Summer 2022
Google Meet link: https://meet.google.com/nvc-kbsy-ssq
Wednesday 5:30 -7:30 PM
Topic: Introduction to derivative pricing: Theory and computation
Duration: 6 weeks, Starting date: Wednesday 8th June, End date: Wednesday 20th July.
Topics: The basic theory of interest, fixed income securities, mean-variance portfolio theory. Meaning and pricing of forwards, futures, options, and swaps. Black-Scholes-Merton model and its various generalizations for continuous-time modeling of asset prices. European option pricing under some of these model assumptions.
Expectations: The participants are supposed to read the study materials in the references before starting summer school. It is important that they gain some level of understanding of the concepts presented in those. The details will be discussed during the summer project.
Reference:
1.Chapters 1,2,3, 6, 10 & 16 of Investment Science [David G. Luenberger]
2 . Chapters 2, 3 & 4 of Introduction to Stochastic calculus for finance [Dieter Sondermann]
Additional Reading for Pre-requisite
Brownian motion and its quadratic variation. video16 video17 https://sites.google.com/site/anindyagoswami/teaching/pde
Participants
- Abhay Chandran
- Abhiti Mishra
- Ajaya Saipriya Sahoo
- Amarpal Singh Basra
- Ankur Dutta
- Anubhab Bose
- Arkoprobho Paul
- Arpan Sanyal
- Ashish Kumar Jha
- Febin Babu
- Hrishikesh Jagtap
- Insha Rashid
- Iqra Jan
- M Manoj Kumar
- Meetkumar Bharatbhai
- Nannapaneni Veena Sri
- Parth Gupte
- Praful Shankar
- Rahul Krishnakumar
- Rukhsana Akhter
- Rutwik Pasani
- Saaba
- Sabrina Mubarik
- Saikat Kundu
- Salma Reyaz
- Samarth Pardhi
- Satya Surya Pranitsai Garikipati
- Satyam Modi
- Shubhankar Sahu
- Sid
- Soumya Ghatak
- Sreeranjini T M
- Suhail Iqbal Khan
- Tandlam Jighnyas Reddy
- Tridash Srivastava
- Ufeeda Akram
- Ujwal Pandey
- Yash Shingare
FAQ
Events occurring in real life tend to have an effect on the market. So, in general, an investor tries to link most of the fluctuations in the market with some economical, political, or natural events. How can a mathematical model predict such fluctuations?
There are two types of models of asset price dynamics. One is econometric another is mathematical.
An econometric model relies on the history of the immediate past and predicts a range of possible values of the asset price for the next time interval with a certain level of confidence. This is basically time series analysis and is based on statistics. Such models may possibly capture usual trading behavior but cannot capture relatively rare events. Please recall that for a sufficiently liquid asset, the price changes every hour, without a need for an event to occur.
A mathematical model on the other hand does not attempt to predict tomorrow's asset price. This rather assumes that asset prices are not predictable and uncertainties are inherent. Instead of predicting the realization of the asset price, a Mathematical model models the conditional law of the price dynamics. In other words, it attempts to answer the following question. "If the price at any future time is treated as a random variable, what is its conditional distribution given the past realization of the asset price?"
Although the real events are not predictable, an asset price gets affected regularly by some events or the other. Although the exact occurrence of such shocks is not predictable, an empirical distribution of the shocks can be obtained and is meaningful. This distribution/law is more robust than the realizations and does not alter frequently. So, mathematical modeling of the conditional distribution of asset price is relevant for the application.Why should one be interested in modeling the conditional distribution of asset price?
In the market, many types of assets are traded. Some secondary risky asset prices depend on the future distribution of a primary risky asset. For finding a rational price of such secondary assets it's important to have a Mathematical model of the corresponding primary asset.I am reading a paper and I do not fully understand this. I need help in finding some appropriate material so that I am able to completely understand.
Please contact me to schedule a class where you will present the concepts of the paper in simple terms to everyone and then place your question. If anybody else has also read that part and has similar or other doubts on that paper may also mention those. We will have a discussion following that.I am not familiar with the concepts of Black Scholes's option pricing theory. What should I read to get a working knowledge?
Read sequentiallyI am willing to learn the subject of math finance beyond the scope of this summer school. I am seeking guidance on how to start with.
Check this link. You may find these useful referencesI wish to learn more about the use of simulation for finding the theoretical price of options. How should I start?
Read this report made by some earlier students.I wish to learn some fundamentals of simulation techniques quickly. How should I start?
Read this report made by some earlier students.
Some Presentations