Generating Alpha Based On Forecasts Integrated Active Asset Management Mitev Kuehrer

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Case Study Presentation at the FoHF Summit 2nd – 4th June 2008 Le Meridien Beach Plaza, Monte-Carlo, Monaco

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Generating Alpha Based On Forecasts Integrated Active Asset Management Mitev Kuehrer

  1. 1. s Alpha Generation based on Forecasts – Intergrated Active Asset Management European fund of hedge funds summit a marcusevans FoF summit series event 2 - 4 June 2008 | Le Méridien Beach Plaza | Monte-Carlo | Monaco
  2. 2. s Disclaimer Quantitative Analysis & Optimization The views and opinions expressed in this presentation are those of the authors only, and do not necessarily represent the views and opinions of Siemens AG, or any of its employees. The authors make no representations or warranty, either expressed or implied, as to the accuracy or completeness of the information contained in this presentation, nor is he recommending that this presentation serves as the basis for any investment decision. This presentation is prepared for the European fund of hedge funds summit on 2 - 4 June 2008 in Monte-Carlo, Monaco only. Research support from Fin4Cast is gratefully acknowledged. Dr. Miroslav Mitev & Dr. Martin Kuehrer - Siemens AG Österreich, Siemens IT Solutions and Services, Program and System Engineering, Fin4Cast, Gudrunstrasse 11, 1100 Vienna, Austria, Phone: +43 (0) 517 07 46253, Fax: +43 (0) 517 07 56256, email: info@fin4cast.com, www.fin4cast.com/indices. The corresponding paper “New trends in Active Asset Management: Integration of Research, Portfolio Construction and Strategy Implementation for Systematic Investment Strategies in the Time of Algo-Trading” is available upon request. May 08 2
  3. 3. s Quantitative Agenda Analysis & Optimization Introduction of Siemens fin4cast New trends in Active Asset Management – Integration of Research, Portfolio Construction and Strategy Implementation Siemens fin4cast Integrated Active Asset Management Approach Case Study – fin4cast Income Index Conclusion and Q&A May 08 3
  4. 4. s Quantitative Introduction of Siemens fin4cast Analysis & Optimization fin4cast has its roots in an internal project for Siemens pension and treasury department in 1995. fin4cast with 50 staff is based in Vienna, Austria. fin4cast is part of the Program and System Engineering (PSE) division of Siemens AG Österreich (SAGÖ). SAGÖ group with 30.000 staff is headquartered in Vienna, Austria. PSE with 7 000 staff and locations in 10 countries is headquartered in Vienna, Austria. PSE offers hardware and software solutions, selected products, as well as a broad range of services for the entire field of information and communications technology, primarily to Siemens in-house groups and divisions. fin4cast is a provider of quantitative and pure systematic investment strategies, designed to adapt to the current market environment. May 08 4
  5. 5. s Quantitative PSE Services provided to Siemens Groups and Divisions Analysis & Optimization PG A&D ICN Siemens AG Österreich PG A&D ICN Siemens AG Österreich Power Generation Automation and Drives Information and Internal contracts Power Generation Automation and Drives Information and Internal contracts Communication Networks Communication Networks PTD I&S ICM Other PTD I&S ICM Other Power Transmission and Industrial Solutions Information an regional companies Power Transmission and Industrial Solutions Information an regional companies Distribution and Services Communication Mobile Distribution and Services Communication Mobile TS SD SBS TS SD SBS Transportation Systems Siemens Dematic AG Siemens Business Services Transportation Systems Siemens Dematic AG Siemens Business Services GmbH & Co. OHG GmbH & Co. OHG SV SBT MED PSE SV SBT MED PSE Siemens VDO Siemens Building Medical Solutions Siemens VDO Siemens Building Medical Solutions Program and Program and Automotive AG Technologies AG Automotive AG Technologies AG System Engineering System Engineering SFS Osram GmbH Central units SFS Osram GmbH Central units Siemens Financial Siemens Financial Services GmbH Services GmbH Infineon Fujitsu Siemens INNOVEST Infineon Fujitsu Siemens INNOVEST Infineon Technologies AG Computers Kapitalanlage AG Infineon Technologies AG Computers Kapitalanlage AG May 08 5
  6. 6. s Quantitative Introduction Siemens fin4cast Analysis & Optimization For its own use Siemens monitored currencies, commodities and - especially for its pension funds – stock and bond markets. Siemens also developed quantitative tactical asset allocation strategies for its own requirements. fin4cast was established in 1995 to develop and to apply complex quantitative methods for predicting returns and estimating risks of individual financial instruments, and for optimizing of investment portfolios. The main objective of fin4cast project was to adapt the already existing load forecasting and power plant optimization Siemens technology to the global financial markets and to leverage the existing quantitative Know-How. As result, the unique fin4cast technology emerged providing Siemens with a strong competitive edge and ability to develop innovative, quantitative and pure systematic investment strategies. May 08 6
  7. 7. s Quantitative New Trends in Active Asset Management Analysis & Optimization Integration of Research, Portfolio Construction & Strategy Implementation Portfolio Strategy Research Construction Implementation • Order Generation • Target Analysis • Maximize Return • Minimize Risk • Order Execution • Input Pre-selection • Risk/Return Optimization • Risk Management • Input Selection • Optimal Asset Allocation • Slippage Analysis • Forecasting • Portfolio Analysis Portfolio Analysis & Back-propagation Slippage Analysis & Back-propagation May 08 7
  8. 8. s fin4cast Integrated Research Process Quantitative Analysis & From Data Acquisition to Forecasts Generation Optimization Data storage, Data Input pre-selection Input Selection processing & Acquisition cleaning Criteria: Search Algorithms: • Reuters • economical • Neighborhood search • Thomson • statistical • Iterative improvement Financial approaches • Genetic Algorithm Linear Models Forecast Post analysis • ARIMA/SARIMA Comparative in sample and out of • VAR/VARX sample tests • Factor Models (Forecast Statistics) • ARCH/GARCH Evaluation rejected Estimation methods: AOLS, WOLS, SUR, ML. Forward tests (Forecast Statistics) Non Linear Models • Single & Multi Output MLP Evaluation rejected Learning Algorithms Forecasts • Steepest Descent • Quick prop May 08 8
  9. 9. s Integration of Research - Input Selection for the Quantitative Analysis & Mathematical Forecasting Models Optimization Original Economical Technical Statistical Input Set Search Optimized Input Set Criteria Analysis Analysis Algorithm Input Set app.. 2000 app.. 800 app.. 3500 app.. 100 app.. 20 Time Series Time Series Time Series Time Series Time Series Macro gs Correlation & La Economic Stationarity Regression Interest Analysis Correlation Rates AN Algorithm Dynamic Price Data Correlation Generic Currency Algorithm Normality Rates Economical Granger etc. Selection Causality Grading Sensitivity Stochastic max. 20 most Analysis Oscillators important driving factors Relative Principal of the future Differences Component & returns of a pre- (Exponential) Factor specified asset, Moving Analysis e.g. S&P 500 Average Cluster Future May 08 etc. Reduction 9
  10. 10. s Integration of Research - Building & Evaluating of the Quantitative Analysis & Mathematical Forecasting Models Optimization Linear Modeling Forecasts Internal Selection of Model & Number of Factors and Method Inputs Forecast Post-analysis ARIMA/SARIMA Optimized Input Set VAR & VARX • Correlation Factor Models • R2 & ARCH/GARCH extended R2 • Hitrate • Residual Non Linear Modeling Analysis • Normality Model & Network Topology and Tests Method Parameter Tuning • etc. Single Output MLP Multi Output MLP May 08 10
  11. 11. s Integration of Research – Selecting of the best Mathematical Quantitative Analysis & Forecasting Models Optimization Use of Model In Sample Out of Sample Forward Combination Models 500.000 Models 200.000 Models 50.000 Models today live calculation of the mathematical models 1. Nov 2003 1. Jan 2000 (model compilation) Evaluation of Selecting the Continuos Postanalysis of accuracy Model building best of forecasts accuracy of adjustment • Building the basic model forecasting min. 30 weeks forecasts and Models • linear vs. non linear min. 4 weeks optimization • stability of the model •Baysian • can take several weeks in real environment Model • Adjusting and to find optimal model Averaging Optimizing •AIC & BIC • real testing Model Combination During the „Out-of-Sample“, „Forward“, and „Use of Model“ Process the mathematical May 08 model is adjusted periodically to the changing market environment! 11
  12. 12. s fin4cast Integrated Portfolio Construction Process Quantitative Analysis & From Forecasts Generation to Asset Allocation Optimization Actual Portfolio Objective Function Weights Maximize φ(x) = pTx – ½ R xTQx – SC(x0, x) Forecast for each Maximization of expected portfolio asset return by simultaneous minimization of expected portfolio risk and Inputs for the Portfolio Construction return forecasts implementation costs for the Long/Short respective coming period directional forecasts Asset Allocation forecasts of the returns’ distribution e.g. Portfolio Optimization Risk matrix + 15% •Quadratic Optimization - 20% •Ranking estimated variance-co- - 10% variance matrix (market risk) + 30% estimated residual Constraints diagonal matrix (forecasting & model risk) Market Neutrality, Long/Short, Exposure, etc. estimated slippage (implementation risk) Min. or max. investment to a single asset or an asset class Combinatorial constraints Risk aversion Turn-over constraints May 08 12
  13. 13. s fin4cast Integrated Strategy Implementation Process Quantitative Analysis & From Asset Allocation to Order Execution & Portfolio Analysis Optimization Siemens in-house or Siemensfin4cast Application Server Siemensfin4cast Thechnology external institutions 13 Portfolio Reconceliation, Portfolio Proposed Asset Allocation & 1 Analysis & Risk Management Consistency Checks Confirmed weights & number of contracts •Slippage Analysis Internet (128 Bit SSL) •Implementation Short Fall Pre-Trade Analysis •Return/Risk Analysis 2 •Stop-Loss 3 •If-than & Stress Tests 12 FIX Engine Scenarios 4 FIX 4.2 11 Radianz Network Brokers FIX Engine Exchange(s) reject 10 5 Consistency Checks Confirmation Orders of the 9 6 Execution Trading System 7 Interfaces 8 May 08 13
  14. 14. s Case Study – fin4cast Income Index Quantitative Analysis & Objectives Optimization The fin4cast Income Index follows a directional long/short investment strategy. This strategy seeks to profit from price inefficiencies between the most liquid stock index futures, currency futures, and commodity futures world wide. Through a combination of long and short positions the strategy targets to take advantage from market moves and relative value opportunities. The strategy is characterized through its broad diversification between regions and asset classes. According to the forecasts generated by Siemens fin4cast Technology the fin4cast Income Index I consists of a basket of long positions in those futures with the highest up wards potential and a basket of short positions in those futures showing signs of weakness. The strategy aims to achieve an absolute equity like return at fixed income level of risk. May 08 14
  15. 15. s Case Study – fin4cast Income Index Quantitative Analysis & Investment Universe Optimization The current investment universe consists of the 37 most liquid futures world wide. Siemens fin4cast is continuously anxious to increase the investment universe subject to forecast ability, tradability and liquidity constraints. According to the results of permanent quality checks Siemens fin4cast might temporarily remove one or more futures from the investment universe due to forecasting quality concerns. Stock Index Futures: DJ Euro Stoxx 50 Index, DAX 30 Index, FTSE 100 Index, S&P 500 Index, Nasdaq 100 Index, Nikkei 225 Index, Russell 2000 Index, Hang Seng Index, MSCI Taiwan Index, S&P ASX 200 Index, Tokyo Price Index, MSCI Singapore Index, Kuala Lumpur Stock Index, Bangkok S.E.T Index, Kospi 200 Index Currency Futures: EUR/GBP, EUR/JPY, EUR/CHF, JPY, CHF, GBP, AUD Commodity Futures: Corn, Soybean, Wheat, Lean Hog, Live Cattle, Copper, Gold, Silver, Cotton, Sugar, Light Sweet Crude Oil, Cocoa, Palladium, Platinum May 08 15
  16. 16. s Case Study – fin4cast Income Index Quantitative Analysis & Portfolio Guidelines Optimization fin4cast Income Index can take long or short positions in the underlying futures The max. allocation to each stock index futures is 50% The max. allocation to each currency futures is 10% The max. allocation to each commodity futures is 40% fin4cast Income Index is rebalanced on a bi-weekly basis, on Monday and Wednesday fin4cast Income Index does not account for interest gains in local currency resulting from the margin account Interest gains on the capital not held in margin account are included. For the interest calculation 3 months USD LIBOR is used Transaction costs of 1 basis point for currency and stock index futures and 2 basis points for commodity futures are included in the index calculation fin4cast Income Index is adjusted to account for 2% p.a. index calculation fee and FIX- technology fee fin4cast Income Index is marked-to-market with close of the day future prices fin4cast Income Index is USD denominated, margins and daily P&L are converted into USD on a daily basis May 08 16
  17. 17. s Case Study – fin4cast Income Index Quantitative Analysis & Performance Optimization May 08 17
  18. 18. s Case Study – fin4cast Income Index Quantitative Analysis & Comparitive Performance & Asset Allocation Optimization May 08 18 Source: Siemens fin4cast. Correlations, Returns and Standard Deviations are based on monthly returns back to March 1999
  19. 19. s Quantitative Conclusion and Q&A Analysis & Optimization New trends in Active Asset Management – Integration of Research, Portfolio Construction and Strategy Implementation fin4cast Integrated Active Asset Management Approach Case Study: fin4cast Income Index Q&A May 08 19
  20. 20. s Quantitative References Analysis & Optimization Bessembinder, H. and Seguin, P. J., (1993); Price Volatility, Trading Volume, and Market Depth: Evidence from Futures Markets; The Journal of Financial and Quantitative Analysis, Vol. 28, No. 1 (pp. 21-39) Brown, S., Koch, T. and Power, E., (2006); Slippage and the Choice of Market or Limit Orders in Futures Trading Gartner, M., Kührer M. and Mitev M., Slippage, (2007); Pre-order and Post-order Analysis in Futures Trading: An Empirical Study Grinold, Richard C. and Kahn, Ronald N., (2000); Active Portfolio Management. A quantitative Approach for Producing Superior Returns and Controlling Risk; 2nd edition McGraw-Hill Lee, Charles M. C., (1993); Market Integration and Price Execution for NYSE-Listed Securities; The Journal of Finance, Vol. 48, No. 3 (pp. 1009-1038) Mitev, Miroslav, (2003); A systematic investment process for alternative and traditional investment strategy, Dissertation, Institute for Statistics and Operations Research, School of Economics and Social Sciences, Karl-Franzen-University GRAZ Perold, Andre F., (1988); The implementation shortfall: Paper versus reality; Journal of Portfolio Management; Vol 14, pp 4-9 Prix, Johannes, Loistl, Otto and Hütl, Michael, (2007); Algorithmic Trading Patterns in Xetra Orders, The European Journal of Finance; Vol 13, No 8, pp 717-739 H. Rehkugler, D. Jandra, Kointegrations- und Fehlerkorrekturmodelle zur Finanzmarktprognose May 08 20
  21. 21. s Biographies Quantitative Analysis & Dr. Miroslav Mitev Dr. Martin Kuehrer Siemens AG Österreich Siemens AG Österreich Optimization Siemens IT Solutions and Services Siemens IT Solutions and Services PSE/fin4cast PSE/fin4cast Phone: +43 (0) 51707 46253 Phone: +43 (0) 51707 46360 Fax: +43 (0) 51707 56465 Fax: +43 (0) 51707 56465 Mobile: +43 (0) 676 9050903 Mobile: +43 (0) 676 3917274 Email: miroslav.mitev@siemens.com Email: martin.kuehrer@siemens.com Dr Martin Kuehrer is a managing director and head of Dr Miroslav Mitev is a managing director and head of quantitative quantitative strategies at Siemens/fin4cast. Dr Kuehrer has been research and strategy development at Siemens/fin4cast. Dr Mitev is with Siemens for 14 years in various different functions. Prior to responsible for the development of innovative, systematic long-short joining Siemens in 1994 Dr Kuehrer held a number of positions investment strategies for institutional investors world wide based on with prominent engineering companies. Dr Kuehrer has steered Siemens/fin4cast technology. After joining Siemens in 2001 Dr Mitev successfully formed a qualified team of 25 professionals which is the quantitative strategies proposition from its beginnings and continuously developing the Siemens/fin4cast Technology and building has formed numerous successful partnerships with financial mathematical forecasting models for a variety of financial instruments institutions. Dr Kuehrer is a regular speaker at international like currency futures, commodity futures, stock index futures, bond conventions on asset management and quantitative investment futures, single stocks and hedge fund indices. Dr Mitev is in charge of management. Dr Kuehrer has degrees in engineering and the Siemens/fin4cast’s research cooperation with various universities business administration as well as a PhD in finance. and is actively involved in the scientific management of numerous master thesis and dissertations. Dr Mitev is a regular speaker at international conventions on liability driven investing, asset management, hedge funds, portable alpha, advanced quantitative studies, algo-trading and system research. Dr Mitev’s research is published on a regular basis in international journals and presented on international scientific conferences. Prior to joining Siemens Dr Mitev was at CA IB, the Investment Bank of Bank Austria Group, where he was in charge of the quantitative research of the securities research division. Dr Mitev received a Master of Economics and Business Administration May 08 with main focus on Investment Banking and Capital Markets. Dr Mitev also received a PhD in Economics with main focus on Finance and 21 Econometrics.

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