American put option. Exercise time is a random variable, calculation of expected payoff

M

Makina

I got an American put option, where the payoff is $V_\tau = \max(K - X_{\tau}, 0)$ and $X_{\tau}$ is the price of an underlying at the stopping time $\tau < T$. The underlying follows a standard GBM with $r = q = 0$; $X_0$ is given.

I need to calculate the expectation $E[V]$ under the assumption that $\tau$ has exponential distribution with intensity $\lambda = 0.025$.



I tried transforming this equation into: $$\int_0^\infty (K - X_0e^{-\frac{1}{2}\sigma^2 \tau + \sigma \sqrt{\tau}Z})^+\lambda e^{-\lambda \tau}d\tau$$ but then I'm just completely lost with how to proceed with the square root. I know that by definition $E[\tau] = \frac{1}{\lambda}$ but can I use this as an answer? As in, can I claim that: $$E[V] = V\left(X_{\frac{1}{\lambda}}, \frac{1}{\lambda}\right) \text{ ?}$$
 

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Existence of a faithful irreducible representation using Möbius function

  • Sebastien Palcoux
  • Mathematics
  • Replies: 0
Let $G$ be a finite group, $L(G)$ its subgroup lattice and $\mu$ the Möbius function.
Consider the Euler totient of $G$ defined as follows:
$$ \varphi(G) = \sum_{H \le G}\mu(H,G) |H| $$ Let $X=\{M_1, \dots, M_n \}$ be the set of maximal subgroups of $G$. By applying the Crosscut Theorem with $X$ (see this comment of Richard Stanley) and next the inclusion–exclusion principle, we get that: $$ \varphi(G) = \left\lvert G \setminus \bigcup_{i=1}^n M_i \right\rvert $$ In other words, $\varphi(G)$ is the number of elements $g \in G$ such that $\langle g \rangle = G$. It follows that $$ \varphi(G) \neq 0 \Leftrightarrow G \text{ cyclic}$$

Note that $\varphi(\mathbb{Z}/n) = \varphi(n)$ the usual Euler's totient function.

Now, consider the dual Euler totient of $G$ defined as follows: $$ \hat{\varphi}(G) = \sum_{H \le G}\mu(1,H) |G:H| $$

Question: $ \hat{\varphi}(G) \neq 0 \Leftrightarrow G$ has a faithful irreducible complex representation?

Remark: We will see below that $(\Rightarrow)$ is true. So the question reduces to $(\Leftarrow)$.
It is true for the finite simple group $G$ of order $<10000$:

$$ \begin{array}{c|c|c|c|c|c} G & |G| & \hat{\varphi}(G) \newline \hline A_5 & 60 & 8 & \newline \hline PSL(2,7) & 168 & 228 & \newline \hline A_6 & 360 & 8748 & \newline \hline PSL(2,8) & 504 & 19056 & \newline \hline PSL(2,11) & 660 & 24932 & \newline \hline PSL(2,13) & 1092 & 105684 & \newline \hline PSL(2,17) & 2448 & 389496 & \newline \hline A_7 & 2520 & 188136 & \newline \hline PSL(2,19)& 3420 & 1148028 & \newline \hline PSL(2,16)& 4080 & 1935584 & \newline \hline PSL(3,3)& 5616 & 395496 & \newline \hline PSU(3,3)& 6048 & 507168 & \newline \hline PSL(2,23)& 6072 & 2234784 & \newline \hline PSL(2,25)& 7800 & 5391800 & \newline \hline M_{11} & 7920 & 1044192 & \newline \hline PSL(2,27)& 9828 & 7778916 & \newline \end{array}$$

Any idea about the meaning of these numbers?



Proof of $(\Rightarrow)$

Consider the relative version $$ \hat{\varphi}(H,G) = \sum_{K \in [H,G]}\mu(H,K) |G:K|.$$ Warning: $-\hat{\varphi}(H,G)$ is not the Möbius invariant of the bounded coset poset $\hat{C}(H,G)$ because $$-\mu(\hat{C}(H,G)) = \sum_{K \in [H,G]}\mu(K,G) |G:K| $$ and $\mu(K,G) \neq \mu(H,K)$ in general.

Now if $[H,G]$ is boolean of rank $n$ then $\mu(K,G) = (-1)^n \mu(H,K)$; moreover (independently) by Theorem 3.21 of this paper, if $ \hat{\varphi}(H,G) \neq 0$ then there is an irreducible complex representation $V$ of $G$ such that $G_{(V^H)} = H$. Next, using a dual reformulation of the Crosscut Theorem with $X$ the set of atoms, we can extend the proof of Theorem 3.21 to any interval $[H,G]$ (i.e. without assuming it to be boolean). Finally by taking $H = 1$, we get that for any finite group $G$, if $\hat{\varphi}(G) \neq 0$ then there is an irreducible complex representation $V$ such that $G_{(V)} = 1$, which means that $V$ is faithful.

How can I use a constant Q transform to detect low frequencies without making the buffer size too large?

I am trying to write code to detect musical notes within a signal. I have been reading up on different methods for extracting frequency information out of a signal to determine which notes were played at a given time and I came across the "constant Q transform" which seems to be very well suited for this application. The main thing that appealed to me with the constant Q transform is that it is supposed to be able to achieve higher resolution for low frequencies than a normal FFT.

I just finished implementing a basic constant Q transform in C++ after reading through this paper and I ran into one major problem.

My code can be found here: https://godbolt.org/z/43b8vohs3

The problem primarily arises from this part of the paper:

enter image description here

If I am understanding what it says here correctly, this means in order to detect a frequency of 27.5Hz (A0, the lowest note on an 88 key piano) in a signal sampled at 44100Hz, The constant Q transform would require the input to have a minimum buffer size of N[k] = (S/f)Q = 44100/27.5*34 = 54523. That is over one full second of audio which is WAY too large to be practical considering notes can be played much faster than that.

I feel like I must be missing something critical here because requiring a buffer size that large would make this algorithm effectively useless for detecting notes in most pieces of music. How can the constant Q transform be used to detect low frequencies like this without increasing the buffer size to a completely unrealistic size?

Ideally I would like to keep the buffer size small enough to work on 100ms of audio or less (around 4096) or even smaller as long as it is possible to achieve a high enough resolution for the output to be useful.

Demeaning (Or Centering) signal in frequency domain

I have a signal in the frequency domain and I am doing an ifft to transform it to the time domain. For obtaining a good resolution in the time domain I am doing a zero padding. The problem is that, some part of the signal remains in negative time domain, this is why I tried subtracting the mean of the signal in the frequency domain before performing the ifft, and this result in signals that always start from t=0. I know that in the time domain the mean of a signal is the DC value, I guess that in the frequency this is equivalent, right?

How do amateur (ham) radio noise reduction filters work?

Amateur radio receivers often have several types of audio filters, and a common one is simply called "Noise Reduction." Compared to notch filters, impulse filters, and adjustable bandpass filters, where the operation is fairly obvious, I have little idea how "Noise Reduction" works.

Some googling implied maybe it was simple smoothing, i.e. some kind of low pass filter, and it does sound like the high end is attenuated. But I can already do that with the adjustable bandpass filter. So I wonder if it is a little more sophisticated than that, perhaps with some non-linear or adaptive characteristics designed for voice on radio.

Any thoughts, and is there a term for this kind of filter that I could use for searching?

Power Spectral Density and Total Power Calculation for Signal

  • Javad Ibrahimli
  • Technology
  • Replies: 0
I am currently working on analyzing a signal with the autocorrelation function given by:

$$R(\tau) = 100 \cos( 10000\pi\tau) (Λ(2000\tau))^2$$

I need assistance in plotting the power spectral density $G_f(\omega)$ of this signal. Additionally, I am interested in calculating the total power of the signal and specifically determining its power within the frequency range of $10\texttt{kHz}\leq |\omega|≤12\texttt{kHz}$.

Could someone please provide guidance on how to approach this problem or share some code snippets in MATLAB/Python that could help me achieve these objectives?

Thank you in advance for your support!

I have attempted to implement the calculation of the power spectral density and total power using the given autocorrelation function in MATLAB/Python. Specifically, I've looked into functions like fft, pwelch, and related signal processing tools.

I was caught cheating on an exam, how can I minimize the damage?

  • user23292
  • Education
  • Replies: 0
I got caught cheating in a two-hour engineering exam consisting of 100 multiple choice questions which was done online through the moodle e-learning software. I feel like my life is almost over.

Having not studied well and having no time to study, I decided to cheat. I know there are no excuses for cheating. Before the exam I dug up research about moodle exams, and it turned out you can take the exam anywhere you want to as long as you have the quiz password. Taking advantage of this, I went up to my engineering library and asked a close friend who was taking the exam to send me the quiz password before he starts.

What I had prepared:

  • Calculator (was not allowed during the quiz).
  • Printed material (consisted of more than 200 pages).
  • Google search engine (on a laptop ready to help).
  • Whatsapp (to ask questions for a friend who took the quiz last year).

As I sat down, I did the first 50 questions, suddenly the quiz froze and moodle told me:

you are not allowed to take the exam from this location.

While I was leaving, one instructor responsible for the course (there are 5) came and found me. She accused me of cheating, took my mobile and made come with her to a huge office where two instructors searched all my mobile (took the name of my friend who gave me the password), and started talking to me, asking for all details of this crime. They confiscated my phone and looked at everything: Whatsapp conversations, all my emails, and images. The instructor took the mobile from my hand without asking me and kept it with her. It seems that the instructors are going to report me as well as my friend who sent me the password for the exam.

The university's Student Code Conduct says that cheating will result in one of the following: a Dean's Warning, Suspension, or Expulsion. If any of that happens, my future is over. A Dean's Warning will cancel my financial aid. A suspension would be for at least two years, and coming back would require a lot of work. An expulsion will be definite.

I've learned the lesson about cheating, now how can I fix this? How can I prevent the five instructors from reporting me? It's obvious that I should speak to them, but what should I say? What can I do? My future is almost over, but many of you are teachers and instructors here, what can I do to fix this?



EDIT: Wow, it has been almost 3 years. I would like to update on how I dealt with the situation.

Lesson: It was obvious to never ever cheat under any circumstances, independent of whether you'd get caught or not.

Consequences: I received a Dean's Warning but the financial aid wasn't revoked. However, I couldn't stay in the department as engineering was not for me, and I was even ashamed to stay in the university.

What happened next: I transferred to an ABET-accredited Computer Science institution and I graduated with distinction in 2.5 years. It was extremely stressful as I took 6 major courses (18 credits) in one semester, but I had to do it.

Future plans: I'm going for an MSc in Computer Science in St. Andrews next year.

Why does a Van de Graaff generator output a constant voltage

  • John greg
  • Physics
  • Replies: 0
Why is a Van de Graaff generator a current source why does it deliver a constant current regardless of the load? I've seen people say that this is due to the fact the belt delivers the same amount of charges per a period of time,but why would the current flowing through the circuit necessarily be equal to the rate of charge deposition what prevents some of those charges accumulate on the metal globe?
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