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Why Aapryl?

 
Home Why Aapryl?
“90% of what passes for brilliance or incompetence in investing is the ebb and flow of investment style” – Jeremy Grantham

Why Aapryl: Because we can leverage your time, expertise and resources to improve performance by:

Providing superior analytics that…
  • Are more predictive of future investment performance
  • Distinguishes luck from skill and alpha from investment style
  • Calculate the factor betas endemic to a manager’s investment process
  • Produce refined factor-based peer groups that go beyond broad investment styles
  • Estimates alpha more accurately to improve portfolio optimization
  • Visually identifies the best and worst market conditions for a manager product or composite portfolio

Common Measures of Skill are not Very Persistent After 3 Years and Random After 5 Years

Information Ratio 1 Year Scatter Plot

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Information Ratio 3 Year Scatter Plot

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Information Ratio 5 Year Scatter Plot

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Limited Persistence in Quartile Rankings

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# of Funds: 1,097
Excess Return Ranking (5 Years Ended 12/31/09): Highest Quintile (1)

Quintile ranking in subsequent non-overlapping 5-year period ended12/31/2014 (percentage of funds)

Highest Quintile (%): 13.5
High (%): 16.6
Medium (%): 20.3
Low (%): 16.2
Lowest Quintile (%): 23.5
Merged/ Closed (%): 9.9
Total (%): 100.0
# of Funds: 1,083
Excess Return Ranking (5 Years Ended 12/31/09): High (2)

Quintile ranking in subsequent non-overlapping 5-year period ended12/31/2014 (percentage of funds)

Highest Quintile (%): 12.4
High (%): 13.5
Medium (%): 16.0
Low (%): 20.6
Lowest Quintile (%): 15.5
Merged/ Closed (%): 22.1
Total (%): 100.0
# of Funds: 1,084
Excess Return Ranking (5 Years Ended 12/31/09): Medium (3)

Quintile ranking in subsequent non-overlapping 5-year period ended12/31/2014 (percentage of funds)

Highest Quintile (%): 14.9
High (%): 13.9
Medium (%): 14.2
Low (%): 17.7
Lowest Quintile (%): 13.4
Merged/ Closed (%): 25.9
Total (%): 100.0
# of Funds: 1,085
Excess Return Ranking (5 Years Ended 12/31/09): Low (4)

Quintile ranking in subsequent non-overlapping 5-year period ended12/31/2014 (percentage of funds)

Highest Quintile (%): 13.8
High (%): 15.1
Medium (%): 11.0
Low (%): 12.3
Lowest Quintile (%): 10.0
Merged/ Closed (%): 37.9
Total (%): 100.0
# of Funds: 1,032
Excess Return Ranking (5 Years Ended 12/31/09): Lowest Quintile (5)

Quintile ranking in subsequent non-overlapping 5-year period ended12/31/2014 (percentage of funds)

Highest Quintile (%): 13.8
High (%): 11.5
Medium (%): 10.9
Low (%): 10.6
Lowest Quintile (%): 8.7
Merged/ Closed (%): 44.6
Total (%): 100.0

Morningstar Ratings Also Demonstrate Limited Persistence

  • Morningstar gives funds one to five stars for past performance, with five the best.
  • Many investors treat the stars as guide to future performance.
  • But over time, the performance of funds with different initial star ratings coverges.

Notes: Year zero represents the initial overall ratings of funds. Other points on chart are their average star ratings for the following three, five or ten years. Funds rated by Morningstar can have upto four ratings: a three-year rating, a five-year rating, a 10 year rating, and an overall rating that is based on a combination of the others.

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Source: By Kirsten Grind, Tom McGinty and Sarah Krouse, Wall Street Journal October 25, 2017

Adding more efficiency to your investment manager selection process by allowing users to…
  • Cut through large volumes of data to hone in on what’s truly important
  • Screen for top performing fund managers who are most likely to outperform so that duediligence time can be spent more efficiently
  • Create fund manager rankings by predicted alpha so that deep dive due diligence is performed on the right managers
  • Visualize the texture of your manager performance on custom charts and graphs
  • Quickly run reports that provide insight into manager and portfolio performance

Aapryl’s Difference in Estimating Alpha

Aapryl’s Perspective on a
Typical Manager’s Investment Process

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How it Works?

Dissection of Total Manager Return
  • Aapryl creates a “clone” portfolio which is an investable portfolio representing a managers style
  • Residual excess returns are dissected into separate components in order to understand the managers performance
  • Manager return texture is analyzed by measuring consistency and magnitude of excess return
  • Stock selection and Style timing are graded and quantified for each manager
  • Predicted performance is forecasted through the quantitative sifting through these processes
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