SHS Web of Conferences 12, 010 8 4 (2014)
DOI: 10.1051/shsconf/ 201412010 8 4
C Owned by the authors, published by EDP Sciences, 2014
Corporate Diversification and Firm Performance: Evidence
from Asian Hotel Industry
Chai-Aun Ooi1 , Chee-Wooi Hooy2, Ahmad
BUSINESS SCHOOL
Unit of Study Outline
Unit Code FINC6000
Unit Title Quantitative Finance
Semester 2, 2016
Pre-requisite Units: FINC5001
Co-requisite Units:
Prohibited Units: FINC5002
Assumed Knowledge and/or Skills: This unit requires students to have bas
The University of Sydney
Discipline of Finance
FINC6000 - Quantitative Finance
Solution to Tutorial Set 5
1. Assuming a piecewise constant asset volatility as a function of time, calibrate the Black-Scholes
model to the following market observed implied v
The University of Sydney
Discipline of Finance
FINC6000 - Quantitative Finance
Solution to Tutorial Set 6
1. Suppose that the coefficients for a pseudo-random number generator with period n = 231 are
= 69,069 and = 1. Assuming the initial seed of X0 = 1,
The University of Sydney
Discipline of Finance
FINC6000 - Quantitative Finance
Solution to Tutorial Set 1
1. The purpose of this question is to provide some intuition behind the definition of self-financing
strategies given in lecture slides. For this, co
The University of Sydney
Discipline of Finance
FINC6000 - Quantitative Finance
Solution to Tutorial Set 4
1. Let Xt be the stock price at time t with constant volatility . Recall that in considering
European calls and puts, we defined d+ and d by
ln(Xt /K
The University of Sydney
Discipline of Finance
FINC6000 - Quantitative Finance
Solution to Tutorial Set 3
asset prices Xt and Yt satisfy sdes
1. Suppose that under the risk-neutral measure P,
dXt = rXt dt + X Xt dwtX ,
dYt = rYt dt + Y Yt dwtY ,
where wt
The University of Sydney
Discipline of Finance
FINC6000 - Quantitative Finance
Solution to Tutorial Set 2
1. This question provides an alternative derivation of the Black-Scholes equation following the
original argument used by Black and Scholes. Let Xt b
Quantitative Finance
FINC6000
Lecture 6: Monte Carlo I
Oh Kang Kwon Discipline of Finance The University of Sydney
Table of Contents
Overview
Uniform random number generators
pseudo random generators
low discrepancy sequences - Sobol
Converting from
Quantitative Finance
FINC6000
Lecture 1: Preliminaries I
Oh Kang Kwon Discipline of Finance The University of Sydney
Table of Contents
Introduction and preliminaries
on mathematical concepts
mathematical framework
trading strategies and absence of arbitr
Quantitative Finance
FINC6000
Lecture 3: Preliminaries II
Oh Kang Kwon Discipline of Finance The University of Sydney
Table of Contents
Mathematical results
change of probability measures
Girsanov theorem and Wiener processes
numeraires
change of numerai
Quantitative Finance
FINC6000
Lecture 4: Black-Scholes Model - Probabilistic Approach
Oh Kang Kwon Discipline of Finance The University of Sydney
Table of Contents
Overview
Probabilistic approach to pricing
review of the Black-Scholes model
European cal
Quantitative Finance
FINC6000
Lecture 5: Volatility Smile
Oh Kang Kwon Discipline of Finance The University of Sydney
Table of Contents
Overview
Implied volatility
Expiry dependent volatility
Volatility smile
Gatherals SVI parameterization
SABR para
Quantitative Finance
FINC6000
Lecture 2: Black-Scholes Model - PDE Approach
Oh Kang Kwon Discipline of Finance The University of Sydney
Table of Contents
Overview
Black-Scholes model
assumptions
asset dynamics under the risk-neutral measure
Black-Schole
7/31/2001codedJFQA #36:3 Reeb, Mansi, and AlleePage 395
JOURNAL OF FINANCIAL AND QUANTITATIVE ANALYSIS
VOL. 36, NO. 3, SEPTEMBER 2001
COPYRIGHT 2001, SCHOOL OF BUSINESS ADMINISTRATION, UNIVERSITY OF WASHINGTON, SEATTLE, WA 98195
Firm Internationalization