SlideShare a Scribd company logo
1 of 2
Sensitivity Analysis: Definition, Uses & Importance
What is SensitivityAnalysis?
Financial riskmodelingtakessensitivityanalysistothe nextlevelandhelpsinassessing the probability
and potential impactof unfavorable outcomes.Basedonthe assessments,variousdecisionswith
respectto managing,hedgingortransferringrisksare taken.
Sensitivityanalysisisone of the toolsthathelpdecisionmakerswithmore thana solutiontoa problem.
It providesanappropriate insightintothe problemsassociatedwiththe model underreference. Finally,
the decisionmakergetsadecentideaabouthow sensitive the optimumsolutionis chosenbyhimtoany
changesinthe inputvaluesof one ormore parameters.
Have you everbeencaughtina situationregardingdatasensitivityanalysisinFinancial Modeling?If you
have faceda problembefore,findyouranswerrighthere!
Measurementofsensitivityanalysis
Beloware mentionedthe stepsusedtoconductsensitivityanalysis:
 Firstly, the base case outputisdefined;saythe NPV ata base case inputvalue (V1) forwhichthe
sensitivityistobe measured.All the otherinputsof the model are keptconstant.
 Thenthe value of the output at a new value of the input(V2) while keepingotherinputs
constantis calculated.
 Findthe percentage change inthe outputandthe percentage change inthe input.
 The sensitivityiscalculatedbydividingthe percentage change inoutputbythe percentage
change in input.
Thisprocessof testingsensitivityforanotherinput(saycashflowsgrowthrate) whilekeepingthe restof
inputsconstantisrepeatedtill the sensitivityfigure foreachof the inputsisobtained.The conclusion
wouldbe that the higherthe sensitivityfigure,the more sensitivethe outputistoanychange inthat
inputandvice versa.
For SensitivityAnalysisfollowthe followingsteps
FirstLINKthe outputyouwant to checksensitivityof?(IN FMCGcase linkthe share Price orEV)
Nextdecide the variableyouwanttocheck the sensitivityof (e.g. WACC;TerminalGrowthrate;tax rate
etc.)
Let’ssay we selectedWACCand Terminal Growthwhichoriginallynthe model is10.7% and 5%. Now
take the range for twovariable whichwill be 8.7;9.7; 10.7;11.7 and 12.7% for WACC and let’ssay3; 4; 5;
6; 7% for T. Growth.place these numbersonthe cell nexttoyourlinkedcell instepone above. So, if you
have linkedEV inthe cell G30 Wickwill come inthe cell fromH30 - L30 and T Growth will come incell
G31 to G35
Nowselectthe cell fromG30 to L35 and go to data tab - "What if Analysis" - "Datatable"
Nowinthe windowwhichpopsupinthe "row input"selectthe cell where youhave originallycalculated
your WACCand inColumn selectcell where youhave originallycalculatedTGrowthRate andpress
enter
Usesof SensitivityAnalysis
 The keyapplicationof sensitivityanalysisistoindicate the sensitivityof simulationto
uncertaintiesinthe inputvaluesof the model.
 Theyhelpindecisionmaking
 Sensitivityanalysisisamethodforpredictingthe outcome of adecisionif asituationturnsout
to be differentcomparedtothe keypredictions.
 It helpsinassessingthe riskinessof astrategy.
 Helpsinidentifyinghowdependentthe outputisona inputvalue.Analysesif the dependencyin
turn helpsinassessingthe riskassociated.
 Helpsintakinginformedandappropriate decisions
 Aidssearchingforerrorsin the model
Conclusion
Sensitivityanalysisisone of the toolsthathelpdecisionmakerswithmore thana solutiontoa problem.
It providesanappropriate insightintothe problemsassociatedwiththe model underreference. Finally,
the decisionmakergetsadecentideaabouthow sensitive the optimumsolutionis chosenbyhimtoany
changesinthe inputvaluesof one ormore parameters.
To know in-depthaboutSensitivityanalysis,readhere: https://www.edupristine.com/blog/all-about-
sensitivity-analysis

More Related Content

What's hot

Factor analysis using spss 2005
Factor analysis using spss 2005Factor analysis using spss 2005
Factor analysis using spss 2005jamescupello
 
Confirmatory Factor Analysis Presented by Mahfoudh Mgammal
Confirmatory Factor Analysis Presented by Mahfoudh MgammalConfirmatory Factor Analysis Presented by Mahfoudh Mgammal
Confirmatory Factor Analysis Presented by Mahfoudh MgammalDr. Mahfoudh Hussein Mgammal
 
Optimization techniques
Optimization  techniquesOptimization  techniques
Optimization techniquesbiniyapatel
 
Comparison statisticalsignificancetestir
Comparison statisticalsignificancetestirComparison statisticalsignificancetestir
Comparison statisticalsignificancetestirClaudia Ribeiro
 
Multivariate analyses
Multivariate analysesMultivariate analyses
Multivariate analysesNaveen Deswal
 
Numerical analysis genetic algorithms
Numerical analysis  genetic algorithmsNumerical analysis  genetic algorithms
Numerical analysis genetic algorithmsSHAMJITH KM
 
Optimization through statistical response surface methods
Optimization through statistical response surface methodsOptimization through statistical response surface methods
Optimization through statistical response surface methodsChristy George
 
An overview of fixed effects assumptions for meta analysis - Pubrica
An overview of fixed effects assumptions for meta analysis - PubricaAn overview of fixed effects assumptions for meta analysis - Pubrica
An overview of fixed effects assumptions for meta analysis - PubricaPubrica
 
Mba2216 week 11 data analysis part 02
Mba2216 week 11 data analysis part 02Mba2216 week 11 data analysis part 02
Mba2216 week 11 data analysis part 02Stephen Ong
 
Specification based or black box techniques 3
Specification based or black box techniques 3Specification based or black box techniques 3
Specification based or black box techniques 3Bima Alvamiko
 

What's hot (20)

Feature selection
Feature selectionFeature selection
Feature selection
 
Factor analysis using spss 2005
Factor analysis using spss 2005Factor analysis using spss 2005
Factor analysis using spss 2005
 
Comparison and evaluation of alternative designs
Comparison and evaluation of alternative designsComparison and evaluation of alternative designs
Comparison and evaluation of alternative designs
 
Confirmatory Factor Analysis Presented by Mahfoudh Mgammal
Confirmatory Factor Analysis Presented by Mahfoudh MgammalConfirmatory Factor Analysis Presented by Mahfoudh Mgammal
Confirmatory Factor Analysis Presented by Mahfoudh Mgammal
 
Optimization techniques
Optimization  techniquesOptimization  techniques
Optimization techniques
 
Comparison statisticalsignificancetestir
Comparison statisticalsignificancetestirComparison statisticalsignificancetestir
Comparison statisticalsignificancetestir
 
Optimization techniques
Optimization techniquesOptimization techniques
Optimization techniques
 
Input modeling
Input modelingInput modeling
Input modeling
 
Multivariate analyses
Multivariate analysesMultivariate analyses
Multivariate analyses
 
Numerical analysis genetic algorithms
Numerical analysis  genetic algorithmsNumerical analysis  genetic algorithms
Numerical analysis genetic algorithms
 
Optimization through statistical response surface methods
Optimization through statistical response surface methodsOptimization through statistical response surface methods
Optimization through statistical response surface methods
 
An overview of fixed effects assumptions for meta analysis - Pubrica
An overview of fixed effects assumptions for meta analysis - PubricaAn overview of fixed effects assumptions for meta analysis - Pubrica
An overview of fixed effects assumptions for meta analysis - Pubrica
 
Factor analysis
Factor analysisFactor analysis
Factor analysis
 
Measurment and scaling
Measurment and scalingMeasurment and scaling
Measurment and scaling
 
simulation modelling
simulation modellingsimulation modelling
simulation modelling
 
Optimization techniques
Optimization techniquesOptimization techniques
Optimization techniques
 
Mba2216 week 11 data analysis part 02
Mba2216 week 11 data analysis part 02Mba2216 week 11 data analysis part 02
Mba2216 week 11 data analysis part 02
 
Propensity Score Matching Methods
Propensity Score Matching MethodsPropensity Score Matching Methods
Propensity Score Matching Methods
 
Factor analysis (1)
Factor analysis (1)Factor analysis (1)
Factor analysis (1)
 
Specification based or black box techniques 3
Specification based or black box techniques 3Specification based or black box techniques 3
Specification based or black box techniques 3
 

Similar to All you want to know about sensitivity analysis

Biostatics 8.pptx
Biostatics 8.pptxBiostatics 8.pptx
Biostatics 8.pptxEyobAlemu11
 
SAMPLING MEAN DEFINITION The term sampling mean .docx
SAMPLING MEAN DEFINITION The term sampling mean .docxSAMPLING MEAN DEFINITION The term sampling mean .docx
SAMPLING MEAN DEFINITION The term sampling mean .docxanhlodge
 
Sampling methods theory and practice
Sampling methods theory and practice Sampling methods theory and practice
Sampling methods theory and practice Ravindra Sharma
 
Steps of hypothesis testingSelect the appropriate testSo far.docx
Steps of hypothesis testingSelect the appropriate testSo far.docxSteps of hypothesis testingSelect the appropriate testSo far.docx
Steps of hypothesis testingSelect the appropriate testSo far.docxdessiechisomjj4
 
Confusion matrix and classification evaluation metrics
Confusion matrix and classification evaluation metricsConfusion matrix and classification evaluation metrics
Confusion matrix and classification evaluation metricsMinesh A. Jethva
 
A General Manger of Harley-Davidson has to decide on the size of a.docx
A General Manger of Harley-Davidson has to decide on the size of a.docxA General Manger of Harley-Davidson has to decide on the size of a.docx
A General Manger of Harley-Davidson has to decide on the size of a.docxevonnehoggarth79783
 
Workbook Project
Workbook ProjectWorkbook Project
Workbook ProjectBrian Ryan
 
Estimation in statistics
Estimation in statisticsEstimation in statistics
Estimation in statisticsRabea Jamal
 
What Is a Model, Anyhow?
What Is a Model, Anyhow?What Is a Model, Anyhow?
What Is a Model, Anyhow?Bill Cassill
 
Answer the questions in one paragraph 4-5 sentences. · Why did t.docx
Answer the questions in one paragraph 4-5 sentences. · Why did t.docxAnswer the questions in one paragraph 4-5 sentences. · Why did t.docx
Answer the questions in one paragraph 4-5 sentences. · Why did t.docxboyfieldhouse
 
MLlectureMethod.ppt
MLlectureMethod.pptMLlectureMethod.ppt
MLlectureMethod.pptbutest
 
MLlectureMethod.ppt
MLlectureMethod.pptMLlectureMethod.ppt
MLlectureMethod.pptbutest
 
Sample Size And Gpower Module
Sample Size And Gpower ModuleSample Size And Gpower Module
Sample Size And Gpower Modulellalablink
 
sample_size_Determination .pdf
sample_size_Determination .pdfsample_size_Determination .pdf
sample_size_Determination .pdfstatsanjal
 
analysis part 02.pptx
analysis part 02.pptxanalysis part 02.pptx
analysis part 02.pptxefrembeyene4
 
Histograms and Descriptive Statistics Scoring GuideCRITERIANON.docx
Histograms and Descriptive Statistics Scoring GuideCRITERIANON.docxHistograms and Descriptive Statistics Scoring GuideCRITERIANON.docx
Histograms and Descriptive Statistics Scoring GuideCRITERIANON.docxpooleavelina
 

Similar to All you want to know about sensitivity analysis (20)

Biostatics 8.pptx
Biostatics 8.pptxBiostatics 8.pptx
Biostatics 8.pptx
 
SAMPLING MEAN DEFINITION The term sampling mean .docx
SAMPLING MEAN DEFINITION The term sampling mean .docxSAMPLING MEAN DEFINITION The term sampling mean .docx
SAMPLING MEAN DEFINITION The term sampling mean .docx
 
Sampling methods theory and practice
Sampling methods theory and practice Sampling methods theory and practice
Sampling methods theory and practice
 
Risk Ana
Risk AnaRisk Ana
Risk Ana
 
hypothesis.pptx
hypothesis.pptxhypothesis.pptx
hypothesis.pptx
 
Chapter 8
Chapter 8Chapter 8
Chapter 8
 
Steps of hypothesis testingSelect the appropriate testSo far.docx
Steps of hypothesis testingSelect the appropriate testSo far.docxSteps of hypothesis testingSelect the appropriate testSo far.docx
Steps of hypothesis testingSelect the appropriate testSo far.docx
 
Confusion matrix and classification evaluation metrics
Confusion matrix and classification evaluation metricsConfusion matrix and classification evaluation metrics
Confusion matrix and classification evaluation metrics
 
A General Manger of Harley-Davidson has to decide on the size of a.docx
A General Manger of Harley-Davidson has to decide on the size of a.docxA General Manger of Harley-Davidson has to decide on the size of a.docx
A General Manger of Harley-Davidson has to decide on the size of a.docx
 
Workbook Project
Workbook ProjectWorkbook Project
Workbook Project
 
PyGotham 2016
PyGotham 2016PyGotham 2016
PyGotham 2016
 
Estimation in statistics
Estimation in statisticsEstimation in statistics
Estimation in statistics
 
What Is a Model, Anyhow?
What Is a Model, Anyhow?What Is a Model, Anyhow?
What Is a Model, Anyhow?
 
Answer the questions in one paragraph 4-5 sentences. · Why did t.docx
Answer the questions in one paragraph 4-5 sentences. · Why did t.docxAnswer the questions in one paragraph 4-5 sentences. · Why did t.docx
Answer the questions in one paragraph 4-5 sentences. · Why did t.docx
 
MLlectureMethod.ppt
MLlectureMethod.pptMLlectureMethod.ppt
MLlectureMethod.ppt
 
MLlectureMethod.ppt
MLlectureMethod.pptMLlectureMethod.ppt
MLlectureMethod.ppt
 
Sample Size And Gpower Module
Sample Size And Gpower ModuleSample Size And Gpower Module
Sample Size And Gpower Module
 
sample_size_Determination .pdf
sample_size_Determination .pdfsample_size_Determination .pdf
sample_size_Determination .pdf
 
analysis part 02.pptx
analysis part 02.pptxanalysis part 02.pptx
analysis part 02.pptx
 
Histograms and Descriptive Statistics Scoring GuideCRITERIANON.docx
Histograms and Descriptive Statistics Scoring GuideCRITERIANON.docxHistograms and Descriptive Statistics Scoring GuideCRITERIANON.docx
Histograms and Descriptive Statistics Scoring GuideCRITERIANON.docx
 

More from Rajan Vishwakarma

Nationality-wise Foreign Tourist Arrivals in India,2019
Nationality-wise Foreign Tourist Arrivals in India,2019Nationality-wise Foreign Tourist Arrivals in India,2019
Nationality-wise Foreign Tourist Arrivals in India,2019Rajan Vishwakarma
 
INDIA’S PRINT INDUSTRY REVOLUTION
INDIA’S PRINT INDUSTRY REVOLUTIONINDIA’S PRINT INDUSTRY REVOLUTION
INDIA’S PRINT INDUSTRY REVOLUTIONRajan Vishwakarma
 
SOURCE COUNTRIES FOR FOREIGN TOURIST ARRIVALS IN INDIA
SOURCE COUNTRIES FOR FOREIGN TOURIST ARRIVALS IN INDIASOURCE COUNTRIES FOR FOREIGN TOURIST ARRIVALS IN INDIA
SOURCE COUNTRIES FOR FOREIGN TOURIST ARRIVALS IN INDIARajan Vishwakarma
 
MOST POPULAR TRAVEL WEBSITES IN INDIA
MOST POPULAR TRAVEL WEBSITES IN INDIAMOST POPULAR TRAVEL WEBSITES IN INDIA
MOST POPULAR TRAVEL WEBSITES IN INDIARajan Vishwakarma
 
INDIA TOURISM STATISTICS AT A GLANCE 2019
INDIA TOURISM STATISTICS AT A GLANCE 2019INDIA TOURISM STATISTICS AT A GLANCE 2019
INDIA TOURISM STATISTICS AT A GLANCE 2019Rajan Vishwakarma
 
Top 5 AGRICULTURE FOOD SUPPLIERS
Top 5 AGRICULTURE FOOD SUPPLIERSTop 5 AGRICULTURE FOOD SUPPLIERS
Top 5 AGRICULTURE FOOD SUPPLIERSRajan Vishwakarma
 
Risk management from project manager
Risk management from project managerRisk management from project manager
Risk management from project managerRajan Vishwakarma
 

More from Rajan Vishwakarma (8)

Nationality-wise Foreign Tourist Arrivals in India,2019
Nationality-wise Foreign Tourist Arrivals in India,2019Nationality-wise Foreign Tourist Arrivals in India,2019
Nationality-wise Foreign Tourist Arrivals in India,2019
 
INDIA’S PRINT INDUSTRY REVOLUTION
INDIA’S PRINT INDUSTRY REVOLUTIONINDIA’S PRINT INDUSTRY REVOLUTION
INDIA’S PRINT INDUSTRY REVOLUTION
 
SOURCE COUNTRIES FOR FOREIGN TOURIST ARRIVALS IN INDIA
SOURCE COUNTRIES FOR FOREIGN TOURIST ARRIVALS IN INDIASOURCE COUNTRIES FOR FOREIGN TOURIST ARRIVALS IN INDIA
SOURCE COUNTRIES FOR FOREIGN TOURIST ARRIVALS IN INDIA
 
MOST POPULAR TRAVEL WEBSITES IN INDIA
MOST POPULAR TRAVEL WEBSITES IN INDIAMOST POPULAR TRAVEL WEBSITES IN INDIA
MOST POPULAR TRAVEL WEBSITES IN INDIA
 
INDIA TOURISM STATISTICS AT A GLANCE 2019
INDIA TOURISM STATISTICS AT A GLANCE 2019INDIA TOURISM STATISTICS AT A GLANCE 2019
INDIA TOURISM STATISTICS AT A GLANCE 2019
 
Google logo change
Google logo changeGoogle logo change
Google logo change
 
Top 5 AGRICULTURE FOOD SUPPLIERS
Top 5 AGRICULTURE FOOD SUPPLIERSTop 5 AGRICULTURE FOOD SUPPLIERS
Top 5 AGRICULTURE FOOD SUPPLIERS
 
Risk management from project manager
Risk management from project managerRisk management from project manager
Risk management from project manager
 

Recently uploaded

Science lesson Moon for 4th quarter lesson
Science lesson Moon for 4th quarter lessonScience lesson Moon for 4th quarter lesson
Science lesson Moon for 4th quarter lessonJericReyAuditor
 
Employee wellbeing at the workplace.pptx
Employee wellbeing at the workplace.pptxEmployee wellbeing at the workplace.pptx
Employee wellbeing at the workplace.pptxNirmalaLoungPoorunde1
 
Incoming and Outgoing Shipments in 1 STEP Using Odoo 17
Incoming and Outgoing Shipments in 1 STEP Using Odoo 17Incoming and Outgoing Shipments in 1 STEP Using Odoo 17
Incoming and Outgoing Shipments in 1 STEP Using Odoo 17Celine George
 
EPANDING THE CONTENT OF AN OUTLINE using notes.pptx
EPANDING THE CONTENT OF AN OUTLINE using notes.pptxEPANDING THE CONTENT OF AN OUTLINE using notes.pptx
EPANDING THE CONTENT OF AN OUTLINE using notes.pptxRaymartEstabillo3
 
Organic Name Reactions for the students and aspirants of Chemistry12th.pptx
Organic Name Reactions  for the students and aspirants of Chemistry12th.pptxOrganic Name Reactions  for the students and aspirants of Chemistry12th.pptx
Organic Name Reactions for the students and aspirants of Chemistry12th.pptxVS Mahajan Coaching Centre
 
History Class XII Ch. 3 Kinship, Caste and Class (1).pptx
History Class XII Ch. 3 Kinship, Caste and Class (1).pptxHistory Class XII Ch. 3 Kinship, Caste and Class (1).pptx
History Class XII Ch. 3 Kinship, Caste and Class (1).pptxsocialsciencegdgrohi
 
Enzyme, Pharmaceutical Aids, Miscellaneous Last Part of Chapter no 5th.pdf
Enzyme, Pharmaceutical Aids, Miscellaneous Last Part of Chapter no 5th.pdfEnzyme, Pharmaceutical Aids, Miscellaneous Last Part of Chapter no 5th.pdf
Enzyme, Pharmaceutical Aids, Miscellaneous Last Part of Chapter no 5th.pdfSumit Tiwari
 
Final demo Grade 9 for demo Plan dessert.pptx
Final demo Grade 9 for demo Plan dessert.pptxFinal demo Grade 9 for demo Plan dessert.pptx
Final demo Grade 9 for demo Plan dessert.pptxAvyJaneVismanos
 
Kisan Call Centre - To harness potential of ICT in Agriculture by answer farm...
Kisan Call Centre - To harness potential of ICT in Agriculture by answer farm...Kisan Call Centre - To harness potential of ICT in Agriculture by answer farm...
Kisan Call Centre - To harness potential of ICT in Agriculture by answer farm...Krashi Coaching
 
POINT- BIOCHEMISTRY SEM 2 ENZYMES UNIT 5.pptx
POINT- BIOCHEMISTRY SEM 2 ENZYMES UNIT 5.pptxPOINT- BIOCHEMISTRY SEM 2 ENZYMES UNIT 5.pptx
POINT- BIOCHEMISTRY SEM 2 ENZYMES UNIT 5.pptxSayali Powar
 
Software Engineering Methodologies (overview)
Software Engineering Methodologies (overview)Software Engineering Methodologies (overview)
Software Engineering Methodologies (overview)eniolaolutunde
 
Solving Puzzles Benefits Everyone (English).pptx
Solving Puzzles Benefits Everyone (English).pptxSolving Puzzles Benefits Everyone (English).pptx
Solving Puzzles Benefits Everyone (English).pptxOH TEIK BIN
 
“Oh GOSH! Reflecting on Hackteria's Collaborative Practices in a Global Do-It...
“Oh GOSH! Reflecting on Hackteria's Collaborative Practices in a Global Do-It...“Oh GOSH! Reflecting on Hackteria's Collaborative Practices in a Global Do-It...
“Oh GOSH! Reflecting on Hackteria's Collaborative Practices in a Global Do-It...Marc Dusseiller Dusjagr
 
18-04-UA_REPORT_MEDIALITERAСY_INDEX-DM_23-1-final-eng.pdf
18-04-UA_REPORT_MEDIALITERAСY_INDEX-DM_23-1-final-eng.pdf18-04-UA_REPORT_MEDIALITERAСY_INDEX-DM_23-1-final-eng.pdf
18-04-UA_REPORT_MEDIALITERAСY_INDEX-DM_23-1-final-eng.pdfssuser54595a
 
internship ppt on smartinternz platform as salesforce developer
internship ppt on smartinternz platform as salesforce developerinternship ppt on smartinternz platform as salesforce developer
internship ppt on smartinternz platform as salesforce developerunnathinaik
 
भारत-रोम व्यापार.pptx, Indo-Roman Trade,
भारत-रोम व्यापार.pptx, Indo-Roman Trade,भारत-रोम व्यापार.pptx, Indo-Roman Trade,
भारत-रोम व्यापार.pptx, Indo-Roman Trade,Virag Sontakke
 
BASLIQ CURRENT LOOKBOOK LOOKBOOK(1) (1).pdf
BASLIQ CURRENT LOOKBOOK  LOOKBOOK(1) (1).pdfBASLIQ CURRENT LOOKBOOK  LOOKBOOK(1) (1).pdf
BASLIQ CURRENT LOOKBOOK LOOKBOOK(1) (1).pdfSoniaTolstoy
 
Proudly South Africa powerpoint Thorisha.pptx
Proudly South Africa powerpoint Thorisha.pptxProudly South Africa powerpoint Thorisha.pptx
Proudly South Africa powerpoint Thorisha.pptxthorishapillay1
 
How to Configure Email Server in Odoo 17
How to Configure Email Server in Odoo 17How to Configure Email Server in Odoo 17
How to Configure Email Server in Odoo 17Celine George
 

Recently uploaded (20)

Science lesson Moon for 4th quarter lesson
Science lesson Moon for 4th quarter lessonScience lesson Moon for 4th quarter lesson
Science lesson Moon for 4th quarter lesson
 
Employee wellbeing at the workplace.pptx
Employee wellbeing at the workplace.pptxEmployee wellbeing at the workplace.pptx
Employee wellbeing at the workplace.pptx
 
Incoming and Outgoing Shipments in 1 STEP Using Odoo 17
Incoming and Outgoing Shipments in 1 STEP Using Odoo 17Incoming and Outgoing Shipments in 1 STEP Using Odoo 17
Incoming and Outgoing Shipments in 1 STEP Using Odoo 17
 
EPANDING THE CONTENT OF AN OUTLINE using notes.pptx
EPANDING THE CONTENT OF AN OUTLINE using notes.pptxEPANDING THE CONTENT OF AN OUTLINE using notes.pptx
EPANDING THE CONTENT OF AN OUTLINE using notes.pptx
 
Organic Name Reactions for the students and aspirants of Chemistry12th.pptx
Organic Name Reactions  for the students and aspirants of Chemistry12th.pptxOrganic Name Reactions  for the students and aspirants of Chemistry12th.pptx
Organic Name Reactions for the students and aspirants of Chemistry12th.pptx
 
History Class XII Ch. 3 Kinship, Caste and Class (1).pptx
History Class XII Ch. 3 Kinship, Caste and Class (1).pptxHistory Class XII Ch. 3 Kinship, Caste and Class (1).pptx
History Class XII Ch. 3 Kinship, Caste and Class (1).pptx
 
Enzyme, Pharmaceutical Aids, Miscellaneous Last Part of Chapter no 5th.pdf
Enzyme, Pharmaceutical Aids, Miscellaneous Last Part of Chapter no 5th.pdfEnzyme, Pharmaceutical Aids, Miscellaneous Last Part of Chapter no 5th.pdf
Enzyme, Pharmaceutical Aids, Miscellaneous Last Part of Chapter no 5th.pdf
 
Final demo Grade 9 for demo Plan dessert.pptx
Final demo Grade 9 for demo Plan dessert.pptxFinal demo Grade 9 for demo Plan dessert.pptx
Final demo Grade 9 for demo Plan dessert.pptx
 
Kisan Call Centre - To harness potential of ICT in Agriculture by answer farm...
Kisan Call Centre - To harness potential of ICT in Agriculture by answer farm...Kisan Call Centre - To harness potential of ICT in Agriculture by answer farm...
Kisan Call Centre - To harness potential of ICT in Agriculture by answer farm...
 
POINT- BIOCHEMISTRY SEM 2 ENZYMES UNIT 5.pptx
POINT- BIOCHEMISTRY SEM 2 ENZYMES UNIT 5.pptxPOINT- BIOCHEMISTRY SEM 2 ENZYMES UNIT 5.pptx
POINT- BIOCHEMISTRY SEM 2 ENZYMES UNIT 5.pptx
 
Software Engineering Methodologies (overview)
Software Engineering Methodologies (overview)Software Engineering Methodologies (overview)
Software Engineering Methodologies (overview)
 
Solving Puzzles Benefits Everyone (English).pptx
Solving Puzzles Benefits Everyone (English).pptxSolving Puzzles Benefits Everyone (English).pptx
Solving Puzzles Benefits Everyone (English).pptx
 
“Oh GOSH! Reflecting on Hackteria's Collaborative Practices in a Global Do-It...
“Oh GOSH! Reflecting on Hackteria's Collaborative Practices in a Global Do-It...“Oh GOSH! Reflecting on Hackteria's Collaborative Practices in a Global Do-It...
“Oh GOSH! Reflecting on Hackteria's Collaborative Practices in a Global Do-It...
 
18-04-UA_REPORT_MEDIALITERAСY_INDEX-DM_23-1-final-eng.pdf
18-04-UA_REPORT_MEDIALITERAСY_INDEX-DM_23-1-final-eng.pdf18-04-UA_REPORT_MEDIALITERAСY_INDEX-DM_23-1-final-eng.pdf
18-04-UA_REPORT_MEDIALITERAСY_INDEX-DM_23-1-final-eng.pdf
 
internship ppt on smartinternz platform as salesforce developer
internship ppt on smartinternz platform as salesforce developerinternship ppt on smartinternz platform as salesforce developer
internship ppt on smartinternz platform as salesforce developer
 
भारत-रोम व्यापार.pptx, Indo-Roman Trade,
भारत-रोम व्यापार.pptx, Indo-Roman Trade,भारत-रोम व्यापार.pptx, Indo-Roman Trade,
भारत-रोम व्यापार.pptx, Indo-Roman Trade,
 
BASLIQ CURRENT LOOKBOOK LOOKBOOK(1) (1).pdf
BASLIQ CURRENT LOOKBOOK  LOOKBOOK(1) (1).pdfBASLIQ CURRENT LOOKBOOK  LOOKBOOK(1) (1).pdf
BASLIQ CURRENT LOOKBOOK LOOKBOOK(1) (1).pdf
 
Staff of Color (SOC) Retention Efforts DDSD
Staff of Color (SOC) Retention Efforts DDSDStaff of Color (SOC) Retention Efforts DDSD
Staff of Color (SOC) Retention Efforts DDSD
 
Proudly South Africa powerpoint Thorisha.pptx
Proudly South Africa powerpoint Thorisha.pptxProudly South Africa powerpoint Thorisha.pptx
Proudly South Africa powerpoint Thorisha.pptx
 
How to Configure Email Server in Odoo 17
How to Configure Email Server in Odoo 17How to Configure Email Server in Odoo 17
How to Configure Email Server in Odoo 17
 

All you want to know about sensitivity analysis

  • 1. Sensitivity Analysis: Definition, Uses & Importance What is SensitivityAnalysis? Financial riskmodelingtakessensitivityanalysistothe nextlevelandhelpsinassessing the probability and potential impactof unfavorable outcomes.Basedonthe assessments,variousdecisionswith respectto managing,hedgingortransferringrisksare taken. Sensitivityanalysisisone of the toolsthathelpdecisionmakerswithmore thana solutiontoa problem. It providesanappropriate insightintothe problemsassociatedwiththe model underreference. Finally, the decisionmakergetsadecentideaabouthow sensitive the optimumsolutionis chosenbyhimtoany changesinthe inputvaluesof one ormore parameters. Have you everbeencaughtina situationregardingdatasensitivityanalysisinFinancial Modeling?If you have faceda problembefore,findyouranswerrighthere! Measurementofsensitivityanalysis Beloware mentionedthe stepsusedtoconductsensitivityanalysis:  Firstly, the base case outputisdefined;saythe NPV ata base case inputvalue (V1) forwhichthe sensitivityistobe measured.All the otherinputsof the model are keptconstant.  Thenthe value of the output at a new value of the input(V2) while keepingotherinputs constantis calculated.  Findthe percentage change inthe outputandthe percentage change inthe input.  The sensitivityiscalculatedbydividingthe percentage change inoutputbythe percentage change in input. Thisprocessof testingsensitivityforanotherinput(saycashflowsgrowthrate) whilekeepingthe restof inputsconstantisrepeatedtill the sensitivityfigure foreachof the inputsisobtained.The conclusion wouldbe that the higherthe sensitivityfigure,the more sensitivethe outputistoanychange inthat inputandvice versa. For SensitivityAnalysisfollowthe followingsteps FirstLINKthe outputyouwant to checksensitivityof?(IN FMCGcase linkthe share Price orEV) Nextdecide the variableyouwanttocheck the sensitivityof (e.g. WACC;TerminalGrowthrate;tax rate etc.) Let’ssay we selectedWACCand Terminal Growthwhichoriginallynthe model is10.7% and 5%. Now take the range for twovariable whichwill be 8.7;9.7; 10.7;11.7 and 12.7% for WACC and let’ssay3; 4; 5; 6; 7% for T. Growth.place these numbersonthe cell nexttoyourlinkedcell instepone above. So, if you have linkedEV inthe cell G30 Wickwill come inthe cell fromH30 - L30 and T Growth will come incell G31 to G35
  • 2. Nowselectthe cell fromG30 to L35 and go to data tab - "What if Analysis" - "Datatable" Nowinthe windowwhichpopsupinthe "row input"selectthe cell where youhave originallycalculated your WACCand inColumn selectcell where youhave originallycalculatedTGrowthRate andpress enter Usesof SensitivityAnalysis  The keyapplicationof sensitivityanalysisistoindicate the sensitivityof simulationto uncertaintiesinthe inputvaluesof the model.  Theyhelpindecisionmaking  Sensitivityanalysisisamethodforpredictingthe outcome of adecisionif asituationturnsout to be differentcomparedtothe keypredictions.  It helpsinassessingthe riskinessof astrategy.  Helpsinidentifyinghowdependentthe outputisona inputvalue.Analysesif the dependencyin turn helpsinassessingthe riskassociated.  Helpsintakinginformedandappropriate decisions  Aidssearchingforerrorsin the model Conclusion Sensitivityanalysisisone of the toolsthathelpdecisionmakerswithmore thana solutiontoa problem. It providesanappropriate insightintothe problemsassociatedwiththe model underreference. Finally, the decisionmakergetsadecentideaabouthow sensitive the optimumsolutionis chosenbyhimtoany changesinthe inputvaluesof one ormore parameters. To know in-depthaboutSensitivityanalysis,readhere: https://www.edupristine.com/blog/all-about- sensitivity-analysis