The Mathematics of Currency Hedging

Similar documents
Practical example of an Economic Scenario Generator

The Black-Scholes Model

Hedging with Life and General Insurance Products

The Black-Scholes Equation using Heat Equation

The Black-Scholes Model

Lecture 3. Sergei Fedotov Introduction to Financial Mathematics. Sergei Fedotov (University of Manchester) / 6

Continuous Processes. Brownian motion Stochastic calculus Ito calculus

European option pricing under parameter uncertainty

Illiquidity, Credit risk and Merton s model

Replication and Absence of Arbitrage in Non-Semimartingale Models

Brownian Motion and Ito s Lemma

Application of Stochastic Calculus to Price a Quanto Spread

BROWNIAN MOTION Antonella Basso, Martina Nardon

1.1 Basic Financial Derivatives: Forward Contracts and Options

Local Volatility Dynamic Models

Interest rate models in continuous time

5. Itô Calculus. Partial derivative are abstractions. Usually they are called multipliers or marginal effects (cf. the Greeks in option theory).

Hedging Credit Derivatives in Intensity Based Models

Queens College, CUNY, Department of Computer Science Computational Finance CSCI 365 / 765 Fall 2017 Instructor: Dr. Sateesh Mane.

Pricing Dynamic Solvency Insurance and Investment Fund Protection

AMH4 - ADVANCED OPTION PRICING. Contents

Optimal Hedging of Variance Derivatives. John Crosby. Centre for Economic and Financial Studies, Department of Economics, Glasgow University

THE USE OF NUMERAIRES IN MULTI-DIMENSIONAL BLACK- SCHOLES PARTIAL DIFFERENTIAL EQUATIONS. Hyong-chol O *, Yong-hwa Ro **, Ning Wan*** 1.

European call option with inflation-linked strike

STOCHASTIC CALCULUS AND BLACK-SCHOLES MODEL

Continuous Time Finance. Tomas Björk

Non-semimartingales in finance

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

The Self-financing Condition: Remembering the Limit Order Book

MODELLING OPTIMAL HEDGE RATIO IN THE PRESENCE OF FUNDING RISK

Basic Arbitrage Theory KTH Tomas Björk

Using of stochastic Ito and Stratonovich integrals derived security pricing

"Pricing Exotic Options using Strong Convergence Properties

Counterparty Credit Risk Simulation

The stochastic calculus

Risk Reduction Potential

CHAPTER 5 ELEMENTARY STOCHASTIC CALCULUS. In all of these X(t) is Brownian motion. 1. By considering X 2 (t), show that

Utility Indifference Pricing and Dynamic Programming Algorithm

COMBINING FAIR PRICING AND CAPITAL REQUIREMENTS

Modeling via Stochastic Processes in Finance

2.3 Mathematical Finance: Option pricing

The University of Chicago, Booth School of Business Business 41202, Spring Quarter 2011, Mr. Ruey S. Tsay. Solutions to Final Exam.

Monte Carlo Simulations

Exponential utility maximization under partial information

M5MF6. Advanced Methods in Derivatives Pricing

TEACHING NOTE 98-04: EXCHANGE OPTION PRICING

1 The continuous time limit

Monte-Carlo Estimations of the Downside Risk of Derivative Portfolios

Risk Neutral Valuation

On worst-case investment with applications in finance and insurance mathematics

Portfolio optimization with transaction costs

25857 Interest Rate Modelling

OPTIMAL PORTFOLIO CONTROL WITH TRADING STRATEGIES OF FINITE

A Moment Matching Approach To The Valuation Of A Volume Weighted Average Price Option

1 Interest Based Instruments

Completeness and Hedging. Tomas Björk

Stochastic Dynamical Systems and SDE s. An Informal Introduction

Bluff Your Way Through Black-Scholes

Analytical formulas for local volatility model with stochastic. Mohammed Miri

θ(t ) = T f(0, T ) + σ2 T

IMPA Commodities Course : Forward Price Models

Robust Optimization Applied to a Currency Portfolio

The University of Chicago, Booth School of Business Business 41202, Spring Quarter 2012, Mr. Ruey S. Tsay. Solutions to Final Exam

Math 416/516: Stochastic Simulation

Economathematics. Problem Sheet 1. Zbigniew Palmowski. Ws 2 dw s = 1 t

STOCHASTIC INTEGRALS

JDEP 384H: Numerical Methods in Business

2.1 Mean-variance Analysis: Single-period Model

Youngrok Lee and Jaesung Lee

Valuation of a New Class of Commodity-Linked Bonds with Partial Indexation Adjustments

The University of Chicago, Booth School of Business Business 41202, Spring Quarter 2009, Mr. Ruey S. Tsay. Solutions to Final Exam

Financial Economics & Insurance

A No-Arbitrage Theorem for Uncertain Stock Model

Lévy models in finance

International Mathematical Forum, Vol. 6, 2011, no. 5, Option on a CPPI. Marcos Escobar

Option Pricing Models for European Options

Forwards and Futures. Chapter Basics of forwards and futures Forwards

Time-Varying Risk Premia and Stock Return Autocorrelation

CONTINUOUS TIME PRICING AND TRADING: A REVIEW, WITH SOME EXTRA PIECES

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

Chapter 3: Black-Scholes Equation and Its Numerical Evaluation

A new approach for scenario generation in risk management

Lecture 4. Finite difference and finite element methods

Advanced topics in continuous time finance

Risk, Return, and Ross Recovery

Computing Bounds on Risk-Neutral Measures from the Observed Prices of Call Options

The Impact of Volatility Estimates in Hedging Effectiveness

Exponential utility maximization under partial information and sufficiency of information

A Two Factor Forward Curve Model with Stochastic Volatility for Commodity Prices arxiv: v2 [q-fin.pr] 8 Aug 2017

13.3 A Stochastic Production Planning Model

A model for a large investor trading at market indifference prices

(A note) on co-integration in commodity markets

Optimal trading strategies under arbitrage

Beyond the Black-Scholes-Merton model

An overview of some financial models using BSDE with enlarged filtrations

Foreign Exchange Derivative Pricing with Stochastic Correlation

Exam Quantitative Finance (35V5A1)

THE BLACK-SCHOLES FORMULA AND THE GREEK PARAMETERS FOR A NONLINEAR BLACK-SCHOLES EQUATION

Optimal Placement of a Small Order Under a Diffusive Limit Order Book (LOB) Model

MASSACHUSETTS INSTITUTE OF TECHNOLOGY 6.265/15.070J Fall 2013 Lecture 19 11/20/2013. Applications of Ito calculus to finance

Transcription:

The Mathematics of Currency Hedging Benoit Bellone 1, 10 September 2010 Abstract In this note, a very simple model is designed in a Gaussian framework to study the properties of currency hedging Analytical conditions are exhibited when possible and help to discuss when an investor should currency hedge her portfolio Conclusions stick to the intuition First, the lower the currency price of risk, the stronger the case for hedging Second, if the correlation between the local risky asset and the currency return is positive, the higher the local asset price of risk or the higher the currency volatility, the stronger the case for hedging Third, if the correlation between the local risky asset and the currency return is negative, there is no clear-cut conclusion Yet, some simulations suggest that the closer the correlation to the zero bound and the higher the volatility ratio (the larger currency volatility relative to the asset price volatility), the stronger the case for hedging 1 Disclaimer: The views expressed in this working paper are those of the author and do not necessarily reflect those of his past and present employers 1

Foreign and domestic currency returns Consider a situation 2 where we have two currencies: the domestic currency 3 (say US dollar, USD) and the foreign emerging currency (say Brazilian real, BRL) The spot exchange rate at time t is denoted e t and is quoted as dollar per real: units of the domestic currency e t = units of the foreign currency, that is 1 USD = e t BRL or 1 BRL = USD/e t We assume that the domestic short rate r d (resp the brazilian, or foreign, short rate r f ) is deterministic and constant We denote the corresponding riskfree money market bills B d and B f We model the exchange rate by a geometric brownian motion under the physical probability P The drift and the volatility are assumed constant and deterministic such that: de = e α e dt + σ e dw e, db d = r d B d dt, db f = r f B f dt Let s assume that the US investor buys the foreign currency (BRL) and invests in the local risk free rate Such a trade is equivalent to the possibility of investing in a domestic asset with price process B f (t) = B f (t)e t Some Ito calculus leads to the following dynamics: d B f = B f (α e + r f ) dt + σ e dw e We introduce the currency price of risk λ e such that : d B f = B f (r d + λ e σ e ) dt + σ e dw e, with, λ e = α e + r f r d σ e Unhedged Fund dynamics In this section, the dynamics of the fund, denominated in foreign currency (BRL), is modelled as a geometric brownian motion with constant drift and volatility: df = F (α + r f ) dt + σdw 2 In this note, we will follow the approach and notations of Björk (2003), Arbitrage Theory in Continuous Time, Oxford, Chap 17 3 Here, we adopt the perspective from a US-based hedged class investor 2

The brownian motion may however be correlated with the factor driving the currency dynamics So, we denote the quadratic covariation between the two processes: d W, W e = ρdt Let s assume that the investor buys the foreign currency and invests in the fund Such a trade is equivalent to the possibility of investing in a domestic risky asset with price process F f (t) = F (t)e t Then, after some Ito calculus, the dynamics follows: d F F = (α + r f ) dt + σdw + α e dt + σ e dw e + ρσσ e dt, = df F + de e + covariation drift, or: d F F = (r f + α + α e + ρσσ e ) dt + σdw + σ e dw e The unhedged investment in the fund is all the more riskier so as the volatilities of the currency and the strategy are elevated and both risky processes are positively correlated The expected return is increasing in the foreign risk free rate, the alpha and the currency expected return It is increasing (resp decreasing) in the covariation if the correlation is positive (resp negative) Unhedged Fund Sharpe ratio Taking expectations from the previous equation, the expected excess return for a US-based investor in the unhedged asset is: α u = 1 dt E t d F F r ddt, = α + ρσσ e + α e + r f r d = σ (λ + ρσ e ) + σ e λ e Let s λ u (resp ) denote the price of risk (or Sharpe ratio) (resp the volatility) of the unhedged investment : λ u = σ eλ e + σλ + ρσσ e, with = ( σ 2 + σ 2 e + 2ρσσ e ) 1 2 Hedging Foreign Investment Let s introduce a Hedged class H, denominated in the domestic currency (USD) Such a hedging strategy may be decomposed in three investment decisions: 3

1 Buying H shares of the fund denominated in foreign currency (BRL), whose dynamics expressed in domestic currency is: H d F F = H ((r f + α + α e + ρσσ e ) dt + σdw + σ e dw e ) 2 Borrowing short in foreign currency, whose dynamics expressed in domestic currency is : H d B f B f = H (α e + r f ) dt + σ e dw e 3 Buying H units of domestic risk-free money market bills, whose dynamics is: H d B d = B H r d dt d Adding those three trades together leads to the following dynamics: d H = H (r d + α + ρσσ e ) dt + σdw The direct impacts of the currency risk factor dw e, the exchange rate drift α e and the foreign risk-free rate r f have been properly eliminated Hedged class return dynamics The return dynamics of the hedged class, expressed in domestic currency, d H H = df F + (r d r f )dt + ρσσ e dt, is split into the main fund return received by foreign (Brazilian) investors, augmented by the interest rate differential and supplemented by a drift term related to the covariation between the investor s currency and the fund strategy In real life conditions, the correlation and volatility terms are likely to be time-varying and locally stochastic Thus, a temporary rise in currency volality may lead to a positive (resp negative) divergence between both excess returns given the sign of the correlation term In such a situation, the higher the correlation, the more significant a short term divergence is likely Hedged vs unhedged Class Sharpe ratio Taking expectations from the previous equation, the alpha ( α) for a US-based investor in the hedged class is: α = 1 dt E t d H H r ddt, = α + ρσσ e = σ (λ + ρσ e ) 4

Let s λ (resp λ) denote the price of risk (Sharpe ratio) of the local investment (resp hedged class): λ = λ + ρσ e Sharpe ratios are identical providing that the correlation between the two risk factors should be null On the contrary, the hedged class sharpe ratio is greater than the local investment s sharpe ratio providing that the correlation between the currency strategy performance and the currency return is positive From the previous section, we may then compare the sharpe ratios of both hedged and unhedged strategiesit follows that the price of risk of an undhedged investment is a weigthed combination of the currency and hedged investment prices of risk: λ u = σ eλ e + σ λ Conditions required to gain from hedging (ie that the hedged class sharpe ratio be greater than the unhedged sharpe ratio) follow from: λ λ u = = ( (λ + ρσ e ) σ σ e λ e (λ + ρσ e ) σ σ e ( ( 1 + ) σe ( σe σ, ) 2 σ e + 2ρ σ ) 1 2 1 ) λ e σe Let s introduce the currency volatility and local (resp unhedgded strategy) asset price volatility ratios, which are by construction strictly positive: Then, λ λ u = χ (λ + ρσ e ) ξ = σ e σ, and, χ = σ e ( (1 + ξ 2 + 2ρξ ) 1 2 1) ξ λ e, = χ (λ + ρσ e ) h (ξ, ρ) λ e As χ is srictly positive, the gain to hedge depends on the sign of the second part of the former expression We remark that h is increasing in ξ if ρ is positive If ρ is negative, h is non-monotonous, alternatively decreasing and increasing in ξ To give a supplementary insight behind this non-linear relation, let s assume that ξ = 1 (ie identical volatilities) 4 and let s explore the two polar cases: 4 This assumption is not extreme as currency volatility is most of the time larger than bonds but lower than equities 5

ρ = 1: λ λ u 0 λ + σ λ e ρ = 0: λ λ u 0 λ λ e ρ = 1 : λ λ u 0 λ σ λ e We can conclude in this over-simplified framework, that when the local asset price and the currency have a perfect positive correlation and a similar volatility, there is a stronger case for a hedged investment if the sharpe ratio of the currency is inferior to the sum of the local asset price s volatility and price of risk If asset and currencies exhibit a perfect negative correlation and similar volatility, there is a stronger case for a hedged investment if the currency sharpe ratio is inferior to the difference between the price of risk and the volatility of the asset In the general case, some conclusions can also be drawn: The lower the currency price of risk, the stronger the case for hedging If the correlation ρ is positive, the higher the local asset price of risk or the higher the currency volatility, the stronger the case for hedging If the correlation ρ is negative, there is no clear-cut conclusion But some simulations suggest that the closer the correlation to the zero bound and the higher the volatility ratio (the larger currency volatility relative to the asset price volatility), the stronger the case for hedging 6