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# Tag Info

7

You have a multidimensional problem - there isn't an answer of "this is what the greeks look like" for all cases, because it depends on the various levels of the different parameters. For example, if we limit ourselves purely to KO Call options, where the spot is 100, and there is no drift, with a time to maturity of 1 year (changing this is equivalent to ...

6

Let \begin{align*} \tau = \inf\{t: t \ge 0, S_t \le L \}. \end{align*} Then the down-out-call option has payoff \begin{align*} (S_T-K, 0)^+\pmb{1}_{\tau >T}, \end{align*} and the down-out version zero-coupon $T$-maturity bond has payoff \begin{align*} \pmb{1}_{\tau >T}. \end{align*} Moreover, for the down-in payoff $X$, since $L=K$, \begin{align*} X &...

6

Presumably the option can be exercised for intrinsic at any point. Note the interviewer asked for a static hedge using the stock, not a dynamic hedge. Hence you must find a buy and hold portfolio that will always give you at least the value of the option (if you’re short it which I suppose is the question) until it is exercised. Note that the maximum ...

5

Here are at least three mistakes in your code: p += s0 * exp(...) should be p *= exp(...). Your volatility and rates are per annum, so divide the days by 365 (or 255) in your function asset_price. In asset_price you multiply by days inside the loop. However, the loop is already iterating over the days - so you don't take two steps of one day but two steps ...

4

The difference is that the barrier option is weakly path dependent while the lookback option is strongly path dependent. In case of a knock-out barrier option, conditional on the option being alive at the pricing time you don't need to carry any additional state variables except for the current asset price. The payoff doesn't directly depend on the level of ...

3

The error is, you are not storing the random numbers for the same path at the end: xbefore = x + c*tau + sigma*sqrt(tau)*randn() A = muA + sigmaA*randn(); xafter = xbefore + A; But then at end you set a different path here by creating a new random number: xT = log(S0)+(c+muA*lambda)*T+sqrt((sigma^2+(muA^2+sigmaA^2)*lambda)*T)*randn(); randn() generates ...

3

You're right that the "real" greeks of a digital option are unwieldy, e.g. delta is zero everywhere except at the barrier where it is an impulse. So sell-side trading desks model/price digital options as tightly struck call/put spreads that will sit and play nicely with the rest of the book. Here's a simple example: let's say a bank sells a digital call on ...

3

No, the pricing of a double barrier knock-out option cannot be decomposed into single barrier options. Here are a few references that apply the method of images to the valuation of double barrier options: A very clear and easy to follow exposition can be found in Chapter 3.5 of the Ph.D. thesis by Konstandatos (2003). If you don't have access to that, then ...

3

Their formula looks correct. As is usually the case, there are multi ways to derive this result. I will outline two of them here. Reflection Principle & Measure Change The solution to the risk-neutral dynamics of $S$ is $$S_t = S_0 \exp \left\{ \left( r - \frac{1}{2} \sigma^2 \right) t + \sigma W_t^* \right\},$$ where $W^*$...

3

As specified I will assume your option is perpetual; I will also assume that it is written on an asset whose price $(S_t)_{t \geq 0}$ follows a Geometric Brownian Motion (GBM) with drift coefficient $rS_t$ and diffusion coefficient $\sigma S_t$ under the risk-neutral measure $\mathbb{Q}$ $-$ we assume a constant risk-free rate: $$dS_t = rS_tdt + \sigma S_t ... 3 Assuming \theta>0 (take \tilde{X}=\mu-X if it is not the case) Let us denote \text{erfi}(x) the imaginary error function Let us denote \tau_L,resp.\tau_U the hitting time of Lresp.U where L<U 1) Using Ito's lemma, prove that :$$Y_t = \text{erfi}\left(\sqrt{\frac{\theta}{\sigma^2}}\left(X_t-\mu\right)\right) \text{ is a martingale}... 3 Since there is a closed form in the BS case for continuous barrier options, you probably won't find a huge amount of work on this since it's not needed. In the discrete case, I did a paper with Tang: http://ssrn.com/abstract=1441142 Pricing and Deltas of Discretely-Monitored Barrier Options Using Stratified Sampling on the Hitting-Times to the Barrier 3 there are a number of ways to do this. You do have to make some modelling assumptions, however. eg continuity, BS model holds, or log stock price process is independent of level. The most common way is to take the pay-off and geometrically reflect in the barrier. (i.e. pass to log coordinates and reflect). i.e. write the function as f(x) where x= \log ... 3 As Daneel mentioned in his comment, you can't simply split your expectation of product into a product of two expecations as the two quantities are far from being independent... Now, to answer your question w.r.t. how you could compute the expectation of the joint event of being in the money while having hit the barrier, you were right in using the reflexion ... 2 As I mentioned above, I am not sure what the variable r is. If we ignore that, or assume the questioner wanted to say its the risk free interest rate, then it has no effect on the number of paths. Then it is clear that after 50 steps going from \1024 to \2500 requires a net of 4 up movements with the given x=y^{-1}=1.25. Thus the number of steps ... 2 I'd recommend M. Joshi and T. Leung "Using Monte Carlo simulation and importance sampling to rapidly obtain jump-diffusion prices of continuous barrier options". Though it assumes jump-diffusion process for the returns it is straightforward to obtain the scheme for a diffusion process. Also Paul Glasserman's [book][2] [2]: http://www.amazon.com/Financial-... 2 I do not have any reference, but I think H is for hitting. 2 May be I have overlooked something, but I believe that \begin{align*} Q(t, S) = \mathbb{P}\left(\tau_{B} \le T \mid \mathcal{F}_t\right). \end{align*} Then \{Q(t, S), \, 0<t < T\} is a martingale, and the PDE follows immediately, by noting that \begin{align*} dQ &= Q_t dt + Q_S dS + \frac{1}{2}Q_{SS} d\langle S, S\rangle_t\\ &=\Big(\... 2 The goal of this exercise is to replicate the payoff of the Secured Barrier Call by a linear combination of the known products: European up-out call (cost 12), digital strike 33 (cost 0.73) and digital strike 50 (cost 0.7). Looks to me it is sufficient to buy: 1x up-out call 50 x digital strike 50 The payout at expiry of this linear combination would be: ... 2 There are a few issues that need to be separated here. Issue "zero" is whether your MC is able to correctly represent the dynamics you've chosen for your assets. If you implement your MC properly, by construction it should converge in distribution to the postulated dynamics. No bias there. Variance yes potentially, because of discretisation, but no ... 1 Formally, let \begin{align*} \tau = \inf\{t: t \ge 0, S_t \ge 50 \}. \end{align*} Then \begin{align*} \text{Payoff} &= \left(S(31)-33 \right)^+\pmb{1}_{\tau >31} + 50\times \pmb{1}_{\tau \le 31}. \end{align*} That is, an up-out barrier call plus 50 digital up-in barrier options. 1 I nearly agree with @phlsmk's answer, but with some small differences. First off, the delta of a digital is not "zero everywhere except at the barrier where it is an impulse". This is what it is at t=T. before this, it is smoothed out, exactly like a regular option is. The problem is on what the delta may become. This is not the only place where it ... 1 Assume you are long an up-and-in put and short and up-and-in call of the same maturity, strike and barrier. When S_t = B for t \in [0, T], then both barrier options knock-in and turn into vanilla options. You are now long a put and short a call with the same maturity and strike. From put/call parity, you know that S_t + C_t = K e^{-r (T ... 1 Idea Let B be a standard brownian motion starting from x_0=0, m_T = \inf_{u\leq T}B_u and M_T =\sup_{u\leq T}B_u. Let's define if it exists for A\in\sigma(B_u,u\leq T), \mathbb{P}(A | B_T=x_T)\stackrel{\rm def}{=}\lim_{\varepsilon\to 0}\mathbb{P}(A|B_T\in(x_T-\varepsilon,x_T+\varepsilon))\begin{split} \mathbb{P}(\tau_U\leq T \cap \tau_U\leq ...

1

Reflection principal ? Reflection principle. It holds for the Brownian process, not the GBM. [Reflection principle is quite specific to symmetric random walks]. By chance, if $\mu-\frac{\sigma^2}{2}=0$ and $\sigma>0$, then you have : $$\mathbb{P}(\tau^S_B<T)=\mathbb{P}(\tau^W_{\frac{1}{\sigma}\ln(B)}<T)$$ and you can apply reflection principle.

1

What you seem to omit is the initial condition for $v(\tau, x)$? Assume you have an up-and-out barrier option for which $v$ satisfies the initial boundary value problem \begin{eqnarray} \mathcal{H} \{ v \} (\tau, x) & = & 0 \qquad \text{for } (\tau, x) \in \mathbb{R}_+ \times \mathbb{R}_-\\ v(0, x) & = & f(x)\\ v(\tau, 0) & = & 0 \...

1

As is often the case, there are generally two solution strategies here. (Probabilistic) You explicitly solve for the expected discount factor at the first passage time $\nu$ of $S$ to the level $B$ under the risk-neutral probability measure $\mathbb{P}^*$, i.e. $$V_0 = \mathbb{E}_{\mathbb{P}^*} \left[ e^{-r \nu} \right].$$ (...

1

You need a couple more assumptions and it becomes doable. (1) no arbitrage (2) no interest rates or dividends (3) spot price moves continuously Then there is a replication possible. Buy the forward struck at $K$ expiring at the same time as the barrier option. If the barrier is ever hit, the forward is at-the-money so has value zero. In that case ...

1

If I understand your question correctly, then you have a barrier option pricer for spot model dynamics of the form $$\mathrm{d}S_t = (r - \delta) S_t \mathrm{d}t + \sigma S_t \mathrm{d}W_t.$$ Now you are wondering whether you can abuse the input parameters in a way such as to use the same model to price options on a forward ...

1

I assume you mean a barrier option on a futures contract? It's not a straight forward thing to do analytically because of the Samuelson effect (futures tend to ramp up in volatility as they approach maturity). Most people build a dedicated vol surface for the futures contract and use a local vol based solution.

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