Corporate Banking and Investment Risk tolerance and optimal portfolio choice Marek Musiela, BNP Paribas, London.

Slides:



Advertisements
Similar presentations
Risk-Averse Adaptive Execution of Portfolio Transactions
Advertisements

Chp.4 Lifetime Portfolio Selection Under Uncertainty
Risk Aversion and Capital Allocation to Risky Assets
Asset Pricing. Pricing Determining a fair value (price) for an investment is an important task. At the beginning of the semester, we dealt with the pricing.
L5: Dynamic Portfolio Management1 Lecture 5: Dynamic Portfolio Management The following topics will be covered: Will risks be washed out over time? Solve.
The securities market economy -- theory Abstracting again to the two- period analysis - - but to different states of payoff.
Chapter 11 Optimal Portfolio Choice
Optimal Risky Portfolios
Valuation of Financial Options Ahmad Alanani Canadian Undergraduate Mathematics Conference 2005.
1 Dynamic portfolio optimization with stochastic programming TIØ4317, H2009.
Quantsmile: Quantitative Portfolio Management Quantsmile: Quantitative Portfolio Management.
Investment Science D.G. Luenberger
Ch.7 The Capital Asset Pricing Model: Another View About Risk
Corporate Banking and Investment Mathematical issues with volatility modelling Marek Musiela BNP Paribas 25th May 2005.
P.V. VISWANATH FOR A FIRST COURSE IN INVESTMENTS.
The Capital Asset Pricing Model. Review Review of portfolio diversification Capital Asset Pricing Model  Capital Market Line (CML)  Security Market.
Chapter 8 Portfolio Selection.
L11: Risk Sharing and Asset Pricing 1 Lecture 11: Risk Sharing and Asset Pricing The following topics will be covered: Pareto Efficient Risk Allocation.
Investment. An Investor’s Perspective An investor has two choices in investment. Risk free asset and risky asset For simplicity, the return on risk free.
Notes – Theory of Choice
5.4 Fundamental Theorems of Asset Pricing (2) 劉彥君.
L9: Consumption, Saving, and Investments 1 Lecture 9: Consumption, Saving, and Investments The following topics will be covered: –Consumption and Saving.
Corporate Finance Portfolio Theory Prof. André Farber SOLVAY BUSINESS SCHOOL UNIVERSITÉ LIBRE DE BRUXELLES.
VNM utility and Risk Aversion  The desire of investors to avoid risk, that is variations in the value of their portfolio of holdings or to smooth their.
5.2Risk-Neutral Measure Part 2 報告者:陳政岳 Stock Under the Risk-Neutral Measure is a Brownian motion on a probability space, and is a filtration for.
5.6 Forwards and Futures 鄭凱允 Forward Contracts Let S(t),, be an asset price process, and let R(t),, be an interest rate process. We consider will.
L6: CAPM & APT 1 Lecture 6: CAPM & APT The following topics are covered: –CAPM –CAPM extensions –Critiques –APT.
L9: Consumption, Saving, and Investments 1 Lecture 9: Consumption, Saving, and Investments The following topics will be covered: –Consumption and Saving.
Chapter 13 Stochastic Optimal Control The state of the system is represented by a controlled stochastic process. Section 13.2 formulates a stochastic optimal.
Lecture 3: Arrow-Debreu Economy
Definition and Properties of the Cost Function
1 ASSET ALLOCATION. 2 With Riskless Asset 3 Mean Variance Relative to a Benchmark.
Expected Utility, Mean-Variance and Risk Aversion Lecture VII.
1 Finance School of Management Chapter 13: The Capital Asset Pricing Model Objective The Theory of the CAPM Use of CAPM in benchmarking Using CAPM to determine.
Investment Analysis and Portfolio Management
Part 4 Chapter 11 Yulin Department of Finance, Xiamen University.
Alternative Measures of Risk. The Optimal Risk Measure Desirable Properties for Risk Measure A risk measure maps the whole distribution of one dollar.
Portfolio Management-Learning Objective
Endogenous growth Sophia Kazinnik University of Houston Economics Department.
STOCHASTIC DOMINANCE APPROACH TO PORTFOLIO OPTIMIZATION Nesrin Alptekin Anadolu University, TURKEY.
Capital Asset Pricing Model CAPM Security Market Line CAPM and Market Efficiency Alpha (  ) vs. Beta (  )
Chapter 3 Discrete Time and State Models. Discount Functions.
0 Portfolio Managment Albert Lee Chun Construction of Portfolios: Introduction to Modern Portfolio Theory Lecture 3 16 Sept 2008.
Lecture 10 The Capital Asset Pricing Model Expectation, variance, standard error (deviation), covariance, and correlation of returns may be based on.
© Markus Rudolf Page 1 Intertemporal Surplus Management BFS meeting Internet-Page: Intertemporal Surplus Management 1. Basics.
5.4 Fundamental Theorems of Asset Pricing 報告者:何俊儒.
Online Financial Intermediation. Types of Intermediaries Brokers –Match buyers and sellers Retailers –Buy products from sellers and resell to buyers Transformers.
A 1/n strategy and Markowitz' problem in continuous time Carl Lindberg
1 Derivatives & Risk Management: Part II Models, valuation and risk management.
MEIE811D Advanced Topics in Finance Optimum Consumption and Portfolio Rules in a Continuous-Time Model Yuna Rhee Seyong Park Robert C. Merton (1971) [Journal.
Chp.5 Optimum Consumption and Portfolio Rules in a Continuous Time Model Hai Lin Department of Finance, Xiamen University.
9. Change of Numeraire 鄭凱允. 9.1 Introduction A numeraire is the unit of account in which other assets are denominated and change the numeraire by changing.
“Differential Information and Performance Measurement Using a Security Market Line” by Philip H. Dybvig and Stephen A. Ross Presented by Jane Zhao.
Option Pricing Models: The Black-Scholes-Merton Model aka Black – Scholes Option Pricing Model (BSOPM)
Investment Performance Measurement, Risk Tolerance and Optimal Portfolio Choice Marek Musiela, BNP Paribas, London.
Risk Management with Coherent Measures of Risk IPAM Conference on Financial Mathematics: Risk Management, Modeling and Numerical Methods January 2001.
All Rights Reserved to Kardan University 2014 Kardan University Kardan.edu.af.
Choosing an Investment Portfolio
1 CHAPTER THREE: Portfolio Theory, Fund Separation and CAPM.
The Capital Asset Pricing Model Lecture XII. .Literature u Most of today’s materials comes from Eugene F. Fama and Merton H. Miller The Theory of Finance.
The Farm Portfolio Problem: Part I Lecture V. An Empirical Model of Mean- Variance Deriving the EV Frontier –Let us begin with the traditional portfolio.
L6: Risk Sharing and Asset Pricing1 Lecture 6: Risk Sharing and Asset Pricing The following topics will be covered: Pareto Efficient Risk Allocation –Defining.
FIN437 Vicentiu Covrig 1 Portfolio management Optimum asset allocation Optimum asset allocation (see chapter 8 RN)
Security Markets V Miloslav S Vošvrda Theory of Capital Markets.
Return and Risk Lecture 2 Calculation of Covariance
Risk Budgeting.
Markowitz Risk - Return Optimization
Theory of Capital Markets
Liquidity Premia & Transaction costs
5.3 Martingale Representation Theorem
Presentation transcript:

Corporate Banking and Investment Risk tolerance and optimal portfolio choice Marek Musiela, BNP Paribas, London

Corporate Banking and Investment 2 Joint work with T. Zariphopoulou (UT Austin) Investments and forward utilities, Preprint 2006 Backward and forward dynamic utilities and their associated pricing systems: Case study of the binomial model, Indifference pricing, PUP (2005) Investment and valuation under backward and forward dynamic utilities in a stochastic factor model, to appear in Dilip Madan’s Festschrift (2006) Investment performance measurement, risk tolerance and optimal portfolio choice, Preprint 2007

Corporate Banking and Investment 3 Contents Investment banking and martingale theory Investment banking and utility theory The classical formulation Remarks Dynamic utility Example – value function Weaknesses of such specification Alternative approach Optimal portfolio Portfolio dynamics Explicit solution Example

Corporate Banking and Investment 4 Investment banking and martingale theory Mathematical logic of the derivative business perfectly in line with the theory Pricing by replication comes down to calculation of an expectation with respect to a martingale measure Issues of the measure choice and model specification and implementation dealt with by the appropriate reserves policy However, the modern investment banking is not about hedging (the essence of pricing by replication) Indeed, it is much more about return on capital - the business of hedging offers the lowest return

Corporate Banking and Investment 5 Investment banking and utility theory No clear idea how to specify the utility function The classical or recursive utility is defined in isolation to the investment opportunities given to an agent Explicit solutions to the optimal investment problems can only be derived under very restrictive model and utility assumptions - dependence on the Markovian assumption and HJB equations The general non Markovian models concentrate on the mathematical questions of existence of optimal allocations and on the dual representation of utility No easy way to develop practical intuition for the asset allocation Creates potential intertemporal inconsistency

Corporate Banking and Investment 6 The classical formulation Choose a utility function, say U(x), for a fixed investment horizon T Specify the investment universe, i.e., the dynamics of assets which can be traded Solve for a self financing strategy which maximizes the expected utility of terminal wealth Shortcomings The investor may want to use intertemporal diversification, i.e., implement short, medium and long term strategies Can the same utility be used for all time horizons? No – in fact the investor gets more value (in terms of the value function) from a longer term investment At the optimum the investor should become indifferent to the investment horizon

Corporate Banking and Investment 7 Remarks In the classical formulation the utility refers to the utility for the last rebalancing period There is a need to define utility (or the investment performance criteria) for any intermediate rebalancing period This needs to be done in a way which maintains the intertemporal consistency For this at the optimum the investor must be indifferent to the investment horizon Only at the optimum the investor achieves on the average his performance objectives Sub optimally he experiences decreasing future expected performance

Corporate Banking and Investment 8 Dynamic performance process U(x,t) is an adapted process As a function of x, U is increasing and concave For each self-financing strategy the associated (discounted) wealth satisfies There exists a self-financing strategy for which the associated (discounted) wealth satisfies

Corporate Banking and Investment 9 Example - value function Value function Dynamic programming principle Value function defines dynamic a performance process

Corporate Banking and Investment 10 Weaknesses of such specification Dynamic performance process U(x,t) is defined by specifying the utility function u(x,T) and then calculating the value function At time 0 U(x,0) may be very complicated and quite unintuitive. Depends strongly on the specification of the market dynamics The analysis of such processes requires Markovian assumption for the asset dynamics and the use of HJB equations Only very specific cases, like exponential, can be analysed in a model independent way

Corporate Banking and Investment 11 Alternative approach – an example Start by defining the utility function at time 0, i.e., set U(x,0)=u(x,0) Define an adapted process U(x,t) by combining the variational and the market related inputs to satisfy the properties of a dynamic performance process Benefits The function u(x,0) represents the utility for today and not for, say, ten years ahead The variational inputs are the same for the general classes of market dynamics – no Markovian assumption required The market inputs have direct intuitive interpretation The family of such processes is sufficiently rich to allow for thinking about allocations in ways which are model and preference choice independent

Corporate Banking and Investment 12 Variational inputs Utility equation Risk tolerance equation

Corporate Banking and Investment 13 Market inputs Investment universe of 1 riskless and k risky securities General Ito type dynamics for the risky securities Standard d-dimensional Brownian motion driving the dynamics of the traded assets Traded assets dynamics

Corporate Banking and Investment 14 Market inputs Using matrix and vector notation assume existence of the market price for risk process which satisfies Benchmark process Views (constraints) process Time rescaling process

Corporate Banking and Investment 15 Alternative approach – an example Under the above assumptions the process U(x,t), defined below is a dynamic performance It turns out that for a given self-financing strategy generating wealth X one can write

Corporate Banking and Investment 16 Optimal portfolio The optimal portfolio is given by Observe that The optimal wealth, the associated risk tolerance and the optimal allocations are benchmarked The optimal portfolio incorporates the investor views or constraints on top of the market equilibrium The optimal portfolio depends on the investor risk tolerance at time 0.

Corporate Banking and Investment 17 Portfolio dynamics Assume that the following processes are continuous vector-valued semimartingales Then, the optimal portfolio turns out to be a continuous vector-valued semimartingale as well. Indeed,

Corporate Banking and Investment 18 Wealth and risk tolerance dynamics The dynamics of the (benchmarked) optimal wealth and risk tolerance are given by Observe that zero risk tolerance translates to following the benchmark and generating pure beta exposure. In what follows we assume that the function r(x,t) is strictly positive for all x and t

Corporate Banking and Investment 19 Canonical variables The wealth and risk tolerance dynamics can be written as follows Observe that Introduce the processes

Corporate Banking and Investment 20 Canonical dynamics The previous system of equations becomes It turns out that it can be solved analytically

Corporate Banking and Investment 21 Linear equation Let h(z,t) be the inverse function of It turns out that h(z,t) solves the following linear equation

Corporate Banking and Investment 22 Explicit representation Solution to the system of equations is given by One can easily revert to the original coordinates and obtain the explicit expressions for

Corporate Banking and Investment 23 Optimal wealth The optimal (benchmarked) wealth can be written as follows

Corporate Banking and Investment 24 Corresponding risk tolerance The risk tolerance process can be written as follows

Corporate Banking and Investment 25 Beta and alpha For an arbitrary risk tolerance the investor will generate pure beta by formulating the appropriate views on top of market equilibrium, indeed, To generate some alpha on top of the beta the investor needs to tolerate some risk but may also formulate views on top of market equilibrium

Corporate Banking and Investment 26 No benchmark and no views The optimal allocations, given below, are expressed in the discounted with the riskless asset amounts They depend on the market price of risk, asset volatilities and the investor’s risk tolerance at time 0. Observe no direct dependence on the utility function, and the link between the distribution of the optimal (discounted) wealth in the future and the implicit to it current risk tolerance of the investor

Corporate Banking and Investment 27 No benchmark and hedging constraint The derivatives business can be seen from the investment perspective as an activity for which it is optimal to hold a portfolio which earns riskless rate By formulating views against market equilibrium, one takes a risk neutral position and allocates zero wealth to the risky investment. Indeed, Other constraints can also be incorporated by the appropriate specification of the benchmark and of the vector of views

Corporate Banking and Investment 28 No riskless allocation Take a vector such that Define The optimal allocation is given by It puts zero wealth into the riskless asset. Indeed,

Corporate Banking and Investment 29 Space time harmonic functions Assume that h(z,t) is positive and satisfies Then there exists a positive random variable H such that Non-positive solutions are differences of positive solutions

Corporate Banking and Investment 30 Risk tolerance function Take an increasing space time harmonic function h(z,t) Define the risk tolerance function r(z,t) by It turns out that r(z,t) satisfies the risk tolerance equation

Corporate Banking and Investment 31 Example For positive constants a and b define Observe that The corresponding u(z,t) function can be calculated explicitly The above class covers the classical exponential, logarithmic and power cases