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Bruno DUPIRE

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Title: Bruno DUPIRE


1
Bruno DUPIRE Bloomberg Quantitative Research
Arbitrage, Symmetry and Dominance
NYU Seminar New York 26 February 2004
2
Background
REAL WORLD
MODEL
anything can happen
stringent assumption
1 possible price,
infinite number of possible
1 perfect hedge
prices,
infinite potential loss
Can we say anything about option prices and
hedges when (almost) all assumptions are relaxed?
Dominance
3
Model free properties
Dominance
4
European profilesnecessary sufficient
conditions on call prices
K
K1
K2
K2
K3
K1
0
K
Dominance
5
A conundrum
Call prices as function of strike are positive
decreasing they converge to a positive value a.
Do we necessary have ?
  • It depends which strategies are admissible!
  • If all strikes can be traded simultaneously, C
    has to converge to 0.
  • If not, no sure gain can be made if a gt 0.

Dominance
6
Arbitrage with Infinite trading

N
Dominance
7
Quiz
Strong smile
80
90
S0 100
Put (80) 10, Put (90) 11.Arbitrageable?
Dominance
8
Answer
  • At first sight
  • P(80) lt P(90), no put spread arbitrage.
  • At second sight
  • P (90) - (90/80) P (80) is a PF
  • with final value gt 0 and premium lt 0.

Dominance
9
Bounds for European claims
If market price lt LB buy f, sell the hedge for
LB
S
Dominance
10
non
Call price monotonicity
Call prices are decreasing with the strikeare
they necessarily increasing with the initial spot?
NO. counter example 1
counter example 2 martingale
120
25
110
100
100
100
90
90
80
75
0
T
0
T
Dominance
11
Call price monotonicity
If model is continuous Markov,Calls are
increasing with the initial spot (Bergman et al)
Take 2 independent paths wx and wy starting from
x and y today.
(1) wx and wy do not cross.
(2) wx and wy cross.
y
y
x
x
Knowing that they cross, the expectation does not
depend on the initial value (Markov property).
Dominance
12
Lookback dominance
  • Domination of
  • Portfolio
  • Strategy when a new maximum is reached, i.e.
  • sell
  • The IV of the call matches the increment of IV of
    the product.

Dominance
13
Lookback dominance (2)
  • More generally for
  • To minimise the price, solve
  • thanks to Hardy-Littlewood transform (see Hobson).

Dominance
14
Normal model with no interest rates
Dominance
15
Digitals
1 American Digital 2 European Digitals
Reflected path
From reflection principle, Proba (Max0-T gt K)
2 Proba (ST gt K)
K
Brownian path
As a hedge, 2 European Digitals meet boundary
conditions for the American Digital.If S
reaches K, the European digital is worth 0.50.
Dominance
16
Down out call
DOC (K, L) C (K) - P (2L - K)
60.00
50.00
40.00
30.00
20.00
10.00
K
2L-K
0.00
50
60
70
80
90
100
110
120
130
140
150
160
170
-10.00
L
-20.00
-30.00
-40.00
The hedge meets boundary conditions.If S
reaches L, unwind at 0 cost.
Dominance
17
Up out call
UOC (K, L) C (K) - C (2L - K) - 2 (L - K) Dig
(L)
The hedge meets boundary conditions for the
American Digital.If S reaches L, unwind at 0
cost.
Dominance
18
General Pay-off
20.00
15.00
10.00
5.00
0.00
80
90
100
110
120
130
140
150
160
170
180
-5.00
-10.00
-15.00
-20.00
The hedge must meet boundary conditions, i.e.
allow unwind at 0 cost.
Dominance
19
Double knock-out digital
2 symmetry points infinite reflections
0.02
0.9
0.02
0.01
0.4
0.01
0.00
-0.1
90
100
110
130
80
120
-0.01
-0.01
-0.6
-0.02
-1.1
-0.02
Price Hedge infinite series of digitals
Dominance
20
Max option
(Max - K) 2 C (K)
Pricing
Hedge when current Max moves from M to MdM sell
2 call spreads C (M) - C (MdM), that is 2 dM
European Digitals strike M.
K
Dominance
21
Extensions
Dominance
22
Extension to other dynamics
Principle symmetric dynamics w.r.t
L antisymmetric payoff w.r.t L
K
0
L
2L-K
No interpretation in terms of hedging portfolio
but gives numerical pricing method.
Dominance
23
Extension double KO
0
K
0
L
Dominance
24
Martingale inequalities
Dominance
25
Cernov
  • Property
  • In financial terms

K
Kl
  • Hedge
  • Buy C (K), sell l AmDig (K l).
  • If S reaches K l , short 1 stock.

Dominance
26
Tchebitchev
  • Property
  • In financial terms


S0
S0 a
S0 - a
Dominance
27
Jensens inequality
f
EX
X
Dominance
28
Applications
X
Dominance
29
Cauchy-Schwarz
  • Property
  • Let us call
  • Which implies

Dominance
30
A sight of Cauchy-Schwarz
Dominance
31
Cauchy-Schwarz (2)
  • Call dominated by parabola
  • In financial terms
  • Hedge
  • Short ATM straddle.
  • Buy a Par b.

Dominance
32
DOOB
  • Property
  • Hedge at date t with current spot x and current
    max a
  • If x lt a do nothing.
  • If x a -gt a da sell 4da stocks
  • total short position 4 (a da) stocks.

Dominance
33
Up Crossings
  • Product pays U(a,b) number of times the spot
    crosses the band a,b upward.
  • Dominance

2
3
1
  • Hedge
  • Buy 1/(b-a) calls strike a.
  • First time b is reached, short 1/(b-a) stocks.
  • Then first time a is reached, buy 1/(b-a) stocks.
  • etc.

Dominance
34
Lookback squared
  • Property ( if S not continuous)
  • In financial terms (Parabola
    centered on S0)
  • Zero cost strategy when a new minimum is lowered
    by dm, buy 2 dm stocks.
  • At maturity long 2 (S0-min) stocks paid in
    average (1/2) (S0min).
  • Final wealth

Dominance
35
A simple inequality
Dominance
36
Quadratic variation
Strategy be long 2xi stock at time ti
In continuous time
Dominance
37
Quadratic variation application
Volatility swap to lock (historical
volatility)2 QV (normal convention)
1) Buy calls and puts of all strikes to create
the profile ST 2 2) Delta hedge (independently
of any volatility assumption) by holding at any
time -2St stocks
Dominance
38
Dominance
We have quite a few examples of the situation
for any martingale measure, which can
be interpreted financially as a portfolio
dominance result. Is it a general result?
i.e. if you sell A, can you cover yourself
whatever happens by buying B and
delta-hedge? The answer is YES.
Dominance
39
General resultRealise your expectations
Theorem If for any martingale measure
Q Then there exists an adapted process H (the
delta-hedge) such as for any path w That is
any product with a positive expected value
whatever the martingale model (even incomplete)
provides a positive pay-off after hedge.
Dominance
40
Sketch of proof
Lemma If any linear functional positive on
B is positive on f, then f is in B
Proof B is convex so if by
Hahn-Banach Theorem, there is a separating
tangent hyperplane H, a linear functional
and a real a such that
Dominance
41
Sketch of proof (2)
The lemma tells us If for any martingale
measure Q, then
Which concludes the theorem.
stoch. int.
positive
Dominance
42
Equality case
Corollary of theorem If for any martingale
measure Q, Then there exists H adapted such that
Proof apply Theorem to f and -f Adding up
Dominance
43
Bounds for derivatives
The theorem does not give a constructive
procedure In incomplete markets, some claims do
not have a unique price. What are the admissible
prices, under the mere assumption of 0 rates
(martingale assumption)
Dominance
44
Bounds for European claims1 date
If market price lt LB buy f, sell the hedge for
LB
S
Dominance
45
Example Call spread
100
50
100
200
ST
Dominance
46
Bounds for n dates
Natural idea intersection of convex hull of g
with (0,,0) vertical line This corresponds to
a time deterministic hedge decide today the
hedge at each date independently from spot.
Dominance
47
Bounds n dates (2)
Lower bound Apply recursively the operator A
used in the one dimensional case, i.e. define
gives the lower bound
Dominance
48
Bounds for path dependent claimscontinuous time
  • Brownian case El Karoui-Quenez (95)
  • Analogous to American option pricing
  • American sup on stopping times
  • Upper bound sup on martingale measures
  • In both cases, dynamic programming
  • For upper bound Bellman equation

Dominance
49
Conclusion
  • It is possible to obtain financial proofs /
    interpretation of many mathematical results
  • If claim A has a lesser price than claim B
    under any martingale model, then there is a hedge
    which allows B to dominate A for each scenario
  • If a mathematical relationship is violated by
    the market, there is an arbitrage opportunity.

Dominance
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