Finance for Science and Technology Students - folk.ntnu.nofolk.ntnu.no/jonasfr/Finans/Foiler/chpt1intro.pdf · Practical information Finance as science Di⁄erence with natural sciences

Practical informationFinance as science

Difference with natural sciencesContents and benefits

Finance for Science and Technology StudentsTIØ4146

Dominicus (Nico) van der WijstRom 501, SB2

Autumn 2014

1 D. van der Wijst TIØ4146 Finance for science and technology students



1 Practical information

2 Finance as science

3 Difference with natural sciences

4 Contents and benefits




Subject matterPracticalitiesCourse’s outlookExam

Subject matter of teaching:

First 9 chapters of course’s book

available at campus bookshopat a competitive pricecontains some non-mandatory extramaterial- techniques in appendices- maybe some paragraphs

Presentations (as this one) used in teaching

The exercises and their solutions

The self test questions (quizzes) are supplied as study aid





The course assumes no previous knowledge in finance

Basic elements are recapitulated in first lecture:

time value of moneydiscounting in investment analysisa bit of micro-economics

We will use little of these elements:

course is about finance, not calculation / micro-economics

Course uses quantitative background of science andtechnology students:

you have seen models and formulae beforethey tell you more than pages of textyou will be addressed as future scientists, not business schoolstudents





Practical details:The course will be taught in English

Teaching hours (week 35 - 47):

Day Time Place ActivityThursdays 09.15-12.00 S3 teachingTuesdays 14.15-16.00 S3 exercises

Exercises are included on a voluntary basis

Presentations, quizzes and (most) other teaching material willbe made available on its learning

Slightly different versions on book’s website(http://www.cambridge.org/9781107029224)


http://www.cambridge.org/9781107029224




Course’s main orientationIs conceptual - not technical:

How should investment decisions be made?

What determines the cost of capital for a project?

What is market effi ciency?

What determines option prices and how?

But with some (voluntary) technical excursions:

just for the fun of it (not mandatory)

gives you a better understanding

gives you easy access to literature





Don’t be misled by deceptively simple calculations!

Answer to a typical exam question could be:

first we calculate the return on equity:re = 0.06+ 1.4× 0.08 = 0.172return on assets can then be found as:0.172 = ra + (ra − 0.09) 0.5

0.5 ⇒ ra = 0.131

This course is not about whether you can multiply 0.08 by 1.4and add 0.06 !

It is about choosing the proper inputs for a Cost of Capitalmodel and combining the models to find the proper CoC





Don’t be misled by the occasional large formula!

All formulae are easy to use

incl. the Black and Scholes’option pricing formula

option pricing has image of diffi culty(among business school students)image is wrong: all you need is a calculator (for ln) and asimple table (for probability)

Proper use, not derivation, of formulae is required for thiscourse





Exam:1 final exam, no mid semester test, mandatory exercises or termpaper

2 December 2014, 09.00 hrs.

open book exam, written

re-examination, if any, may be oral or written

exam will be available in English and/or Norwegian

you can answer in English or Norwegian

4 hours

all calculators allowed (NTNU’s definition)

Check date and make arrangements early, the rules become moreand more strict.




What is finance?How does finance work?Theoretical financeEmpirical/applied finance

Financestudies how people choose between uncertain future values

it is part of economics

social science

studies how people allocate scarce resources

among competing goals

finance studies economic problems for alternatives that involve

time

money

uncertainty





Finance studies these problems of different parties:

Businesses ⇒ Corporate Finance

Governments ⇒ Public Finance

Private persons ⇒ Personal Finance

Emphasis is on corporate finance, also personal applications

Finance as a science is ± 100 years oldfirst descriptive (what is..)

now analytic (what should be..if..)

Gradually acquired more and more quantitative content





Still 2 angles of approach, combined in the course:

1 Managerial Financetool box for solving decision problems in practice

1 gives "the approximate answer to the precise problem" 1

2 this is where money is earned

2 Theory of Finance (or Financial Economics)seeks to generate knowledge of general validity

1 gives "the precise answer to the approximate problem" 1

2 this is where Nobel prizes are earned

1The terminology is based on Hastie (1982).12 D. van der Wijst TIØ4146 Finance for science and technology students




Nobel prizes for financial economists

Year Name Topics1970 Paul Samuelson Dynamic economic theory1972 Kenneth Arrow General economic equilibrium theory1983 Gerard Debreu Theory of general equilibrium1985 Franco Modigliani Analyses of financial markets

Harry Markowitz Pioneering work1990 Merton Miller in the theory of

William Sharpe financial economics1994 John Nash Game theory1997 Robert Merton New method to determine

Myron Scholes the value of derivatives2013 Gene Fama, P. Asset pricing,

Hansen, R. Shiller Market effi ciency

We will be standing on the shoulders of these giants13 D. van der Wijst TIØ4146 Finance for science and technology students




Main tools of financeare similar to those of other scientific disciplines:

1 the formulation (mathematical modelling) of theories2 their empirical testing through confrontation with real life data3 the application of results

Finance is special among social sciences in all three elements:

it stands closer to the natural sciences than most othersciences do (cf. ’rocket scientists’on Wall Street)

financial markets lend themselves very well for modelling,testing and application

Enables a full cycle of scientific research, from formal theory totests and practical applications.





The interlocking cycles of scientific and applied research

Theoretical Empirical Practical

Assumptions

Model

Predictions

Results

Tests

Prices/Hypotheses

Applications

Conclusions/

Questions





Finance as a theoretical science:

takes actual, relevant problem

makes problem manageable by simplifying assumptions

about investors (e.g. greediness)about financial markets (e.g. no transaction costs)

translates stylized problem in mathematical terms

uses the analytical power of mathematics to formulatepredictions in terms of:

hypothesesprices





Example: option pricing

Actual, relevant problem:what is the proper price of a stock option?

Simplifying assumptions:interest rate, volatility are constant, frictionless markets, etc.

Translation in mathematical terms:formulate stock price as stochastic differential equation andoption’s payoff as boundary condition

Analytical power of mathematics:solve the ’boundary value problem’to find proper option price

Result is the famous Black & Scholes formula!





Finance as an empirical science:

tests financial theories

by confronting their conclusions with real life data:

prices on financial markets for stocks, bonds, derivatives, etc.accounting and other data

empirical relations in finance are ’special’(see later)


To tests option pricing theory:

Confront theoretical prices with market prices:

run model ’in reverse’to calculate implied volatilitiessee if implied volatility is constant across different exercisedates/prices






ln(S)

prob. implied

B&S

strike

vola.

implied

B&S





Finance as an applied science uses results of not rejected theoriesto:

buy or sell on financial market

accept or reject investment proposal

choose a capital structure for project or company


If model prices are acceptable, use them to:

Trade in options on the exchange

Find price of a new option you want to create and sell(’write’an option)

Hedge (i.e. neutralize) obligations from another contract, e.g.if you have to deliver a stock in 3 months time




Empirical relations in financeTwo examplesReason for dispersion

Difference with natural sciences

Natural sciences study phenomena that can be:

measured very precisely in controlled experiments

predicted accurately from laws of nature

⇒ observations show little dispersion around (predicted) relations

Finance is social science, studies human behaviour:

no controlled experiments, only noisy real life data

incomplete models: cannot contain all relevant information

both are used in statistical estimation of relations

⇒ observations show large dispersion around (predicted) relations





Illustrate differences with extreme example from both

Example from NASA space program:

Wilkinson Microwave Anisotropy Probe

$150 million satellite, launched in 2001

mapped cosmic background radiation

oldest light in the universe

released shortly after birth of universe 13.73 billion years ago

Point here: observations, even of the oldest light in the universe,show very little dispersion.





Relative brightness (temperature) of spots vs. size (angle). Credit:NASA / Wilkinson Microwave Anisotropy Probe Science Team





Example from finance:

Risk-return relation of 100 large US companies (Nasdaq-100)

data include Apple, Adobe, Intel, Microsoft

Return=(∆stock price+dividends)/market valuerisk=β, measures contribution to portfolio varianceLine is theoretical model: Capital Asset Pricing Model

for which Sharpe was awarded 1990 Nobel Prize

Point here: observations, even of the world’s largest companies, arewidely dispersed, even around a Nobel prize winning model





0.5 1.0 1.5 2.0

50

0

50

100

Beta

Return

Risk-return relationship for Nasdaq-100 companies, October 2010to September 2011





Nature of financial economicsmakes relations less precise:

it studies how people choose between uncertain future values

these future values are largely unpredictable:

not because financial economists do a bad jobbut because properly functioning financial markets make themunpredictable

On such markets, accurate predictions ’self-destruct’

information allowing accurate prediction is immediatelyincorporated into priceslater price changes depend on new informationwhich is unpredictable by definition





That is Market Effi ciency:

also called Effi cient Market Hypothesis (EMH)

a theory discovered ’by accident’in 1950s

explains why important study-objects as stock price changesshould be unpredictable!

Essence was accurately and succinctly worded by Samuelson:

Properly anticipated prices fluctuate randomly





Same information effect also makes observed, historical relationsnoisy:

There is a constant flow of economic news

causes large daily stock price changes

expected, structural part is much smaller

High unexplained variance is a positive, not a negative, qualityindicator of financial markets:

unexplained variance has increased over time

it increases with the sophistication of financial markets

it increases with the informativeness of stock prices

means financial market is functioning properly!




Central issueHandling riskBenefits of the courseTime table

Central issue is valuation

of investment projects, firms, options, contracts, etc.In finance, value is often the discounted value of expected futurecash flows:

Value =t

∑Exp [Cash flow t]

(1+ discount ratet)t

Value has a time and an uncertainty dimension

Uncertainty can be accounted for in 3 different ways:





1 Adjust the discount rate to the risk adjusted discount rate

using the Capital Asset Pricing Model (CAPM) or

Ross’Arbitrage Pricing Theory (APT)

2 Adjust the cash flows to certainty equivalent cash flows

using the CAPM

or derivative securities such as futures

3 Adjust the probabilities (expectations operator) from normalto risk neutral or equivalent martingale probabilities

using the Black-Scholes-Merton Option Pricing Theory,

a fundamentally different way to account for risk.





Course benefitsCompleting the course gives students financial literacy:

knowledge to evaluate investment proposals, including thevalue of flexibility (real options)

be a competent discussion partner of ’specialists’

Means you have an educated opinion about questions like these:

What are the relevant risks in investment decisions, and howcan they be priced?

Should your (and my) pension fund pursue an activeinvestment strategy or not?





Course benefits (cont.ed)

Why are options more risky and more diffi cult to price thanshares?

How can new financial products be constructed with financialengineering and how did such products help to create thecredit crunch?

When has flexibility in projects value, and how can that valuebe calculated?

Why can good projects be turned down and bad projectsaccepted?

Why is it nonsense to take up a loan in another country witha lower interest rate?





Approximate and preliminary time table

Week Subject Chapt.34 Introduction 135 Recap fundamentals 236-38 Portfolio theory, CAPM and APT 338-39 Market effi ciency 440 Capital Structure 541 Valuing levered projects 642 Guest lecture -43 Options and their pricing foundations 744 Binomial option pricing 745 Black and Scholes option pricing 846 Real options analysis 947 Summary and exam instructions -





Welcome

to the

Wonderful World

of

Financial Modelling!


Documents

Finance for Science and Technology Students - folk.ntnu.nofolk.ntnu.no/jonasfr/Finans/Foiler/chpt1intro.pdf · Practical information Finance as science Di⁄erence with natural sciences