Scribd
Upload
47 views1 page

Homework 6

This document provides instructions for Homework 6, which is due on October 20th by 11:59 PM. Students are asked to download daily stock price data for 3 companies from WRDS and perform financial analysis on the returns, including calculating quadratic variation, probability of up/down movements, average daily return, and plotting a histogram of daily returns. The homework will be graded based on a rubric for correctness and efficiency when run on a separate test data set.

Uploaded by

Victor Cabrejos
Copyright
© © All Rights Reserved
We take content rights seriously. If you suspect this is your content, claim it here.
Available Formats
Download as PDF, TXT or read online on Scribd
47 views1 page

Homework 6

This document provides instructions for Homework 6, which is due on October 20th by 11:59 PM. Students are asked to download daily stock price data for 3 companies from WRDS and perform financial analysis on the returns, including calculating quadratic variation, probability of up/down movements, average daily return, and plotting a histogram of daily returns. The homework will be graded based on a rubric for correctness and efficiency when run on a separate test data set.

Uploaded by

Victor Cabrejos
Copyright
© © All Rights Reserved
We take content rights seriously. If you suspect this is your content, claim it here.
Available Formats
Download as PDF, TXT or read online on Scribd
You are on page 1/ 1

Homework 6

Due October 20th by 11:59 PM


Submit assignments as last_first_hw6.py

Notation for financial mathematics


- Denote the spot price and logarithmic price as 𝑆𝑡 and 𝑋𝑡 = log⁡(𝑆𝑡 ), respectively
▪ Logarithmic return at time 𝑡 is then defined as 𝑟𝑡 = 𝑋𝑡 − 𝑋𝑡−1
- Denote continuous time as 𝑡 ∈ [0, 𝑇]
- Denote the discretization of 𝑇 into a grid of 𝑛 ∈ [0, 𝑁] steps (indexes) as 𝑡𝑛
𝑇
▪ The step size is then Δ𝑡 =
𝑁
▪ The time of the initial observation occurs at 𝑛 = 0, i.e. 𝑡 = 𝑡0.
▪ In our setting, 𝑇 = 23400, 𝑁 = 4680, and Δ𝑡 = 5

Homework Instructions:

Start with a fresh Python script:


1. Download daily stock prices for Adobe (ADBE), Netflix (NFLX) and Tesla (TSLA)
from WRDS for the date range Jan 1, 2018 – Dec 31, 2018 as a CSV.
2. Read the price series, 𝑆𝑡 , for the stocks into Python.
3. Approximate the following in discrete time Δ𝑡 = 1 day for each stock, as well as for all
three stocks combined:

a. 𝑄𝑢𝑎𝑑𝑟𝑎𝑡𝑖𝑐⁡𝑉𝑎𝑟𝑖𝑎𝑡𝑖𝑜𝑛 = ⁡ ∑𝑛𝑖=1 𝑟𝑖,𝑛


2

b. Probability of up movements / down movements


c. Average daily return
d. Plot a histogram of the daily returns
e.

Grading Process

I will award points according the rubric in the syllabus. To determine whether the script
is correct and efficient, the program will be run on a separate stock-day file. The script, if
done correctly, will report accurate results for a random stock day file.
If you are unable to complete all the tasks above, at a minimum make sure your script can
run and produce some output. A script that doesn’t run receives the least amount of points.

You might also like