From Quantitative Finance ToIntelligent Finance Financial Information Fusion, Multilevel Process Ana

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From Quantitative Finance To Intelligent
Finance--- Financial Information Fusion,
Multilevel Process Analysis, and Dynamic
Portfolio Management
International Workshop on Forecasting and Risk
Management IWFRM06

• Prof Dr PAN Heping, Director
• International Institute for Financial Prediction
  (IIFP)
• Australia and China, URL www.iifp.net, Email
  h.pan_at_iifp.net
• IIFP China, Finance Research Centre of China
  (FRCC)Southwest University of Finance and
  Economics (SWUFE)IIFP AustraliaSchool of
  Information Technology and Mathematical Sciences
• University of Ballarat, Mt Helen, 3353, Victoria,
  Australia
• Phone/Fax [phone], Mobile
  0411-489-847

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Key Points

• Finance has evolved along a natural sequence of
  stages from Economic Finance through
  Quantitative Finance now to Intelligent
  FinanceThese developments are still coexistent
  and will remain so.
• Intelligent Finance as a science aims to
  understand the global financial markets as the
  world most complicated social complex systems of
  intelligent agents investors, traders and
  players.
• Intelligent Finance as an engineering aims to
  develop consistently profitable trading systems
  operating in global financial markets stocks,
  bonds, currencies, commodities and their
  derivatives futures and options.
• Intelligent Finance integrates information flows
  from multiple perspectives Fundamental,
  Technical and Strategic Analysis into a coherent
  framework which can help investors/traders to
  detect, anticipate and capture profitable
  investing/trading opportunities in real time and
  on multiple time frames, and manage portfolios
  dynamically.

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Key Points

• Intelligent Finance represents a philosophy that
  
• The market is always in a state of swings between
  efficient and inefficient modes, on multiple
  levels of time scale
• It is possible to go beyond EMH to study the
  dynamic evolving processes of the market between
  equilibrium, non-equilibrium and
  far-from-equilibrium, in multiple dimensions
• There are robust dynamic patterns in the evolving
  processes, most of them are quite abstract,
  beyond common sense, and against human nature,
  due to bounded rationality, limited resources,
  and very human nature of market participants.
• It is possible to break the symmetry between
  profit and loss by exploiting such robust dynamic
  patterns using a trading system.

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Contents

• Evolution of Academic Finance vs Professional
  Finance- Economic Finance, Quantitative Finance
  and Intelligent Finance- Fundamental Analysis
  and Investors- Technical Analysis and Traders-
  Strategic Analysis and Players
• Financial Information Fusion (FIF)- Information
  Source Identification- Historical Process
  Analysis- Current Situation Assessment- Future
  Scenario Projection- Market Selection and
  Monitoring
• Multilevel Process Analysis (MPA)- Multilevel
  Fractal Decomposition of Financial Time Series-
  Multilevel Structural Time Series Models-
  Multilevel Stochastic Differential Equations-
  Multilevel Dynamic Pattern Recognition-
  Multimarket Multilevel Stochastic Dynamics
• Dynamic Portfolio Management (DPM)- Stocks,
  Bonds, Interest Rates (and Forex Rates and
  Commodity Prices)- Influence Factors- Phases of
  Trends, Cycles and Seasonality and Market
  Timing- Multilevel Multiperiod Portfolio
  Theory- Multilevel Value at Risk in General and
  Extreme Conditions
• Conclusions and Outlook

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1. Evolution of Academic vs Professional Finance

• Finance to Economy of a nation is like the blood
  circulation system and the central nervous system
  to a living animal body. Finance not only
  circulate the money (energy) through the economy,
  but also reflects the information about the
  economy.
• Finance vs Economics are inherently connected,
  but now quite different disciplines, each with
  its own substantially developed methodologies. It
  is inappropriate and even harmful to try to apply
  economic principles to finance problems. E.g.
  equilibrium vs disequilibrium, - feedback loops.
• Academic vs Professional Finance are inherently
  connected, but now quite different schools of
  thought, each with its own substantially
  developed methodologies. Academic Finance
  focuses more on financial governance and risk
  management, while Professional Finance is more
  concerned with profit making while keeping risk
  checked only as a necessary condition.

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From Economic Thru Quantitative to Intelligent
Finance

• Finance has evolved along a natural sequence of
  development stages from Economic Finance through
  Quantitative Finance now to Intelligent Finance.
  Of course these three developments are still
  coexistent and will remain so for the foreseeable
  future.
• Economic Finance refers to the traditional and
  still mainstream finance which originates as a
  coherent part of economics, including currency,
  banking and financial markets from
  macroeconomics, and corporate finance, accounting
  and insurance from microeconomics and business
  management.
• Quantitative Finance has aimed at quantitative
  analysis of every part of finance and developing
  mathematical and computational models.
• Intelligent Finance takes the finance of a nation
  or the whole mankind as a living complex system
  made up of intelligent agents and aims at
  developing intelligent finance systems for
  banking, investing, trading and other financial
  applications.

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Origin of Quantitative Finance Problem of
Predictability

• Theorie de Speculation by Bachelier (1900)
  Brownian Motion, Wiener Process, Random Walk
• Efficient Market Hypothesis (EMH) (Fama 1970
  Fama French 1992)
• Modern Portfolio Theory by Markowitz (1952)
• Super Effective Portfolio by Tobin (1958),
• Capital Asset Pricing Model (CAPM) by Sharpe
  (1964),
• Arbitrage Pricing Theory by Ross (1976).
• A Paradox A modeling process based on
  prediction-free assumptions leads to predicting
  discrepancies of the market prices from the model
  prediction.

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Quantitative Finance, Econophysics, and
Socionomics

• Theory of Option Pricing by Black, Scholes and
  Merton (1970s), Long-term Capital Management
  Company, Option Pricing and Option Speculation
  are two different games.
• Econophysics Fractal, Multi-fractal, Power Laws,
  Log-Periodicity, Criticality, Singularity, Mean
  Field Theory, Regularization Group, Minority
  Game, Minority-Majority Game, Herding, Financial
  Bubbles, Super-Geometrical Spiking, Trend
  Reversal, Financial Anti-Bubbles, Market Crashes,
  Threshold-based Decision Process, Jump Diffusion,
  Turbulence, Chaos, Intermittent Chaos.
• Socionomics Robust Fractals, Elliott Waves,
  Spirals, Branches, Fibonacci Numbers, Social
  Mood, Fluctuation and Flow Patterns of Societal
  Activities, Historys Hidden Engine.

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Schools of Thought in Quantitative Finance

• Financial Mathematics Statistics
  Stochastic DE, volatility, option pricing, time
  series, GARCH
• Econophysics Mandelbrot (1967, 1984, 1997,
  2004) Mantegna and Stanley 1999 Ilinski 2001
  Bouchaud and Potters 2003 Voit 2004 Sornette
  1996, 2003, 2005 Challet, Marsili Zhang
  (2005)
• Behaviour Finance Shiller 2002
• Computational Finance Farmer 2002 Farmer and
  Joshi 2002 Farmer et al 2003 LeBaron 2005
• Long-term Prediction Campbell and Shiller
  1988 Sornette 1996-2006 Zhou and Sornette 2003
  Wang et al, 2003-2006
• Short-term Prediction Lo and MacKinlay
  1988 Pan 2003-2006
• Multilevel Process Analysis and Modelling Pan
  2003-2006 Kaufman 2005 Dacorogna et al 2001

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Intelligent Finance An Introduction

• Intelligent Finance represents an emerging
  comprehensive perspective to global financial
  markets unifying professional empirical wisdom
  and art of market analysis and academic research
  and science of market modeling.
• Professional Schools include Fundamental,
  Technical and Strategic Analysis.
• Academic Schools include Stochastic Process,
  Dynamical Systems, and Agent Models.
• Intelligent Finance is a quest for a
  comprehensive approach, methodology and system of
  financial market analysis, investing and trading,
  aiming to generate absolute positive and
  nontrivial returns of investment by means of
  exploiting the complete information about the
  markets from all conceivable general
  perspectives, and simultaneously minimizing the
  very last risk incompleteness of a seemingly
  comprehensive investing or trading method or
  system.

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• The key tenet of Intelligent Finance
• Every existing approach or methodology of
  market analysis, investing and trading should be
  considered a part of the total toolkit (arsenal)
  for profitable trading its effectiveness is
  time-varying relative to the state of the art of
  the total toolkit currently possessed by the
  investing public and to the current market mode
  and situation.

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Absolute Positive Nontrivial Returns

• Benchmark Levels of Intelligent Finance
• RoIk (110)(k1) 1
• RoI1 21 Qualification
• RoI2 33 Buffett (24), Soros (32)
• RoI6-7 100 Day Traders
• RoI48-49 110 x 100 Robbins World Record
  Larry Williams,
  1987

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How is the world record 110 x 100 possible ?
Weekly Return (1 1)52 1.68
x 100 (1 2)52 2.80 x 100 (1
3)52 4.65 x 100 (1 4)52
7.69 x 100 (1 5)52 12.64 x 100
(1 6)52 20.70 x 100 (1 7)52
33.73 x 100 (1 8)52 54.71 x 100
(1 9)52 88.34 x 100 (1 10)52
142.04 x 100 The world record of futures
trading 110.00 x 100
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A Trading System
The Pragmatic Objective of Intelligent Finance

• can consistently generate positive and nontrivial
  returns of investment
• with trivial draw-downs
• at a sufficiently high degree of automation
• operating in the global financial markets
• (such as Medallion Fund and Santa Fe Institute)

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Four Pillers of Intelligent Finance

• Comprehensive exploit all the legally available
  information about the markets, economies and
  societies.
• Predictive exploit all the historical patterns
  from the existing data and current information to
  project the world into the future.
• Dynamic assume the patterns are nonlinear and
  complex with both stochastic and dynamic natures
  and open to the future.
• Strategic always be aware of the limitations of
  mathematical and computational modeling, react
  and act on the strategic intents of strategic
  investors.

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Topics of Research and Development

• Historical Process Analysis
• Current Situation Assessment
• Effective Cycles and Seasonality Analysis
• Future Price Tendency
• Future Price Volatility
• Macroeconomic Analysis
• Microeconomic-Fundamental Analysis
• Real-time Technical Analysis (Price, Volume,
  Money Flow, Mood)
• Automated News Analysis (Politico-Economic-Financ
  ial Events)
• Detecting Profitable Opportunities
• Trade Planning (Entry, Stop Loss, Profit-Taking
  Exit, Positions)
• Portfolio Construction and Management
• Risk Analysis and Early Warning of Market
  Crashes
• Financial Strategic Analysis (Maker Makers,
  Minority-Majority Game, Financial Warfare)
• Global Stock Market Analysis
• Global Currency Market Analysis (Forex)
• Global Bond Market Analysis
• Global Commodity Spot and Futures Market
  Analysis
• Global Interest Rate Market Analysis

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A Theoretical Framework of Intelligent
Finance(Pan, Sornette Kortanek, Quantitative
Finance, Vol. 6, No. 4, 2006)

• Stylized Facts of Financial Market Structures and
  Prices
• Unified Assumptions underlying Financial Market
  Prices
• Financial Information Fusion from Fundamental,
  Technical, Strategic Analysis
• Multilevel Stochastic Dynamic Process Modelling
  of Financial Prices
• Active Porfolio Management and Total Risk Control
• Financial Strategic Analysis and Intelligent
  Agent Modelling
• Dynamic Optimization
• Objective Prediction and Intelligent Trading
  Systems
• Macrowave Investing and Multifractal Trend
  Following

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Three Major Research Directions of Intelligent
Finance

• Financial Information Fusion
• Multilevel Process Analysis
• Dynamic Portfolio Management

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2. Financial Information Fusion

• Multiple Information Sources
• Multiple Analysis Perspectives
• Multiple Levels of Time Scale
• Multiple Classes of Assets
• Multiple Markets
• Multiple Nations and Regions
• Lead to
• Many Profitable Opportunities
• Many Sources of Risks
• Too Many Things to Consider
• Where Do We Start and End?
• How Do We Streamline Information, Decision and
  Execution?

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Multiple Perspectives of Financial Markets

• Fundamental AnalysisValue, Growth, Price, Margin
  of Safety, Market Shocks, Business Cycles,
  Industry Trends and Life Cycles, Competitive
  Advantage, Management Quality, Financial Health
  and Efficiency
• Technical AnalysisPrice, Index, Trend, Market
  Cycles, Price Waves, Swings Momentum, Support
  Resistance, Market Timing, Time Frames,
  Volatility Breakout, Stop Loss, Trendline Break,
  Trend Reversal
• Strategic AnalysisVenture Capital, Public
  Listing, Liquidation, Market Makers,
  Accumulation, Lifting, Distribution, Dumping,
  Currencies-Stocks-Bonds, Takeover, Macrowave
  Investing, Conscious Reflexivity Process
  Investing, Market Catalysts, Shark School,
  Wolf Pack, Stop Running Game,
• Mental AnalysisSurvival of the Fittest, Your
  Personalized Trading System, Trade your System
  Carefree, Follow your System Religiously

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The Pyramid of Financial Market Analysis
Strategic Analysis
Scale Gap
Mental Analysis
Psychological Gap
Technical Analysis
Marketplace Gap
Fundamental Analysis
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All Master Investors are Complete Master

• Warren Buffett is not only the world greatest
  Fundamental Analyst and Investor (value growth,
  long only), but also he had learned the
  essentials of Technical Analysis even before he
  started attending Benjamin Grahams class at his
  20s.
• George Soros has been the world greatest Trader
  with a mix of short and long strategies,
  profiting from testing conscious hypotheses on
  reflexivity processes on macroeconomic and
  international financial events, exhibiting FA,
  TA, SA.
• Both Warren Buffett and George Soros share a same
  complete set of mental habits for consistently
  winning investment and grand-scale success.

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Practical Exemplars of Intelligent Finance

• Use Macro-Fundamental Analysis (global
  macroeconomical and financial macrowaves,
  business cycles, leading stock market cycles and
  sector rotations) to select international stock
  markets, bonds, currency pairs, commodities.
• Use Micro-Fundamental Analysis (stock valuation,
  growth prospecting, competitive advantage,
  financial efficiency, management quality, ) to
  select stocks.
• Use Macro-Technical Analysis (stock market index
  and sector indexes) for market timing and
  macro-portfolio planning.
• Use Micro-Technical Analysis (daily charts,
  realtime intraday charts and live quotes) for
  trade timing.
• Enter the Market using intraday charting and
  tactics with stop loss protection.
• Hold the Position and Follow Trend in motion with
  trailing stop loss.
• Exit the Market when either fundamental or
  technical criteria for profit taking or stop loss
  are met.
• Manage General Portfolios (long and short)
  dynamically according to phase and strength of
  trends and risk management principles.

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A Masterpiece by John Templeton, 2000-2001
Shorting NASDAQ with a trigger before the end
of lock-up period
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A true story about John Templeton, told by Mark
Tier 2004, 2006

• Throughout 1999 until 13 March 2000, dot-com
  stocks zoomed to absurdly high levels.
• Many value investors, realizing these stocks were
  wildly overvalued, shorted them all the way up.
• This included some legendary money managers.
• Having shorted even a bit too early before the
  peak could cause unlimited losses.
• E.g. Julian Robertson eventually couldnt bear
  the pain any more and quit in disgust, shutting
  down his fund entirely. (Soros took some painful
  loss too).
• However, John Templeton, at the tender age of 87,
  made a brilliant and enormously profitable foray
  back into the stockmarket.

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• Three months before the NASDAQ peaked, he
  discovered a trigger that allowed him to
  initiate one of the most creative short selling
  strategies ever devised.
• The venture capitalists and insiders who floated
  these internet companies were typically
  restricted from selling their stock until six
  months or a year after the company had gone
  public.
• Templetons insight was to use the end of this
  lock-up period as his trigger.
• He systematically initiated short positions in 84
  different dot-com companies 11 days before the
  lock-up period for each stock expired.
• 18 months later, hed added 86 million to his
  wealth.

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• During the Internet bubble and anti-bubble
• Fundamental Investors missed
• Technical Traders lost
• But intelligent speculators made money-
  Integrate Fundamental, Technical and Strategic
  Analysis (like John Templeton)

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A Framework of Financial Information Fusion
Strategic Intelligence
Market Maker Situation Intent
Stock Price Prediction
Stock Price Situation Analysis
Market Activity Events
Sector Situation Analysis
Politico-Economic Events
Strong vs Weak Stocks
Index Situation Analysis
Trading System
Market Price Data
Company Value Growth
Sector Index Prediction
Company Fundamentals
Industry Cycle Sector Rotation
Fiscal Policy
Interest Rate Yield Curve
Market Index Prediction
Macroeconomic Indexes
Growth Trend Business Cycle
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An Empirical Model of Business Cycle, Stock
Market Cycle and Sector Rotation (ref Navarro,
2004 and macroeconomics textbooks)
Stock Market Sectors1 Transportation 2
Technology 3 Capital Goods 4 Basic Industries
and Materials 5 Energy 6 Food, Drugs, Health
Care 7 Utilities 8 Financials 9 Autos,
Housing, Consumer Cyclicals
Business Cycle
Stock Market Cycle
Peak
Top
6
5
4
Bear
Bull
Recession
3
7
2
Expansion
8
1
9
Trough
Bottom
Trough
Bottom
time
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source www.martincapital.com
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Economic Indicators Most Sensitive to US
Stocks(Bernard Baumhohl, 2006)
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Economic Indicators Most Sensitive to US
Bonds(Bernard Baumhohl, 2006)
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Economic Indicators Most Influential to US
(Bernard Baumhohl, 2006)
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source money.cnn.com
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3. Multilevel Process Analysis of Financial
Prices

• Why ? Heterogeneous Dynamic Market Hypothesis
• How ?Multilevel Stochastic Dynamic Process
  (MSDP) Models of Financial Time Series

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Facts and Assumptions underlying MSDP Models
(Dow 1880s, Graham 1930s Elliott 1930s,
Mandelbrot 1970-2004 Peters, 1991 Dacorogna et
al, 2001 Pan 2003-2006)

• Heterogeneous Market Hypothesis Market
  participants are not homogeneous there are
  producers, hedgers, investors, traders and
  speculators different participants react to the
  same information in different ways with these
  characteristics- Different participants have
  different time horizons and dealing
  frequencies- Different participants are likely
  to settle for different prices and decide to
  execute their transactions in different
  situations, so they create volatility- The
  market is also heterogeneous in industrial and
  financial sectors and in the geographic
  location of the participants.
• Fractal Market Hypothesis Different participants
  with different time horizons and dealing
  frequencies share the same human nature,
  consequently the market prices exhibit a fractal
  structure.
• Dynamic Market Hypothesis (Swingtum Market
  Hypothesis)The fractal market prices exhibit
  robust stochastic dynamic patterns in the scale
  space of time and price, which can be described
  in terms of multilevel trends, swings and
  momentums.

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Multilevel Stochastic Dynamic Process (MSDP)
Models of Financial Time Series

• Multilevel Chart Reading Unconscious
  Competence(MSDP - MCR)
• Multilevel Fractal Decomposition- Top-Down
  (Fractal-Preserving Generalization)- Bottom-Up
  (Hilbert-Huang Transform)(MSDP MFD)
• Multilevel Structural Time Series Models
• Multilevel Stochastic Differential Equations
• Multilevel Dynamic Process Patterns(Super
  Bayesian Influence Networks SBIN)
• (MSDP - Models)

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4. Dynamic Portfolio Management

• Stationary Portfolio Theory
• Arbitrage Pricing Theory
• Dynamic Portfolio Theory
• Factors and Models for Stock Returns
• Factors and Models for Bond Returns
• Factors and Models for Interest Rates
• Factors and Models for Currency Exchange Rates
• Factors and Models for Commodity Prices
• Multilevel Phase Reconstruction and Market Timing
• Multilevel Multiperiod Portfolio Theory
• Multilevel Value at Risk Theory (general vs
  extreme conditions bubbles vs crashes)

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A Trading System Must Be PersonalizedE.g. Pan
Swingtum Trading System

• Human Intelligence
• Swingtum Principles for Expert Trader
• Swingtum Principles for Master Trader
• Swingtum Trading Strategies
• Swingtum Trading Time Windows
• Swingtum Trading Signals
• Computational Intelligence
• Swingtum Prediction System
• Swingtum Trading System

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5. Conclusions

• Finance has entered the era of Intelligent
  Finance out of a 100-years history of investing,
  trading, thinking and research.
• Intelligent Finance provides a comprehensive
  approach to break through the Efficient Market
  Hypothesis to study the multilevel swing
  processes of market equilibrium.
• Human being and the world are not chaotic, so
  there are invariant patterns, though maybe highly
  abstract and deeply hidden, in the market price
  behaviors, embedded in the economic dynamics.
• Financial Information Fusion and Multilevel
  Process Analysis make it possible to break the
  symmetry between profit and loss on multiple time
  frames.
• Dynamic Portfolio Management provides a natural
  way to realize this possibility through a
  complete operational loop.
• Intelligent Finance in general, are still at its
  early phases of research and development. Much
  remains to be done.

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Pan Swingtum Principles

• For Expert Trader
• Survival of the Fittest
• Enter Your Zone of Freedom
• Avoid the Markets of Your Disadvantage
• Be Practical
• Be Empirical
• Keep It Simple, Stupid! (KISS)
• Trade Carefree
• For Master Trader
• Only Trade High-Probability Events
• Invest First, Investigate Later
• Exit First, Analyze Later
• Concentrate with Minimal Diversification
• Ride Reflexivity Process Consciously
• Use Leverages, but Judiciously
• Follow Your System Religiously

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• Read my motto
• Before entering the market
• Everyday

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Pan Swingtum Daily Reading (Motto)

• My God, show me the big way, give me the big
  morality and big wisdom
• Follow the day trend first thing first, keep a
  distance. Dont be addicted to technicalities,
  remain natural, return to nature.
• Every time when you trade, think as if you are
  standing on the verge of a cliff you strike back
  either to win or to die. Therefore, you must have
  infinite patience, but when you move, move
  decisively.
• Remain tranquil and empty your desire. Do
  nothing most of the time, waiting for the right
  moment. Take no action until you see the trend
  emerge Enter with daylight.
• Follow trend in motion with trailing stop loss.
  Make your decisions and take your
  responsibility. Survival of the fittest, not the
  smartest, not the coolest, not the prettiest.
  Leave your ego behind when entering the market.
  Always have your respect to the market, befriend
  with the market, dance with the market.

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• The End.
• Thank you for your attention!