Style Analysis

Overview

Why is it important to break out the performance derived from factor selection from stock selection? If a database is screened for large value or large growth, aren’t the managers within each styles category similar?

Even within the archetypal style groups such as growth and value, different factor weightings can cause very different return patterns, and performance will vary over time as a result of the relationship between a manager’s dominant factor or style characteristics to changes in market liquidity and profits over a market cycle.

Total Number of Funds on the Aapryl Platform

Equity Fixed Income Total
Mutual Funds & ETFs 5,537 2,284 7,821
SMAs 7,342 7,868 15,210
Total 12,879 10,152 23,301

*Since/2023

How it works

START A STYLE ANALYSIS

Style Analysis offers you the ability to further analyse a Managers style, or investment approach.

SELECT A UNIVERSE

Select a single or multiple Products to compare.

ANALYZE CLUSTERS

View multiple charts and tables which provide historical measurements of a products style, and other attributes.

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Purpose: Aapryl’s Style Analysis module decomposes a manager’s historical returns into market factors or “betas” so that users can understand what is driving a manager’s returns, identify changes in a manager’s strategy and distinguish true skill from market return.  Aapryl’s Style Analysis not only shows the factor exposures and how they have evolved over time, but also how the factor exposures react to different market environments and economic regimes.  This allows users to more accurately predict future manager performance.

Glossary of Terms:

  • Style Analysis– Sometimes referred to as Returns Based Style Analysis, it is the process of determining the market factors or betas that are driving a manager’s returns by regressing a manager’s returns against said factors.
  • Betas– These are the market factors that are used to analyze a manager’s style in the regression.  Aapryl uses commonly used factors such as ROE, Earnings Stability, leverage, dividend yield and momentum.
  • Cycle Phases– This refers to the phases of the economic cycle.  Aapryl breaks the cycle into Recovery (early), Expansion (mid), Slowing Growth (late), and Recession.

Description of Methodology:   Aapryl’s Style Analysis module uses the factor regression run in the Clustering Module to identify the manager’s exposures to various factors.  Based on exposure, managers are classified into one of the following six categories:  Low Quality Value, Low Quality Blend, Low Quality Growth, High Quality Value, High Quality Blend, and High Quality Growth.    The system has preprogrammed the market environment in which each category will provide the most excess return to provide users with more accurate predictions of manager performance in various market conditions.

Information Provided:  Aapryl is able to use the information generated in the Style Analysis module to provide users with charts and graphs that contain an abundance of useful information which includes the following:

  • Market Cycle Positioning Aapryl shows the market environment in which a manager or group of managers are expected to perform the best.
  • Style Analysis– Aapryl provides users with the results of the style analysis in a 2 dimensional style box.  The results are shown across time so that users can see changes in manager behavior.
  • Factor Exposures– Aapryl provides users with multiple views of the factor exposures that were determined by the style analysis.  Manager and benchmarks results can be seen both for the current period and across time.

Additional Information

For more information on the methodology behind Aapryl’s Style Analysis, please review the following material(s):

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