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Lecture Eight

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					Lecture Eight



                    Finance Theory
                The Capital Assets Pricing Model
                     A Keynesian Critique
                    A Keynesian Alternative
     Recap
•   “Breakdown” of Phillips curve
•   Rise of neoclassicism
•   Critiques of logical foundations of neoclassical micro
•   Today
     – Neoclassical foundations of finance theory
     – Some problems
     – An alternative view
        • Fisher‟s “Debt-Deflation theory of Great Depressions”
          elaborated
        • Minsky‟s Financial Instability Hypothesis
        • Peter‟s Fractal Markets Hypothesis
    – Prospects for US…
    The Capital Assets Pricing Model
• Problem: How to “predict the behaviour of capital
  markets”
• Solution: extension of economic theories of investment
  under certainty...
   – to investment under conditions of risk
      • Based on neoclassical utility theory
      • Investor maximises utility subject to (s.t.) constraints
      • Utility is a:
          – Positive function(+ive fn) of expected return ER
          – -ive fn of risk (standard deviation) sR
      • Constraints are available spectrum of investment
        opportunities
    The Capital Assets Pricing Model


                                      “Efficient”
             Investment              opportunities
             opportunities            on the edge
Z inferior
to C
(lower ER)                               Indifference
and B                                       curves
(higher
sR)
                                    Increasing utility:
  Optimal                            Higher expected
combination                        returns & lower risk
  for this
  investor
   Border (AFBDCX) is Investment Opportunity Curve (IOC)
     The Capital Assets Pricing Model
• IOC reflects correlation of separate investments.
  Consider 3 investments A, B, C:
   – A contains investment A only
      • Expected return is ERa,     Variance due to A
       • Risk is sRa                          Perceived
    – B contains investment B only        correlation of A
       • Expected return is ERb,               with B
       • Risk is sRb                     (varies between -1
    – C some combination of a of A & (1-a) of B & +1)
       • ERc=aERa + (1-a)ERb


s Rc   .s Ra  (1   ) s Rb  2. rab . . 1   .s Ra .s Rb
           2     2             2   2
     The Capital Assets Pricing Model
• If rab=1, C lies on straight line between A & B:
                                                This is 1

s Rc   2 .s Ra 2  (1   ) 2 s Rb 2  2. rab . . 1   .s Ra .s Rb
     The Capital Assets Pricing Model
• If rab=1, C lies on straight line between A & B:


s Rc   2 .s Ra 2  (1   ) 2 s Rb 2  2. rab . . 1   .s Ra .s Rb
       2 .s Ra 2  (1   ) 2 s Rb 2  2. . 1   .s Ra .s Rb



   This can be factored
    The Capital Assets Pricing Model
• If rab=1, C lies on straight line between A & B:


s Rc   .s Ra  (1   ) s Rb  2. rab . . 1   .s Ra .s Rb
           2          2          2    2



      .s Ra  (1   ) s Rb  2. . 1   .s Ra .s Rb
           2          2          2    2



         .s   Ra    (1   ).s Rb    .s Ra  (1   )s Rb
                                      2




     Identical to straight line relation for expected return:
The Capital Assets Pricing Model

        sR      W h en rab= 1
                                       B



                      t
              In v e sm en t
             O ppo r tun ity C
                C u rv e


               A


                                           ER

                                
     The Capital Assets Pricing Model
• If rab=0, C lies on curved path between A & B:

                                          This is zero


s Rc   2 .s Ra 2  (1   ) 2 s Rb 2  2. rab . . 1   .s Ra .s Rb

                                              Hence this is zero
    The Capital Assets Pricing Model
• If rab=0, C lies on curved path between A & B:




s Rc   .s Ra  (1   ) s Rb  2. rab . . 1   .s Ra .s Rb
           2     2            2     2



      2 .s Ra 2  (1   ) 2 s Rb 2
     The Capital Assets Pricing Model
• If rab=0, C lies on curved path between A & B:




s Rc   2 .s Ra 2  (1   ) 2 s Rb 2  2. rab . . 1   .s Ra .s Rb
       2 .s Ra 2  (1   ) 2 s Rb 2
                                               Straight line relation
          .s   Ra    (1   )s Rb 
                                          2




Hence lower risk for diversified portfolio
  (if assets not perfectly correlated)
The Capital Assets Pricing Model

       sR     W h en rab< 1
                                      B



                     t
             In v e sm en t
            O ppo r tun ity C              Fall in sR due to
                                           diversification
               C u rv e

                                          when investments
              A                           are not perfectly
                                             correlated

                                          ER

                               
    The Capital Assets Pricing Model
• Sharpe assumes riskless asset P with ERP=pure interest
  rate, sRP=0.
• Investor can form portfolio of P with any other
  combination of assets
• One asset combination will initially dominate all others:
The Capital Assets Pricing Model

           Efficiency: maximise expected return
             & minimise risk given constraints



                             Only asset combination
                              which can efficiently
                                be combined with
                               riskless asset P in
                                   a portfolio
    The Capital Assets Pricing Model
• Assume limitless borrowing/lending at riskless interest
  rate = return on asset P
• Investor can move to anywhere along PfZ line by
  borrowing/lending
• Problem:
   – P the same for all investors (“simplifying assumption”)
   – But investor perceptions of expected return, risk,
     investment correlation will differ
• Solution:
   – assume “homogeneity of investor expectations” [OREF
     II]
   – utterly unrealistic assumption, as is assumption of
     limitless borrowing by all borrowers at riskless
     interest rate. So...
    The Capital Assets Pricing Model
• Defended by appeal to Friedman‟s “Instrumentalism”
  (next lecture):
   – “the proper test of a theory is not the realism of its
     assumptions but the acceptability of its implications”
• Consequence of assumptions:
   – spectrum of available investments/IOC identical for
     all investors
   – P same for all investors
   – PfZ line same for all investors
   – Investors distribute along line by borrowing/lending
     according to own risk preferences:
The Capital Assets Pricing Model


                 Thrill seeker...




          Highly
        risk-averse
    The Capital Assets Pricing Model
• Next, the (perfect) market mechanism
  – Price of assets in f will rise
  – Price of assets not in f will fall
  – Price changes shift expected returns
  – Causes new pattern of efficient investments aligned
    with PfZ line:
The Capital Assets Pricing Model




                               Capital market line

                                  Range of
                               efficient asset
                                combinations
                                after market
                                    price
                                adjustments:
                               more than just
                                one efficient
                                  portfolio
    The Capital Assets Pricing Model
• Theory so far applies to combinations of assets
• Individual assets normally lie above capital market line
  (no diversification)
• Can‟t relate between ERi & si
• Can relate ERi to “systematic risk”:
• Investment i can be part of efficient combination g:
   – Can invest (additional)  in i and (1-) in g
      • =1 means invest solely in i;
      • =0 means some investment in i (since part of portfolio
        g);
      • Some <0 means no investment in i;
      • Only =0 is “efficient”
 The Capital Assets Pricing Model




Single investment
i which is part of             Efficient
   portfolio g               combination g



                             Additional investment
                             in i is zero (a=0) here
    The Capital Assets Pricing Model
• Slope of IOC and igg‟ curve at tangency can be used to
  derive relation for expected return of single asset


      E Ri  P  rig
                       s Ri
                       s Rg
                               
                               E Rg  P   
   • This allows correlation of variation in ERi to
     variation in ERg (undiversifiable, or systematic, or
     “trade cycle” risk)
   • Remaining variation is due to risk inherent in i:
The Capital Assets Pricing Model



                   Risk peculiar
                     to asset i




              Higher return for assets more strongly
              affected by trade cycle (systematic risk
    The Capital Assets Pricing Model
• Efficient portfolio enables investor to minimise asset
  specific risk
• Systematic risk (risk inherent in efficient portfolio) can‟t
  be diversified against
• Hence market prices adjust to degree of responsiveness
  of investments to trade cycle:
   – “Assets which are unaffected by changes in economic
     activity will return the pure interest rate; those which
     move with economic activity will promise appropriately
     higher expected rates of return.” [OREF II]
    The Capital Assets Pricing Model
• Crux/basis of model: markets efficiently value
  investments on basis of expected returns/risk tradeoff
• Modigliani-Miller extend model to argue valuation of
  firms independent of debt structure (see OREF II)
• Combination: the “efficient markets hypothesis”
• Focus on portfolio allocation across investments at a
  point in time, rather than trend of value over time
• Argues investors focus on “fundamentals”:
   – Expected return
   – Risk
• So long as assumptions are defensible…
     The Capital Assets Pricing Model
• In order to derive conditions for equilibrium in the capital
  market we invoke two assumptions. First, we assume a common
  pure rate of interest, with all investors able to borrow or lend
  funds on equal terms. Second, we assume homogeneity of
  investor expectations: investors are assumed to agree on the
  prospects of various investments–the expected values, standard
  deviations and correlation coefficients described in Part II.
  Needless to say, these are highly restrictive and undoubtedly
  unrealistic assumptions. However, since the proper test of a
  theory is not the realism of its assumptions but the
  acceptability of its implications, and since these assumptions
  imply equilibrium conditions which form a major part of classical
  financial doctrine, it is far from clear that this formulation
  should be rejected–especially in view of the dearth of
  alternative models leading to similar results. (Sharpe 1964
  [1991]; emphasis added)
• But Sharpe later admits to some qualms with this:
     The CAPM: Reservations
• “People often hold passionately to beliefs that are far from
  universal. The seller of a share of IBM stock may be convinced
  that it is worth considerably less than the sales price. The
  buyer may be convinced that it is worth considerably more.”
  (Sharpe 1970)
• However, if we try to be more realistic:
   – “The consequence of accommodating such aspects of reality
     are likely to be disastrous in terms of the usefulness of the
     resulting theory... The capital market line no longer exists.
     Instead, there is a capital market curve–linear over some
     ranges, perhaps, but becoming flatter as [risk] increases over
     other ranges. Moreover, there is no single optimal
     combination of risky securities; the preferred combination
     depends upon the investors‟ preferences... The demise of the
     capital market line is followed immediately by that of the
     security market line. The theory is in a shambles.” (Sharpe
     1970 emphasis added)
    A Keynesian view
• Key issue is uncertainty, not risk
   – Cannot possibly estimate expected returns far into
     future:
      • “our basis of knowledge for estimating the yield ten
        years hence of [an investment] amounts to little... those
        who seriously attempt to make any such estimate are
        often so much in the minority that their behaviour does
        not govern the market.”
   – Instead, conventions to cope with uncertain future:
      • “assume that the present is a ... serviceable guide to the
        future… that the existing state of ... prices ... is based
        on a correct summing up of future prospects… we
        endeavor to fall back on the judgment of the rest of the
        world which is perhaps better informed.”
    Keynes‟s view
• Investors profit by picking shifts in confidence:
   – “the professional investor and speculator are ...
     concerned, not with making superior long-term
     forecasts of the probable yield of an investment over
     its whole life, but with foreseeing changes in the
     conventional basis of valuation a short time ahead of
     the general public… this behaviour... is an inevitable
     result of an investment market... For it is not sensible
     to pay 25 for an investment of which you believe the
     prospective yield to justify a value of 30, if you also
     believe that the market will value it at 20 three
     months hence.” [OREF II]
• Markets thus conducted by speculation on immediate
  behaviour of other speculators, rather than rational
  calculation:
    Keynes‟s view
• Recall earlier lectures on Keynes and uncertainty
• The Stockmarket as a beauty contest and “the third
  degree”:
   – “… pick out the six prettiest faces … the prize being
     awarded to the competitor whose choice most nearly
     corresponds to the average preferences of the
     competitors as a whole... We have reached the third
     degree where we devote our intelligences to
     anticipating what average opinion expects the average
     opinion to be.”
• The practicality of rational calculation?:
   – “Investment based on genuine long-term expectation is
     … scarcely practicable. He who attempts it must surely
     … run greater risks than he who tries to guess better
     than the crowd how the crowd will behave…”
    The “Price system” and Asset Markets
• Normal micro theory:
   – Supply a positive function of price
   – Demand a negative function of price
   – Supply and demand independent
• If price rises
   – Supply rises
   – Demand falls
   – Tendency towards equilibrium
• But finance markets
   – Supply (of assets, shares) possibly a positive function
     of price
   – Demand also a positive function of price:
    The “Price system” and Asset Markets
• If price of assets (shares, real estate, etc.) rising,
  demand also rises
• Buyers hope to buy and sell on a rising market
• The faster the rate of price increase (generally speaking)
  the faster the growth of demand
• Tendency to move away from “equilibrium” (“fundamental
  value”, historic price to earnings ratios, etc.)
• Price thus destabilises an asset market
• An alternative theory to equilibrium-oriented
  conventional finance theory needed which acknowledges
  destabilising role of asset prices
• Derived from Fisher and Keynes by Minsky
    Fisher: Keynes‟s unlikely ally
• Conventional theory of finance an extension of Fisher‟s
  Theory of Interest (1930)
   – The rate of interest “expresses a price in the
     exchange between present and future goods”
   – Three elements combine to determine rate of
     interest:
       • Subjective: “the marginal preference for present over
        future goods”
          – strong preference: borrower; weak preference:
            lender; balance determines supply of funds
      • Objective: “investment opportunity” determines demand
        for funds
      • The Market: equilibrium interest rate equates supply to
        demand
    Fisher: Keynes‟s unlikely ally
• “Market for loans” differs from normal market:
   – normal market, payment made and goods exchanged
     simultaneously (in absence of credit)
   – Loans: goods (loaned money) exchanged now;
     repayment (principal + interest) occurs later
• Two special assumptions needed to eliminate this
  difference:
   – (A) The market must be cleared--and cleared with
     respect to every interval of time. (B) The debts must
     be paid. (Fisher 1930: 495)
• Fisher‟s book published in 1930
• In 1929, Fisher comments “Stocks appear to have
  reached a permanently high plateau”… and then came
  October 23rd: “Black Wednesday”…
    Alternative Finance (1): Financial Instability
• Fisher & Keynes blended into alternative theory of
  finance by Minsky: the “Financial Instability Hypothesis”
   – partial objective: to explain Great Depressions
   – overall objective: an alternative economics to
     neoclassical micro/macro
    Minsky‟s interpretation of Keynes
• Two price levels
   – Commodity prices set by markup on cost of production
   – Assets / equipment prices based on expected revenue
• Volatile basis for expectations essential
   – Future fundamentally uncertain: “we simply do not
     know”, so conventions developed:
       • Present accepted as a “serviceable guide” to the future
       • Current expectations presumed correct
       • Mass sentiment
• Finance demand for money
   – “it is ... the „financial‟ facilities which regulate the pace
     of new investment” [Keynes 1937]
    Minsky‟s Hypothesis
• Economy in historical time
• Debt-induced recession in recent past
• Firms and banks conservative re debt/equity ratios, asset
  valuation
• Only conservative projects are funded
• Recovery means conservative projects succeed
• Firms and banks revise risk premiums
   – Accepted debt/equity ratio rises
   – Assets revalued upwards
    The Euphoric Economy
• Self-fulfilling expectations
   – Decline in risk aversion causes increase in investment
      • Investment expansion causes economy to grow faster
   – Asset prices rise, making speculation on assets
     profitable
   – Increased willingness to lend increases money supply
     (endogenous money)
   – Riskier investments enabled, asset speculation rises
• The emergence of “Ponzi” (Bondy?) financiers
   – Cash flow from “investments” always less than debt
     servicing costs
   – Profits made by selling assets on a rising market
   – Interest-rate insensitive demand for finance
    The Assets Boom and Bust
• Initial profitability of asset speculation:
   – reduces debt and interest rate sensitivity
   – drives up supply of and demand for finance
   – market interest rates rise
• But eventually:
   – rising interest rates make many once conservative
     projects speculative
   – forces non-Ponzi investors to attempt to sell assets to
     service debts
   – entry of new sellers floods asset markets
   – rising trend of asset prices falters or reverses
    Crisis
• Ponzi financiers go bankrupt:
   – can no longer sell assets for a profit
   – debt servicing on assets far exceeds cash flows
• Asset prices collapse, drastically increasing debt/equity
  ratios
• Endogenous expansion of money supply reverses
• Investment evaporates; economic growth slows or
  reverses
• Economy enters a debt-induced recession ...
    The Aftermath
• High Inflation?
   – Debts repaid by rising price level
   – Economic growth remains low: Stagflation
   – Renewal of cycle once debt levels reduced
• Low Inflation?
   – Debts cannot be repaid
   – Chain of bankruptcy affects even non-speculative
     businesses
   – Economic activity remains suppressed: a Depression
• Big Government?
   – Anti-cyclical spending and taxation of government
     enables debts to be repaid
   – Renewal of cycle once debt levels reduced
    Modelling Minsky
• A taste of dynamics: a model of Minsky built on Marx‟s
  model of cyclical economy:
   – “accumulation slackens in consequence of the rise in
     the price of labour, because the stimulus of gain is
     blunted. The rate of accumulation lessens; but with its
     lessening, the primary cause of that lessening
     vanishes, i.e. the disproportion between capital and
     exploitable labour power… The price of labor falls
     again to a level corresponding with the needs of the
     self-expansion of capital… To put it mathematically,
     the rate of accumulation is the independent, not the
     dependent variable; the rate of wages the dependent,
     not the independent variable.” (Marx 1867, 1954: 580-
     581)
    Modelling Minsky
• Mechanism is:
  – high rate of growth causes high level of employment
  – high level of employment causes increase in wage level
  – increase in wage level reduces profit
  – reduced profit reduces investment
  – lower investment reduces growth rate
  – lower growth rate reduces employment
  – lower employment leads to falling wage level
  – falling wage level restores profitability, restarting
    cycle
    Modelling Minsky
• Minsky‟s theory explicitly based on time and changes in
  variables over time
• Can‟t be modelled using simultaneous equations (which
  ignore time)
• Instead have to use
   – Differential equations (rate of change of y with
     respect to time is a function of…)
   – Computer simulation (artificial economies with time-
     based variables)
• Differential equations (normally) show rate of change of
  one variable as a function of values of another.
• Much of classical economics can be described as “verbal
  differential equations”. An example: Malthus on
  population:
    Digression: Dynamics & Equations
• “I think I may fairly make two postulata. First, That food
  is necessary to the existence of man. Secondly, That the
  passion between the sexes is necessary and will remain
  nearly in its present state...”
• “ Population, when unchecked, increases in a geometrical
  ratio. Subsistence increases only in an arithmetical ratio.
  A slight acquaintance with numbers will shew the
  immensity of the first power in comparison of the
  second.”
• These can be put into “verbal differential equations”:
   – In the absence of food shortages, population grows
     exponentially
   – Food increases linearly
• In actual differential equations, we get:
   Malthus‟s Population Dynamics


           d  b         Births minus
    1 dP
    P dt                     deaths

                       A small constant for high F/P ratios but
Percentage rate         rises dramatically as F/P falls below a
of change of                         critical levelP
population                          d F , P      
                                                           F
           dF
              a
           dt                         No “ceteris
                                  paribus”: Feedback
                       A
                                     from F to P.
                       constant
  Slope of food                     Modelling this:
  output
                    Malthus‟s Population Dynamics

                Putting it all together, we get:
                                                                                               “Nonlinear”
      1 dP                                                             2
                                                                                                 negative
             b     P    
                                      P
                                             
      P dt                       C  a  t 
                                                                                              feedback
Population growth in                                                                           contribution
the absence of food                                                                          from population
shortages
                                                                                            Linear attenuating
                             5
                     2 10
 1.557997 .10
                5



                                                                                              feedback from
                                                                                              food (C is initial
                             5
                    1.5 10




      Z
       1           1 10
                             5
                                                                                                    level)
                                                                                        I don‟t think Malthus
            i




                     5 10
                             4                                                          ever realised that this
                                                                                        was (roughly) the path
          100                    0
                                     0   200   400             600   800       1000
                                                                                        he predicted for
                                                                                        population...
                                                      0 
                                                                               1 .10
                       0                                                            3
                                                     Z     i
    Modelling Minsky
• Same type of logic needed to express Minsky‟s model of
  finance
   – Specify relationships in terms of “rate of change of y
     is a function of…”
   – Relate all elements in causal chain until it “loops back”
     on itself
      • (Malthus‟s theory is incomplete here; there is no
        “feedback” from population to food)
   – No more “ceteris paribus” since everything determines
     everything else, but in a time sequence.
• So to model Minsky, we start with Marx 1867 and
  Goodwin 1967...
    Modelling Minsky
• Causal chain                           “accelerator”
   – Capital (K) determines Output (Y)      Y
                                                K
                                                 v
   – Output determines employment
     (L)                                    L
                                                 Y
   – Employment determines wages                 a




                                                     productivity
     (w)
   – Wages (w´L) determine profit (P) dw        U 
                                          w f  
   – Profit determines investment (I) dt        N
   – Investment I determines capital
     K                                   Y  w L




                                                    Phillips
                                                     curve
   – chain is closed dK     
                         k  Y    K
                     dt    K
     
I  k 
     K      Investment Depreciation
               function
An Economic Model without Finance

                                Basic Goodwin Growth Cycle
                      1


               0.95
  Proportion




                0.9


               0.85


                0.8


               0.75
                          0          5             10        15   20
                                                 Time
                              Wage Share
                              Employment
                              Equilibrium Wage Share
                              Equilibrium Employment
    A Economic Model with Finance
• Add debt:
                                 Debt
   – Firms borrow when
     desired investment
     exceeds profits        dD
                                r  D  I  Y  W 
   – Debt solely used to    dt
     finance investment             Interest rate
   – Profit is now output                     Gross Profit
     net of wages and
     debt repayment           Y  w L  r  D
A Economic Model with Finance
A Economic Model with Finance
    The “Inefficient Markets Hypothesis”
• Argument that investors
   – react slowly to news
   – over-react
   – ignore “reversion to the mean”
• Series of good reports leads to expectation of more good
  news
• Firm valuation rises, seen as “growth stock”
   – rise becomes self-fulfilling; bandwaggon buying
• Firm cannot sustain above sector/economy performance
  indefinitely
• Initial “bad news” reports ignored as firm “reverts to
  mean”
• Finally, “bear” valuations set in; bandwaggon selling
   – “growth stock” underperforms in medium term
    The “Inefficient Markets Hypothesis”
• 90% of price variability due to internal dynamics of
  speculators watching other speculators:
   – EMH idea of investors focusing solely upon expected
     risk/return wrong:
                     Instead,
                   speculators
                   watch other
                   speculators
    The “Fractal Markets Hypothesis”
• Puzzle
   – If EMH is so wrong intellectually, how come it almost
     seems right in the data?
      • Solution: a highly chaotic distribution is very hard to
        distinguish from a truly random distribution
• Chaos/Complexity
   – Deterministic system (no shocks involved) which
     generates highly complex, aperiodic cycles
      • Discussed in lecture on dynamics
• Applied to finance, the “Fractal Markets Hypothesis”
   – Apparently random movements of stock market in fact
     mask a “fractal” dynamic process
      • so what‟s a fractal?
    The “Fractal Markets Hypothesis”
• A pattern produced by a highly nonlinear self-referential
  process…
• Or in English:
   – Take an initial number
      • Apply some (possibly simple but) nonlinear
        transformation to it
      • Use the resulting number as the next input to be
        transformed
   – Resulting time series can appear highly random, but at
     the same time
      • is generated by a process with no chance (risk) involved
      • has an underlying structure, which can however be very
        hard to discern
    The “Fractal Markets Hypothesis”
• Peters applies fractal analysis to time series generated
  by asset markets
   – Dow Jones, S&P 500, interest rate spreads, etc.
   – finds a “fractal” structure
   – intellectually consistent with
      • Inefficient Markets Hypothesis
      • Financial Instability Hypothesis
   – Based upon
      • heterogeneous investors with different expectations,
        different time horizons
          – trouble breaks out when all investors suddenly
            operate on same time horizon with same expectations
    The “Fractal Markets Hypothesis”
• Take a typical day trader who has an investment horizon of
  five minutes and is currently long in the market. The average
  five-minute price change in 1992 was -0.000284 per cent [it
  was a “bear” market], with a standard deviation of 0.05976
  per cent. If, for technical reasons, a six standard deviation
  drop occurred for a five minute horizon, or 0.359 per cent, our
  day trader could be wiped out if the fall continued. However,
  an institutional investor–a pension fund, for example–with a
  weekly trading horizon, would probably consider that drop a
  buying opportunity because weekly returns over the past ten
  years have averaged 0.22 per cent with a standard deviation
  of 2.37 per cent. In addition, the technical drop has not
  changed the outlook of the weekly trader, who looks at either
  longer technical or fundamental information. Thus the day
  trader‟s six-sigma [standard deviation] event is a 0.15-sigma
  event to the weekly trader, or no big deal. The weekly trader
  steps in, buys, and creates liquidity. This liquidity in turn
  stabilises the market. (Peters 1994)
  Conclusion
• View of finance depends on whether take equilibrium or
  dynamic view
   – equilibrium:
      • optimum allocation of funds, rational markets
   – dynamic:
      • speculative markets, accumulation of debt, possibility
        of crisis
• Current crises difficult, if not impossible, to explain in
  equilibrium terms
   – Rapid movements in markets (e.g., sevenfold
     devaluation of Indonesian rupiah in a week by money
     markets) can‟t be due to similar fall in real
     productivity of Indonesian economy
   – Finance and economic outcomes clearly linked
     (rather than independent as in standard theory)
    Conclusion: Asian Crisis
• Debt-deflation probable cause of Asian crisis
   – Originating in Japan‟s “Bubble Economy” 1987-90
   – Huge bad debts carried by banks after crash of real
     estate market
   – Boom in Asia partly funded by Japanese/American
     banks seeking profit after collapse of own markets in
     90/91
   – Crash in Asia amplified by free capital markets
      • Currencies devalued on fear of inability to repay loans
         – Devaluation (4-fold for Thailand, 7-fold for
           Indonesia) guarantees loans cannot be repaid
      • Depression ensues
         – “Solution” must involve repudiation of debt
    Conclusion: New York New York…
• Current US economic boom (now probably over) underwritten
  by asset price boom
   – Boom due to
      • “Euphoric” expectations on Internet
      • Feedback from rising prices to rising prices
      • Debt Financing of share purchases
   – The bust? Complicated by Mutual Funds, but
      • At 35:1, P:E ratio highest in (non-Depression) history
      • Broad market in decline now for more than 2 years;
        boom focused in very narrow range of stocks (as in
        1929)
      • USA debt/output ratio 150% (vs 60% in 1929 [Fisher
        1933])
      • Inflation on border of deflation (as in 1929)…
      • one major difference: Big Government
          – impact discussed in Week 11

				
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