Paper: SSRN 2265693
Abstract
We examine the effectiveness of applying a trend following methodology to global asset allocation between equities, bonds, commodities and real estate. The appl
Complexity vs Empirical Score
- Math Complexity: 5.0/10
- Empirical Rigor: 8.5/10
- Quadrant: Holy Grail — high math complexity, high empirical rigor
Why this score: The paper applies advanced statistical and financial mathematics (e.g., risk parity, momentum models, volatility adjustments) but is heavily grounded in empirical backtesting across multiple asset classes with clear performance metrics, making it both mathematically sophisticated and data/implementation-focused.
Research Flowchart
flowchart TD A["Research Goal: Test trend following in multi-asset allocation<br/>(Equities, Bonds, Commodities, Real Estate)"] --> B["Data & Inputs"] B --> B1["Historical Price Data"] B --> B2["4 Asset Classes"] B --> B3["Risk Parity & Trend Following Models"] A --> C["Methodology & Computation"] C --> C1["Estimate Covariance Matrix"] C --> C2["Apply Portfolio Optimization<br/>(Risk Parity / MV)"] C --> C3["Compute Time-Series Momentum<br/>(Rolling Returns & Signals)"] C --> D["Key Outcomes"] D --> D1["Robust Diversification Benefits"] D --> D2["Improved Risk-Adjusted Returns"] D --> D3["Effective Hedge Against Market Shocks"] D --> D4["Trend & Risk Parity Synergy"] B1 --> C B2 --> C B3 --> C C1 --> D C2 --> D C3 --> D