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Lecture 2: Conditional Expectation
Discounted Cash Flow, Section 1.2
© 2004, Lutz Kruschwitz and Andreas Löffler
No. 2
1.2.1 Uncertainty
Uncertainty is a distinguished feature of valuation usually modelled as different states of nature with corresponding cash flows
But: to the best of our knowledge particular states of nature play no role in the valuation equations of firms, instead one uses expectation of cash flows.
( ).tFCF
[ ]tE FCF
No. 3
1.2.1 Information
Today is certain, the future is uncertain.
Now: we always stay at time 0!
And think about the futureSimon Vouet: «Fortune-teller» (1617)
No. 4
1.2.1 A finite example
There are three points in
time in the future.
Different cash flow
realizations can be
observed.
The movements up and
down along the path
occur with probability
0.5.
No. 5
1.2.1 Actual and possible cash flow
What happens if actual cash flow at time t=1 is neither 90 nor 110 (for example, 100)?
Our model proved to be wrong…Nostradamus (1503-1566),
failed fortune-teller
No. 6
1.2.1 Expectations
Let us think about cash flow paid at time
t=3, i.e. What will its
expectation be tomorrow?
This depends on the state we will have
tomorrow. Two cases are possible:
3.FCF
1 1110 or FCF 90.FCF A.N. Kolmogorov (1903-1987),
founded theory of
conditional expectation
No. 7
1.2.1 Thinking about the future today
1
3
1
3
3
3 1
Case 1 ( 110) :
1 2 1 Expectation of FCF 193.6 96.8 145.2 133.1.
4 4 4
Case 2 ( 90) :
1 2 1 Expectation of 48.4 145.2 96.8 108.9.
4 4 4
Hence, expectation of is
133.1[ | ]
FCF
FCF
FCF
FCF
E FCF
F if the developement at 1 is up,
108.9 if the developement at 1 is down.
t
t
No. 8
1.2.2 Conditional expectation
The expectation of FCF3 depends on the state of nature at time
t=1. Hence the expectation is conditional: conditional on the
information at time t=1 (abbreviated as |1).
A conditional expectation covers our ideas about future
thoughts.
This conditional expectation can be uncertain.
No. 9
1.2.2 Rules
How to use conditional expectations?
We will not present proofs, but only
rules for calculation.
The following three rules will be well-known from classical expectations, two will be new.
Arithmetic textbook of
Adam Ries (1492-1559)
No. 10
1.2.2 Rule 1: Classical expectation
At t=0 conditional expectation
and classical expectation coincide.
Or: conditional expectation generalizes classical expectation.
0|E X E X F
No. 11
1.2.2 Rule 2: Linearity
Business as usual…
| | |t t tE a X b Y a E X b E Y F F F
No. 12
1.2.2 Rule 3: Certain quantity
Safety first… 1| 1tE F
From this and linearity for certain quantities X,
| 1 |
1 |
t t
t
E X E X
XE
X
F F
F
No. 13
1.2.2 Rule 4: Iterated expectation
When we think today about
what we will know tomorrow
about the day after tomorrow,
we will only know what we
today already believe to know
tomorrow.
Let s t then
| | |t s sE E X E X
F F F
No. 14
1.2.2 Rule 5: Known quanitites
We can take out from the
expectation what is known.
Or: known quantities are
like certain quantities.
If X is known at time
| |t t
t
E XY XE Y F F
No. 15
1.2.3 Using the rules
We want to check our rules by looking at– the finite example and– an infinite example.
No. 16
1.2.3 Finite example
3 1
3 1
Remember that we had
133.1 if up at time 1, |
108.9 if down at time 1.
From this we get
1 1| 133.1 108.9 121.
2 2
tE FCF
t
E E FCF
F
F
We want to check our rules by looking at the finite example and an infinite example.
No. 17
1.2.3 Finite example
3 1 3 1 0
3 0
3
| | | by rule 1
| by rule 4
by rule 1
121 !
E E FCF E E FCF
E FCF
E FCF
F F F
F
And indeed
It seems purely by chance that
But it is on purpose! This will become clear later…
3 13 1
1| 1.1 ,E FCF FCF F
No. 18
1.2.3 Infinite example
Again two factors up and
down with probability pu
and pd and 0<d<u
or
1
up,
down.t
tt
uFCFFCF
dFCF
No. 19
1.2.3 Infinite exampleLet us evaluate the conditional expectation
where g is the expected growth rate.
If g=0 it is said that the cash flows «form a martingal». We will
later assume no growth (g=0).
1
: 1
|
,
t t u t d t
u d t
g
E FCF p uFCF p dFCF
p u p d FCF
F
No. 20
1.2.3 Infinite example
Compare this if using only the rules
1
1
1
| | by rule 4
1 | see above
1 | by rule 2
(1 ) repeating argument.
t s t t s
t s
t s
t ss
E E FCF E E FCF
E g FCF
g E FCF
g FCF
tF F F
F
F
No. 21
Summary
We always stay in the present. Conditional expectation
handles our knowledge of the future.
Five rules cover necessary mathematics.