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Governance, Transparency and Good Portfolio Management with Internetbased Tools www.mcubeit.com Dr. Arun Muralidhar Outline 1) Keys to Effective Portfolio Management: 5 Key Steps 2) Good Process Overcomes Challenges in Managing Funds 3) Technology Challenges: Where Web Applications Help 4) Using Web-based Technologies Effectively – Demo Structuring portfolios; understanding risks; converting risks into higher returns; using attribution to improve decisions 5) Using the Internet to Empower Investors 6) Summary and Conclusions 2 Who Benefits from This Presentation? Country pension funds Central banks Funds-for-the-future (e.g., funds to preserve wealth from the extraction and sale of commodities) Liability management organizations IT Departments: Help make front and middle office effective 3 1. Key to Success – Effective Decisions Annual Set Determine Objectives Benchmark Daily Outperform Benchmark Monthly Monthly Evaluate Performance Measure Risk Good management = must make many decisions well Must make these decisions in an informed manner Process, transparency and governance are critical Challenge: Can technology integrate front & back office? 4 1. Many Share Responsibility for a Fund AssetLiability Risk Tactical & Benchmark Risk Manager/ Active Risk Responsibility Responsibility Board of Governors Internal Staff Outside Managers Monitor Decision Frequency Annually Daily/Monthly Monthly Manage How to Manage the Risk Strategic Decisions – Need Good Reporting Effective Investment Decisions – Need IT Support Manager Selection Decisions – Good Reporting Need good technology to track and manage all decisions 5 1. Portfolio =Many Decisions Portfolio Asset Allocation Equity = 40% Bonds = 40% Sector/ Regional By Market (Local, US etc.) By Market (Local, US, Euro) Style Selection Large Stocks/ Small Stocks Govt./Agency etc. Manager Selection Cash/ Currency = 20% Mgr Mgr Mgr Mgr Mgr Mgr A B C D E F Bank 1 Bank 2 for Deposits for Deposits 6 2. Challenges in Managing Portfolios 1. Manage ongoing cash inflows and outflows 2. Evaluate and implement rebalancing strategies 3. Manager selection and allocations 4. Asset, country, style, sector or currency allocation A portfolio is very dynamic – impacted daily. Each decision can be a source of return or, if badly managed, can reduce returns 7 2. Challenges in Public Entities 1. Resource constrained: financial (budget) and staffing 2. “In public eye”: decisions are reviewed publicly 3. Need to demonstrate that decisions not political; need to show financial impact of political constraints 4. Good governance and transparency critical Challenge: Can technology empower staff, to raise return and lower risk while maintaining control? 8 3. Current Technology Challenges SILO SYSTEMS – Narrow Applicability: 1) Focus on only one asset (stocks/bonds) or one aspect (e.g., risk or performance measurement; trading) 2) Multiple systems; high cost to integrate/maintain 3) Required extensive training and client IT backup 4) Not designed by people who managed funds Senior managers are at risk – not knowing what is impacting the fund or how to correct it 9 3. Current Technology Challenges EXCEL based models are often used to make investment decisions, which from a technology perspective pose serious challenges: EXCEL models prone to error (not transparent) Key man risk (if staff leaves); create large teams as insurance Difficult to share ideas/analyses across organization Managers are at risk if the models have errors Alternative technology must be transparent, robust, inexpensive and easy to use! 10 3. Web/ASP Model Overcomes Problems Enterprise system can be implemented at low cost Easy to use and can customize their overall fund Support all asset areas in one technology Link portfolio management, risk and performance in one system/framework: transparent, flexible, quick Data management can be simplified Senior managers are empowered – access results from their desktop (intranet or internet) 11 4. Using Web-based Technologies Effectively A Case Study: Integrated system that allows user to follow specific process steps: 1. Specify a clear investment process (i.e., who makes what decisions at what level of the fund) = GOVERNANCE 2. Understand all the risks taken by the fund = GOVERNANCE 3. Model decisions in a TRANSPARENT way (i.e., simple so that anyone can understand/evaluate) 4. Attribute performance to improve decisions Governance, process & transparency = better returns 12 Case Study: Step 1 Articulate Responsibilities/Decisions Portfolio Asset Allocation Equity = 40% Bonds = 40% Sector/ Regional By Market (Local, US etc.) By Market (Local, US, Euro) Style Selection Large Stocks/ Small Stocks Govt./Agency etc. Manager Selection Cash/ Currency = 20% Mgr Mgr Mgr Mgr Mgr Mgr A B C D E F Bank 1 Bank 2 for Deposits for Deposits 13 Case Study: Step 2 Use Portfolio Tree to Pinpoint Risk Structuring risk at total fund level=1.5% (or $300 mn) From asset allocation and style tilts (excludes managers) From allocations to assets other than fund benchmark Allocation decisions have historically had big drawdowns Pension Risk= 1.5% Fund Maximum Drawdown = -7.5% Risk = 1.5% Risk = 3.2% Risk = 1.8% Maximum Drawdown = -5.5% Maximum Drawdown = -11% Maximum Drawdown = -6.8% 14 Case Study: Step 3 Ensure Decisions Generate Returns Total Excess = 2% Total Portfolio Asset allocation strategy Equities Bonds Cash 1-mo LIBOR Country allocation strategy Local Bonds + Currency Excess Return = 0.5% + Foreign bonds Sector allocation strategy Government Bonds Excess Return = 0.5% Mortgage/ Corporate Internal/External Managers Excess Return = 0.5% + Manager Excess Return = 0.5% 15 Case Study: Step 4 Use Attribution to Improve Decisions Total Excess = 0% Total Portfolio Naïve Rebalancing Equities Bonds Cash 1-mo LIBOR Excess Return =- 0.5% Let Portfolio Drift Local Bonds Excess Return = - 0.5% Foreign bonds Sector allocation strategy Government Bonds + Currency Mortgage/ Corporate Internal/External Managers Too much focus on manager selection Excess Return = 0.5% + Manager Excess Return = 0.5% 16 Case Study: Step 5 Portfolio Rules: Web = Transparency Example: Investment Idea: Cash vs Bonds: Apparently, the price of gold is a good indicator of whether funds should be invested in cash or higher duration assets (bonds). Rising gold prices are good for cash relative to bonds. Rule Criteria: IF ((Price of Gold Today > Price of Gold a Year Ago)) THEN Allocate more to Cash ELSEIF ((Price of Gold Today < Price of Gold a Year Ago)) THEN Allocate less to Cash ELSE Do Nothing Performance Statistics: Excess Annualized Return: 0.61% Risk: 0.94% Information Ratio: 0.65 Max Drawdown: -1.24% on 3/31/1999 Success Ratio: 61.1% Confidence in Skill: 97.95% Good decisions add returns and reduce risk *Purely hypothetical example and not an investment recommendation 17 Case Study: Step 6 Deliver Detailed Reports Through Web Performance Measures Benchmark Strategy Excess 6.47 9.25 2.78 36.79 55.64 18.85 Risk % 2.28 5.58 3.55 Return / Risk Ratio 2.84 1.66 0.78 Return % Cum. Return % Strategy Excess 70 56.67 Average returns when positive % 1.51 0.86 Average returns when negative % -1.02 -0.60 Max. consecutive periods of positive returns 7 7 Max. consecutive periods of negative returns 4 5 -2.54 -1.99 Success ratio of the rule % Max. relative loss for a period % 18 5. Mcube IT: Better Governance/Returns Through Web Applications 1. Boards/Senior Managers can set fund structure and monitor all decisions easily 2. Portfolio managers can use to make better decisions 3. Middle office can use to evaluate risks/performance 4. Web-technology for 3 Ms of Portfolio Management: “Measure”, “Monitor” and “Manage” 19 6. Summary & Conclusions Portfolio management = many decisions and requires many groups to coordinate (board, front office, back office, external managers) Silo systems make it difficult and expensive to manage fund Web (internet/intranet) can overcome challenges Can create customized portfolio structure, analysis and reports Can create transparency for good governance, returns and risk management AlphaEngineTM: adopt best practices quickly and easily 20 Appendix 5. Converting Ideas To Rules to Give Good Process and Add Value Rule Rule Description Cash vs. Bonds, based on Gold Duration choice based on price of gold. If the spot price of gold is higher than it was a year ago, overweight cash, otherwise overweight bonds Stocks vs Bonds: Halloween Effect Stocks vs Bonds: Inflation/Growth Market Volatility Stocks tend to underperform bonds between June and Sept - apparently works in 16 out of 18 stock markets, so underweight stocks during this period Equities undervalued when inflation rises (Modigliani-Cohn insight); equities favored when industrial production is increasing Low equity volatility in a rising stock environment is bullish for equities. Oil and Economy Rising oil prices affect the economy and tend to depress equities. P/E Ratio Rule Value rule for equity (vs FI) using the S&P 500 P/E Fed Model When equity yield is higher than treasury yield then buy equity, else sell equity Unemployment Rate Buy stocks when the unemployment rate is falling (good for economy) US/International: LIBOR Rates US/EAFE: Favor Underperformer Overweight equity market with the stronger currency (higher interest rate) Overweight equity market which has underperformed over past year (i.e., buy the laggard) 22 Rule Performance (1998-2004) Rule Excess Annualized Information Confidence Success Ratio Good Max Return Ratio in Skill Ratio /Bad Risk Drawdown Cash vs. Bonds, based on Gold 0.04% 0.20 68.8% 56.4% 1.30 -0.44% Halloween Effect 0.98% 0.88 98.0% 63.8% 1.42 -1.58% Inflation/Growth 0.50% 0.57 93.1% 79.7% 1.07 -1.31% Market Volatility 0.12% 0.11 67.8% 56.4% 1.41 -2.74% Oil and Economy 0.45% 0.57 91.6% 70.5% 1.16 -0.84% P/E Ratio Rule 0.17% 0.39 87.1% 50.0% 2.12 -0.80% Fed Model Unemployment Rate 0.47% 0.51% 0.50 0.61 91.8% 94.1% 61.5% 59.0% 1.43 0.99 -2.17% US/EAFE: LIBOR Rates US/EAFE: Favor Underperformer 0.17% 0.53% 0.43 0.95 84.7% 99.3% 55.1% 64.1% 1.07 1.33 -0.71% -1.11% -1.07% 23