1 conventions in the foreign exchange market: do they really explain exchange rate dynamics ?...
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1
Conventions in the Foreign Exchange Market:
Do they really Explain Exchange Rate Dynamics ?
Gabriele Di Filippo
LEDA-SDFi University Paris IX Dauphine
Third FIW Research Conference in International Economics
2
1 Intuition
Stylised Fact:
De Grauwe (2000) [Statistical Study]
« Market agents look for fundamentals that justify the dynamics of exchange rates »
Examples:
Appreciation of the dollar vis-à-vis the euro between January 1999 and December 2002
→ High growth perspectives in the US economy
Depreciation of the dollar vis-à-vis the euro between January 2003 and December 2004
→ Fears concerning the sustainability of the US debt
Bachetta and Van Wincoop (2005) [Theoretical Study]
Theoretical model based on the idea of De Grauwe (2000) – « Scapegoat Model »
3
Definition:
Financial Convention (Orléan (2002)) = « Particular model based on fundamentals and adopted by the majority of agents in the market »
The Building of Conventions:
Step 1: Research of the Convention => Existence of multiple equilibria => High exchange rate volatility
Step 2: Adoption of the Convention => Adoption of a specific fundamental model => Low exchange rate volatility
Step 3: End of the Convention => Empirical facts against the convention => High exchange rate volatility
2 The Main Pillars of Convention Theory
4
3 Identification of the Prevailing Conventions on the Euro/Dollar Exchange Rate
Figure 1 : Dynamics of the Euro/Dollar exchange rate between January 1995 and December 2008
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January 1995 - December 2000 : internet convention
January 2001 - June 2003 : end
internet convention
July 2003 - December
2005: : “the US as a net
debtor” vs “the US as the
engine of the world
economy”
January2006 – June 2007:
“the US as a net debtor”
July 2007 -
December2008:
subprime crisis
Growth Rate Debt
Growth Rate;
Debt
Oil Prices;
House Prices;
Debt
5
tUStPIHtopUS
tniipgdpEUtniipgdp
tUSa
tprofitsEUatprofitsUS
tindprodEUtindprod
ts,22423222120
,1,
14,
13121110
BeartS
BulltS
4 Empirical Model
Estimation Period: January 1995-December 2008
Data Frequency: Daily
Estimation Method: EM algorithm (Hamilton (1990))
Endogeneous Variables: Euro/Dollar Nominal Exchange Rate (1 euro = S dollars)
Exogenous Variables: Bull State: Growth Rate of the Industrial Production
Growth Rate of Expected Profits
Bear State: External Debt/ GDP
Oil Prices
US House Prices
6
tUStPIHtopUS
tniipgdpEUtniipgdp
tUSa
tprofitsEUatprofitsUS
tindprodEUtindprod
ts,22423222120
,1,
14,
13121110
BeartS
BulltS
5 Results
→ Bull Market : Increase in Growth Rate => Appreciation of the dollar
Surprising result on Expected Profits (multicollinearity?)
→ Bear Market: Increase in Debt => Depreciation of the dollar
Increase in Oil Prices => Depreciation of the dollar
Increase in US House Prices => Depreciation of the dollar
Estimated Model (Recall):
Table 1: Estimation output
7
6 Does the Model represent the Variations of Conventions ? E
con
omet
rica
l Res
ult
(F
ilte
red
Pro
bab
ilit
ies)
Con
ven
tion
s A
nal
ysis
8
0
0,5
1
1,5
2
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3
Jan-9
5
Jun-9
5
Nov-9
5
May-9
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Oct-
96
Apr-
97
Sep-9
7
Mar-
98
Aug-9
8
Feb-9
9
Jul-99
Jan-0
0
Jun-0
0
Dec-0
0
May-0
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Nov-0
1
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02
Oct-
02
Mar-
03
Sep-0
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Feb-0
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Jul-04
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Jun-0
5
Dec-0
5
May-0
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Nov-0
6
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07
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Mar-
08
Sep-0
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1
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6 Does the Model represent the Variations of Conventions ?
Internet Convention; Bull Market; Appreciation of the dollar
End internet convention; Bear Market Depreciation of the dollar
Domination of the bear convention;
Depreciation of the dollar
January 1995 - December 2000
Two opposed conventions ;
Bull/Bear; Appreciation/Depreciation of the dollar
Figure 2 : Filtered Probabilities and Euro/Dollar Dynamics (January 1995 - December 2008)
January 2001 – June
2003
July 2003 - December 2005
January 2006 – June 2007
July 2007 - December
2008
9
7 Exchange Rate Volatility and Conventions VariationsE
xces
s of
Exc
han
ge
Rat
e V
olai
lity
Eco
nom
etri
cal R
esu
lt
(Fil
tere
d P
rob
abil
itie
s)
10
7 Exchange Rate Volatility and Conventions Variations
=> Episodes of high exchange rate volatility coincide with conventions variations: research for a new convention (step 1) or end of a new convention (step 2)
=> Exchange rate volatility comes from the uncertainty concerning the prevailing convention in the market
=> When the future becomes uncertain, Public Authorities should intervene in the market to guide agents
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-08
-0,001
-0,0005
0
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0,002
Figure 3 : Filtered Probabilities and Euro/Dollar Excess Volatility
11
8 Resolution of the Exchange Rate Disconnection Puzzle
Exchange Rate Disconnection Puzzle (Meese et Rogoff (1983)):
=> Exchange Rate Dynamics is disconnected from the fundamentals
Advantages related to the Convention Model:
=> Asymmetric World
=> Non-Linear Structure
Problems with Traditional Models of Exchange Rate:
Invariance of the coefficients associated to fundamentals
=> Exchange Rate Disconnection Puzzle = Pure Artefact ?
12
9 Limits of the Model
Limits:
Daily Frequency Model => Extrapolation of Macroeconomic Data
=> Very Strong Hypothesis => Highly contestable hypothesis
Choice of the Variables ?
Questions:
Is the model correctly specified ?
If the model is badly specified, then why does it provide the expected results ?
13
10 Other
Filtered Probabilities in monthly variation with daily data:
0
0,5
1
1,5
2
2,5
3
Jan-
95
Aug
-95
Mar
-96
Oct
-96
May
-97
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-97
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-99
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-99
May
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-00
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-02
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-02
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-03
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-03
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-05
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-08
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-08
0
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11 Other
Filtered Probabilities in monthly variation with monthly data:
0
0,5
1
1,5
2
2,5
3
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95
Jan-
96
Jan-
97
Jan-
98
Jan-
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Jan-
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