Quantitative Data Driven and Systematic

Our research maintains a keen focus on Macroeconomic Environment Segmentation. This approach strategically narrows down the range of potential economic and financial market outcomes. This targeted approach enables our firm to zero in on a more probable and manageable sample. The first step involves identifying four distinct states in which an economy can function, primarily based on the trending three-month delta of economic growth and inflation—the primary components influencing most asset class returns:

GOLDILOCKS (click for dropdown)

GROWTH momentum ↑ and INFLATION momentum ↓

REFLATION (click for dropdown)

GROWTH momentum ↑ and INFLATION momentum ↑

STAGFLATION (click for dropdown)

GROWTH momentum ↓ and INFLATION momentum ↑

DEFLATION (click for dropdown)

GROWTH momentum ↓ and INFLATION momentum ↓

From there, we apply a combination of proprietary econometric tools. These include our Mean Reversion Time Series and our Cross-Sectional Coincident Model. This helps us project the most probable path for GROWTH and INFLATION over our near-term forecast horizon. We use those monthly GROWTH and INFLATION projections to derive outcomes for each month. We denote these outcomes as the bottom-up Macroeconomic Environment – i.e., what the economy is doing in trending three-month delta terms.

Looking at carefully back-tested major financial market instruments, across asset classes, from the perspective of historical bottom-up Macroeconomic Environment observations. Those back-tests allow us to understand the general behavior of each exposure within the four environments. We also analyze their behavior across these environments through the quantitative lenses of annualized returns. Additional metrics include percent positive ratios, volatility, and covariance. That data is programmed into our Macro Risk Medium. It scores the Volatility-Adjusted Signals of the most liquid and widely followed asset markets based on those findings. At every interval, any combination of asset markets could independently confirm each Macroeconomic Environment. The confirmation occurs to varying degrees over time. This process is repeatable. It helps us quickly identify how asset markets are behaving on a trending basis. We express this as the top-down Investment Portfolio.

1) Factor Selection Process

  1. The firm starts with understanding asset market history via Pries Capital Dynamic Asset Securities Back-testing Chart.
  2. Determine the Probability-Adjusted Annualized Expected Returns for each asset in each Macro Environment. Using the calculated Expected Sharpe Ratio Rankings for each asset in each Macro Environment.
  3. The firm allocates a minimum Target Exposure of 10% to three of the top five Expected Sharpe Ratios. This applies in each of the three main asset classes. It also allocates a minimum 10% Target Exposure to a qualitative best idea. Each is according to the current Macro Environment.

2) Top-Down Risk Management Overlay

  1. Systematically incorporate changing market conditions via Expected Volatility Targeting.
  2. If the Pries Capital Macroeconomic Environment Model signals an “Expected Low Volatility”, the Target Exposure per corresponding position equals 10%.
  3. If the Pries Capital Macroeconomic Environment Model signals an “Expected Mid-range Volatility”, the Target Exposure is set to 7. This applies to each corresponding position.
  4. If the Pries Capital Macroeconomic Environment Model signals an “Expected High Volatility”, the Target Exposure per corresponding position equals 5%.

3) Bottom-Up Risk Management Overlay

  1. Systematically incorporate a Multifractal Model of Asset Returns via Dynamic Position Sizing.
  2. If the Price Volatility-Adjusted Risk Signal is Low, then the Actual Exposure equals 100% of Target Exposure.
  3. If the Price Volatility-Adjusted Risk Signal is Neutral, then the Actual Exposure equals 50% of Target Exposure.
  4. If the Price Volatility-Adjusted Risk Signal is High, then the Actual Exposure equals 0% of Target Exposure.

Sharpe Ratio indicates the reward per unit of risk by using standard deviation and excess return. The higher the Sharpe ratio, the better the investment’s historical risk-adjusted performance.

4) Dynamic Asset Dispersion Overlay

Pries Capital consistently studies MoM Sharpe Ratio DISPERSION among equity sectors and style factors for three primary reasons:

  1. It gives us a general sense of what Macroeconomic Environment other investors implicitly or explicitly think we are in.
  2. It provides insight into what sectors and style factors multi-manager hedge funds are emphasizing. These funds push their portfolio managers into or out of these areas. This action occurs implicitly through delta hedging activity or explicitly through capital reallocation.
  3. It provides us with a delayed perspective on the sectors “Pure Quants” are bidding up. It also shows the style factor exposures they are selling down.

At Pries Capital, we offer more than just data – we offer PERSPECTIVE…