Predictive analysis for equity valuation_new editPresentation Transcript
Predictive Analysis for Financial Valuation of equities ANIL NALLAMOTU email@example.com
Objective of the Study To provide an overview of the current valuation methods being used to identify the value of a listed companies and present some of the constraints limiting an accurate estimation of the price. ‘Predictive Analysis’, a recent methodology of identifying the impact of the external factors affecting the price performance of a company is presented.
Financial Valuation – To find Value and forecast the price WACC and Discounted Cash Flow Future Cash Flow, Enterprise Value, EBITDA, Capital structure, Leverage and WACC Market Multiples Method /Ratio based Valuation Price-Equity, PEG, EV/EBITDA, EV/NOPAT etc Sum of Total Parts A Hybrid approach
Techniques Used DCF is theoretically strong and standardized technique Ratio multiples are used in price discovery following the forecast But Limitations exist
Case in Point , circa 2001 – picture perfect A NIFTY 50 Blue Chip Market Multiples Method Sum of Total Parts Financial Ratios Technical Analysis Technical Charting Moving Averages Relative Strength Index
But, markets are irrational. So 10 years later.. Price = f(Value) + External Factors (Opportunities/Threats + Uncertainties) By 2010, The reasons for performance are different over the 3 market cycles since 2001.
Case in Point – the performance
How can the external factors be accounted What-If The Auto Sector How does Automobile sector react to a Repo-rate hike of 0.5% How would HMV/LMV perform versus Two-wheelers. How would market volume differ in these sectors in the near term. What If Oil Prices increase, would it benefit two wheeler companies Monsoon is affected this year, how would it affect the sector. If GDP is revised downwards and High Inflation continues, what could the likely impact be? Every company performs differently to an external event. A What-If analysis is needed to provide insight into the impact of these events.
Predictive Analytics is about: “Applying Historical Patterns on data to predict Potential future outcomes”
Predictive Analytics is about Using Internal and external data to help make the best possible decision in a given situation. Provide insights to help and guide in decision making. Based on previous impact of the events on the price of the company. Addresses the impact of external events on price behaviour. Leading Indicators enable prediction of direction of market movement. Coverage of all potential factors that can impact a company.
Predictive Analytics: How is it different from traditional BI tools Focus on What-If versus transactional analysis Models can be set to be either predict outcome or to enable decisions Uses Clustering, Regression Methods and generic algorithms
What can it be used for? Helps in decision making and identification of opportunities. Data deduction and reporting. Focus on including all possible impacts of the outcome of the event. Virtual dashboard and benchmarking tool. Present opportunities and risks in terms of potential performance of the company over a time period. Predictive Models vs Decision Models
Focus on identifying historical data patterns that affect the performance of a company/a constituent group representing the same scale of operations.
Cluster formed based on variables that are perceived as a risk or opportunity in case of an occurrence of the event.
Ex – A simplistic approach for Banks, if the Event is an RBI Monetary Policy or adverse monsoon, the cluster could be formed based on Internal Factors: CASA Ratio, Interest Earned, Net Interest Margin, NPA Ratio, EPS and RoA External Factors: Market Price Movement, Duration of Change, Trading Volume
The constituents considered would be of a similar scale and are benchmarked against the sector average. Ratio analysis screens like P/E, P/B etc
Focus on identifying the outcome/direction in the case of multiple events
Ex. To identify the impact of Dollar depreciation by 2% vs the Rupee. Upward revision of GDP by 0.2% On the stock performance of L&T. Does the company benefit or lose due to the occurrence of these two events?
Decision models enable prediction of a result when many variables are involved.
Predictive Analytics in Use Is already being used in a variety of Industries. Insurance – to forecast accurate premiums Consumer Finance – Credit scores to evaluate a Customer Profile Marketing – Identify potential customers based on purchasing patterns. But there are challenges
But limitations exist..
Predictive Analytics in use SAS, Sybase and Opera are some of the leading companies in Predictive Analytical Tools Used to empower business analysts Capture Organization Knowledge and insights on Big Data
Nothing is impossible.. But everything is imperfect(in one way or the other, i.e,)
What Predictive Analytics is Not Intuitive
Based on hard data, with a high impact on events/decisions that are game-changers.
Not a KPO tool
Data deduction and subjective understanding are still the key.
It is based on historical data using Data mining and identifying how the company/sector have behaved in a similar scenario earlier. Works when events are cyclical or lead to a change in investor behavior. Every company performs differently to external factors. Does not replace the human element in decision making
Youremember the first, predictivereminds you of the latter two cardinal rules: never invest in hope; never be surprised