Performance Attribution Analysis of investment performance.

Transcription

1 Performance Attribution Analysis of investment performance. 1 1 Performance Analysis Performance Attribution

2 Portfolio attribution is an integral component of the investment value chain for the portfolio manager, an aid for marketing and sales staff and enables relationship managers to demonstrate the success of an investment strategy.

3 Institutional investors expect their asset managers to keep them regularly apprised of the performance of their investment strategies. In this regard, highquality standardized and meaningful performance attribution analyses form a key part of the communication process. Portfolio managers need to be able to count on highly flexible attribution analyses that are tailored to the investment process to compare the results achieved against their expectations. But, what do investors and asset managers need when it comes to actual implementation of the performance attribution results? What were the significant factors and drivers of performance throughout the period under analysis? Are they in line with the agreed investment process? What practical steps must be taken for implementation of a low-resource process of continual performance attribution in an environment of diverse fund products, a growing variety of investment instruments and divergent demands on availability and quality of necessary data? For example: If deviations between the transaction price, individual position and benchmark valuations are outside of the defined tolerances, this has a bearing on the measures to be implemented. Such discrepancies can only be rectified through conscientious revaluation. In order to derive effective solutions, the questions above must be answered. To this end, a structured Needs Analysis ( see fig. 1 ) is used to generate a customer-specific catalog of demands. Figure 1 Needs Analysis Identification of target groups (portfolio managers, management...) Identification of investment process determinants Definition of necessary reports Determination of general methodological and technical requirements Transaction vs. positionbased method Factor-based vs. Brinson method Relevant fund products and financial instruments Necessary data and interface analysis Preparation of detailed requirement catalog Selection of preferred solution Performance Analysis Performance Attribution 2 3

4 Conventional methods, however, are unable to equally address all of these different needs. There are differences, e.g. between position-based and transaction-based methods, or emerging from the special set of characteristics affecting funds of funds (see fig. 2 and 3). IDS GmbH Analysis and Reporting Services (IDS) offers a broad spectrum of customized solutions, and onestop shopping no matter what your specific needs. Portfolio managers trust IDS to provide comprehensive answers to their questions. IDS achieves solutions that also provide valuable information for product management and can be drawn on by marketing and sales teams. The analysis can focus on contribution information with regard to absolute performance as well as on attribution information in terms of relative performance against a benchmark. Figure 2 Comparison of transaction and position-based methods Data basis Transaction-based Includes intraday transaction data with trading prices Position-based Aggregate end-of-day position valuations per asset Time lag Accuracy Higher data demand, time lag resulting from transaction settlement, longer computing times More precise replication of official portfolio return Lower data demand, no time lag given ready data availability, shorter computing times Approximate replication of portfolio return Use Frequently used for regular reporting to institutional clients Frequently used as operational support for the daily management process Figure 3 Special characteristics: funds of funds Special characteristics: funds of funds Breakdown of asset management process into an allocation decision hierarchy (asset allocation, sub-segment allocation, target fund selection) Classical breakdown into allocation and selection is often ineffective for precise attribution of performance to decision makers / situations Method Time lag Accuracy Allocation-based approach Expansion of attribution components: asset class allocation, sub-segment allocation, target fund contribution at sub-segment level Timing dependent on publication of unit prices of the target fund Generally no limit on sub-segments Use Special method developed for use with funds of funds Performance Analysis Performance Attribution

5 As a client, you will receive detailed insight, not only from individual instrument-based analysis, but also asset class-based analysis that can be effectively deployed to derive appropriate allocation and selection decisions in the investment process for multi-asset class portfolios. This type of analysis is also useful in relation to the special aspects of investing in target funds for evaluating funds of funds. Features Transaction-based or position-based performance attributions Brinson-type attributions or attributions based on (multi-)factor models Any desired valuation frequency (daily, weekly, monthly ) Multi-asset class attributions Individual instrument-based and asset class-based attributions Broad coverage of almost all established investment types and asset classes Treatment of derivatives according to purpose (asset allocation, maturity management, hedging) Separation of allocation and selection contributions of target funds for fund of funds analysis Individual and multi-period analysis Flexible reporting engine Benefits Access to market-proven performance attribution methods Attribution models customized to client needs Low implementation costs Maximum process reliability Option of adding market data (e.g. benchmark data or investment static data) to optimize data quality Option of a benchmark-based revaluation Option of benchmark adjustment for funds of funds, to minimize performance effects from the time lag between target fund and benchmark valuation Access to expert knowledge in the application and interpretation of performance attribution analyses 4 5

6 Functionalities Transaction-based attribution Transaction-based attribution analyses explain the investment performance right down to its basis point. This is not only an important asset for account managers when communicating with the client, but also plays a key role in controlling the investment value chain of multi-manager and multi-asset portfolios. If basis points are crucial, transaction-based attribution is the method of choice explained performance being equal to official performance. Position and transaction data is usually transmitted from back office or custodian bank systems into the IDS infrastructure. Thanks to our long experience in interface design, IDS is able to actively support the integration process. Figure 4 Performance, benchmark and portfolio structure of a bond portfolio Overview Portfolio Return 3.14 % Initial Market Value 9,317,449 EUR Initial Cash Value 11,735 EUR Benchmark Return 4.17 % Final Market Value 9,24,479 EUR Final Cash Value 198,53 EUR Relative Return 1.57 % Net Investment 313,684 EUR Performance 3 Sep Mar 211 Portfolio Structure /21 1/21 11/21 12/21 1/211 2/211 3/211 9/21 3/211 Portfolio Benchmark Bonds Cash Performance Analysis Performance Attribution

7 In addition, IDS offers the option of adding market data to the information available, thus opening up new dimensions of analysis and further pinpointing results. Besides adding attribution-relevant measures such as duration or Greeks, a large number of indices and benchmarks at the individual instrument level can be retrieved from IDS proprietary market data pool. Position data can be revalued based on benchmark prices to minimize any distortions arising due to different pricing sources. The analysis systems used by IDS are also distinguished by their high degree of flexibility with regard to the attribution methodology they apply. This allows for the use of traditional models such as Brinson-Fachler, as well as specifying and applying factor models that are customized to the client's needs and wishes in the case of complex investment strategies. Figure 5 Performance breakdown of a bond portfolio according to shift, curve and credit spread effects Performance 3 Sep Mar Shift Effect Active Duration Contribution Movement in Yield Shift Effect -1 yr yrs yrs yrs yrs yrs yrs yrs 3 yrs and above /21 1/21 11/21 12/21 1/211 2/211 3/211 Total (yrs) (bp/yr) (bp) Active Duration Contribution Movement in Yield Shift Effect Curve Effect Active Duration Contribution Government Yield in Buckets Curve Credit Spread Effect Active Duration Contribution Yield in Buckets Movement -1 yr yr yrs yrs yrs yrs yrs yrs yrs yrs yrs yrs yrs yrs yrs yrs yrs and above yrs and above Total Total (yrs) (bp/yr) (bp) (yrs) (bp/yr) (bp) Active Duration Contribution Government Yield in Buckets Shift Effect Active Duration Contribution Yield in Buckets Movement Credit Spread 6 7

8 Position-based attribution Only a few data items from the client are needed to perform a position-based attribution analysis. The required data can be sourced from front, middle and back office or from custodian bank systems. IDS also offers the option of adding market data, which further reduces the input required from the client. Although usually less exact than their transactionbased counterparts, the position-based analyses are a particularly useful support in the investment process. As our client, you will benefit from the analysis systems used by IDS, which are distinguished not only by their scalable infrastructure that provides for timely and highfrequency analyses, but also by their high degree of flexibility as regards the attribution methodology applied. Figure 6 Performance attribution by industry sector of an equity portfolio Stoxx 5 (in EUR) 4.79 % MSCI Europe (in EUR) 6.42 % Active Return (AR) 1.63 % Intra-Period Effect. % Groups Average Weight Total Return Attribution Effects Sector Consumer Discretionary Consumer Staples Energy Financials Health Care Industrials Information Technology Materials Telecomm Services Utilities Portfolio Benchmark Relative 2.7 % 8.8 % 6.1 % 13.1 % 12.4 %.6% 13.6 % 1.4 % 3.2 % 26.5 % 22.2 % 4.3 % 15.7 % 9.9 % 5.8% 4.2 % 1.8 % 6.6% 3.3 % 2.8 %.5 % 8.7 % 1.3 % 1.6 % 9.1 % 6.8 % 2.2 % 3.1 % 5.5 % 2.3 % Portfolio Benchmark Relative 3.1 % 9.7 % 6.6% 7.5 % 5.7 % 1.8 % 1.6 % 11.8 % 1.2 % 4.8 % 2.4 % 2.4 % 2.3 % 3.6% 1.4 % 15.4 % 11.1 % 4.3 % 5.7 % 7.8 % 2.1 % 27.3 % 2.8 % 6.5 % 1.9 % 2.3 %.4% 5.7 % 5. %.8 % Allocation Selection Total.2 %.17 %.38 %.1%.24%.23 %.17 %.16%.1%.4 %.69 % 1.8 %.17 %.22 %.38 %.3 %.17 %.13 %. %.7 %.6%.23 %.45 %.23 %.9 %.3 %.13 %.1%.2 %.6% Equity 1. % 1. % 4.8 % 6.4% 1.6 % 1.19 %.44% 1.63 % Attribution Charts Average Weight Total Return Attribution Effects Relative Weight Sector Return (Bmk) Allocation Effect Selection Effect Total Effect Consumer Discretionary Consumer Staples Energy Financials Health Care Industrials Information Technology Materials Telecomm Services Utilities 1% 1% 2% 1% 1% 1% 1% 2% 1% Performance Analysis Performance Attribution

9 Model-based multi-factor attributions are supported, as are single- and multi-level Brinson-Fachler attributions. Thanks to the latter s high degree of flexibility, investment performance can be analyzed from a large variety of perspectives an indispensable tool for any asset manager when ensuring that performance sources are consistent with the investment process. Figure 7 Best and worst individual position contribution in an equity portfolio Stoxx 5 (in EUR) 2.73 % Best Average Weight Stock Absolute Contrib. Worst Average Weight Stock Absolute Contrib. Name Banco Santander Sa Bnp Paribas Total Banco Bilbao Vizcaya Ar Hsbc Hldgs Vodafone Group Allianz Se Axa Telefonica Sa Societe Generale Unicredit Spa Bp Barclays Intesa Sanpaolo S.P.A. Bg Group Ing Greop Nv Sap Ag Deutsche Bank Ag Siemens Ag Ubs Ag Portfolio 2.6 % 1.9 % 3.4 % 1.4 % 5.3 % 4. % 1.6 % 1. % 2.6 % 1.2 % 1.1 % 4. % 1.4 %.9 % 1.9 % 1.1 % 1.4 % 1.5 % 2.9 % 1.7 % Return 14 % 15 % 8% 2 % 5% 6% 14 % 24 % 8% 17 % 17 % 4% 12 % 2 % 8% 14 % 11 % 1 % 4% 7% 36 bp 27 bp 26 bp 26 bp 24 bp 23 bp 22 bp 21 bp 21 bp 2 bp 17 bp 17 bp 16 bp 16 bp 16 bp 15 bp 15 bp 14 bp 12 bp 12 bp Name Nestle Sa Novartis Ag Glaxosmithkline Bhp Billiton Plc Anglo American British American Tobacc Rio Tinto Basf Se Unilever Nv Standard Chartered Tesco Anheuser-Busch Inbev Bayer Ag Hennes & Mauritz Portfolio 5.3 % 3.9 % 2.8 % 2.4 % 1.9 % 2.1 % 2.7 % 2. % 1.3 % 1.5 % 1.5 % 1.2 % 1.7 %.9 % Return 9 % 7 % 9 % 7 % 8 % 6 % 4 % 6 % 7 % 5 % 5 % 6 % 3 % 3 % 55 bp 29 bp 26 bp 17 bp 16 bp 14 bp 13 bp 12 bp 1 bp 8 bp 8 bp 7 bp 5 bp 3 bp Totals Best 1 Next Best % 17.9 % 244 bp 15 bp Totals Worst 1 Next Worst % 2.5 % 2 bp 22 bp Best % 393 bp Worst % 222 bp All Positive (439) (ex cash) 69. % 495 bp All Negativ (14) (ex cash) 31. % 222 bp 8 9

10 Allocation-oriented attribution Based on comparable data demands for transactionbased attribution, IDS offers highly flexible asset class-based attribution analyses for fund of funds and multi-asset portfolios that are tailored to the investment process. Typically, these types of portfolios have an investment process that is characterized by allocation decisions at a variety of levels and generally involve investment in numerous different asset classes. A wide range of funds, certificates and derivatives are employed for implementation of selection decisions. In order to minimize relative performance distortions arising from timing differences in the valuation of portfolio components and the benchmark, IDS offers benchmark-based revaluation of position data. For funds of funds, valuation gaps are minimized through benchmark adjustment. The quality of analyses depends largely on the right mapping of the asset class-structure, allocation of individual instruments to the appropriate segments and assignment of target funds to specific target fund benchmarks. This kind of information is usually not available in the data delivery systems, and must instead be obtained directly from the portfolio management. Grounded and purposeful analysis is ensured through result-driven communication with the experts from IDS, which forms a key element of the overall process. Flexible reporting engine In terms of the necessary information and desired level of detail, reporting for the purpose of direct investor communication usually differs from the high-frequency reporting needed to support the investment process. IDS attribution tools are integrated into an efficient and scalable reporting infrastructure, enabling us to offer client-specific reporting services. Consequently, IDS supports numerous reporting formats, which can be customized for a variety of distribution channels. The spectrum ranges from pixel-perfect reports that are packaged and ready for printing, to size-optimized report files for Web download or data streaming for Web applications. You can draw on existing reporting solutions or develop a reporting solution in collaboration with IDS, which is custom-tailored to your specific needs. Advisory service maximum process reliability You will also benefit from the many years of experience IDS has in implementing and using various attribution analysis systems and methods. Having detailed knowledge of the strengths and weaknesses of individual approaches is a key factor in the appropriate interpretation of the analysis results. IDS places its excellent expertise at your disposal to ensure your success. By professionally implementing the data interface and using an efficient, stable and scalable technical infrastructure, IDS eliminates the process risk associated with local installation of performance attribution solutions. Performance Analysis Performance Attribution

11 Risiko Liquiditätsreporting Risiko Liquiditätsreporting Risiko Liquiditätsreporting Performance Analysis Return results from many decisions. We calculate and compare portfolio performance and identify major factors of success. Related Products Outperformance Fee GIPS Service Peer Group Analysis Outperformance Fee Result-oriented management compensation. GIPS Service Calculating and reporting performance according to the Global Investment Performance Standards (GIPS). Peer Group Analysis Identifying the competitive positioning of funds

12 Contact Thomas Kirchherr Tel thomas.kirchherr@investmentdataservices.com Dr. Ulrich Raber Tel ulrich.raber@investmentdataservices.com Dr. Kamil Zielinski Tel kamil.zielinski@idsffm.com IDS GmbH Analysis and Reporting Services Koeniginstrasse 28, 882 Munich, Germany For further information about IDS and all of our products, please visit IDS GmbH Analysis and Reporting Services All rights reserved. All information subject to change at any time. February Performance 214-2_EN_PFS_Performance_Attribution Analysis Performance Attribution