Many of the top pension funds are using the Aapryl platform to gain insight into your products and skill. Aapryl’s manager skill prediction algorithms increase the likelihood of choosing tomorrow’s top performing managers, rather than yesterday’s. See what they see to with our customizable Aapryl Reports and be fully prepared when stepping into the boardroom.
By offering the ability to consolidate data, streamline processes, reduce risk, and increase performance, Aapryl provides you with a one-stop platform which integrates cutting edge intuitive tools that will transform the way in which you build and monitor your investment portfolios.
Centralized Data Hub
Aapryl integrates data from multiple data providers for equity and fixed income products:
Aapryl saves you time and expense by providing broad access to data from market leading 3rd party providers. Focus on what’s important – your investments – and let Aapryl manage the rest
Identify Skilled Managers
Average Alpha of Top Scoring Product vs Peer Group Average
Average Alpha, forward looking 36 months
Source: Out of sample average 3 year forward looking excess return vs Static clone (Managers with best Aapryl Score relative to peer group average) Equity – All quarterly Ratings from 1Q 2010, with performance through 2Q 2018 Please see our efficacy paper in the resource center at www.aapryl.com for a more detailed explanation of methods. Fixed income – All quarterly Ratings from 1Q 2005, with performance through 4Q 2019.
Improved Quantitative Screening
How much Alpha would you need to be a top quintile manager (Trailing 12 months)?
Aapryl contextualizes the market conditions under which managers are likely to outperform, allowing investors to diversify their portfolio in a manner that aligns with their economic outlook
More Accurate Benchmarking
Aapryl Skill Scores replace standard market benchmarks with ”clone” portfolio benchmarks that capture significant and persistent style effects
Skill Metrics are further normalized for the length of the track record, with confidence and conviction growing with time.
Performance benchmarks are frequently imprecise measurements of manager skill
Aapryl’s customized benchmarks, or portfolio replication “clones” render superior performance evaluation
Skill Metrics are further normalized for the length of the track record, with confidence and conviction growing with time.
Sharper Alpha Targets
Aapryl Provides More Accurate and Stable Alpha Targets for Mean Variance Portfolio Optimization Along With Robust Risk Analysis
Frontier Chart
7 Manager Products; 1/1988 to 3/2019
Stress Test
7 Manager Products; 1/1988 to 6/2019
Skill Metrics are further normalized for the length of the track record, with confidence and conviction growing with time.
Aapryl’s Portfolio Analysis tool allows allocators to construct new portfolios and analyze existing ones. Construct your portfolio to maximize true alpha and skill as well as manage your risk
Insightful Portfolio Analysis & Optimization
Factor Exposures vs. Peer Group Average
Manager A – Stable Value; Weights (%); As of 6/2020
Aapryl’s customized benchmarks, or portfolio replication “clones”, render superior performance evaluation and objectively create peer groups for more relevant insights
Aapryl’s customized benchmarks, or portfolio replication “clones”, render superior performance evaluation and objectively create peer groups for more relevant insights
Style Engine
Benchmarks by which managers assess themselves are too broad, and thus fail to define the true style of a given asset manager. Aapryl addresses this problem by building 2 clone portfolios using returns based analysis (RBSA), where a time series of portfolio returns are regressed against a number of factors to explain what’s driving performance. The Static Clone uses inception to date figures capturing the dominant style exposure while the Static Clone identifies more recent style creep
Skill Analysis
Once a manager’s style is identified, their “true excess return” or skill can be calculated and decomposed. Traditionally, Excess Return or alpha is calculated as the difference between the manager’s return and it’s stated benchmark. Aapryl breaks down the traditional alpha further by stripping the style return away from its traditional Alpha, focusing on returns directly attributed to the manager’s active decisions and hence its true Alpha.
Clustering
When comparing managers to other managers, utilizing benchmark as the sole filtering criteria is not sufficient. A manager’s true style can vary significantly from their stated benchmark. Aapryl, using these clone portfolios, sorts managers into distinct peer groups or “clusters”. Excess return and thus, manager skill, can be compared to more like peers
Ranking
The calculation methodology within Aapryl’s skill analysis minimizes the past performance limitation evident in traditional metrics e.g. Information Ratio, Sharpe, Sortino etc. Based on extensive research and backtesting, Aapryl created a score system which calculates the probability a manager will be a top quartile manager over the next 3 years.
Market Trend Analysis
This provides users with an expectation of how managers can be expected to perform in various market environments. The chart also displays the returns of the benchmark and the manager’s peer group average for comparative purposes.
Centralized Data Hub
Aapryl integrates data from multiple data providers for equity and fixed income products:
Aapryl saves you time and expense by providing broad access to data from market leading 3rd party providers. Focus on what’s important – your investments – and let Aapryl manage the rest
Identify Skilled Managers
Average Alpha of Top Scoring Product vs Peer Group Average
Average Alpha, forward looking 36 months
Source: Out of sample average 3 year forward looking excess return vs Static clone (Managers with best Aapryl Score relative to peer group average) Equity – All quarterly Ratings from 1Q 2010, with performance through 2Q 2018 Please see our efficacy paper in the resource center at www.aapryl.com for a more detailed explanation of methods. Fixed income – All quarterly Ratings from 1Q 2005, with performance through 4Q 2019.
Improved Quantitative Screening
How much Alpha would you need to be a top quintile manager (Trailing 12 months)?
Aapryl contextualizes the market conditions under which managers are likely to outperform, allowing investors to diversify their portfolio in a manner that aligns with their economic outlook
More Accurate Benchmarking
Aapryl Skill Scores replace standard market benchmarks with ”clone” portfolio benchmarks that capture significant and persistent style effects
Skill Metrics are further normalized for the length of the track record, with confidence and conviction growing with time.
Performance benchmarks are frequently imprecise measurements of manager skill
Aapryl’s customized benchmarks, or portfolio replication “clones” render superior performance evaluation
Skill Metrics are further normalized for the length of the track record, with confidence and conviction growing with time.
Sharper Alpha Targets
Aapryl Provides More Accurate and Stable Alpha Targets for Mean Variance Portfolio Optimization Along With Robust Risk Analysis
Frontier Chart
7 Manager Products; 1/1988 to 3/2019
Stress Test
7 Manager Products; 1/1988 to 6/2019
Skill Metrics are further normalized for the length of the track record, with confidence and conviction growing with time.
Aapryl’s Portfolio Analysis tool allows allocators to construct new portfolios and analyze existing ones. Construct your portfolio to maximize true alpha and skill as well as manage your risk
Insightful Portfolio Analysis & Optimization
Factor Exposures vs. Peer Group Average
Manager A – Stable Value; Weights (%); As of 6/2020
Aapryl’s customized benchmarks, or portfolio replication “clones”, render superior performance evaluation and objectively create peer groups for more relevant insights
Aapryl’s customized benchmarks, or portfolio replication “clones”, render superior performance evaluation and objectively create peer groups for more relevant insights