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#1




Question About Delta (Greeks)
Delta is the partial derivative of the option price with respect to the stock price and given to be calculated as .
Looking at BlackScholes where , the given formula for Delta would be the partial of the option price with respect to the stock price, but only if is a constant. But is dependent on stock price, so it's not a constant. Can anyone help me understand why ?
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If you don't know where you are going, any road will take you there. Lewis Carroll Last edited by Phantomwise; 02192008 at 11:15 AM.. Reason: Learning MimeTex 
#2




The important point is that d2 also depends on S, and so
But those last two terms exactly cancel out (you need to work out the partial derivatives of d1 and d2 for that to be clear, though). EDIT: Oh, you probably also need to use the formula for , too. It's been a little while since I checked this formula.
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The Poisson distribution wasn't named after a fish  it was named after a man ... who was named after a fish. Last edited by jraven; 02152008 at 07:48 PM.. 
#3




Bah, I might as well just work it out.
We know , so that tells us that . We also know that so Putting this into our formula for gives
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The Poisson distribution wasn't named after a fish  it was named after a man ... who was named after a fish. 
#4




I'd forgotten about . It doesn't seem intuitive that the terms would cancel like that, but looking at your proof I see that it does indeed work out that way mathematically. Interesting.
It probably took you a while to type that out, but it does clear things up a great deal. Many thanks!
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#5




Quote:
However when all you have to work with is the final BlackScholes formula there's not much you can do but take the derivative and grind away, and then it does seem like a bit of a miracle that the formula for Delta is so simple.
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The Poisson distribution wasn't named after a fish  it was named after a man ... who was named after a fish. 
#6




SOA sample no. 18
(18) A market maker sells 1000 1yr euro gap call options, and deltahedges the position with shares. You are given:
1. each gap call is written on 1 share 2. S(0)=100 3.sigma=100% 4. K=130 5. trigger=100 6. r=0% Under BS framework, determine the initial number of shares in the delta hedge. ANS=586. The solution is a direct application of the discussion above. where C(gap)=S*N(d1)130*N(d2) = [S*N(d1)100*N(d2)]30*N(d2)=C30*N(d2) Delta(gap)=partial derivative of C(gap) wrt S Ive never thought about the N(d) formula into detail and exactly how it works with the BS formula.........can anyone shed some light on this thanks
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#7




can anyone elaborate on this way of viewing BS. and also can this be used to solve SOA sample 18. (ie intuitively instead of the direct approach in the SOA solution)
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#8




I don't think it would really help with computing the delta of gap options; the problem is that a term which is negligible for ordinary options can't be ignored in the gap option case, and working out it's contribution is annoying. (Doable, but annoying.) The trick with writing the value of the gap option as a plain call plus an extra term is probably the simplest approach.
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The Poisson distribution wasn't named after a fish  it was named after a man ... who was named after a fish. 
#9




Quote:
where is a lognormal random variable with parameters and (where that second sigma is the volatility of the stock). The product repesents the stock price at time t in a risk neutral world, so we're computing the discounted expected payoff in a riskneutral world; but since the price of an option doesn't depend on the market's attitude about risk, this will give the correct price in the real world too. [Well, assuming stocks actually followed GBM in the real world.] But then Some explicit computations for lognormal variables results in When those are plugged into the formula for the price of the option you get Ok, that's not very simple. But what does it tell us about ? Well, informally speaking (because there's a HUGE catch hidden here) But So (using the formulas above for the expected value and probability). So what's the catch? Can we actually move the derivative inside the expected value? The function isn't differentiable with respect to when (something I specifically ignored when I gave the derivative above), which makes it questionable whether you can. It turns out that in this specific case you can move it inside the expectation, and everything I typed is fine. But in the case of a gap option, where you can't (the fact that the payoff isn't continuous is a big problem). Anyway, it means you have to be more careful with computing the derivative of the expectation in the gap option case. And at that point you might as well just find some other way.
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The Poisson distribution wasn't named after a fish  it was named after a man ... who was named after a fish. Last edited by jraven; 03082008 at 07:11 PM.. 
#10




Can we use the fact that BlackScholes is homogeneous of degree 1 in K and S?
It looks like people were wondering about that Delta formula right around the same time a year ago
The expected value discussion is very interesting and seems essential...and yet I keep wondering whether there's a simpler derivation. A mathematician named Rolf Poulsen has a paper on the subject, in which he says this: Euler's Theorem (that is otherwise predominantly used in microeconomics) says that a differentiable function f is homogenous [of degree 1] if and only if it has the formI have two problems with this: (1) I believe that there needs to be more discussion about the "term that multiplies S." A decomposition of a homogeneous function.Now observe that the BlackScholes callprice is homogenous in stockprice and strike. Then Euler’s Theorem tells us that the term that "multiplies S" in the formula is indeed the partial derivative with respect to S; the delta. is not unique in general: For example, we have and .Therefore, you can't necessarily "read off" the partial derivatives of a homogeneous function from a decomposition like that. Hmm. Also, (2) I'm used to spelling "homogeneous" with two e's 
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delta, delta hedging 
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