Performance Attribution

When analysing performance, measuring a portfolio’s actual return answers the “what” and “when” questions –– it tells us what return the portfolio delivered over a specified period of time. While that information is obviously important, the goal of a performance attribution analysis is to go beyond “what” and “when” to explain “how” and “why”.

Measuring actual performance (answering the “what” and “when”) is no simple feat. It requires keeping an accurate record of the portfolio’s daily positions and transactions, the prices for all of the securities and the ability to link daily returns together. That demands a system that can pull together a combination of data feeds from various sources, even for portfolios that contain only equities and listed derivatives. When portfolios hold fixed income securities there is another layer of complexity, as there is no single, “true” source of prices in that market. OTC derivatives are also often difficult to price, and one must apply the appropriate FX rates if there is more than one currency held in the portfolio.

Constructing a robust, multi-asset class Performance Attribution analysis is even more challenging. In addition to the portfolio positions and securities prices mentioned above, analysing whether a return came from a change in accruals, a yield curve shift, or a change in volatility requires market data, terms and conditions such as coupon or dividend rates, payment dates and day counts for accruals for each security held, and more calculations. This precise, extensive set of data needed to capture what the portfolio held over the period in question and what happened in the relevant markets, is the starting point for a portfolio attribution analysis.

Portfolio Attribution solutions should be flexible, transparent and scalable

The Portfolio Attribution analysis in TS Imagine is designed to be intuitive, flexible and transparent, with the ability to drill down to obtain the level of detail required. We provide the market data, terms and conditions data to support the underlying calculations instead of requiring clients to source those inputs separately. We also recognize that speed and scalability are essential. An asset management firm with hundreds (or even thousands) of portfolios cannot use a system that takes 30 minutes or more to produce a set of reports for one portfolio.

As noted above, before we can begin attribution analysis we must first compute return. TS Imagine offers the following flexibility in computing performance:

  • Time-weighted and Money-weighted (IRR) return methodologies
  • Calculations gross or net of fees
  • Transactions-based or Holdings-based calculations
  • Ability to track cash flow movements (subscriptions/redemptions)
  • Relative returns linked geometrically over time
  • Accurate treatment of derivatives and short positions
  • Firm-wide performance (by Team, Asset Class etc.)

Returns can be calculated at various frequencies (daily, weekly, monthly, quarterly and yearly), and clients can customise the start/end dates of the calculation period.

The Performance Summary screen in Figure 1 shows returns by asset type, with drill-down capabilities in each category. P&L and Market Value are provided in absolute terms, along with percentage returns and return contributions for both the portfolio and benchmark, for each asset type. Returns can be calculated for Daily, Weekly, Monthly or Yearly time periods.

We also summarize Weekly, Monthly and Annual returns on a single report that shows P&L and percentage returns, along with a comparison to the selected benchmark, as shown in Figure 1.

Single report screen

Figure 1

Sources of Return

The heart of the Attribution analysis shows results by asset type, with drill-down to the security level. First, we break down the unrealised returns for positions held in the portfolio based on changes in market factors over the chosen period, as well as to the passage of time (i.e., accruals).

Figure 2

Unrealized returns are attributable to a number of components, including changes in FX rates, equity price changes, dividend accruals, an imputed borrowing cost for short positions, and various yield curve-based return elements such as roll, shifts and twists in the underlying yield curve, and changes in forward rates.

Clients have the ability to specify the tenors they want to use to define a yield curve shift and twist. Of course, that requires the necessary yield curves to be available –– we provide daily yield curves covering fixed income markets globally and have a robust approach to constructing curves, including situations when inputs between key tenors are sparse. Returns for derivatives are attributed to the change in the underlying (delta), to the passage of time (theta), and to a change in volatility (vega). The effect of changes in credit spreads is calculated where appropriate (e.g., corporate bonds and CDS).

Ideally, the sum of all of these components fully explains the returns for every instrument held in the portfolio. In practice, that is rarely the case. The residual represents the portion of return that is not explained by the various components, typically representing idiosyncratic returns. Note that an unusually large residual may be a red flag indicating a pricing error in a data feed.

We also attribute realised returns for positions that were reduced or exited during the analysis period. This includes adjustments for financing and dividends, fees and commissions, and trading effects. Finally, for fixed income securities we differentiate between realized and unrealized interest income.

The suite of Performance Attribution tools includes a Brinson analysis that attributes returns relative to a benchmark based on asset allocation/weighting choices, the security selections (relative performance) within each asset class or category, and an interaction component. Charts help to clearly identify the main drivers of return in the Brinson context.

Brinson analysis
Figure 3

Detailed and Customizable

Accurate, detailed calculations are essential to an attribution analysis as portfolio managers and CIOs must be able to rely on the results to understand whether or not buy/sell decisions and portfolio allocation strategies worked well and why. That informs decisions about where to go from here, whether to modify, stay the course, or re-examine key assumptions. The ability to drill down to the security level and to extract information for internal audit purposes is essential, and TS Imagine makes this process easy.

An attribution analysis must be designed in a way that is consistent with how the portfolios are actually managed. Therefore, we give clients the ability to customize the attribution framework.

  • Brinson allocation categories – Clients can define and combine an infinite number of categories for performance calculations and Brinson attribution analyses. For example, some clients may wish to analyse portfolio returns by country because that is the primary allocation decision, and then by asset class within each country. Others may use GICS sectors as the primary classification, and so on.
  • Benchmark selection and rebalancing – In addition to the standard market indices supported in TS Imagine, clients have the ability to define their own benchmarks by combining two or more benchmarks with custom weights (e.g., 40% equity benchmark, 40% fixed income benchmark, 20% FX benchmark). A “model portfolio” can also be used as the benchmark. Custom benchmarks can be rebalanced with different frequencies to be consistent with how a manager’s performance is being evaluated.This flexibility allows clients to conduct various “What If” analyses, such as “what if we chose a different benchmark or grouped portfolio holding by different categories, etc.”. Important insights can be gained when performance is first analysed by grouping holdings by country, using country-specific benchmarks, then grouping by asset class and analysing performance against asset class-based benchmarks, rather than trying to find a single benchmark that contains all countries and all asset classes.

Risk Analytics

Given that return and risk are inextricably linked, in addition to the attribution analyses described above TS Imagine also provides the following risk analytics to help managers evaluate returns in light of the risks embedded in their portfolios.

  • Information ratio
  • Beta
  • Correlation coefficient
  • Sharpe , Treynor and Sortino Ratios
  • Max drawdown

Clients can specify the time period used for these calculations, can define beta against a specific benchmark or group of securities, and can even choose a specific risk-free rate. This degree of customization allows these risk metrics to be consistent with the way performance is evaluated.

Select a solution that is data driven with smart system architecture

Measuring and attributing portfolio performance across asset classes and geographic markets is a data-intensive, calculation-intensive exercise. It requires the ability to store daily positions, prices and market data, record or infer transactions, build yield curves, maintain benchmarks and link returns over time. To be usable, a system must be capable of generating reports quickly and at scale. All of this requires a thoughtfully designed system architecture and the expertise to understand all of the instruments held across all types of strategies, from long-only institutional portfolios to actively managed mutual funds, global macro hedge funds, family offices, sovereign wealth funds and more.

For more information about TS Imagine’s Performance Attribution capabilities or to schedule a demo of these features, please contact us.

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