Conditional Value-at-Risk in particular — to limit the damage from adverse regimes.

Collaboration Highlights and Outcomes

Close work with Quoniam’s quantitative research team aligned the models with the firm’s systematic investment process and with the operational and regulatory requirements under which Quoniam trades, and the trend-following signals were integrated into production systems in a way consistent with operational risk controls and compliance guidelines. The collaboration enhanced portfolio diversification and performance through the systematic incorporation of multi-asset and cross-asset trend signals, delivered quantitative models that identified momentum persistence and contributed to risk-adjusted returns, and produced scenario-analysis and stress-testing frameworks that support continued evaluation of model performance under varying market conditions. The Quoniam Asset Management collaboration covers the design, implementation, and validation of traditional quantitative multi-asset and cross-asset momentum and trend-following strategies, and the work emphasises statistical techniques, risk-management integration, and operational implementation that supports the firm’s systematic investment process.