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					   International Workshop on
Forecasting and Risk Management
            IWFRM’06
From Quantitative Finance
To Intelligent Finance
--- Financial Information Fusion,
    Multilevel Process Analysis, and
    Dynamic Portfolio Management

 Prof Dr PAN Heping, Director
 International Institute for Financial Prediction (IIFP)
 Australia and China, URL: www.iifp.net, Email: h.pan@iifp.net

 IIFP China, Finance Research Centre of China (FRCC)
 Southwest University of Finance and Economics (SWUFE)
 IIFP Australia
 School of Information Technology and Mathematical Sciences
 University of Ballarat, Mt Helen, 3353, Victoria, Australia
 Phone/Fax: +61-3-5327-9860/-9289, Mobile: 0411-489-847
        Key Points
• Finance has evolved along a natural sequence of stages
  from         Economic Finance
  through      Quantitative Finance
  now to       Intelligent Finance
  These 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.
  2006-12-21              www.iifp.net   h.pan@iifp.net                2
        Key Points
Intelligent Finance represents a philosophy that

1. The market is always in a state of swings between efficient and
   inefficient modes, on multiple levels of time scale;

2. 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;


3. 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.

4. It is possible to break the symmetry between profit and loss by
   exploiting such robust dynamic patterns using a trading system.



  2006-12-21              www.iifp.net   h.pan@iifp.net              3
            Contents
1.      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
2.      Financial Information Fusion (FIF)
        -   Information Source Identification
        -   Historical Process Analysis
        -   Current Situation Assessment
        -   Future Scenario Projection
        -   Market Selection and Monitoring
3.      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
4.      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
5.      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
     (1970’s), 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, History’s 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 = (1+10%)(k+1) – 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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      The Pragmatic Objective of Intelligent Finance

A Trading System
1)     can consistently generate positive and nontrivial
       returns of investment
2)     with trivial draw-downs
3)     at a sufficiently high degree of automation
4)     operating in the global financial markets


(such as Medallion Fund and Santa Fe Institute)




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      Four Pillers of Intelligent Finance

1)      Comprehensive: exploit all the legally available
        information about the markets, economies and
        societies.
2)      Predictive: exploit all the historical patterns from the
        existing data and current information to project the
        world into the future.
3)      Dynamic: assume the patterns are nonlinear and
        complex with both stochastic and dynamic natures
        and open to the future.
4)      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
  1)    Historical Process Analysis
  2)    Current Situation Assessment
  3)    Effective Cycles and Seasonality Analysis
  4)    Future Price Tendency
  5)    Future Price Volatility
  6)    Macroeconomic Analysis
  7)    Microeconomic-Fundamental Analysis
  8)    Real-time Technical Analysis (Price, Volume, Money Flow, Mood)
  9)    Automated News Analysis (Politico-Economic-Financial Events)
  10)   Detecting Profitable Opportunities
  11)   Trade Planning (Entry, Stop Loss, Profit-Taking Exit, Positions)
  12)   Portfolio Construction and Management
  13)   Risk Analysis and Early Warning of Market Crashes
  14)   Financial Strategic Analysis
        (Maker Makers, Minority-Majority Game, Financial Warfare)
  15)   Global Stock Market Analysis
  16)   Global Currency Market Analysis (Forex)
  17)   Global Bond Market Analysis
  18)   Global Commodity Spot and Futures Market Analysis
  19)   Global Interest Rate Market Analysis
  20)   Trading System Development
  21)   Investment Fund Management

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

1)    Stylized Facts of Financial Market Structures and Prices

2)    Unified Assumptions underlying Financial Market Prices

3)    Financial Information Fusion from Fundamental, Technical, &
      Strategic Analysis

4)    Multilevel Stochastic Dynamic Process Modelling of Financial
      Prices

5)    Active Porfolio Management and Total Risk Control

6)    Financial Strategic Analysis and Intelligent Agent Modelling

7)    Dynamic Optimization

8)    Objective Prediction and Intelligent Trading Systems

9)    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

1)    Fundamental Analysis
      Value, Growth, Price, Margin of Safety, Market Shocks, Business Cycles,
      Industry Trends and Life Cycles, Competitive Advantage, Management
      Quality, Financial Health and Efficiency …
2)    Technical Analysis
      Price, Index, Trend, Market Cycles, Price Waves, Swings & Momentum,
      Support & Resistance, Market Timing, Time Frames, Volatility Breakout,
      Stop Loss, Trendline Break, Trend Reversal …
3)    Strategic Analysis
      Venture 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, …
4)    Mental Analysis
      Survival 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

1)      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 Graham’s class at his 20s.
2)      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.
3)      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
1)      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.
2)      Use Micro-Fundamental Analysis (stock valuation, growth
        prospecting, competitive advantage, financial efficiency,
        management quality, …) to select stocks.
3)      Use Macro-Technical Analysis (stock market index and sector indexes)
        for market timing and macro-portfolio planning.
4)      Use Micro-Technical Analysis (daily charts, realtime intraday charts
        and live quotes) for trade timing.
5)      Enter the Market using intraday charting and tactics with stop loss
        protection.
6)      Hold the Position and Follow Trend in motion with trailing stop loss.
7)      Exit the Market when either fundamental or technical criteria for
        profit taking or stop loss are met.
8)      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
    55 00                          IXIC (2,07 3.01 , 2,16 8.11 , 2,06 7.69 , 2,16 3.95 , +1 06 .2 40), p p+ (de mo) :: Pi vots *, Parabo l ic SAR (2 ,0 12.7 8)                      55 00

    50 00                                                                                                                                                                            50 00

    45 00                                                                                                                                                                            45 00

    40 00                                                                                                                                                                            40 00

    35 00                                                                                                                                                                            35 00

    30 00                                                                                                                                                                            30 00

    25 00                                                                                                                                                                            25 00

    20 00                                                                                                                                                                            20 00

    15 00                                                                                                                                                                            15 00

    10 00                                                                                                                                                                            10 00

        50 0                                                                                                                                                                          50 0

          0                                                                                                                                                                             0

        10 0                                                                                                                                                                          10 0
         90                                                                                                                                                                            90
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         40                                                                                                                                                                            40
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         10                                                                                                                                                                            10

19 88      19 89   19 90   19 91   19 92    19 93     19 94      19 95     19 96     19 97     19 98      19 99     20 00     20 01     20 02      20 03     20 04   20 05   20 06




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                                IXIC (2,15 7.14 , 2,16 5.47 , 2,13 8.45 , 2,16 3.95 , +6 .339 84), p p+ (de mo) :: Pi vots *, Parabo l ic SAR (2 ,0 60.4 3)

50 00                                                                                                                                                                                50 00


45 00                                                                                                                                                                                45 00


40 00                                                                                                                                                                                40 00


35 00                                                                                                                                                                                35 00


30 00                                                                                                                                                                                30 00


25 00                                                                                                                                                                                25 00


20 00                                                                                                                                                                                20 00


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  90                                                                                                                                                                                   90
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  70                                                                                                                                                                                   70
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  30                                                                                                                                                                                   30
  20                                                                                                                                                                                   20
  10                                                                                                                                                                                   10

Apr     May Ju n   Ju l   Aug   Sep   Oct    Nov Dec       19 99        Mar     Apr    May Ju n      Ju l   Aug    Sep    Oct     Nov   Dec     20 00         Mar   Apr May   Ju n    Ju l




      2006-12-21                                                   www.iifp.net              h.pan@iifp.net                                                                   26
       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 couldn’t 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.
    Templeton’s 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, he’d added $86 million to his wealth.

2006-12-21           www.iifp.net   h.pan@iifp.net       28
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)




2006-12-21           www.iifp.net   h.pan@iifp.net     29
        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




                                                                                             Trading System
Politico-Economic Events                                           Strong vs Weak Stocks

                               Index Situation Analysis
   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 Sectors
                                                                           1 – Transportation
                                                                           2 – Technology
                                                                           3 – Capital Goods
             Business Cycle                                                4 – Basic Industries and Materials
                                                                           5 – Energy
                                                                           6 – Food, Drugs, Health Care
             Stock Market Cycle                                            7 – Utilities
                                                                           8 – Financials
                                                                           9 – Autos, Housing, Consumer Cyclicals
                                              Top            Peak
                                          5          6

                                      4
                                                            Bear
                       Bull
                                  3                                        Recession
                                                               7
                              2                Expansion
                                                                   8
                         1                                             9



             Bottom           Trough                                   Bottom          Trough




                                                                                                      time

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      source: www.martincapital.com




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      Economic Indicators Most Sensitive to US Stocks
      (Bernard Baumhohl, 2006)



   Rank                                          Indicator
      1        Employment Situation Report (Payroll Survey)
      2        ISM (Institute for Supply Management) Report – Manufacturing
      3        Weekly Claims for Unemployment Insurance
      4        Consumer Prices
      5        Producer Prices
      6        Retail Sales
      7        Consumer Confidence and Sentiment Surveys
      8        Advance Report on Durable Goods
      9        Industrial Production
     10        GDP



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      Economic Indicators Most Sensitive to US Bonds
      (Bernard Baumhohl, 2006)



   Rank                                           Indicator
       1         Employment Situation Report (Payroll Survey)
       2         Consumer Prices
       3         ISM Report – Manufacturing
       4         Producer Prices
       5         Weekly Claims for Unemployment Insurance
       6         Retail Sales
       7         Housing Starts
       8         Chicago Purchasing Managers Report
       9         Industrial Production/Capacity Utilization
      10         GDP



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      Economic Indicators Most Influential to US $
      (Bernard Baumhohl, 2006)



   Rank                                           Indicator
       1         Employment Situation Report (Payroll Survey)
       2         International Trade
       3         GDP
       4         Current Account
       5         Industrial Production/Capacity Utilization
       6         ISM Report – Manufacturing
       7         Retail Sales
       8         Consumer Prices
       9         Weekly Claims for Unemployment Insurance
      10         Productivity and Costs



2006-12-21                       www.iifp.net   h.pan@iifp.net   41
         source: money.cnn.com

Monday, 21            Tuesday, 22              Wednesday, 23             Thursday, 24         Friday,
                                                                                                25
                        Economic                 Economic                  Economic
                  US - ICSC-UBS Store            US - MBA             US - Durable Goods
                  Sales (wk8/19 , 2006)          Purchase             Orders (Jul , 2006)
                                                Applications
                 US - Redbook (wk8/19 ,        (wk8/18 , 2006)
                         2006)                                       US - Jobless Claims
                                                                       (wk8/19 , 2006)
                US - State Street Investor     US - Existing
                 Confiden (Aug , 2006)       Home Sales (Jul ,
                                                  2006)              US - New Home Sales
                                                                          (Jul , 2006)

                                                 US - EIA
                                             Petroleum Status         US - EIA Natual Gas
                                             Report (wk8/18 ,        Report (wk8/19 , 2006)
                                                   2006)

                                                                      US - Money Supply
                                                                       (wk8/14 , 2006)




   2006-12-21                        www.iifp.net   h.pan@iifp.net                            42
      3. Multilevel Process Analysis of Financial Prices

    Why ?

    Heterogeneous Dynamic Market Hypothesis

    How ?

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




2006-12-21          www.iifp.net   h.pan@iifp.net   43
      Facts and Assumptions underlying MSDP Models
        (Dow 1880’s, Graham 1930’s; Elliott 1930’s,
         Mandelbrot 1970-2004; Peters, 1991; Dacorogna et al, 2001; Pan 2003-2006)
1)    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.

2)    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.

3)    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 Personalized
      E.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:
             1.    Survival of the Fittest
             2.    Enter Your Zone of Freedom
             3.    Avoid the Markets of Your Disadvantage
             4.    Be Practical
             5.    Be Empirical
             6.    Keep It Simple, Stupid! (KISS)
             7.    Trade Carefree
             For Master Trader:
             8.    Only Trade High-Probability Events
             9.    Invest First, Investigate Later
             10.   Exit First, Analyze Later
             11.   Concentrate with Minimal Diversification
             12.   Ride Reflexivity Process Consciously
             13.   Use Leverages, but Judiciously
             14.   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
             1.   Follow the day trend first thing first, keep a distance.
                  Don’t be addicted to technicalities,
                  remain natural, return to nature.
             2.   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.
             3.   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.
             4.   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!




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