6 th Annual Funds Forum China Hedge Fund Management & Risk - - PowerPoint PPT Presentation

China Hedge Fund Management & Risk Control: Creating Stability in Markets

Beijing : 21-22 September 2011 Lanz Chan, Ph.D. Galaxy Asset Management

6th Annual Funds Forum

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Outline

• China hedge fund industry
• Hedging with CSI300 futures
• Risk cybernetics and control for stable markets
• Q&A

History of Hedge Funds History of Hedge Funds

1945 1955 1965 1975 1985 1995 1950 1960 1970 1980 1990 2000

Alfred Winslow Jones starts the first long/short hedge fund Alfred Winslow Jones starts the first long/short hedge fund 140 US hedge funds including Soros and Steinhardt 140 US hedge funds including Soros and Steinhardt First fund of funds launched – Haussmann and LCH First fund of funds launched – Haussmann and LCH Hedge funds decline – by 1984 there were only 68 Hedge funds decline – by 1984 there were only 68 Industry dominated by a small number of global macro Industry dominated by a small number of global macro funds – Soros, Tudor Jones, Niederhoffer funds – Soros, Tudor Jones, Niederhoffer Indices start, equity hedged and relative value Indices start, equity hedged and relative value strategies gain favour; LTCM debacle of 1998 strategies gain favour; LTCM debacle of 1998 Rapid growth, fuelled by Rapid growth, fuelled by bear market, increasing bear market, increasing transparency, greater transparency, greater understanding of the market understanding of the market and entry of institutional and entry of institutional investors investors

… since 1949

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Introduction

• Reported in Financial Times, April 2011
• China moves slowly to lift hedge fund barriers
• 20-year China stock market history
• 10-year asset management history
• 2010: China fund management $392b AUM

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China Hedge Fund Industry: Overview

• Approved large asset management hedge funds
• Unregulated private fund managers
• More than 100 sunshine private hedge funds (trusts)
• Soon to be under CSRC regulation
• Potentially offering retail products
• Implications for strict risk control requirements
• Objective: increase efficiency & stability in the markets

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China HF Industry: Overview

• E Fund Management 29b yuan AUM
• Onshore hedge fund strategies since Sep 2010
• Next few years: multi-billion China onshore hedge funds
• April 2010: CSI300 index futures
• Margin trading allowed
• Borrowing individual stocks to short still difficult

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China Hedge Funds (15+ years)

2 Categories: 1) Govt-backed companies, including brokers – managing pooled property, trust, investment companies' trust, investment projects – Investment companies managing own capital 2) Private hedge funds: – in form of “Investment Consulting Company" or "Investment Management Company", provide management for pooled property.

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China Hedge Funds 2011

• China Southern Fund Management
• One of first “hedge fund” since Oct 2009
• Performance-fee driven
• 2011: RMB 1.2b AUM in 7 hedge funds
• Feb 2011:Guotai Junan, $45m hedge fund
• One of first approved by CSRC
• Plans to raise 300m yuan initially
• Use index futures to mitigate systematic market risks

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China Hedge Funds 2011

• Growing demand for hedge funds in China
• Investors seek modest, but stable returns
• Target HNWI: subscription of >1m yuan.
• Target annual return of 10-15 percent
• Risk exposure of about half target returns
• Strict risk policies

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CSI300 Futures

• Only 50 stocks in CSI300 can be short with govt approval
• Expensive process
• Broker allowed to buy stocks to loan to clients
• Broker uses own funds, cannot use client's stocks
• Cannot borrow to invest
• Gearing up using borrowed funds from close relationships
• Some paying >6% interest on loan

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Hedge Fund Considerations & Directions

• Manage investor expectations
• Reduce market volatility
• China stock market surged 80% in 2009
• Fell 65% in 2008 due to global financial crisis
• China deregulation but with more enforcement
• Encourage innovation but supervise and enforce

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Hedge Fund Industry Directions

• 200 licensed institutions potentially start hedge funds
• 63 asset management firms
• 100 or so brokerages
• 20 insurance companies
• Real Hedge Funds:
• HNWI, performance fees, hedging with futures,
• Using leverage

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Future of Hedge Funds

• Current situation: private managers off-radar
• With basic asset management license
• Future: Hedge funds under CSRC framework
• Monitor risk-return
• Employ efficient hedging strategies
• Objective to enhance efficiency of China's capital markets
• Where information is reflected in markets
• In timely and stable way
• QDII: investments into foreign hedge funds not allowed
• Current formation of private partnerships
• Double taxation issue
• Tianjin tax breaks
• Shenzhen, Shanghai fund formation hotspots

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Volatility, Risk, Uncertainty

Risk: quantifiable uncertainty Vol: Risk measure

• Vol comes in many forms
• Vol measure must suit purpose
• Vol-trading is key to sustained algo-returns
• Risk control implemented with stop-loss
• Maximum draw-downs
• Target returns achieved with signal-optimization

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Risk Control Considerations

• Problem of unknown relationships
• Market inefficiency
• Statistical challenges
• Non-linearity
• Pareidolia: insignificance perceived as significant
• Ludic Fallacy: misuse of games to model real-life
• Black swans
• Reflexivity
• Strategic risks
• Vol-trading
• Financial engineering, quantitative financial tools
• Solve problems in logical way

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Creating Stability with Risk Control & Allocation

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Risk Control Paradigm

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Risk Control: Back, Forward Tests

• Back-tests, forward-tests essential, critical
• High-Prob High-Vol Systems: Optimization?

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Implement Financial Engineering

Applications:

• High-vol instruments
• Mis-pricing activity
• Arbitrage opps
• FX and Premium Puzzle
• Martingale Strategy
• Volatility Clusters, Jumps, Fractals, Order Flow
• Extreme Values
• New Movement in Methodology
• Randomness vs Unpredictability
• Stochastic Process and Random Theory
• Random Number Generator

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Advanced FE

• Cybernetics
• Automated Discovery in Econometrics
• Genetic / Evolutionary Algorithms
• Decision Support System (DSS)
• Artificial Neural Network (ANN)
• Forecast Evaluation
• Optimization

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Successful FE?

• Articulate facts to decision
• Verify intuition, translate to information
• Seemingly random behavior
• Detect order in randomness
• Seamless execution

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Enhancing Efficiency

• Weak
• Semi-Strong
• Strong
• Manage expectations
• Invest in efficient people, efficient systems
• Direct Memory Access
• Detecting patterns
• Crytanalysis, decoding data

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Efficiency & Stability

If financial markets are “efficient”:

• News embedded in prices, quickly becomes useless
• No differential advantage to trading with news
• Prices are always fair; they reflect all that is known
• Enhances stability in market prices

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Efficiency & Stability

What features set the stage for an efficient market? a) There are many active participants b) Participants have similar objectives c) Participants have equal access to same data

• Volume, no single investor may influence prices
• Hedging
• Transparency

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Inefficiencies as Opportunity?

• Markets are not efficient at all times
• In IT age, markets becoming more efficient
• Key is to detect inefficiencies with FE tools
• Transparent risk-return
• Efficiency-edge is key driver

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Hedge Fund Management

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ISO 31000:2009 Risk Management Guidelines

 Risk management should create value;  be an integral part of organizational processes;  be part of decision-making;  explicitly address uncertainty;  be systematic and structured;  be based on the best available information;  be tailored;  take into account human factors;  be transparent and inclusive;  be dynamic, iterative and responsive to change; and  be capable of continual improvement and enhancement.

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What is Risk Cybernetics?

 Practice of risk management with cybernetic (man and machine become one) technologies.  Application of optimization with circular causal feedback control features.  Technique applied to any form of market data.  Development of risk-pricing models.  Implementation in trading strategies/programs.  Part of risk management plan.  Risk assessment, characterization, evaluation.  Automated vol-trading.

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Cybernetic Framework

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First-order Cybernetics

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Second-order Cybernetics

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Why Risk Cybernetics?

 Smorgasbord of market information is overwhelming.  Current risk management techniques are limited.  Limited functionality for dynamic effects.  Static models are at best relevant for that moment.  In vol-markets, short-term predictions are flawed by the common estimation methods.  Limitations of financial theory

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Genetic-Algo Optimization: Risk Control

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Risk Control: Cryptanalysis & Decoding

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Risk Control with Variance, Skewness & Kurtosis

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Risk Cybernetics: Objectives

• Upgrade and boost existing risk knowledge;
• Risk Cybernetics (RC) is ISO 31000:2009 compliant;
• Implement in risk-pricing;
• Create expert advisors;
• RC most suited for high-volatility trading;
• Low-latency automated algorithmic trading;
• Suited for FX, futures, hedging instruments;
• Applied for government monetary policy;
• As MNC financial risk control tool.

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Summary

• Implementing proper risk policies
• Ensures transparency
• More predictability
• More stability in China's financial markets

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Thank you

Lanz Chan, Ph.D. Galaxy Asset Management lanzchan@galaxyfunds.net

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