Recent Developments in Production Forecasting and Optimisation Methods

Size: px
Start display at page:

Download "Recent Developments in Production Forecasting and Optimisation Methods"

Transcription

1 Recent Developments in Production Forecasting and Optimisation Methods Ahmed Khamassi, Serafim Ltd Peter Cunningham, Serafim Ltd

2 Content Programme Dual Discount Rate Method for Oil & Gas Project Development Well Number Optimisation Injector Producer Optimisation C-Curves Curves Decline Curve Analysis C-Curves: Curves: Well Density and Infill Drilling Free-Gas:Liquid Ratio

3 Dual Discount Rate For Projects NPV

4 Dual Discount Rate For Projects Current Practice: NPV Assume constant discount rate Assume constant oil price Calculate NPV as (Discounted Revenues Discounted Expenditures) Carry out sensitivity analysis to estimate a range of NPVs under different senarios

5 Dual Discount Rate For Projects NPV Current Practice (Continued): Calculate Internal Rate of Return (IRR: the discount rate that leads to NPV = 0) Use a capital efficiency measure of the type NPV/NPC (Net Present Value of CAPEX)

6 Dual Discount Rate For Projects NPV Issues with current practices: Nature of the discount rate: NPV a measure of value that depends critically on discount rate. Use cost of capital (interest rate, expected shareholders return etc ) ) or opportunity cost (expected returns from alternative investments)? Do we need to discount capital investment?

7 Dual Discount Rate For Projects NPV Use of weighted average of cost of capital Assumption that post-tax tax revenues convert itself back into capital and should be discounted Uncertainty? Capital efficiency measure: When using weighted average cost of capital Generally NPV/NPC hurdle Useful for one-off off decisions: How do I allocate my capital now to maximise NPV?

8 Dual Discount Rate For Projects NPV Not so useful when trying to answer the question: How do I allocate my capital now, and next year, and the year after to maximise long-term value of my company? Example: an NPV/NPC = 0.1 is very attractive for a 2-month 2 project, but unattractive for a 20-year project. Internal Rate of Return (IRR) Discount rate at which project NPV = 0

9 Dual Discount Rate For Projects NPV Multiple IRRs if capital expenditure occurs in tranches Treatment of risk Conventional practice: calculate NPV in a deterministic way then vary NPV parameters For most parameters, it is usual to concentrate on expected NPV Risk is defined by the variance of the distribution

10 Dual Discount Rate For Projects NPV E(NPV): 3.9 NPV SD: 0.6 P(NPV)

11 Dual Discount Rate For Projects NPV E(NPV): 3.9 NPV SD: 5.7 P(NPV)

12 Dual Discount Rate For Projects NPV Oil and gas price uncertainty: Affects the entire company s s portfolio Use of screening criteria: low oil price ($10/bbl) Ignores time effects Obscures risk reduction measures

13 Dual Discount Rate For Projects NPV Capital Asset Pricing Model (CAPM): The expected rate of return on a capital asset is a linear function of its non- diversifiable risk The value of the capital asset is determined by this relationship

14 Dual Discount Rate For Projects NPV Capital Asset Pricing Model Expected return on asset Government bonds Stock market Ratio - Standard deviation of return on asset : SD of return on market portfolio

15 Dual Discount Rate For Projects NPV Advantages of the Capital Asset Pricing Model (CAPM): The value of a project depends on the uncertainty Uncertainty will be imbedded in the calculation of the NPV NPV includes all scenarios and their probabilities

16 Dual Discount Rate For Projects NPV The Dual Discount Rate NPV: Definition: NPV model that uses two discount rates: the expenditure stream is discounted at the cost of capital and the revenue stream is discounted at a rate that takes account of oil and gas price risk.

17 Dual Discount Rate For Projects Equation: NPV NPV = n 1 a t.p 0 + ( ) t 1+ E(r ) ( 1+ r ) p b t f t a t, b t coefficients such that year t cash flow = a t P t + b t P 0 : starting point oil price E(r p ): expected rate of return on writing oil futures r f : risk free rate of return

18 Dual Discount Rate For Projects NPV DDR NPV vs. Conventional NPV DDR NPV is a measure of value given uncertainty DDR NPV resolves the cost of capital vs. opportunity cost of capital problem DDR NPV emphasises the fact that the IRR is an instantaneous quantity

19 Dual Discount Rate For Projects NPV We suggest the use of a NPC x Payback measure instead of NPV/NPC measure Expected returns of oil prices: Futures market indicative of value of future oil or gas Problem with longer term investments

20 Dual Discount Rate For Projects NPV Discount rate in oil futures - 7/8/2000 Discount in oil price (per annum) Mar- 00 Oct- 00 Apr- 01 Nov- 01 May- 02 Dec- 02 Jun- 03 Jan- 04 Settlement date

21 Dual Discount Rate For Projects NPV 0.4 Discount rates from IPE oil futures Discount rate over life of futures year 2 years 3 years month oil futures price ($/bbl)

22 NPV Formulas: Optimising the number of wells

23 NPV Formulas Aim Alternative to complicated spreadsheet models Provide auditable formulas Study inter-relationships relationships Effects of drilling more wells Economics: Increased CAPEX (scalable and possibly unscalable) Increased OPEX Production and recovery Speeding up field production Increased recovery

24 NPV Formulas Number of wells that maximise NPV: N Maximi sin gnpv = R. d q. L α. E q C. d C. d + E q + E α E q α. E R where α = (1+d) -Tab L.q and T ab (abandonment time)=.ln q.n E and q initial oil production per well per year, averaged over all wells, including injectors N total number of wells, including injectors R technical reserves i.e. the amount of oil that could be recovered if the field were run for a very long time L net revenue per tonne of oil (i.e. after all taxes and royalties, including profit tax) d discount rate C net capital cost per well D net capital costs not related to numbers of wells, e.g. roads and pipelines E net opex per well Note:- In this context, net means expressed in terms of effect on present value, after all taxes and royalties

25 Assumptions: NPV Formulas Technically recoverable reserves independent of number of wells Initial well rates independent of number of wells The field follows exponential decline from start

26 Interpretation: NPV Formulas Reformulate the equation Express the NPV as function of NPV maximising well number Ignore abandonment NPV Maximi sin g Well Number 1 = R. L. 1 N. C + N. q + 1 R. d E D d

27 NPV Formulas NPV Maximi sin g Well Number 1 = R. L. 1 N. C + N. q + 1 R. d E D d R.L: value of oil in the ground R. L : the value lost because of discounting N. q + 1 R. d D: value lost as net capex (C+E/d): value lost per well drilled

28 NPV Formulas Effects of changing the number of wells $500,000,000 $450,000,000 $400,000,000 $350,000,000 Present Value $300,000,000 $250,000,000 $200,000,000 $150,000,000 Value lost to time effects Opex and variable capex Sum of value lost $100,000,000 $50,000,000 $ Number of wells

29 Number of wells and NPV model Conventional NPV vs Number of Wells 1, NPV Number of Wells

30 Number of wells and NPV model Effects of changing the revenue discount rate 1, NPV ($ million) NPV with 25 wells (conventional optimal) NPV optimised with dual discount method Optimal number of wells Number of wells drilled Oil discount rate

31 Injector:Producer and NPV Assumptions Water flood Bottom whole pressure constraints Derivation Material balance Link average well rate (producers and injectors) and injector:producer ratio Feed relationship in NPV formula

32 Injector:Producer and NPV Optimal injector : producer ratio = PI. Bo.( Cp. d II. Bw.( Ci. d + Ep) + Ei) PI = productivity index of average production well II = injectivity index of average injection well Bo = oil formation volume factor Bw = water formation volume factor Cp = net capex cost per producer

33 C-Curve Curve Decline Curves Analysis

34 Summary Practical problem with decline analysis Hyperbolic decline rate converges to zero unrealistic late life production Solutions C-curve generalisation of the hyperbolic curve

35 Introduction (Simple decline analysis = calculation of oil-cut or oil-rate from cumulative production) Production forecasts for existing wells/fields Approximate production profiles for new wells/fields (from initial rates and ultimate recovery)

36 Exponential Hyperbolic Li-Horne Main formulations q ( t ) = α. ( UR Np ) b ( UR Np) ( ) 1 q( t) = α. q ( t ) = α Np β Shapes of the different decline equations (idealised example) Oil production rate (stb/day) Cumulative production (MM stb) Exponential Hyperbolic; b=0.3 Hyperbolic; b=0.7 Li-Horne

37 Typical decline in simulation run 1.2 Decline in Ebughu North-East sector simulation model Oil-cut Cumulative oil (k stb)

38 Generalisation of exponential to hyperbolic dq dt oil q oil = a dq dt oil q oil = a. q b oil

39 Generalisation of exponential to C-C curve dq dt oil ( ) = a R Q oil dq dt oil ( ) = ( a + β ( R Q ) oil ) R Q oil b

40 Integrating the C-curve C equation = R. 1 Q oil b a. b. Q a a 1+ e Oil R

41 C (cumulatives)) curve q( t) = α. ( ) ( ) b+ UR Np + β. UR Np 1 C-curve and hyperbolic match to well simulation profile (Alba Field) dr/dx r P10 eclipse results P50 eclipse results C-curve - a=0.263; b = 8 C-curve - a=0.081; b =20 Hyperbolic with fixed reserves - b = 0.79

42 C-Curves Curves and Number of Wells From basic C-curve C equation and the derivation work dr 2 = βr dx Where: x is the number of wells drilled and r the fraction of removable oil remaining Gives a good approximation of the effect of increasing the number of wells

43 C-Curves Curves and Number of Wells AXS area - Effects of well density on recovery Ultimate recovery in 2020 (mm b) UR Calibration to simulation Validation to additional simulation runs Additional rec per well Additional recovery per 1000 ft (mmb) Well footage (1000 ft)

44 Free Gas:Liquid Ratio

45 Free Gas:Liquid Ratio Problems with Muskat material balance method: Depends on field relative permeabilities, but no information on these Core plug relative permeabilities do not include main mechanism at play - gravity Result relative permeabilities adjusted until profiles are no longer obviously wrong But Not obviously wrong correct

46 North Oron I-2 Material balance (Muskat method) calculation Jan-05 Jan-06 Jan-07 Rates (bbl or Mscf per day) Jan-08 Jan-09 Jan-10 Jan-11 Jan-12 Jan-13 Jan-14 Jan-15 Jan-16 Jan-17 Jan-18 Jan-19 Oil Rate Total Gas Rate Water Rate

47 NOR I-1 (North Oron simulation run) Jan-04 Jan-05 Jan-06 Rates (bbl or Mscf per day) Jan-07 Jan-08 Oil Rate Produced Gas Rate Water Rate

48 FGLR (Free-gas:liquid ratio) equilibrium method Gas much more mobile than oil or water Once gas cone reaches well, then can produce very high levels of gas Result cone does not easily move further down i.e. gas-liquid contact reaches equilibrium position Easy to calculate equilibrium FGLR (= (Gas expansion + injection) / (Liquid expansion + injection))

49 FGLR equation ( ) QL a FGLR FGLR. e FGLR FGLRinitial + equilibrium initial 1 = where Q L = cumulative liquid production a = gas breakthrough parameter, a measure of the speed of convergence to equilibrium.

50 NOR (North Oron FGLR profile) Rates (bbl or Mscf per day) Jan-05 Jan-06 Jan-07 Jan-08 Oil Rate Produced Gas Rate Water Rate

51 Thank you For more information visit:

Total 100 All learning outcomes must be evidenced; a 10% aggregate variance is allowed.

Total 100 All learning outcomes must be evidenced; a 10% aggregate variance is allowed. Prescription: 603 Business Finance Elective prescription Level 6 Credit 20 Version 3 Aim Prerequisites Recommended prior knowledge Students will apply financial management knowledge and skills to small

More information

Midterm Exam Suggested Solutions

Midterm Exam Suggested Solutions JEM034 Corporate Finance Winter Semester 2017/2018 Instructor: Olga Bychkova Date: 7/11/2017 Midterm Exam Suggested Solutions Problem 1. 4 points) Which of the following statements about the relationship

More information

IDENTIFYING AND QUANTIFYING RISKS AND UNCERTAINTIES IN DEVELOPING AN OFFSHORE OILFIELD UNDER VARYING OIL PRICE REGIMES

IDENTIFYING AND QUANTIFYING RISKS AND UNCERTAINTIES IN DEVELOPING AN OFFSHORE OILFIELD UNDER VARYING OIL PRICE REGIMES IDENTIFYING AND QUANTIFYING RISKS AND UNCERTAINTIES IN DEVELOPING AN OFFSHORE OILFIELD UNDER VARYING OIL PRICE REGIMES By Adeogun Oyebimpe, Wumi Iledare, Green Ovunda Emerald Energy Institute University

More information

Disclaimer: This resource package is for studying purposes only EDUCATION

Disclaimer: This resource package is for studying purposes only EDUCATION Disclaimer: This resource package is for studying purposes only EDUCATION Chapter 6: Valuing stocks Bond Cash Flows, Prices, and Yields - Maturity date: Final payment date - Term: Time remaining until

More information

Advanced Budgeting Workshop. Contents are subject to change. For the latest updates visit

Advanced Budgeting Workshop. Contents are subject to change. For the latest updates visit Advanced Budgeting Workshop Page 1 of 8 Why Attend 'Advanced Budgeting Workshop' is the second level course in budgeting after Meirc's 'Effective Budgeting and Cost ' course. It goes beyond the theory

More information

Real Options for Engineering Systems

Real Options for Engineering Systems Real Options for Engineering Systems Session 1: What s wrong with the Net Present Value criterion? Stefan Scholtes Judge Institute of Management, CU Slide 1 Main issues of the module! Project valuation:

More information

SUGGESTED SOLUTIONS. KE2 Management Accounting Information. March All Rights Reserved

SUGGESTED SOLUTIONS. KE2 Management Accounting Information. March All Rights Reserved SUGGESTED SOLUTIONS KE2 Management Accounting Information March 2017 All Rights Reserved Answer 01 SECTION 01 1.1 Relevant Learning outcome : 1.1.2 Explain the nature, scope and purpose of cost classifications

More information

MBA 203 Executive Summary

MBA 203 Executive Summary MBA 203 Executive Summary Professor Fedyk and Sraer Class 1. Present and Future Value Class 2. Putting Present Value to Work Class 3. Decision Rules Class 4. Capital Budgeting Class 6. Stock Valuation

More information

Index Models and APT

Index Models and APT Index Models and APT (Text reference: Chapter 8) Index models Parameter estimation Multifactor models Arbitrage Single factor APT Multifactor APT Index models predate CAPM, originally proposed as a simplification

More information

FNCE 4030 Fall 2012 Roberto Caccia, Ph.D. Midterm_2a (2-Nov-2012) Your name:

FNCE 4030 Fall 2012 Roberto Caccia, Ph.D. Midterm_2a (2-Nov-2012) Your name: Answer the questions in the space below. Written answers require no more than few compact sentences to show you understood and master the concept. Show your work to receive partial credit. Points are as

More information

POSITIONED FOR SUCCESS

POSITIONED FOR SUCCESS POSITIONED FOR SUCCESS CORPORATE PRESENTATION November 2018 TSX: BNE 1 Forward Looking Information Certain statements contained in this Presentation include statements which contain words such as anticipate,

More information

Lesson Plan for Simulation with Spreadsheets (8/31/11 & 9/7/11)

Lesson Plan for Simulation with Spreadsheets (8/31/11 & 9/7/11) Jeremy Tejada ISE 441 - Introduction to Simulation Learning Outcomes: Lesson Plan for Simulation with Spreadsheets (8/31/11 & 9/7/11) 1. Students will be able to list and define the different components

More information

Chapter 8: CAPM. 1. Single Index Model. 2. Adding a Riskless Asset. 3. The Capital Market Line 4. CAPM. 5. The One-Fund Theorem

Chapter 8: CAPM. 1. Single Index Model. 2. Adding a Riskless Asset. 3. The Capital Market Line 4. CAPM. 5. The One-Fund Theorem Chapter 8: CAPM 1. Single Index Model 2. Adding a Riskless Asset 3. The Capital Market Line 4. CAPM 5. The One-Fund Theorem 6. The Characteristic Line 7. The Pricing Model Single Index Model 1 1. Covariance

More information

Week 1 FINC $260,000 $106,680 $118,200 $89,400 $116,720. Capital Budgeting Analysis

Week 1 FINC $260,000 $106,680 $118,200 $89,400 $116,720. Capital Budgeting Analysis Dr. Ahmed FINC 5880 Week 1 Name Capital Budgeting Analysis Facts: Calculations Cost $200,000 Shipping $10,000 Installation $30,000 Depreciable cost $24,000 Inventories will rise by $25,000 Payables will

More information

Corporate Finance Finance Ch t ap er 1: I t nves t men D i ec sions Albert Banal-Estanol

Corporate Finance Finance Ch t ap er 1: I t nves t men D i ec sions Albert Banal-Estanol Corporate Finance Chapter : Investment tdecisions i Albert Banal-Estanol In this chapter Part (a): Compute projects cash flows : Computing earnings, and free cash flows Necessary inputs? Part (b): Evaluate

More information

Practical example of an Economic Scenario Generator

Practical example of an Economic Scenario Generator Practical example of an Economic Scenario Generator Martin Schenk Actuarial & Insurance Solutions SAV 7 March 2014 Agenda Introduction Deterministic vs. stochastic approach Mathematical model Application

More information

SPE Seminar: Introduction to E&P. Economics & Commercial. November 21 st, Lamé Verre Halliburton. All rights reserved.

SPE Seminar: Introduction to E&P. Economics & Commercial. November 21 st, Lamé Verre Halliburton. All rights reserved. SPE Seminar: Introduction to E&P Economics & Commercial November 21 st, 2017 Lamé Verre Halliburton Global Footprint Northern Region Eurasia TC TC TC TC Europe/ Sub-Saharan Africa Gulf of Mexico Area TC

More information

Writing Exponential Equations Day 2

Writing Exponential Equations Day 2 Writing Exponential Equations Day 2 MGSE9 12.A.CED.1 Create equations and inequalities in one variable and use them to solve problems. Include equations arising from linear, quadratic, simple rational,

More information

We have the building blocks to be a successful heavy oil company

We have the building blocks to be a successful heavy oil company F A L L 2 0 0 9 We have the building blocks to be a successful heavy oil company 1 TSX:PXX Introduction Corporate Summary Symbol: Exchanges: PXX, PXXS TSX, OMX Shares Outstanding (MM): Basic 261.7 Fully

More information

The Yield Envelope: Price Ranges for Fixed Income Products

The Yield Envelope: Price Ranges for Fixed Income Products The Yield Envelope: Price Ranges for Fixed Income Products by David Epstein (LINK:www.maths.ox.ac.uk/users/epstein) Mathematical Institute (LINK:www.maths.ox.ac.uk) Oxford Paul Wilmott (LINK:www.oxfordfinancial.co.uk/pw)

More information

Certificate in Advanced Budgeting and Forecasting

Certificate in Advanced Budgeting and Forecasting Certificate in Advanced Budgeting and Forecasting Page 1 of 9 Why Attend This course is the second level course in budgeting after Meirc's 'Effective Budgeting and Cost ' course. It goes beyond the theory

More information

CHAPTER 9: THE CAPITAL ASSET PRICING MODEL

CHAPTER 9: THE CAPITAL ASSET PRICING MODEL CHAPTER 9: THE CAPITAL ASSET PRICING MODEL 1. E(r P ) = r f + β P [E(r M ) r f ] 18 = 6 + β P(14 6) β P = 12/8 = 1.5 2. If the security s correlation coefficient with the market portfolio doubles (with

More information

Futures markets allow the possibility of forward pricing. Forward pricing or hedging allows decision makers pricing flexibility.

Futures markets allow the possibility of forward pricing. Forward pricing or hedging allows decision makers pricing flexibility. II) Forward Pricing and Risk Transfer Cash market participants are price takers. Futures markets allow the possibility of forward pricing. Forward pricing or hedging allows decision makers pricing flexibility.

More information

CHAPTER 9: THE CAPITAL ASSET PRICING MODEL

CHAPTER 9: THE CAPITAL ASSET PRICING MODEL CHAPTER 9: THE CAPITAL ASSET PRICING MODEL 1. E(r P ) = r f + β P [E(r M ) r f ] 18 = 6 + β P(14 6) β P = 12/8 = 1.5 2. If the security s correlation coefficient with the market portfolio doubles (with

More information

RATIONAL PRICING OF INTERNET COMPANIES

RATIONAL PRICING OF INTERNET COMPANIES RATIONAL PRICING OF INTERNET COMPANIES September 1999 Revised January 2000 Eduardo S. Schwartz Anderson School at UCLA Mark Moon Fuller & Thaler Asset Management ABSTRACT In this article, we apply real

More information

Characterization of the Optimum

Characterization of the Optimum ECO 317 Economics of Uncertainty Fall Term 2009 Notes for lectures 5. Portfolio Allocation with One Riskless, One Risky Asset Characterization of the Optimum Consider a risk-averse, expected-utility-maximizing

More information

Real Options. Katharina Lewellen Finance Theory II April 28, 2003

Real Options. Katharina Lewellen Finance Theory II April 28, 2003 Real Options Katharina Lewellen Finance Theory II April 28, 2003 Real options Managers have many options to adapt and revise decisions in response to unexpected developments. Such flexibility is clearly

More information

The Fixed Income Valuation Course. Sanjay K. Nawalkha Gloria M. Soto Natalia A. Beliaeva

The Fixed Income Valuation Course. Sanjay K. Nawalkha Gloria M. Soto Natalia A. Beliaeva Interest Rate Risk Modeling The Fixed Income Valuation Course Sanjay K. Nawalkha Gloria M. Soto Natalia A. Beliaeva Interest t Rate Risk Modeling : The Fixed Income Valuation Course. Sanjay K. Nawalkha,

More information

Partial Equilibrium Model: An Example. ARTNet Capacity Building Workshop for Trade Research Phnom Penh, Cambodia 2-6 June 2008

Partial Equilibrium Model: An Example. ARTNet Capacity Building Workshop for Trade Research Phnom Penh, Cambodia 2-6 June 2008 Partial Equilibrium Model: An Example ARTNet Capacity Building Workshop for Trade Research Phnom Penh, Cambodia 2-6 June 2008 Outline Graphical Analysis Mathematical formulation Equations Parameters Endogenous

More information

u (x) < 0. and if you believe in diminishing return of the wealth, then you would require

u (x) < 0. and if you believe in diminishing return of the wealth, then you would require Chapter 8 Markowitz Portfolio Theory 8.7 Investor Utility Functions People are always asked the question: would more money make you happier? The answer is usually yes. The next question is how much more

More information

ISAPP field development optimization challenge

ISAPP field development optimization challenge ISAPP (Integrated Systems Approach to Petroleum Production) is a joint project of TNO, Delft University of Technology, ENI, Statoil and Petrobras. Document title: Well Control Optimization Exercise Version

More information

Demand Characteristics for Imported Cod Products in Portugal: An Application of PCAIDS and Demand Growth Index Modelling

Demand Characteristics for Imported Cod Products in Portugal: An Application of PCAIDS and Demand Growth Index Modelling Demand Characteristics for Imported Cod Products in Portugal: An Application of PCAIDS and Demand Growth Index Modelling Frank Asche & Daniel V. Gordon University of Stavanger University of Florida University

More information

Random Variables and Probability Distributions

Random Variables and Probability Distributions Chapter 3 Random Variables and Probability Distributions Chapter Three Random Variables and Probability Distributions 3. Introduction An event is defined as the possible outcome of an experiment. In engineering

More information

Principles of Finance

Principles of Finance Principles of Finance Grzegorz Trojanowski Lecture 7: Arbitrage Pricing Theory Principles of Finance - Lecture 7 1 Lecture 7 material Required reading: Elton et al., Chapter 16 Supplementary reading: Luenberger,

More information

Dynamic Replication of Non-Maturing Assets and Liabilities

Dynamic Replication of Non-Maturing Assets and Liabilities Dynamic Replication of Non-Maturing Assets and Liabilities Michael Schürle Institute for Operations Research and Computational Finance, University of St. Gallen, Bodanstr. 6, CH-9000 St. Gallen, Switzerland

More information

Gas storage: overview and static valuation

Gas storage: overview and static valuation In this first article of the new gas storage segment of the Masterclass series, John Breslin, Les Clewlow, Tobias Elbert, Calvin Kwok and Chris Strickland provide an illustration of how the four most common

More information

Back to basis Evolving technical matters

Back to basis Evolving technical matters Back to basis Evolving technical matters Savings and retirement products with guarantees: how to get a better return with lower risks? Prepared by Clement Bonnet Consulting Actuary Clement Bonnet Consulting

More information

Use of EVM Trends to Forecast Cost Risks 2011 ISPA/SCEA Conference, Albuquerque, NM

Use of EVM Trends to Forecast Cost Risks 2011 ISPA/SCEA Conference, Albuquerque, NM Use of EVM Trends to Forecast Cost Risks 2011 ISPA/SCEA Conference, Albuquerque, NM presented by: (C)2011 MCR, LLC Dr. Roy Smoker MCR LLC rsmoker@mcri.com (C)2011 MCR, LLC 2 OVERVIEW Introduction EVM Trend

More information

One note for Session Two

One note for Session Two ESD.70J Engineering Economy Module Fall 2004 Session Three Link for PPT: http://web.mit.edu/tao/www/esd70/s3/p.ppt ESD.70J Engineering Economy Module - Session 3 1 One note for Session Two If you Excel

More information

ELEMENTS OF MONTE CARLO SIMULATION

ELEMENTS OF MONTE CARLO SIMULATION APPENDIX B ELEMENTS OF MONTE CARLO SIMULATION B. GENERAL CONCEPT The basic idea of Monte Carlo simulation is to create a series of experimental samples using a random number sequence. According to the

More information

CA. Sonali Jagath Prasad ACA, ACMA, CGMA, B.Com.

CA. Sonali Jagath Prasad ACA, ACMA, CGMA, B.Com. MANAGEMENT OF FINANCIAL RESOURCES AND PERFORMANCE SESSIONS 3& 4 INVESTMENT APPRAISAL METHODS June 10 to 24, 2013 CA. Sonali Jagath Prasad ACA, ACMA, CGMA, B.Com. WESTFORD 2008 Thomson SCHOOL South-Western

More information

PROBABLISTIC EVALUATION OF ONSHORE MARGINALOIL FIELDS DEVELOPMENT IN NIGERIA

PROBABLISTIC EVALUATION OF ONSHORE MARGINALOIL FIELDS DEVELOPMENT IN NIGERIA PROBABLISTIC EVALUATION OF ONSHORE MARGINALOIL FIELDS DEVELOPMENT IN NIGERIA Oruwari Humphrey 1, AdewaleDosunmu 2 and Dagogo Opiribo 3 1Institute Innovation, Technology and Engineering Management, University

More information

The Impact of Basel Accords on the Lender's Profitability under Different Pricing Decisions

The Impact of Basel Accords on the Lender's Profitability under Different Pricing Decisions The Impact of Basel Accords on the Lender's Profitability under Different Pricing Decisions Bo Huang and Lyn C. Thomas School of Management, University of Southampton, Highfield, Southampton, UK, SO17

More information

Chapter 13 Return, Risk, and Security Market Line

Chapter 13 Return, Risk, and Security Market Line 1 Chapter 13 Return, Risk, and Security Market Line Konan Chan Financial Management, Spring 2018 Topics Covered Expected Return and Variance Portfolio Risk and Return Risk & Diversification Systematic

More information

Making Decisions Using Uncertain Forecasts. Environmental Modelling in Industry Study Group, Cambridge March 2017

Making Decisions Using Uncertain Forecasts. Environmental Modelling in Industry Study Group, Cambridge March 2017 Making Decisions Using Uncertain Forecasts Environment Agency Environmental Modelling in Industry Study Group, Cambridge March 2017 Green M., Kabir S., Peters, J., Georgieva, L., Zyskin, M., and Beckerleg,

More information

Dependence Modeling and Credit Risk

Dependence Modeling and Credit Risk Dependence Modeling and Credit Risk Paola Mosconi Banca IMI Bocconi University, 20/04/2015 Paola Mosconi Lecture 6 1 / 53 Disclaimer The opinion expressed here are solely those of the author and do not

More information

Continuing Success in Heavy Oil

Continuing Success in Heavy Oil Continuing Success in Heavy Oil Corporate Presentation March 2018 Advisory FORWARD-LOOKING STATEMENTS: This presentation contains certain forward-looking statements and forward-looking information (collectively

More information

Writing Exponential Equations Day 2

Writing Exponential Equations Day 2 Writing Exponential Equations Day 2 MGSE9 12.A.CED.1 Create equations and inequalities in one variable and use them to solve problems. Include equations arising from linear, quadratic, simple rational,

More information

15.414: COURSE REVIEW. Main Ideas of the Course. Approach: Discounted Cashflows (i.e. PV, NPV): CF 1 CF 2 P V = (1 + r 1 ) (1 + r 2 ) 2

15.414: COURSE REVIEW. Main Ideas of the Course. Approach: Discounted Cashflows (i.e. PV, NPV): CF 1 CF 2 P V = (1 + r 1 ) (1 + r 2 ) 2 15.414: COURSE REVIEW JIRO E. KONDO Valuation: Main Ideas of the Course. Approach: Discounted Cashflows (i.e. PV, NPV): and CF 1 CF 2 P V = + +... (1 + r 1 ) (1 + r 2 ) 2 CF 1 CF 2 NP V = CF 0 + + +...

More information

Using a Market Value Concept to Facilitate Negotiation of Alternative Price Formulas. 6 December 2006 Kaoru Kawamoto Osaka Gas Co.

Using a Market Value Concept to Facilitate Negotiation of Alternative Price Formulas. 6 December 2006 Kaoru Kawamoto Osaka Gas Co. Using a Market Value Concept to Facilitate Negotiation of Alternative Price Formulas 6 December 2006 Kaoru Kawamoto Osaka Gas Co., Ltd Table of Contents 1. Background 2. Definition and Methodology Defining

More information

Uncertainty related to ownership allocation

Uncertainty related to ownership allocation Uncertainty related to ownership allocation By Astrid Marie Skålvik 2014-06-06 Content Introduction Field allocation uncertainty Ownership allocation uncertainty Risk related to ownership allocation Comparison

More information

Chapter 6 Analyzing Accumulated Change: Integrals in Action

Chapter 6 Analyzing Accumulated Change: Integrals in Action Chapter 6 Analyzing Accumulated Change: Integrals in Action 6. Streams in Business and Biology You will find Excel very helpful when dealing with streams that are accumulated over finite intervals. Finding

More information

Actuarial Society of India

Actuarial Society of India Actuarial Society of India EXAMINATIONS June 005 CT1 Financial Mathematics Indicative Solution Question 1 a. Rate of interest over and above the rate of inflation is called real rate of interest. b. Real

More information

WITH SKETCH ANSWERS. Postgraduate Certificate in Finance Postgraduate Certificate in Economics and Finance

WITH SKETCH ANSWERS. Postgraduate Certificate in Finance Postgraduate Certificate in Economics and Finance WITH SKETCH ANSWERS BIRKBECK COLLEGE (University of London) BIRKBECK COLLEGE (University of London) Postgraduate Certificate in Finance Postgraduate Certificate in Economics and Finance SCHOOL OF ECONOMICS,

More information

Introduction to the Toolkit Financial Models

Introduction to the Toolkit Financial Models World Bank & Brazilian Ministry of Transport Workshop on the Toolkit for PPP in Roads and Highways Introduction to the Toolkit Financial Models Cesar Queiroz World Bank Brasilia, Brazil, June 8-9, 2010

More information

STUDY HINTS FOR THE LEVEL I CFA EXAM

STUDY HINTS FOR THE LEVEL I CFA EXAM STUDY HINTS FOR THE LEVEL I CFA EXAM The Level I CFA exam is a multiple choice test consisting of 240 multiple choice questions, half of which will be given in the morning session and half of which will

More information

Modelling the Zero Coupon Yield Curve:

Modelling the Zero Coupon Yield Curve: Modelling the Zero Coupon Yield Curve: A regression based approach February,2010 12 th Global Conference of Actuaries Srijan Sengupta Section 1: Introduction What is the zero coupon yield curve? Its importance

More information

High Dimensional Bayesian Optimisation and Bandits via Additive Models

High Dimensional Bayesian Optimisation and Bandits via Additive Models 1/20 High Dimensional Bayesian Optimisation and Bandits via Additive Models Kirthevasan Kandasamy, Jeff Schneider, Barnabás Póczos ICML 15 July 8 2015 2/20 Bandits & Optimisation Maximum Likelihood inference

More information

planease Financial Utilities

planease Financial Utilities planease Financial Utilities Provides loan amortization, discounted cash flow analysis, depreciation, and 1031 exchange recap reports. planease (obviously) amortizes loans to analyze an investment, but

More information

ESTABLISHING A CASH FLOW MODEL

ESTABLISHING A CASH FLOW MODEL Government Finance Officers Association of Texas Fall Conference 2017 ESTABLISHING A CASH FLOW MODEL EMILY A. UPSHAW, CPA VALLEY VIEW CONSULTING, LLC Objectives: Understand the importance of developing

More information

1. What is Implied Volatility?

1. What is Implied Volatility? Numerical Methods FEQA MSc Lectures, Spring Term 2 Data Modelling Module Lecture 2 Implied Volatility Professor Carol Alexander Spring Term 2 1 1. What is Implied Volatility? Implied volatility is: the

More information

Certificate in Advanced Budgeting and Forecasting

Certificate in Advanced Budgeting and Forecasting Certificate in Advanced Budgeting and Forecasting Page 1 of 12 Why Attend This course is the second level course in budgeting after Meirc's 'Effective Budgeting and Cost Control' course. It goes beyond

More information

Short & Long Run impact of volatility on the effect monetary shocks

Short & Long Run impact of volatility on the effect monetary shocks Short & Long Run impact of volatility on the effect monetary shocks Fernando Alvarez University of Chicago & NBER Inflation: Drivers & Dynamics Conference 218 Cleveland Fed Alvarez Volatility & Monetary

More information

When we model expected returns, we implicitly model expected prices

When we model expected returns, we implicitly model expected prices Week 1: Risk and Return Securities: why do we buy them? To take advantage of future cash flows (in the form of dividends or selling a security for a higher price). How much should we pay for this, considering

More information

80 Solved MCQs of MGT201 Financial Management By

80 Solved MCQs of MGT201 Financial Management By 80 Solved MCQs of MGT201 Financial Management By http://vustudents.ning.com Question No: 1 ( Marks: 1 ) - Please choose one What is the long-run objective of financial management? Maximize earnings per

More information

Gulf Keystone Petroleum

Gulf Keystone Petroleum Gulf Keystone Petroleum 13 July 2018 Annual General Meeting Amsterdam Disclaimer This proprietary presentation (the Presentation ) has been prepared by Gulf Keystone Petroleum Limited (the Company ). Under

More information

Midterm Review. P resent value = P V =

Midterm Review. P resent value = P V = JEM034 Corporate Finance Winter Semester 2017/2018 Instructor: Olga Bychkova Midterm Review F uture value of $100 = $100 (1 + r) t Suppose that you will receive a cash flow of C t dollars at the end of

More information

Riccardo Rebonato Global Head of Quantitative Research, FM, RBS Global Head of Market Risk, CBFM, RBS

Riccardo Rebonato Global Head of Quantitative Research, FM, RBS Global Head of Market Risk, CBFM, RBS Why Neither Time Homogeneity nor Time Dependence Will Do: Evidence from the US$ Swaption Market Cambridge, May 2005 Riccardo Rebonato Global Head of Quantitative Research, FM, RBS Global Head of Market

More information

BFC2140: Corporate Finance 1

BFC2140: Corporate Finance 1 BFC2140: Corporate Finance 1 Table of Contents Topic 1: Introduction to Financial Mathematics... 2 Topic 2: Financial Mathematics II... 5 Topic 3: Valuation of Bonds & Equities... 9 Topic 4: Project Evaluation

More information

BONTERRA ENERGY CORP. AGM EFFICIENT SUSTAINABLE DISCIPLINED

BONTERRA ENERGY CORP. AGM EFFICIENT SUSTAINABLE DISCIPLINED BONTERRA ENERGY CORP. AGM EFFICIENT SUSTAINABLE DISCIPLINED FORWARD LOOKING INFORMATION Certain statements contained in this Presentation include statements which contain words such as anticipate, could,

More information

Note on Cost of Capital

Note on Cost of Capital DUKE UNIVERSITY, FUQUA SCHOOL OF BUSINESS ACCOUNTG 512F: FUNDAMENTALS OF FINANCIAL ANALYSIS Note on Cost of Capital For the course, you should concentrate on the CAPM and the weighted average cost of capital.

More information

AFM 271 Practice Problem Set #2 Spring 2005 Suggested Solutions

AFM 271 Practice Problem Set #2 Spring 2005 Suggested Solutions AFM 271 Practice Problem Set #2 Spring 2005 Suggested Solutions 1. Text Problems: 6.2 (a) Consider the following table: time cash flow cumulative cash flow 0 -$1,000,000 -$1,000,000 1 $150,000 -$850,000

More information

OR-Notes. J E Beasley

OR-Notes. J E Beasley 1 of 17 15-05-2013 23:46 OR-Notes J E Beasley OR-Notes are a series of introductory notes on topics that fall under the broad heading of the field of operations research (OR). They were originally used

More information

SDMR Finance (2) Olivier Brandouy. University of Paris 1, Panthéon-Sorbonne, IAE (Sorbonne Graduate Business School)

SDMR Finance (2) Olivier Brandouy. University of Paris 1, Panthéon-Sorbonne, IAE (Sorbonne Graduate Business School) SDMR Finance (2) Olivier Brandouy University of Paris 1, Panthéon-Sorbonne, IAE (Sorbonne Graduate Business School) Outline 1 Formal Approach to QAM : concepts and notations 2 3 Portfolio risk and return

More information

Introduction to Financial Mathematics

Introduction to Financial Mathematics Department of Mathematics University of Michigan November 7, 2008 My Information E-mail address: marymorj (at) umich.edu Financial work experience includes 2 years in public finance investment banking

More information

PROBLEM SET 7 ANSWERS: Answers to Exercises in Jean Tirole s Theory of Industrial Organization

PROBLEM SET 7 ANSWERS: Answers to Exercises in Jean Tirole s Theory of Industrial Organization PROBLEM SET 7 ANSWERS: Answers to Exercises in Jean Tirole s Theory of Industrial Organization 12 December 2006. 0.1 (p. 26), 0.2 (p. 41), 1.2 (p. 67) and 1.3 (p.68) 0.1** (p. 26) In the text, it is assumed

More information

Appendix to: AMoreElaborateModel

Appendix to: AMoreElaborateModel Appendix to: Why Do Demand Curves for Stocks Slope Down? AMoreElaborateModel Antti Petajisto Yale School of Management February 2004 1 A More Elaborate Model 1.1 Motivation Our earlier model provides a

More information

International Financial Markets 1. How Capital Markets Work

International Financial Markets 1. How Capital Markets Work International Financial Markets Lecture Notes: E-Mail: Colloquium: www.rainer-maurer.de rainer.maurer@hs-pforzheim.de Friday 15.30-17.00 (room W4.1.03) -1-1.1. Supply and Demand on Capital Markets 1.1.1.

More information

Why net present value leads to better investment decisions than other criteria

Why net present value leads to better investment decisions than other criteria Why net present value leads to better investment decisions than other criteria Introduction: When deciding, wether or not it is worth making an investment, or leaving the capital in the bank, there are

More information

Numerical Model for Financial Simulation of Highway PPP Projects User guide

Numerical Model for Financial Simulation of Highway PPP Projects User guide Numerical Model for Financial Simulation of Highway PPP Projects User guide Main characteristics of the Numerical Financial Model General This financial tool is based on the following main criteria: Sources

More information

Statistical Tables Compiled by Alan J. Terry

Statistical Tables Compiled by Alan J. Terry Statistical Tables Compiled by Alan J. Terry School of Science and Sport University of the West of Scotland Paisley, Scotland Contents Table 1: Cumulative binomial probabilities Page 1 Table 2: Cumulative

More information

IB132 - Fundations of Finance Notes

IB132 - Fundations of Finance Notes IB132 - Fundations of Finance Notes Marco Del Vecchio Last revised on May 31, 2016 Based on the offical lecture notes. M.Del-Vecchio@Warwick.ac.uk 1 Contents 1 Prelude 1 2 Present Value 1 2.1 Rate of Return.......................................

More information

The Complete Course On Budgeting: Planning, Forecasting, What If Analysis And Reporting

The Complete Course On Budgeting: Planning, Forecasting, What If Analysis And Reporting The Complete Course On Budgeting: Planning, Forecasting, What If Analysis And Reporting SECTOR / ACCOUNTING AND FINANCE NON-TECHNICAL & CERTIFIED TRAINING COURSE The use of Excel as the toolbox of choice

More information

Week #7 - Maxima and Minima, Concavity, Applications Section 4.4

Week #7 - Maxima and Minima, Concavity, Applications Section 4.4 Week #7 - Maxima and Minima, Concavity, Applications Section 4.4 From Calculus, Single Variable by Hughes-Hallett, Gleason, McCallum et. al. Copyright 2005 by John Wiley & Sons, Inc. This material is used

More information

STUDY HINTS FOR THE LEVEL I CFA EXAM

STUDY HINTS FOR THE LEVEL I CFA EXAM STUDY HINTS FOR THE LEVEL I CFA EXAM The Level I CFA exam is a multiple choice test consisting of 240 multiple choice questions, half of which will be given in the morning session and half of which will

More information

Evolution Petroleum Corporation Corporate Presentation August 2017 Corporate Presentation August 2017

Evolution Petroleum Corporation Corporate Presentation August 2017 Corporate Presentation August 2017 Evolution Petroleum Corporation Corporate Presentation August 2017 Corporate Presentation August 2017 1 Forward Looking Statements This presentation contains forward-looking statements. Such statements

More information

Growth Opportunities, Investment-Specific Technology Shocks and the Cross-Section of Stock Returns

Growth Opportunities, Investment-Specific Technology Shocks and the Cross-Section of Stock Returns Growth Opportunities, Investment-Specific Technology Shocks and the Cross-Section of Stock Returns Leonid Kogan 1 Dimitris Papanikolaou 2 1 MIT and NBER 2 Northwestern University Boston, June 5, 2009 Kogan,

More information

Exam #2 Review Questions (Answers) ECNS 303 October 31, 2011

Exam #2 Review Questions (Answers) ECNS 303 October 31, 2011 Exam #2 Review Questions (Answers) ECNS 303 October 31, 2011 1.) For Ch. 9 and 10: Review your Ch. 9 and 10 notes, Quiz #6, and any practice problems that were assigned for Ch. 10. 2.) Exogenous vs. Endogenous

More information

Effective Budgeting and Cost Control. Contents are subject to change. For the latest updates visit

Effective Budgeting and Cost Control. Contents are subject to change. For the latest updates visit Effective Budgeting and Cost Page 1 of 9 Why Attend ning and budgeting are must-have skills for all professionals regardless of their function or managerial level. This course covers the concept of budgeting

More information

Eco504 Spring 2010 C. Sims MID-TERM EXAM. (1) (45 minutes) Consider a model in which a representative agent has the objective. B t 1.

Eco504 Spring 2010 C. Sims MID-TERM EXAM. (1) (45 minutes) Consider a model in which a representative agent has the objective. B t 1. Eco504 Spring 2010 C. Sims MID-TERM EXAM (1) (45 minutes) Consider a model in which a representative agent has the objective function max C,K,B t=0 β t C1 γ t 1 γ and faces the constraints at each period

More information

Real Time Price Forward Curve & Valuation. Munich, September 2016

Real Time Price Forward Curve & Valuation. Munich, September 2016 Real Time Price Forward Curve & Valuation Munich, September 2016 Arbitrage free live Prices and live Price-Forward-Curve 2 live Broker-Screen Bid Ask Apr 13 26,2 26,25 May-13 26,03 26,18 Jun 13 Jul 13

More information

Copyright 2009 Pearson Education Canada

Copyright 2009 Pearson Education Canada Operating Cash Flows: Sales $682,500 $771,750 $868,219 $972,405 $957,211 less expenses $477,750 $540,225 $607,753 $680,684 $670,048 Difference $204,750 $231,525 $260,466 $291,722 $287,163 After-tax (1

More information

Chapter 6: Supply and Demand with Income in the Form of Endowments

Chapter 6: Supply and Demand with Income in the Form of Endowments Chapter 6: Supply and Demand with Income in the Form of Endowments 6.1: Introduction This chapter and the next contain almost identical analyses concerning the supply and demand implied by different kinds

More information

Harnessing Uncertainty for Orebody Modelling and Strategic Mine Planning

Harnessing Uncertainty for Orebody Modelling and Strategic Mine Planning Harnessing Uncertainty for Orebody Modelling and Strategic Mine Planning Roussos Dimitrakopoulos Canada Research Chair in Sustainable Mineral Resource Development and Optimization under Uncertainty Department

More information

Simple Dynamic model for pricing and hedging of heterogeneous CDOs. Andrei Lopatin

Simple Dynamic model for pricing and hedging of heterogeneous CDOs. Andrei Lopatin Simple Dynamic model for pricing and hedging of heterogeneous CDOs Andrei Lopatin Outline Top down (aggregate loss) vs. bottom up models. Local Intensity (LI) Model. Calibration of the LI model to the

More information

A Comparative Study of Various Forecasting Techniques in Predicting. BSE S&P Sensex

A Comparative Study of Various Forecasting Techniques in Predicting. BSE S&P Sensex NavaJyoti, International Journal of Multi-Disciplinary Research Volume 1, Issue 1, August 2016 A Comparative Study of Various Forecasting Techniques in Predicting BSE S&P Sensex Dr. Jahnavi M 1 Assistant

More information

MLEMVD: A R Package for Maximum Likelihood Estimation of Multivariate Diffusion Models

MLEMVD: A R Package for Maximum Likelihood Estimation of Multivariate Diffusion Models MLEMVD: A R Package for Maximum Likelihood Estimation of Multivariate Diffusion Models Matthew Dixon and Tao Wu 1 Illinois Institute of Technology May 19th 2017 1 https://papers.ssrn.com/sol3/papers.cfm?abstract

More information

What About p-charts?

What About p-charts? When should we use the specialty charts count data? All charts count-based data are charts individual values. Regardless of whether we are working with a count or a rate, we obtain one value per time period

More information

Integration & Aggregation in Risk Management: An Insurance Perspective

Integration & Aggregation in Risk Management: An Insurance Perspective Integration & Aggregation in Risk Management: An Insurance Perspective Stephen Mildenhall Aon Re Services May 2, 2005 Overview Similarities and Differences Between Risks What is Risk? Source-Based vs.

More information

CA - FINAL 1.1 Capital Budgeting LOS No. 1: Introduction Capital Budgeting is the process of Identifying & Evaluating capital projects i.e. projects where the cash flows to the firm will be received

More information