REFLECTIONS ON REAL OPTIONS · valuation, risk and portfolio mgt and empirical testing Valuation of...

REFLECTIONS ON REAL OPTIONS

What We Know (or Should Seek to Know) about Decision Making Under Uncertainty

Lenos Trigeorgis

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Agenda

Current state: theory meets practice

What we know (insights) on investing under uncertainty

Research streams/directions

– Past

– Current

– Future

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Current State

More than 3000 research papers and books on RO

Early aps in natural resources E&D (mining, oil & gas),

pharma R&D, manufacturing and power capacity

planning (high uncertainty, long-horizon, staged)

Reach well beyond finance and economics, to strategy,

operations mgt and OR, IT, HRM, marketing,

engineering/architecture, environment & transportation,

contracts and law etc

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Current State

Corporate adoption respectable 10-30% (e.g., Graham

& Harvey, Bain) but high defection (Bain)

Lag (gap) between theory and practice; criticised for

unrealistic assumptions (rational & loyal mgt; non-

tradeability; independent of other projects, capital

structure or other parties actions etc) and complexity

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What we Know: Investing under Uncertainty

Uncertainty and flexibility are key drivers of value (ROV)

Uncertainty seen not as risk to be avoided but as

window of opportunity to create value through flexible

project design and corporate strategy (via learning,

staging, modular design, infrastructure/platform, multiple

prototypes/ suppliers etc.)

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Traditional paradigm (DCF) based on expected plans

and passive management inadequate; flexibility to revise

decisions when deviating from expected plans

introduces asymmetry expanding upside and limiting

downside; this calls for expanded (strategic) NPV to

capture operating flexibility and strategic interactions

Expanded NPV = passive NPV + Real Option Value (ROV)

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Managerial flexibility (ROV) tends to be higher

- in industries/markets with higher uncertainty

- for investment opportunities with longer horizons or that can be delayed longer to gain info.

- when (real) interest rates are higher

- for multi-stage (compound) options

May be justified to

• accept projects with - NPV (I > V) or OTM calls (growth options) (early-stage or compound, undeveloped reserves)

• delay projects with + NPV or ITM calls (beyond g > r)

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Higher uncertainty tends to increase value of option

to defer (a single, irreversible, proprietary) investment (if there are no “dividends” or other early-exercise benefits, competitive erosion or strategic interactions, or other embedded follow on options). Higher value to “wait-and-see” necessitates a higher investment threshold (when V is at premium above inv. cost I) --leading to investing less or later (“uncertainty suppresses investment”)

If can reverse the decision, easier to make it (invest)

in first place (e.g., move, get married etc.)

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Under uncertainty, staging investment provides valuable

flexibility to continue to next stage (option) or abandon (exit) midway; continuation (e.g., financing in VC) should be contingent on success of earlier stages

Multistage opportunities may have significant growth

(compound) option value that may justify making strategic investment despite negative NPV

(e.g., invest in Spain for expansion option in EU or LA)

Firms/industries facing higher uncertainty have higher GO/P

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If investing early creates other options (e.g., to later

expand, abandon or switch), then more uncertainty

would also increase their flexibility value –

increasing value of early investing (nonmonotonic

impact of uncertainty on investment)

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In presence of competition, early investment may

have strategic value by influencing equilibrium actions (quantity or price setting) of competitors or even preempting competitive entry

Value of strategic investment and optimal

competitive strategy depends on proprietary or shared investment and on contrarian (Q) or reciprocating (P) competitive reaction

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Competitive Strategies

Contrarian Reciprocating

flexible and inoffensive commiting and

offensive

flexible and offensive commiting and

inoffensive

COMPETITION

PIONEER

(A)

Proprietary

(capture most of

total market value)

Shared

Preemptive commitment

(+) effect

Vulnerable (-) effect

Non-provoking (-) effect

Cooperative

commitment (+) effect

(+) effect

(fixed market value)

e.g., Quantity competition

(altered market value)

e.g., Price competition

(share total

market value)

1 2

4 3

Depend on type of investment (proprietary vs. shared)

and competitive reaction (contrarian vs. reciprocating)

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When benefits are proprietary (pioneer can get stronger

at expense of competitor) and competitor’s reaction is contrarian (e.g. retreat under Q competition), should commit to early investment (aggressive strategy)

When benefits are shared (“nice”) and competition is

contrarian (responds aggressively), should follow flexible “wait and see” strategy

Above can be reversed under reciprocating (e.g. price

cutting) competition: shared (“nice”/collaborate) increases industry value (smaller share of larger pie)

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Competitive pressure may induce firms (e.g., in a

“winner takes all” innovation race) to invest early

(prematurely), resulting in prisoner’s dilemma situation

A joint (research) venture enables the cooperating

firms to more fully appropriate the flexibility value from

waiting given demand uncertainty (avoiding the

prisoner’s dilemma)

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Multiple options may interact, i.e. (option value)

additivity may break down. Value of a combination

of options typically less than sum of separate

option values. Incremental contribution to a group

(portfolio) depends on other options doing similar

task (redundancy). Incremental value of an option

is portfolio value with vs. w/o the option. Hard to

value a company (portfolio of interacting options).

Using analytic formula like Black-Scholes to value

parts may be misleading

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Options to switch (cheapest inputs, best/max of

outputs, countries of operation) provide valuable

flexibility and risk management value (e.g., MNC)

Portfolio (mean-var) theory based on min portfolio

risk inadequate – needs to be extended for

portfolios of options (incorporating higher moments)

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With options to switch (or on max or min of assets)

lower correlation increases relative volatility and

option value of flexible system/network

MNC’s operating in several countries prefer next

strategic location with lower correlation not to

diversify and reduce portfolio risk but to increase

the option value of flexible network

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When switching among operating “modes” or

strategies, presence of switching costs (e.g., to enter,

exit, shut down) may induce a “hysteresis,” inertia or

delay/lag effect (even though immediate switching is

attractive based on short-term cash-flow it may be

long-term optimal to wait e.g. due to high cost or prob

of switching back later) e.g. continue operating a

currently unprofitable mine or oil field (keep OMC);

Japanese auto producers hanging-on in US; hiring

and firing lags; divorce delay

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Past Research Streams (1986/96)

More actual case applications and tackling

implementation issues (e.g. volatility estimation,

non-normal distributions)

Generic user-friendly options software as practical

aid to corporate planners (focusing on structure of

optional decisions)

More field, survey or empirical studies to test

conformity of RO implications with managerial

experience and market data

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Past Research Streams

Explain empirical phenomena, e.g. if mgt of target

firms turn down tenders for better offers

(ancestors waiting for a better mate)

Applying RO in related areas e.g., competitive

bidding (Antamina), IT or platform investments,

energy and R&D, international finance & business

(JVs, MNC flexibility, outsourcing)

Endogenous competition and strategy, merging

options and game theory (option games)

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Analyzing investments that generate info. & learning

(e.g. pilot or market test, excavations) extending

options with Bayesian analysis

Modeling growth and strategic effects e.g. project

synergies or across-time interactions

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Recognizing interactions among real and financial

options (leverage) and understanding implications

for interdependent corporate investment &

financing decisions. E.g. external financing, internal

excess liquid funds (RE) or even franchising

policies can provide alternative means of financing

and exercising the firm’s growth options, so the

costs and constraints (or relaxation) they bring may

affect firm growth option value

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Incorporating agency issues resulting in suboptimal

option exercise policies due to divisional size or

budget concerns (e.g., overexpansion or growth,

delay/avoid abandonment, premature exercise of

GO to generate s/t earnings). Design proper

corrective incentive contracts (also accounting for

asymmetric info). Develop more dynamic EVA–like

measures consistent with expanded-NPV that limit

cognitive biases, using conditional control targets

(e.g., ROA, growth) contingent on future options. In

separating performance from luck, benchmark to

industry performance and average out comp

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Current Research Streams

Valuing a company as [assets in place plus] portfolio

of growth options (remove g from TV perpetuity

assumption); but various projects or growth options

within company may interact (care). Exercise of

one growth option may affect others

Valuing intangibles: brand expansion strategy,

infrastructure investment; licensing terms/strategy,

cooperating vs. fighting patent strategies, flexible

human capital architecture)

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Strategy applications and empirical evidence

• Infrastructure investment, JVs, sequential acquisitions

• When to compete or cooperate (dynamic strategy)

• Outsourcing flexibility or manufacturing close to home (reduce lead

time); franchising (overcoming financing constraints)

• Multinational flexibility, MNC performance and downside risk

• Conglomerate diversification discount and corporate spinoffs

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Asset pricing and empirical corporate finance

• Managerial discretion and earnings mgt

• Bankruptcy prediction and credit risk models

• Implied volatility and pessimism under ambiguity

• Explaining MV of equity & stock returns driven by

growth options, default risk or skewness

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Future Directions

More care in finding “comparable” (pure-play, option-

free) underlying asset(s). Likely to embed prior

(growth) options and itself be asymmetric. Guidance

to get clean estimate of “pure” underlying without the

growth option (unlever and relever). Similar issue for

company valuation (using growth in TV perpetuity)

Analogous care needed for getting the discount rate

(k) for pure play projects. Using company WACC (a

weighted mix of assets in place and GO)

misestimates true cost of capital. Moreover, the

required return and k is less (not more). More

skewness lowers k

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Future Directions

More realistic asset (P, D or V) distributions (jumps,

changing “dividend “yields, volatilities or correlations)

Develop generic valuation of asymmetric lotteries or

valuing options on asymmetric assets when

underlying log-return distribution (observation error) is

non-Gaussian and involves higher moments (market

utility with vs. w/o lottery; covariance with down

market); how real options-induced skewness gets

preserved or goes away in portfolio diversification

(implications for conglomerate diversification, spinoffs,

R&D or VC portfolio mgt, IPO underpricing etc.)

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Future Directions

Implications of rear extreme events for real options

valuation, risk and portfolio mgt and empirical testing

Valuation of real options in public sector /incomplete

markets (public intangibles); more work on valuation of

shared or cooperative options among multiple parties in

the value chain (e.g. collaboration and contractual

agreements among airlines, plane manufacturers,

airports even the public sector in EU). Government

regulation and incentives can affect how industry growth

options are shared (also with consumer as in utilities)

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Future Directions

Macroeconomic policy implications: need to limit boom and

bust cycles from pro-cyclical or momentum investment

strategies

Use of annual budgets by firms or governments that are

inflexibly “balanced” or driven by free cash flow or

effectively last year’s revenue are pro-cyclical. If last year

was good there is bigger budget and more investment;

but following down years or at times of austerity

budgets shrink and investment/development is cut,

causing more contraction. Such pro-cyclical investment

leads to boom and bust cycles

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Future Directions

More stabilizing policies: 5-year budget averaging

(require govnts to balance budget only in last year);

GDP-linked bonds for Eurozone or emerging

markets; lower tax rates in contraction/austerity

Real options switching “hysteresis” brings hesitation

(lag), smoothing or mean-reversion (rather than

momentum) e.g. use flexible, P/T or contingent

workforce & outsourcing (out of recession)

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Future Directions

Investments that enhance learning and info. updating;

more effective representation of data for human

brain processing; information and network options

(non dissipating or enhanced with more use(rs));

better understanding of ambiguity (uncertainty in

what we don’t know), accounting for the possible but

currently unthinkable (foresight) etc. (e.g. space

shuttle crew)

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Future Directions

Understand better behavioral biases and puzzling

phenomena in investor decision making (innate or

unintentional overconfidence due to cognitive biases

e.g., in estimating demand, reserves or cash flows by

mgrs vs. intentional incentive-induced actions from

misaligned incentives e.g. by analysts); pessimism and

ambiguity; role of incentives and organizational culture

(Ir)rationality & rules of thumb. Reduce complexity

through heuristics (roughly correct on average) –tested

against RO models and exercise policies. E.g., if have

follow-on GO, lower (not raise) k; if options in a portfolio

are not redundant add them up etc.

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The Road Ahead: Closing the Gap

RO is in a unique position to marry valuation science with

the art and intuition of mgt. Corporate adoption will be

enhanced with increased modeling realism and less

complexity, user-friendly software (that focus on framing

managerial decisions), training more analysts and

managers through the ranks, better-aligned managerial

incentives and controls, and particularly more empirical

evidence and successful applications. These efforts

should help bridge the gap between theory and

practice!

REFLECTIONS ON REAL OPTIONS · valuation, risk and portfolio mgt and empirical testing Valuation of...

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