CHAPTER 5
UNDERSTANDING LINEAR DEPENDENCE:
A LINK TO ECONOMIC MODELS
5.1 Price Dynamics: The Cob-Web Model
Figure 5.1 The Cob-Web Model: Price Dynamics (One Supply Shock)
Supply
p1
p3
1
p
p5
 2 1
*
 1
p4
p2
Demand
q1
q3
q*
q4 q2
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5.1.4 Simulation of the Model pt
Autocorrelation Function
 p * (1   )   pt 1   t and
Figure 5.2 Time Series and Autocorrelation Functions of the AR Model
pt  22.4  0.6 pt 1   t
15.5
15.0
14.5
14.0
13.5
13.0
12.5
12.0
200
225
250
275
300
Simulated price
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Figure 5.3 Time Series and Autocorrelation Functions of Producer Prices
of Oranges in Florida
24
22
20
18
16
14
12
10
8
1992
1994
1996
1998
2000
2002
Price of oranges in Florida
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Figure 5.4 Alternative Price Dynamics (Smooth Adjustment to Equilibrium)
Supply
p1
p2
1
p
 1
*
p3
 1
2
Demand
q1
q2 q3 q *
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5.2 Portfolio Returns and Nonsynchronous Trading
Figure 5.5 Two Assets Trading at Different Frequencies
(Nonsynchronous Trading)
p0i
.
news
0 day 1
.
p0j
news
.
p1j
p2i
news
day 2
day 3
.
news
.
p2j
news
p4i
.
day 4
.
p3j
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news
.
p4j
5
Table 5.1 Returns and their News Content
R1j  p1j  p 0j
R1i  p0i  p0i  0
R2j  p 2j  p1j
R2i  p 2i  p 0i
R3j  p3j  p 2j
R3i  p 2i  p 2i  0
R4j  p 4j  p3j
R4i  p4i  p2i
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Figure 5.6 Autocorrelation Functions of Daily Portfolio Returns
AMEX portfolio
SP500 portfolio
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5.3 Asset Prices and the Bid-Ask Bounce
Figure 5.7 Time Series and Autocorrelation of Monthly Returns to BBVA
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Figure 5.8 Time Series and Autocorrelation Functions of the Simulated Series
pt  0.2  t 1   t
20
10
0
-10
-20
-30
200
225
250
275
300
Simulated returns
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