Portfolio Optimization Constrained by Performance Attribution

This paper investigates performance attribution measures as a basis for constraining portfolio optimization. We employ optimizations that minimize conditional value-at-risk and investigate two performance attributes, asset allocation (AA) and the selection effect (SE), as constraints on asset weights. The test portfolio consists of stocks from the Dow Jones Industrial Average index. Values for the performance attributes are established relative to two benchmarks, equi-weighted and price-weighted portfolios of the same stocks. Performance of the optimized portfolios is judged using comparisons of cumulative price and the risk-measures: maximum drawdown, Sharpe ratio, Sortino–Satchell ratio and Rachev ratio. The results suggest that achieving SE performance thresholds requires larger turnover values than that required for achieving comparable AA thresholds. The results also suggest a positive role in price and risk-measure performance for the imposition of constraints on AA and SE.

The Friend of Your Trend

Standard performance attribution to beta and alpha is not simple without full transparency into the investment process. This article develops an analytical framework to shed light on ex-ante stylized characteristics of a simple trend following strategy. Our analytical results show that rewards from the trend following strategy embed different degrees of underlying asset beta, which are determined by the asset’s return-to-volatility ratio, in addition to the trending behaviors that the strategy is built to harvest. We compare the results to ex-post realized returns-based style analysis of a CTA index. We discuss practical implications of our results with respect to fees and allocations to trend following strategies.