Relevance
8/10
Highly relevant for institutional quantitative trading and portfolio management. The paper provides an evidence-based framework for evaluating backtested structured strategies, quantifies the decay from pro-forma to live performance, identifies regime timing as the primary driver of backtest overstatement, and offers a practical haircut rule for allocators. Directly applicable to strategy selection, position sizing, and due diligence in systematic/quantitative trading contexts. Less relevant for high-frequency or intraday trading strategies.
Implementation Complexity
5/10
The core methodology (OLS with fixed effects, LOO peer benchmark construction, bootstrap inference) is standard econometrics. However, implementing the full pipeline requires: (1) a large proprietary dataset of structured strategies with pro-forma and live returns, (2) bucket classification of strategies, (3) construction of daily LOO benchmarks across 1,726 strategies, (4) Bloomberg benchmark mapping, (5) moving-block and wild-cluster bootstrap procedures, and (6) time-split logistic/linear probability classifiers. The main barrier is data access rather than algorithmic complexity.
Reproducibility
2/5
The underlying strategy-level data are proprietary (provided by Resonanz Capital GmbH under commercial license) and cannot be redistributed. Code is available from the author on reasonable request but subject to data restrictions. Aggregated descriptive statistics and regression outputs are reported in the paper. The small number of institution clusters (10) limits external replication. Wild-cluster bootstrap and moving-block bootstrap procedures are fully specified.