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Applying Real Option Theory to Software Architecture Valuation Yuanfang Cai University of Virginia

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Outline Issues that are Unsolved by Information Hiding Options: What and Why? Summer Efforts Real Options in Avaya Summary and Discussion

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Issues that are Unsolved by Information Hiding Difficult Justification of the Cost Predict future Study the commonality among family members Time/Quality Dilemma Future Prediction Never Happens Taken Software Design as an Investment Activity, What are the Values of Information hiding Infrastructures?

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Current Valuation Practices and their Insufficiency Valuation by Products Discount Cash flow (DCF) Present Value = Future Value/(1 + k) t k: Risk Adjusted Discount Rate t: Project Time Decision Tree Analysis (DTA) Each possible outcomes in each time period is treated as a branch Probabilities of each outcome are estimated Backward Dynamic Programming Why They are not Suitable for Product Line Architecture Valuation? DCF: Operational Flexibilities are ignored DTA: Fixed Discount Rate

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Options: What and Why Financial Origin the right without symmetry obligation Financial Options give investors the right without symmetry obligation to buy/sell stocks at a predetermined price (exercise price) before/at a preset time (expiration time). From Wall Street to Main Street the right without symmetry obligation Real Options give investors the right without symmetry obligation to take an action at a predetermined cost (exercise price) at a certain point of time (expiration time). Options Way of Thinking: Risk Management Strategy Uncertainties create opportunities Create Options to manage risks and master the upside Make minimal investment at the beginning and make incremental investment stage by stage

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Options: What and Why Early Exploration of RO Application in Software Architecture Modularization create portfolios of options Information hiding gives the rights without symmetry obligation Product Line Strategy implies Options way of thinking Why Option Pricing in Financial and Real Option World? Why Option Valuation in Software Infrastructure? Black-Scholes Option-Pricing Model

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Options: What and Why Black-Scholes Option-Pricing Model C(S, ; E) = SN(d 1 ) – Ee - r N(d 2 ) d 1 = (ln(S/E) + (r + 1/2 2 ) )/ ( 1/2 ) d 2 = d1 - 1/2 Key Elements in the Model S: Underlying asset value E: Exercise price : Standard deviation of the rate of return : Expiration time r: Risk free interest rate C: Option premium/option price

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Examples that Show Differences A Project Business Case Five years Total Investment: $11 Million Expected Cash Flow in year 5: $21 Million Non-phased development NPV computed by Traditional DCF (worst case): $1mm Phased Development Phase 1 First year: I 1 =$5 Million The expected Net Cash flow from Local Distribution: V1 = $5 Million NPV of phase 1 is 0 Non-Phased Development vs. Phased Development

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Examples that Show Differences Phased Development Phase 2 (option) The second outlay in 3 rd year: I 2 =$6 Million The expected Net Cash flow from expanding Distribution: V2 = $15 Million The Uncertainty of V2: = 0.5 Value of the Option: $10 Million Expanded NPV = NPV of phase 1 + option premium of phase 2 = 10 Million Non-Phased Development vs. Phased Development

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Summer Efforts Applicability of RO Valuation to Software projects Recognizing Options in Software Product Line Data Collection for Valuation on Real Projects

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Applicability of RO Valuation to Software Projects Assumptions Stochastic Process No-arbitrage equilibrium Existence of traded securities to replicate the payoff to options Communication with RO community

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Recognizing Options in Software Product Line engineering Identify Options: Deferrable, Expiring, Compound and Simple S: Underlying asset value Net cash flow from family members E: Exercise price Cost of building new family members : Standard deviation of the rate of return : Expiration time Project terminal year r: Risk free interest rate C: Option premium/option price The Value of the product line infrastructure

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Real Options in Avaya Fertile Fields The Need for Real Options Valuation is recognized Most Data are available Sterile Fields Data are hard to get Insights into Business Data must be improved Established Ways of thinking

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Summary and discussion Justification of applicability to software architectures Identification of options in software architectures and product line engineering There is a big gap between architecture side and business side Quantification and Ways of Thinking

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