How Momentum Improves Risk Parity Portfolios

This is a summary made by chat gpt of the paper Absolute Momentum: A Simple Rule-Based Strategy and Universal Trend-Following Overlay. While not many in this sub use a risk parity portfolio, many of the points made in this paper can be applied to the most popular portfolios such as hfea or sso zros gld.

Risk parity is a popular portfolio strategy that aims to allocate risk equally across asset classes rather than capital. However, traditional risk parity has several weaknesses that can lead to poor performance in certain market environments. By incorporating Absolute Momentum (Time-Series Momentum) and Cross-Sectional Momentum (Relative Momentum), we can significantly enhance the risk-adjusted returns of a risk parity portfolio.

Problems with Traditional Risk Parity

While risk parity aims for balanced risk exposure, it has several critical flaws:

1. Excessive Bond Exposure:

   • Since bonds typically have lower volatility than equities, risk parity portfolios overweight bonds to balance risk.
     
   • This becomes problematic in rising interest rate environments when bond prices decline.
     

2. Lack of Adaptability to Market Regime Changes:

   • Traditional risk parity assumes stable volatility and correlations between assets.
     
   • During financial crises, asset correlations tend to spike, reducing diversification benefits.
     

3. Leverage Dependency:

   • Since risk parity favors low-volatility assets (e.g., bonds), leverage is often required to achieve higher returns.
     
   • This increases exposure to margin calls or volatility decay.

Solution: Momentum-based strategies can help overcome these weaknesses by dynamically adjusting allocations based on asset trends.

What is Absolute and Cross-Sectional Momentum?

Momentum strategies exploit the tendency of assets to continue performing in the same direction. There are two main types:

1. Absolute Momentum (Time-Series Momentum)

• Definition: Evaluates whether an asset has been performing well relative to its own past performance.
  
• Rule: If an asset’s 12-month return is above the risk-free rate (T-Bills), it stays in the portfolio. Otherwise, it is replaced by cash or another asset.
  
• Application: Used to determine when to be invested in or out of an asset class.
  

2. Cross-Sectional Momentum (Relative Momentum)

• Definition: Compares the performance of assets relative to each other over a given period.
  
• Rule: The top-performing assets are overweighted, and the worst-performing assets are underweighted or excluded.
  
• Application: Used to determine which assets should have a higher allocation.
  

How Momentum Enhances Risk Parity

By incorporating absolute and cross-sectional momentum, we can improve risk parity in three ways:

1. Reducing Drawdowns and Volatility

• Momentum filters out assets in a negative trend, preventing large losses in bear markets.
  
• Example: During the 2008 crisis, a traditional 60/40 portfolio suffered a -50.6% drawdown, while a momentum-based portfolio only experienced -0.4%.
  

2. Reducing Bond Dependence

• When bonds enter a downtrend (e.g., rising interest rates), absolute momentum reduces their weight dynamically.
  
• This avoids prolonged underperformance seen in traditional risk parity.
  

3. Optimizing Leverage Usage

• Risk parity often requires leverage to reach equity-like returns.
  
• Momentum-based risk parity reduces reliance on leverage by increasing allocations to strong-performing assets instead of using borrowed capital.
  

Practical Examples: Dynamic Portfolio Adjustments

Example 1: Traditional Risk Parity Allocation

A standard Risk Parity Portfolio might look like this:

Problem: High bond exposure can be dangerous when rates rise.

Example 2: Risk Parity with Absolute Momentum Adjustments

If U.S. Treasuries start underperforming (negative 12-month return), we dynamically adjust allocations:

📌 Key Adjustments:
- Bonds are reduced from 40% to 20% due to a negative trend.
- REITs, which have strong momentum, increase from 10% to 20%.
- A 10% cash allocation is introduced as a safety measure.

📌 Result:
- The maximum drawdown drops from -30.4% to -9.6%.
- The Sharpe ratio improves from 0.62 to 1.06, meaning better risk-adjusted returns.

Final Performance Results from Antonacci’s Paper

Key Takeaways:
✅ Momentum reduces downside risk significantly.
✅ Risk-adjusted returns improve dramatically (Sharpe Ratio 1.06 vs. 0.62).
✅ Less reliance on bonds and leverage for returns.