Binomial tree

darshang3

New Member
Hi david

In calculating the size of up move factor U wat does square root of t mean is it time to maturity or the length of the step in the binomial model.

for example to calculate the value of a 6 month american call option using a 2 step binomial model wat will be the t value taken here to calculate U.

THANKS.
 

darshang3

New Member
i m still not getting it...
can u tell me wat will be the t value in my above example.

is it SQRT of 2....correct me if m wrong.


thanks.
 

David Harper CFA FRM

David Harper CFA FRM
Subscriber
sorry - read too fast:
re: 6 month american call option using a 2 step binomial model
each step is 3 months and the usage is: SQRT(3/12) because typically the vol input is annual
e.g, if annual volatility = 30%, (volatility connotes annualized standard deviation)
then up (u) = exp(30%*SQRT(3/12)) for the 1st 3-month step
i.e., you can see the "square root rule" at work: SQRT(3/12) scales an annual volatility into a 3 month volatility

David
 

brian.field

Well-Known Member
Subscriber
"a" sometimes refers to alpha = the actual expected return from the asset but I can't see the entire question here. It may be irrelevant.
 

David Harper CFA FRM

David Harper CFA FRM
Subscriber
Hi @surojitpalb Actually (a) is used, but it's not Brian's fault, the notes could be better help here (we are updating this note this semester) :( In case you want to see it "in action," I pulled out the above example (from the learning XLS) to a single sheet here at https://www.dropbox.com/s/6q5vxl1lmyrqvvv/0110-Hulls-2step-binomial.xlsx?dl=0 (snapshot below). This is Hull's own example.

Here a = exp(Rf - q)*Δt = exp(0.05 - 0.02)*0.25 = 1.007528. Then (a) does inform (p) via p = (a-d)/(u-d) = (1.007528 - 0.9048)/(1.1052-0.9048) = where u = exp[σ*sqrt(Δt)] = exp[0.20*sqrt(0.25)] = exp(and d = 1/u = exp(-σ*sqrt Δt). I hope that clarifies!

0110-hull-2step-binomial.png
 

David Harper CFA FRM

David Harper CFA FRM
Subscriber
Hi @surojitpalb It's the expected discounted price based on the two forward nodes:
  • Expected future value (at time 0.25) is weighted by p and (1-): (100.66 * 51.26% + 5.06 * 48.74%) = $54.07; this is the "expected" part
  • Discounted to current value at risk-free rate = $54.07 *exp(-5%*0.25 years) = $53.39; this is the "discounted" part
  • Together $53.39 = (100.66 * 51.26% + 5.06 * 48.74%) / exp(-5%*0.25 years) which is rightly called by Tuckman the expected discounted value.
Each of 100.66, which is called node[1,1] for node[state 1 in time, row 1 up from the bottom at 0], and 5.06 which is called node[1,0] for node[state 1, row 0] are themselves each discounted expected values. But the final option node values (e,g, $189.24) are just intrinsic values at maturity. I hope that helps!
 

brian.field

Well-Known Member
Subscriber
The figures in blue are the option values - I can't tell if they are American or European but you should be able to simply calculate the option values using the data that is provided. Take a look at the referenced reading as well.
 

David Harper CFA FRM

David Harper CFA FRM
Subscriber
@surojitpalb I trust you noticed that I shared the XLS? To get node[1,0] and node [1,1] is it the same "backward induction;" eg, for node [1,1]
  • Expected future value (at time 0.50) is weighted by p and (1-): ($189.3362 * 51.26% + $10.00 * 48.74%) = $101.9276; ie, conditional at node [1,1] the expected future value is probability-weighed average of node[2,1] and node[2,2]
  • Discounted to current value at risk-free rate = $101.9276 *exp(-5%*0.25 years) = $100.6614; ie, discounted from t=0.5 to t=0.25
  • Together $100.6614 = ($189.3362 * 51.26% + $1.00 * 48.74%)/exp(-5%*0.25 years); i.e., "discounted expected value"
@brian.field re the (a) I just noticed for the first time that Hull calls it "growth factor per step" consistent with your label for it :cool: I just happen to be currently revising these binomial exhibits, I think they look better (eg, including some formulas in the exhibit):
0112-hull-binomial-13-11.png
 
Last edited:
Small correction above @David Harper CFA FRM - should be "$10 + 48.74%" - you have $1.

I understand from your two examples how you discount to the present, but there is a slide that you have in your lecture video that I can't get your values when using the method above. If you look at the image I attached, to get to 2.0256, I did: (3.2*.652) + (0*0.348) = 2.1056. Now if I discount that: 2.1056 * e(-.25*.12), I get 2.024738. You have 2.0256. Is this a rounding issue? If so, how do I approach these issues on the exam?
 

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ShaktiRathore

Well-Known Member
Subscriber
Hi,
p=(exp(.12*.25)-0.90)/(.20)
[3.20*(exp(.12*.25)-0.90)/(.20)+0*(1-(exp(.12*.25)-0.90)/(.20))]*exp(-.12*.25) = 2.0256 (checked this formula in excel its coming exactly 2.0256) yes its due to rounding.
thanks
 

David Harper CFA FRM

David Harper CFA FRM
Subscriber
@omar72787 thanks for the correction mentioned (fixed above). I agree with @ShaktiRathore if i use p = 0.6520 then i get c[1,1] = 2.024738, but the true value of p = p=(exp(.12*.25)-0.90)/(.20). Re: If so, how do I approach these issues on the exam? Over the years, GARP has gotten lots of feedback about this sort of thing: the modern exam should never expose the candidate to such rounding error trade-offs. The choices given should not be near enough for it to matter. I hope that helps!
 
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