Mini Quiz Competition Island Shangri La Hotel Hong Kong May 26, CFE School Risk Latte Company Limited

Size: px
Start display at page:

Download "Mini Quiz Competition Island Shangri La Hotel Hong Kong May 26, CFE School Risk Latte Company Limited"

Transcription

1 Mini Quiz Competition Island Shangri La Hotel Hong Kong May 26, 2011 CFE School Risk Latte Company Limited

2 Are You Better than a Goldman Sachs Trader? (This is a mini-quiz and not a full Quiz) The objective of this mini-quiz is to test whether a person has the potential to become as good as a Goldman Sachs trader. There are three metrics on which a person is tested in this mini-quiz: (1) Basic level of knowledge of Quantitative Finance (2) Intuitive understanding of concepts of Quantitative Finance (3) Thinking about concepts in Quantitative Finance Quiz Questions:» All questions are developed and compiled with the help and under the advice of market professionals working in top tier global banks and financial institutions. Risk Latte Company and CFE School owns the copyright to his quiz and all the questions contained therein.

3 Question #1 You are an options trader and a client approaches you to buy a call option on this building (where we are now sitting). You d be very reluctant to sell a call on this building primarily because: (a)it s not possible to estimate the volatility of this asset (b)the property market (of which this asset is a part) is not complete. (c)transaction costs for this trade would be too high (d)no closed form solution / model (Black-Scholes type) exists for such an option This question carries 5 points.

4 Question #2 In the Black-Scholes option pricing formula we see two terms N(d1) and N(d2). Call = S*N(d1) K*exp(-rT)*N(d2) Mathematically speaking, which one of these is a probability measure? (a) N(d1) measures the probability (b) N(d2) measures the probability (c) Both N(d1) and N(d2) represent probabilities under different measures (d) N(-d2) measures the probability This question carries 5 points.

5 Question #3 You are trading an asset that is capped at 100 (like the Eurodollar futures Contract which is capped at 100 and cannot go above this value. Implying an interest rate of zero). The asset is currently trading at 100. What is the value of a 100 strike call and a 100 strike put? (a)the call will be valued at zero and the put value will be infinite (very large) (b)both the call and the put will be valued at zero (c)the call will be valued slightly more than zero and the put value will be extremely difficult to determine (as the put-call parity will break down at 100). (d) The call and put will both be valued at infinity (very large) This question carries 5 points.

6 Question #4 Dollar-Yen (USD/JPY) follows a lognormal distribution and a Geometric Brownian motion. USD/JPY has a volatility of 20% and a drift (foreign interest rate minus domestic interest rate) of 3%. If you are pricing an option on Yen-Dollar (JPY/USD) the values of volatility and drift that you d input in your option pricing model would be: (a)volatility of 20% and drift of 3% (same as USD/JPY) (b)volatility of 20% and drift of 1% (c)volatility of 18% and drift of 3% (d)volatility 17.5% and drift of 2.5% This question carries 5 points.

7 Question #5 They say that traders have GARCH in their heads. GARCH has the most resemblance with: (a)stochastic Volatility models (b)exponentially Weighted Moving Average (EWMA) models (c)dupiere Volatility Surface model (d)implied Volatility tree This question carries 5 points.

8 Question #6 A trader dynamically hedges a sold binary (digital) option with a call spread. He finds that the call spread always trades a bit higher than the binary and as the spread narrows the difference begins to vanish but the prices of the binary and the call spread never becomes exactly equal (even ignoring the transaction costs). The main reason for this is (a)the dynamic hedging makes the binary option path dependent (b)the binary has a substantial pin risk (c)the mathematical approximation of a binary using call spread is not exact. (d)none of the above. This questions carries 5 points.

9 Question #7 Black-Scholes option pricing model is an equilibrium model. Equilibrium is a concept borrowed from physics. In the context of quantitative finance, equilibrium means: (a)the price of a security reflects all available information in the market (b)a security can infinitely divided into component securities (c)there are no arbitrage opportunities in the market (d)the price of a security can be in a particular state for a long period of time. This questions carries 5 points.

10 Question #8 EUR/USD volatility is 10% and is represented by a vector of length 10 from the origin (USD). GBP/USD volatility is 8% and is represented by a vector of length 8 from the origin (USD). If the correlation between EUR/USD and GBP/USD is zero then the angle between the two vectors will be: (a)90 degrees (b)45 degrees (c)25 degrees (d)zero degree This questions carries 5 points.

11 Question #9 Ito s Lemma is used in Stochastic Calculus, which is the bedrock of quant finance models for valuation of financial derivatives. Simply put, in a trader s language (English), Ito s lemma states that: (a)both the stock price equation (SDE) and the option price equation (PDE) are non-differentiable and not smooth; (b)the stock price equation (SDE) is a random walk and non-differentiable but the function of the stock price, the option price equation is smooth and differentiable; (c)no matter how small a slice we make, the stock price always remains non-differentiable; (d)any variable multiplied by an infinitesimal increment of time (delta t) vanishes. This questions carries 5 points.

12 Question #10 For a particular asset, the volatility on an hourly sampled basis turns out to be higher than the volatility on a daily sampled basis. You would then conclude that the asset is mostly like in a: (a) mean reverting mode (b) Trending mode (c) In a sideways model (d) Nothing can be said based on this information This questions carries 5 points.

13 Question #11 Stock A is 100% correlated with stock B. Over a particular period, stock A went up by 2%. A trader expected stock B to also go up by 2%. However, she observed that stock B actually went up by 4%. Why is that? (a)this is because correlation is a linear measure and cannot capture non-linearity; (b)the volatility of stock B must have been double the volatility of stock A; (c)correlation gets distorted by noise (randomness) in the market (d)none of the above This questions carries 5 points.

14 Question #12 A stock is trading at $100 and the volatility of stock is 10%. If risk free rates in the economy are extremely low, then a one year at the money (ATM), i.e. spot equal to the strike, will approximately cost (assuming no transaction costs and vol skew): (a)$2 (b)$3 (c)$4 (d)$5 This questions carries 5 points.

15 Question #13 A one year at the money (ATM) call option on a stock costs $1. Assuming low interest rates and no transaction costs and volatility skew, a two year ATM option on the same stock will cost: (a)$1.15 (b)$1.41 (c)$2.00 (d)$2.15 This question carries 5 points

16 Question #14 If Google = 8, Yahoo = 8, facebook = 8 then Hotmail is equal to (a)2 (b)4 (c)6 (d)8 This question carries 5 points

17 Question #15 A proprietary trader at a hedge fund trades a basket of derivatives. With regard to the trader s P&L, his boss should, on an average, expect it: (a)to remain six months in profits (black) and six months in loss (red); (b)to remain 11 months in black and one month in red or 11 months in red and one month in black; (c) to remain all the 12 months in black or all the 12 months in red; (d) to remain 4 months in black and 8 months in red or 8 months in black and 4 months in red; This question carries 5 points

18 Question #16 Volatility of volatility (or what the traders call vvol ) is the: (a)second moment of the Normal distribution (b)third moment of the Normal distribution (c)fourth moment of the Normal distribution (d)fifth moment of the Normal distribution This question carries 5 points

19 Question #17 An asset, S, say, USD/JPY, is assumed to follow a Geometric Brownian motion (GBM), which is the most conventional way of looking at assets like equity and FX on the trading floor of banks. The asset has a certain drift and a volatility. If we now consider the process for the inverse of the asset, 1/S, i.e. JPY/USD then: (a)the volatility of (1/S) will change from that of S. (b)the drift of (1/S) will change from that of S. (c)both the drift and the volatility of (1/S) will change from that of S. (d)both the drift and the volatility of (1/S) will remain the same as that of S. This question carries 5 points

20 Question #18 The head trader of the swaps desk of a bank recently remarked that 3 month USD LIBOR (short term interest rate) is itself a call option. Your reaction would be that: (a)the head trader actually means a call option on the USD LIBOR, i.e. a cap; (b)the head trader is alluding to the fact that some structured products tied to 3 month USD LIBOR may display convexity in their payoff and hence resemble the payoff of a call option (c)the head trader is absolutely correct and a short term interest rate can be itself thought of as a call option; (d)the head trader usually hides the fact that he s sometimes drunk during the office hours. This question carries 5 points

21 Question #19 Bank A with a capital of $1 million enters into a game of coin tossing with Bank B with a capital of $10,000. Bank A wins $1 every time a head shows up and loses $1 every time a tail shows up. It s a very cruel world and the game (the show) must go on until one of them goes bankrupt. The probability of Bank B going bankrupt is: (a)0.99% (b)10% (c)50% (d)99.01% This question carries 5 points

22 Question #20 Which of the following options (financial products) is the odd one out? (a)israeli option (b)parisian option (c)napoleon option (d)himalayan option This question carries 5 points

23 Answers 1.(b) 2.(c) 3.(c) 4.(b) 5.(b) 6.(a) 7.(c) 8.(d) 9.(b) 10.(a) 11.(b) 12.(c) 13.(b) 14.(b) 15.(b) 16. (c) 17. (b) 18. (c) 19. (d) 20. (c)

24 Winners 1 st Prize: Girish Kumarguru Equity Derivatives Trader Royal Bank of Scotland Hong Kong 2 nd Prize: Lynn Raebsamen and Brian Chau Commodity Analytics Market Risk Management Bloomberg Wing Lung Bank Hong Kong Hong Kong 3 rd Prize: Catherine Mak Middle Office UBS Hong Kong

The Black-Scholes Model

The Black-Scholes Model The Black-Scholes Model Liuren Wu Options Markets Liuren Wu ( c ) The Black-Merton-Scholes Model colorhmoptions Markets 1 / 18 The Black-Merton-Scholes-Merton (BMS) model Black and Scholes (1973) and Merton

More information

The Black-Scholes Model

The Black-Scholes Model The Black-Scholes Model Liuren Wu Options Markets (Hull chapter: 12, 13, 14) Liuren Wu ( c ) The Black-Scholes Model colorhmoptions Markets 1 / 17 The Black-Scholes-Merton (BSM) model Black and Scholes

More information

CFE: Level 1 Exam Sample Questions

CFE: Level 1 Exam Sample Questions CFE: Level 1 Exam Sample Questions he following are the sample questions that are illustrative of the questions that may be asked in a CFE Level 1 examination. hese questions are only for illustration.

More information

Advanced Topics in Derivative Pricing Models. Topic 4 - Variance products and volatility derivatives

Advanced Topics in Derivative Pricing Models. Topic 4 - Variance products and volatility derivatives Advanced Topics in Derivative Pricing Models Topic 4 - Variance products and volatility derivatives 4.1 Volatility trading and replication of variance swaps 4.2 Volatility swaps 4.3 Pricing of discrete

More information

The Black-Scholes Model

The Black-Scholes Model IEOR E4706: Foundations of Financial Engineering c 2016 by Martin Haugh The Black-Scholes Model In these notes we will use Itô s Lemma and a replicating argument to derive the famous Black-Scholes formula

More information

Continuous Processes. Brownian motion Stochastic calculus Ito calculus

Continuous Processes. Brownian motion Stochastic calculus Ito calculus Continuous Processes Brownian motion Stochastic calculus Ito calculus Continuous Processes The binomial models are the building block for our realistic models. Three small-scale principles in continuous

More information

Derivative Securities Fall 2012 Final Exam Guidance Extended version includes full semester

Derivative Securities Fall 2012 Final Exam Guidance Extended version includes full semester Derivative Securities Fall 2012 Final Exam Guidance Extended version includes full semester Our exam is Wednesday, December 19, at the normal class place and time. You may bring two sheets of notes (8.5

More information

Pricing Options with Mathematical Models

Pricing Options with Mathematical Models Pricing Options with Mathematical Models 1. OVERVIEW Some of the content of these slides is based on material from the book Introduction to the Economics and Mathematics of Financial Markets by Jaksa Cvitanic

More information

Handbook of Financial Risk Management

Handbook of Financial Risk Management Handbook of Financial Risk Management Simulations and Case Studies N.H. Chan H.Y. Wong The Chinese University of Hong Kong WILEY Contents Preface xi 1 An Introduction to Excel VBA 1 1.1 How to Start Excel

More information

Financial Markets & Risk

Financial Markets & Risk Financial Markets & Risk Dr Cesario MATEUS Senior Lecturer in Finance and Banking Room QA259 Department of Accounting and Finance c.mateus@greenwich.ac.uk www.cesariomateus.com Session 3 Derivatives Binomial

More information

Asset-or-nothing digitals

Asset-or-nothing digitals School of Education, Culture and Communication Division of Applied Mathematics MMA707 Analytical Finance I Asset-or-nothing digitals 202-0-9 Mahamadi Ouoba Amina El Gaabiiy David Johansson Examinator:

More information

Table of Contents. Chapter 1 General Principles... 1

Table of Contents. Chapter 1 General Principles... 1 Table of Contents Chapter 1 General Principles... 1 1. Build a broad knowledge base...1 2. Practice your interview skills...1 3. Listen carefully...2 4. Speak your mind...2 5. Make reasonable assumptions...2

More information

Financial derivatives exam Winter term 2014/2015

Financial derivatives exam Winter term 2014/2015 Financial derivatives exam Winter term 2014/2015 Problem 1: [max. 13 points] Determine whether the following assertions are true or false. Write your answers, without explanations. Grading: correct answer

More information

Option Pricing. Simple Arbitrage Relations. Payoffs to Call and Put Options. Black-Scholes Model. Put-Call Parity. Implied Volatility

Option Pricing. Simple Arbitrage Relations. Payoffs to Call and Put Options. Black-Scholes Model. Put-Call Parity. Implied Volatility Simple Arbitrage Relations Payoffs to Call and Put Options Black-Scholes Model Put-Call Parity Implied Volatility Option Pricing Options: Definitions A call option gives the buyer the right, but not the

More information

Mathematics of Finance Final Preparation December 19. To be thoroughly prepared for the final exam, you should

Mathematics of Finance Final Preparation December 19. To be thoroughly prepared for the final exam, you should Mathematics of Finance Final Preparation December 19 To be thoroughly prepared for the final exam, you should 1. know how to do the homework problems. 2. be able to provide (correct and complete!) definitions

More information

Martingale Methods in Financial Modelling

Martingale Methods in Financial Modelling Marek Musiela Marek Rutkowski Martingale Methods in Financial Modelling Second Edition Springer Table of Contents Preface to the First Edition Preface to the Second Edition V VII Part I. Spot and Futures

More information

Interest Rate Modeling

Interest Rate Modeling Chapman & Hall/CRC FINANCIAL MATHEMATICS SERIES Interest Rate Modeling Theory and Practice Lixin Wu CRC Press Taylor & Francis Group Boca Raton London New York CRC Press is an imprint of the Taylor & Francis

More information

1) Understanding Equity Options 2) Setting up Brokerage Systems

1) Understanding Equity Options 2) Setting up Brokerage Systems 1) Understanding Equity Options 2) Setting up Brokerage Systems M. Aras Orhan, 12.10.2013 FE 500 Intro to Financial Engineering 12.10.2013, ARAS ORHAN, Intro to Fin Eng, Boğaziçi University 1 Today s agenda

More information

Valuation of Equity Derivatives

Valuation of Equity Derivatives Valuation of Equity Derivatives Dr. Mark W. Beinker XXV Heidelberg Physics Graduate Days, October 4, 010 1 What s a derivative? More complex financial products are derived from simpler products What s

More information

Lecture 1, Jan

Lecture 1, Jan Markets and Financial Derivatives Tradable Assets Lecture 1, Jan 28 21 Introduction Prof. Boyan ostadinov, City Tech of CUNY The key players in finance are the tradable assets. Examples of tradables are:

More information

INTEREST RATES AND FX MODELS

INTEREST RATES AND FX MODELS INTEREST RATES AND FX MODELS 7. Risk Management Andrew Lesniewski Courant Institute of Mathematical Sciences New York University New York March 8, 2012 2 Interest Rates & FX Models Contents 1 Introduction

More information

Boundary conditions for options

Boundary conditions for options Boundary conditions for options Boundary conditions for options can refer to the non-arbitrage conditions that option prices has to satisfy. If these conditions are broken, arbitrage can exist. to the

More information

Martingale Methods in Financial Modelling

Martingale Methods in Financial Modelling Marek Musiela Marek Rutkowski Martingale Methods in Financial Modelling Second Edition \ 42 Springer - . Preface to the First Edition... V Preface to the Second Edition... VII I Part I. Spot and Futures

More information

Reading: You should read Hull chapter 12 and perhaps the very first part of chapter 13.

Reading: You should read Hull chapter 12 and perhaps the very first part of chapter 13. FIN-40008 FINANCIAL INSTRUMENTS SPRING 2008 Asset Price Dynamics Introduction These notes give assumptions of asset price returns that are derived from the efficient markets hypothesis. Although a hypothesis,

More information

1. What is Implied Volatility?

1. What is Implied Volatility? Numerical Methods FEQA MSc Lectures, Spring Term 2 Data Modelling Module Lecture 2 Implied Volatility Professor Carol Alexander Spring Term 2 1 1. What is Implied Volatility? Implied volatility is: the

More information

From Discrete Time to Continuous Time Modeling

From Discrete Time to Continuous Time Modeling From Discrete Time to Continuous Time Modeling Prof. S. Jaimungal, Department of Statistics, University of Toronto 2004 Arrow-Debreu Securities 2004 Prof. S. Jaimungal 2 Consider a simple one-period economy

More information

Appendix to Supplement: What Determines Prices in the Futures and Options Markets?

Appendix to Supplement: What Determines Prices in the Futures and Options Markets? Appendix to Supplement: What Determines Prices in the Futures and Options Markets? 0 ne probably does need to be a rocket scientist to figure out the latest wrinkles in the pricing formulas used by professionals

More information

MFE/3F Questions Answer Key

MFE/3F Questions Answer Key MFE/3F Questions Download free full solutions from www.actuarialbrew.com, or purchase a hard copy from www.actexmadriver.com, or www.actuarialbookstore.com. Chapter 1 Put-Call Parity and Replication 1.01

More information

Practical Hedging: From Theory to Practice. OSU Financial Mathematics Seminar May 5, 2008

Practical Hedging: From Theory to Practice. OSU Financial Mathematics Seminar May 5, 2008 Practical Hedging: From Theory to Practice OSU Financial Mathematics Seminar May 5, 008 Background Dynamic replication is a risk management technique used to mitigate market risk We hope to spend a certain

More information

Finance 651: PDEs and Stochastic Calculus Midterm Examination November 9, 2012

Finance 651: PDEs and Stochastic Calculus Midterm Examination November 9, 2012 Finance 65: PDEs and Stochastic Calculus Midterm Examination November 9, 0 Instructor: Bjørn Kjos-anssen Student name Disclaimer: It is essential to write legibly and show your work. If your work is absent

More information

An arbitrage-free method for smile extrapolation

An arbitrage-free method for smile extrapolation An arbitrage-free method for smile extrapolation Shalom Benaim, Matthew Dodgson and Dherminder Kainth Royal Bank of Scotland A robust method for pricing options at strikes where there is not an observed

More information

Mathematical Modeling and Methods of Option Pricing

Mathematical Modeling and Methods of Option Pricing Mathematical Modeling and Methods of Option Pricing This page is intentionally left blank Mathematical Modeling and Methods of Option Pricing Lishang Jiang Tongji University, China Translated by Canguo

More information

Hedging Credit Derivatives in Intensity Based Models

Hedging Credit Derivatives in Intensity Based Models Hedging Credit Derivatives in Intensity Based Models PETER CARR Head of Quantitative Financial Research, Bloomberg LP, New York Director of the Masters Program in Math Finance, Courant Institute, NYU Stanford

More information

Hull, Options, Futures & Other Derivatives Exotic Options

Hull, Options, Futures & Other Derivatives Exotic Options P1.T3. Financial Markets & Products Hull, Options, Futures & Other Derivatives Exotic Options Bionic Turtle FRM Video Tutorials By David Harper, CFA FRM 1 Exotic Options Define and contrast exotic derivatives

More information

INTRODUCTION TO THE ECONOMICS AND MATHEMATICS OF FINANCIAL MARKETS. Jakša Cvitanić and Fernando Zapatero

INTRODUCTION TO THE ECONOMICS AND MATHEMATICS OF FINANCIAL MARKETS. Jakša Cvitanić and Fernando Zapatero INTRODUCTION TO THE ECONOMICS AND MATHEMATICS OF FINANCIAL MARKETS Jakša Cvitanić and Fernando Zapatero INTRODUCTION TO THE ECONOMICS AND MATHEMATICS OF FINANCIAL MARKETS Table of Contents PREFACE...1

More information

MSc Financial Mathematics

MSc Financial Mathematics MSc Financial Mathematics Programme Structure Week Zero Induction Week MA9010 Fundamental Tools TERM 1 Weeks 1-1 0 ST9080 MA9070 IB9110 ST9570 Probability & Numerical Asset Pricing Financial Stoch. Processes

More information

Institute of Actuaries of India. Subject. ST6 Finance and Investment B. For 2018 Examinationspecialist Technical B. Syllabus

Institute of Actuaries of India. Subject. ST6 Finance and Investment B. For 2018 Examinationspecialist Technical B. Syllabus Institute of Actuaries of India Subject ST6 Finance and Investment B For 2018 Examinationspecialist Technical B Syllabus Aim The aim of the second finance and investment technical subject is to instil

More information

FIN FINANCIAL INSTRUMENTS SPRING 2008

FIN FINANCIAL INSTRUMENTS SPRING 2008 FIN-40008 FINANCIAL INSTRUMENTS SPRING 2008 The Greeks Introduction We have studied how to price an option using the Black-Scholes formula. Now we wish to consider how the option price changes, either

More information

Introduction to Stochastic Calculus With Applications

Introduction to Stochastic Calculus With Applications Introduction to Stochastic Calculus With Applications Fima C Klebaner University of Melbourne \ Imperial College Press Contents Preliminaries From Calculus 1 1.1 Continuous and Differentiable Functions.

More information

MFIN 7003 Module 2. Mathematical Techniques in Finance. Sessions B&C: Oct 12, 2015 Nov 28, 2015

MFIN 7003 Module 2. Mathematical Techniques in Finance. Sessions B&C: Oct 12, 2015 Nov 28, 2015 MFIN 7003 Module 2 Mathematical Techniques in Finance Sessions B&C: Oct 12, 2015 Nov 28, 2015 Instructor: Dr. Rujing Meng Room 922, K. K. Leung Building School of Economics and Finance The University of

More information

Volatility Smiles and Yield Frowns

Volatility Smiles and Yield Frowns Volatility Smiles and Yield Frowns Peter Carr NYU IFS, Chengdu, China, July 30, 2018 Peter Carr (NYU) Volatility Smiles and Yield Frowns 7/30/2018 1 / 35 Interest Rates and Volatility Practitioners and

More information

Risk-Neutral Valuation

Risk-Neutral Valuation N.H. Bingham and Rüdiger Kiesel Risk-Neutral Valuation Pricing and Hedging of Financial Derivatives W) Springer Contents 1. Derivative Background 1 1.1 Financial Markets and Instruments 2 1.1.1 Derivative

More information

Appendix A Financial Calculations

Appendix A Financial Calculations Derivatives Demystified: A Step-by-Step Guide to Forwards, Futures, Swaps and Options, Second Edition By Andrew M. Chisholm 010 John Wiley & Sons, Ltd. Appendix A Financial Calculations TIME VALUE OF MONEY

More information

MFE/3F Questions Answer Key

MFE/3F Questions Answer Key MFE/3F Questions Download free full solutions from www.actuarialbrew.com, or purchase a hard copy from www.actexmadriver.com, or www.actuarialbookstore.com. Chapter 1 Put-Call Parity and Replication 1.01

More information

Zekuang Tan. January, 2018 Working Paper No

Zekuang Tan. January, 2018 Working Paper No RBC LiONS S&P 500 Buffered Protection Securities (USD) Series 4 Analysis Option Pricing Analysis, Issuing Company Riskhedging Analysis, and Recommended Investment Strategy Zekuang Tan January, 2018 Working

More information

MATH 425 EXERCISES G. BERKOLAIKO

MATH 425 EXERCISES G. BERKOLAIKO MATH 425 EXERCISES G. BERKOLAIKO 1. Definitions and basic properties of options and other derivatives 1.1. Summary. Definition of European call and put options, American call and put option, forward (futures)

More information

MSc Financial Mathematics

MSc Financial Mathematics MSc Financial Mathematics The following information is applicable for academic year 2018-19 Programme Structure Week Zero Induction Week MA9010 Fundamental Tools TERM 1 Weeks 1-1 0 ST9080 MA9070 IB9110

More information

Lecture 9: Practicalities in Using Black-Scholes. Sunday, September 23, 12

Lecture 9: Practicalities in Using Black-Scholes. Sunday, September 23, 12 Lecture 9: Practicalities in Using Black-Scholes Major Complaints Most stocks and FX products don t have log-normal distribution Typically fat-tailed distributions are observed Constant volatility assumed,

More information

Lahore University of Management Sciences. FINN 422 Quantitative Finance Fall Semester 2015

Lahore University of Management Sciences. FINN 422 Quantitative Finance Fall Semester 2015 FINN 422 Quantitative Finance Fall Semester 2015 Instructors Room No. Office Hours Email Telephone Secretary/TA TA Office Hours Course URL (if any) Ferhana Ahmad 314 SDSB TBD ferhana.ahmad@lums.edu.pk

More information

Introduction to Financial Mathematics

Introduction to Financial Mathematics Introduction to Financial Mathematics Zsolt Bihary 211, ELTE Outline Financial mathematics in general, and in market modelling Introduction to classical theory Hedging efficiency in incomplete markets

More information

FX Smile Modelling. 9 September September 9, 2008

FX Smile Modelling. 9 September September 9, 2008 FX Smile Modelling 9 September 008 September 9, 008 Contents 1 FX Implied Volatility 1 Interpolation.1 Parametrisation............................. Pure Interpolation.......................... Abstract

More information

Long Dated FX products. Dr. Sebastián del Baño Rollin Global Head FX and Equity Quantitative Research

Long Dated FX products. Dr. Sebastián del Baño Rollin Global Head FX and Equity Quantitative Research Long Dated FX products Dr. Sebastián del Baño Rollin Global Head FX and Equity Quantitative Research Overview 1. Long dated FX products 2. The Power Reverse Dual Currency Note 3. Modelling of long dated

More information

FIXED INCOME SECURITIES

FIXED INCOME SECURITIES FIXED INCOME SECURITIES Valuation, Risk, and Risk Management Pietro Veronesi University of Chicago WILEY JOHN WILEY & SONS, INC. CONTENTS Preface Acknowledgments PART I BASICS xix xxxiii AN INTRODUCTION

More information

Lecture 11: Ito Calculus. Tuesday, October 23, 12

Lecture 11: Ito Calculus. Tuesday, October 23, 12 Lecture 11: Ito Calculus Continuous time models We start with the model from Chapter 3 log S j log S j 1 = µ t + p tz j Sum it over j: log S N log S 0 = NX µ t + NX p tzj j=1 j=1 Can we take the limit

More information

Using Fractals to Improve Currency Risk Management Strategies

Using Fractals to Improve Currency Risk Management Strategies Using Fractals to Improve Currency Risk Management Strategies Michael K. Lauren Operational Analysis Section Defence Technology Agency New Zealand m.lauren@dta.mil.nz Dr_Michael_Lauren@hotmail.com Abstract

More information

Bloomberg. Variations on the Vanna-Volga Adjustment. Travis Fisher. Quantitative Research and Development, FX Team. January 26, Version 1.

Bloomberg. Variations on the Vanna-Volga Adjustment. Travis Fisher. Quantitative Research and Development, FX Team. January 26, Version 1. Bloomberg Variations on the Vanna-Volga Adjustment Travis Fisher Quantitative Research and Development, FX Team January 26, 27 Version 1.1 c 27 Bloomberg L.P. All rights reserved. Bloomberg FINANCIAL MARKETS

More information

Stats243 Introduction to Mathematical Finance

Stats243 Introduction to Mathematical Finance Stats243 Introduction to Mathematical Finance Haipeng Xing Department of Statistics Stanford University Summer 2006 Stats243, Xing, Summer 2007 1 Agenda Administrative, course description & reference,

More information

Preface Objectives and Audience

Preface Objectives and Audience Objectives and Audience In the past three decades, we have witnessed the phenomenal growth in the trading of financial derivatives and structured products in the financial markets around the globe and

More information

FINN 422 Quantitative Finance Fall Semester 2016

FINN 422 Quantitative Finance Fall Semester 2016 FINN 422 Quantitative Finance Fall Semester 2016 Instructors Ferhana Ahmad Room No. 314 SDSB Office Hours TBD Email ferhana.ahmad@lums.edu.pk, ferhanaahmad@gmail.com Telephone +92 42 3560 8044 (Ferhana)

More information

Lecture Note 8 of Bus 41202, Spring 2017: Stochastic Diffusion Equation & Option Pricing

Lecture Note 8 of Bus 41202, Spring 2017: Stochastic Diffusion Equation & Option Pricing Lecture Note 8 of Bus 41202, Spring 2017: Stochastic Diffusion Equation & Option Pricing We shall go over this note quickly due to time constraints. Key concept: Ito s lemma Stock Options: A contract giving

More information

3.1 Itô s Lemma for Continuous Stochastic Variables

3.1 Itô s Lemma for Continuous Stochastic Variables Lecture 3 Log Normal Distribution 3.1 Itô s Lemma for Continuous Stochastic Variables Mathematical Finance is about pricing (or valuing) financial contracts, and in particular those contracts which depend

More information

Financial Derivatives Section 5

Financial Derivatives Section 5 Financial Derivatives Section 5 The Black and Scholes Model Michail Anthropelos anthropel@unipi.gr http://web.xrh.unipi.gr/faculty/anthropelos/ University of Piraeus Spring 2018 M. Anthropelos (Un. of

More information

( ) since this is the benefit of buying the asset at the strike price rather

( ) since this is the benefit of buying the asset at the strike price rather Review of some financial models for MAT 483 Parity and Other Option Relationships The basic parity relationship for European options with the same strike price and the same time to expiration is: C( KT

More information

Real-World Quantitative Finance

Real-World Quantitative Finance Sachs Real-World Quantitative Finance (A Poor Man s Guide To What Physicists Do On Wall St.) Emanuel Derman Goldman, Sachs & Co. March 21, 2002 Page 1 of 16 Sachs Introduction Models in Physics Models

More information

Lecture 8: The Black-Scholes theory

Lecture 8: The Black-Scholes theory Lecture 8: The Black-Scholes theory Dr. Roman V Belavkin MSO4112 Contents 1 Geometric Brownian motion 1 2 The Black-Scholes pricing 2 3 The Black-Scholes equation 3 References 5 1 Geometric Brownian motion

More information

MATH20180: Foundations of Financial Mathematics

MATH20180: Foundations of Financial Mathematics MATH20180: Foundations of Financial Mathematics Vincent Astier email: vincent.astier@ucd.ie office: room S1.72 (Science South) Lecture 1 Vincent Astier MATH20180 1 / 35 Our goal: the Black-Scholes Formula

More information

Corporate Finance, Module 21: Option Valuation. Practice Problems. (The attached PDF file has better formatting.) Updated: July 7, 2005

Corporate Finance, Module 21: Option Valuation. Practice Problems. (The attached PDF file has better formatting.) Updated: July 7, 2005 Corporate Finance, Module 21: Option Valuation Practice Problems (The attached PDF file has better formatting.) Updated: July 7, 2005 {This posting has more information than is needed for the corporate

More information

CHAPTER 17 OPTIONS AND CORPORATE FINANCE

CHAPTER 17 OPTIONS AND CORPORATE FINANCE CHAPTER 17 OPTIONS AND CORPORATE FINANCE Answers to Concept Questions 1. A call option confers the right, without the obligation, to buy an asset at a given price on or before a given date. A put option

More information

Implied Volatility Surface

Implied Volatility Surface Implied Volatility Surface Liuren Wu Zicklin School of Business, Baruch College Fall, 2007 Liuren Wu Implied Volatility Surface Option Pricing, Fall, 2007 1 / 22 Implied volatility Recall the BSM formula:

More information

CME FX Link LIQUIDITY, LINKED QUOTATION AND PRICING GUIDE

CME FX Link LIQUIDITY, LINKED QUOTATION AND PRICING GUIDE CME FX Link LIQUIDITY, LINKED QUOTATION AND PRICING GUIDE CME FX Link: One CME Globex Spread, Connecting OTC FX and FX Futures Markets CME FX Link is a CME Globex basis spread between FX Futures and OTC

More information

Monte Carlo Methods in Structuring and Derivatives Pricing

Monte Carlo Methods in Structuring and Derivatives Pricing Monte Carlo Methods in Structuring and Derivatives Pricing Prof. Manuela Pedio (guest) 20263 Advanced Tools for Risk Management and Pricing Spring 2017 Outline and objectives The basic Monte Carlo algorithm

More information

How Much Should You Pay For a Financial Derivative?

How Much Should You Pay For a Financial Derivative? City University of New York (CUNY) CUNY Academic Works Publications and Research New York City College of Technology Winter 2-26-2016 How Much Should You Pay For a Financial Derivative? Boyan Kostadinov

More information

1 Interest Based Instruments

1 Interest Based Instruments 1 Interest Based Instruments e.g., Bonds, forward rate agreements (FRA), and swaps. Note that the higher the credit risk, the higher the interest rate. Zero Rates: n year zero rate (or simply n-year zero)

More information

1.1 Basic Financial Derivatives: Forward Contracts and Options

1.1 Basic Financial Derivatives: Forward Contracts and Options Chapter 1 Preliminaries 1.1 Basic Financial Derivatives: Forward Contracts and Options A derivative is a financial instrument whose value depends on the values of other, more basic underlying variables

More information

Monte Carlo Methods in Financial Engineering

Monte Carlo Methods in Financial Engineering Paul Glassennan Monte Carlo Methods in Financial Engineering With 99 Figures

More information

Chapter 15: Jump Processes and Incomplete Markets. 1 Jumps as One Explanation of Incomplete Markets

Chapter 15: Jump Processes and Incomplete Markets. 1 Jumps as One Explanation of Incomplete Markets Chapter 5: Jump Processes and Incomplete Markets Jumps as One Explanation of Incomplete Markets It is easy to argue that Brownian motion paths cannot model actual stock price movements properly in reality,

More information

Exotic Derivatives & Structured Products. Zénó Farkas (MSCI)

Exotic Derivatives & Structured Products. Zénó Farkas (MSCI) Exotic Derivatives & Structured Products Zénó Farkas (MSCI) Part 1: Exotic Derivatives Over the counter products Generally more profitable (and more risky) than vanilla derivatives Why do they exist? Possible

More information

ECON 459 Game Theory. Lecture Notes Auctions. Luca Anderlini Spring 2017

ECON 459 Game Theory. Lecture Notes Auctions. Luca Anderlini Spring 2017 ECON 459 Game Theory Lecture Notes Auctions Luca Anderlini Spring 2017 These notes have been used and commented on before. If you can still spot any errors or have any suggestions for improvement, please

More information

Derivatives Options on Bonds and Interest Rates. Professor André Farber Solvay Business School Université Libre de Bruxelles

Derivatives Options on Bonds and Interest Rates. Professor André Farber Solvay Business School Université Libre de Bruxelles Derivatives Options on Bonds and Interest Rates Professor André Farber Solvay Business School Université Libre de Bruxelles Caps Floors Swaption Options on IR futures Options on Government bond futures

More information

4. Black-Scholes Models and PDEs. Math6911 S08, HM Zhu

4. Black-Scholes Models and PDEs. Math6911 S08, HM Zhu 4. Black-Scholes Models and PDEs Math6911 S08, HM Zhu References 1. Chapter 13, J. Hull. Section.6, P. Brandimarte Outline Derivation of Black-Scholes equation Black-Scholes models for options Implied

More information

1 Mathematics in a Pill 1.1 PROBABILITY SPACE AND RANDOM VARIABLES. A probability triple P consists of the following components:

1 Mathematics in a Pill 1.1 PROBABILITY SPACE AND RANDOM VARIABLES. A probability triple P consists of the following components: 1 Mathematics in a Pill The purpose of this chapter is to give a brief outline of the probability theory underlying the mathematics inside the book, and to introduce necessary notation and conventions

More information

Options. An Undergraduate Introduction to Financial Mathematics. J. Robert Buchanan. J. Robert Buchanan Options

Options. An Undergraduate Introduction to Financial Mathematics. J. Robert Buchanan. J. Robert Buchanan Options Options An Undergraduate Introduction to Financial Mathematics J. Robert Buchanan 2014 Definitions and Terminology Definition An option is the right, but not the obligation, to buy or sell a security such

More information

The Black-Scholes PDE from Scratch

The Black-Scholes PDE from Scratch The Black-Scholes PDE from Scratch chris bemis November 27, 2006 0-0 Goal: Derive the Black-Scholes PDE To do this, we will need to: Come up with some dynamics for the stock returns Discuss Brownian motion

More information

Modelling Credit Spreads for Counterparty Risk: Mean-Reversion is not Needed

Modelling Credit Spreads for Counterparty Risk: Mean-Reversion is not Needed Modelling Credit Spreads for Counterparty Risk: Mean-Reversion is not Needed Ignacio Ruiz, Piero Del Boca May 2012 Version 1.0.5 A version of this paper was published in Intelligent Risk, October 2012

More information

CHAPTER 10 OPTION PRICING - II. Derivatives and Risk Management By Rajiv Srivastava. Copyright Oxford University Press

CHAPTER 10 OPTION PRICING - II. Derivatives and Risk Management By Rajiv Srivastava. Copyright Oxford University Press CHAPTER 10 OPTION PRICING - II Options Pricing II Intrinsic Value and Time Value Boundary Conditions for Option Pricing Arbitrage Based Relationship for Option Pricing Put Call Parity 2 Binomial Option

More information

Market risk measurement in practice

Market risk measurement in practice Lecture notes on risk management, public policy, and the financial system Allan M. Malz Columbia University 2018 Allan M. Malz Last updated: October 23, 2018 2/32 Outline Nonlinearity in market risk Market

More information

Modeling via Stochastic Processes in Finance

Modeling via Stochastic Processes in Finance Modeling via Stochastic Processes in Finance Dimbinirina Ramarimbahoaka Department of Mathematics and Statistics University of Calgary AMAT 621 - Fall 2012 October 15, 2012 Question: What are appropriate

More information

Monte Carlo Methods in Financial Practice. Derivates Pricing and Arbitrage

Monte Carlo Methods in Financial Practice. Derivates Pricing and Arbitrage Derivates Pricing and Arbitrage What are Derivatives? Derivatives are complex financial products which come in many different forms. They are, simply said, a contract between two parties, which specify

More information

SYLLABUS. IEOR E4728 Topics in Quantitative Finance: Inflation Derivatives

SYLLABUS. IEOR E4728 Topics in Quantitative Finance: Inflation Derivatives SYLLABUS IEOR E4728 Topics in Quantitative Finance: Inflation Derivatives Term: Summer 2007 Department: Industrial Engineering and Operations Research (IEOR) Instructor: Iraj Kani TA: Wayne Lu References:

More information

Vanilla interest rate options

Vanilla interest rate options Vanilla interest rate options Marco Marchioro derivati2@marchioro.org October 26, 2011 Vanilla interest rate options 1 Summary Probability evolution at information arrival Brownian motion and option pricing

More information

Introduction Random Walk One-Period Option Pricing Binomial Option Pricing Nice Math. Binomial Models. Christopher Ting.

Introduction Random Walk One-Period Option Pricing Binomial Option Pricing Nice Math. Binomial Models. Christopher Ting. Binomial Models Christopher Ting Christopher Ting http://www.mysmu.edu/faculty/christophert/ : christopherting@smu.edu.sg : 6828 0364 : LKCSB 5036 October 14, 2016 Christopher Ting QF 101 Week 9 October

More information

Energy Price Processes

Energy Price Processes Energy Processes Used for Derivatives Pricing & Risk Management In this first of three articles, we will describe the most commonly used process, Geometric Brownian Motion, and in the second and third

More information

The mathematical finance of Quants and backward stochastic differential equations

The mathematical finance of Quants and backward stochastic differential equations The mathematical finance of Quants and backward stochastic differential equations Arnaud LIONNET INRIA (Mathrisk) INRIA-PRO Junior Seminar 17th February 2015 Financial derivatives Derivative contract :

More information

How to Trade Options Using VantagePoint and Trade Management

How to Trade Options Using VantagePoint and Trade Management How to Trade Options Using VantagePoint and Trade Management Course 3.2 + 3.3 Copyright 2016 Market Technologies, LLC. 1 Option Basics Part I Agenda Option Basics and Lingo Call and Put Attributes Profit

More information

European call option with inflation-linked strike

European call option with inflation-linked strike Mathematical Statistics Stockholm University European call option with inflation-linked strike Ola Hammarlid Research Report 2010:2 ISSN 1650-0377 Postal address: Mathematical Statistics Dept. of Mathematics

More information

Callability Features

Callability Features 2 Callability Features 2.1 Introduction and Objectives In this chapter, we introduce callability which gives one party in a transaction the right (but not the obligation) to terminate the transaction early.

More information

Volatility Smiles and Yield Frowns

Volatility Smiles and Yield Frowns Volatility Smiles and Yield Frowns Peter Carr NYU CBOE Conference on Derivatives and Volatility, Chicago, Nov. 10, 2017 Peter Carr (NYU) Volatility Smiles and Yield Frowns 11/10/2017 1 / 33 Interest Rates

More information

Risk Neutral Pricing Black-Scholes Formula Lecture 19. Dr. Vasily Strela (Morgan Stanley and MIT)

Risk Neutral Pricing Black-Scholes Formula Lecture 19. Dr. Vasily Strela (Morgan Stanley and MIT) Risk Neutral Pricing Black-Scholes Formula Lecture 19 Dr. Vasily Strela (Morgan Stanley and MIT) Risk Neutral Valuation: Two-Horse Race Example One horse has 20% chance to win another has 80% chance $10000

More information

On Arbitrage Possibilities via Linear Feedback in an Idealized Market

On Arbitrage Possibilities via Linear Feedback in an Idealized Market On Arbitrage Possibilities via Linear Feedback in an Idealized Market B. Ross Barmish University of Wisconsin barmish@engr.wisc.edu James A. Primbs Stanford University japrimbs@stanford.edu Workshop on

More information

Practice of Finance: Advanced Corporate Risk Management

Practice of Finance: Advanced Corporate Risk Management MIT OpenCourseWare http://ocw.mit.edu 15.997 Practice of Finance: Advanced Corporate Risk Management Spring 2009 For information about citing these materials or our Terms of Use, visit: http://ocw.mit.edu/terms.

More information