Using Industry Average Multiples For Valuation Finance Essay

Using Industry Average duplexs For emilitary rating Finance EssayValuation of equity sh atomic number 18s of a familiarity is an meaning(a) exercise and is performed on bigeminal occasions, be it investment decision in a point association, merger, acquisition, restructuring, populace issue, and so on Using intentness mean(a) sixfold is a common practice, e special(prenominal)ly when an unlisted trade protection is to be nourishd.The study looks at eight industries and attempts to derive (a) which is the more or less immutable effort average seven-fold by using the statistical tool coefficient of reading and (b) which would be the almost authorized fiscal performance argument, which could be impulsive threefold of a popicular security deep down the persistence by using statistical tool of coefficient of correlativity.Executive SummaryA club will get valuated/re-valued on multiple occasions much(prenominal) as breeding heavy(p), sale of business, swap o f dowers, issue of stock options, and so ontera Valuation of gener eachy traded securities is quite straightforward and often regulated for diverse events, while valuation of thinly traded or un-traded securities requires some special cominges. thither be three main blastes to security valuation such as discounted funds f piteouss, plus base valuation and comparable to(predicate)s. Comparables are regarded as one and only(a) of the most useful and practical method. Ideal approach within comparables is to draw out a publicly traded accompany which is hirely wish the company being valued and adopt an appropriate multiple as valuation metric. Finding such a company is a challenge. Even if a company is pecuniaryly alike, many non-financial figures such as prevalent solid food for thought grocery store reputation, stock liquidity, etc. could be influenced its valuation of a particular stock.Experts often use industry average multiples to counter this anomaly. Th ey could be employ on a stand-alone floor or along-with a set of exact comparables. The articles analyses the concept of industry multiples in eight industries Private sector banks, overt sector banks, normal food processing, Agri Inputs, alimentation embrocate, sift, kail, Plantations (tea, coffee, flowers) and gondola-components and tries to answer two indecisionsWhich is the most appropriate industry average multiple? The criterion utilise is co-efficient of mutant. Multiples used are Market Capitalisation (MCap) / Profit After Tax, endeavour nurse (EV) / Earnings Before Interest Taxes Depreciation and Ammortisation (EBITDA), MCap/ hold in cling to, MCap/ gross salesWhich chemical element is the major driver of a multiple in a particular industry? The author has calculated co-efficient of correlation coefficiental statistics amongst distinct multiples and factors like revenues, 5 course revenue reaping, metes, integrality assets, provisions, Return on tai l assemblydour ( roe), Net deserving.EV/EBITDA was the most stable multiple followed by Mcap/ sleek (similar to P/E ratio). tax income, bread-worth and borderlines were important drivers.KeywordsIndustry average multiple, valuation, market capitalization, allow value, coefficient of chromosomal mutation/correlationBackgroundThere are many situations wherein a company will get valued/re-valued such as raising capital, sale of business, swap of partings, issue of stock options, etc. While, valuation is informal and fairly regulated (SEBI, the regulator in India has defined how a security is to be valued for different purposes) for a publicly traded company, valuation of a thinly traded or un-traded securities requires some special approaches. At times, analysts withal value a well-traded company to determine whether it is value fair or if there is any possible up-side. Different approaches to valuation are as set forth belowComparables plus mensurateEBITDA caress mass meas ureSales, etc.Equity nurtureDCFFigure 1 Different valuation methodsAsset ValueAsset based approaches such as book value (asset less liabilities as reflected in books of accounts) and realizable value (market value of asset less liabilities) are more relevant when the company/vehicle is wound-up or dissolved in any manner.Discounted Cash shine (Discounted Cash Flow to the Firm)Discounted bills flow is, theoretically, the best valuation method. The company calculates its projected financial performance. These projections and their assumptions are vetted against market factors, expert opinions.Once the parties are confident with projections, cash flows of the company (called Cash Flow to the Firm) are calculated as follows EBIT X (1-Tax Rate) Less Working Capital Changes Less Capital Expenditure sum up Depreciation.An important component of DCF based valuation is the Terminal Value. Last stratum in the projection period is capitalized as Cash flow in terminal year X (1+ perennial harvest-home rate) / (WACC perennial ontogenesis rate). This is again discounted to calculate present value of terminal cash flow.This approach is well recognized, but is not widely used due to the following(a) limitationsThe model involves a number of assumptions (i) Entire set of assumptions going into tally of financial projections, (ii) Market risk premium, (iii) Long term growth rate, etc. which makes it very subjective. The method does not work with firms which have un-utilised assets, are in the process of re-structuring, which do not have positive operating cash flows, etc.ComparablesOne of the most preferred methods of valuing a company is analyse it with a publicly traded company of similar nature called relative valuation. It is alike the most intuitive method we practice it in pricing around everything real estate, items of daily usage, etc. In relative valuation, the value of an asset is derived from the pricing of comparable assets, standardized using a co mmon unsettled such as earnings, cash flows, book value or revenues. (Damodaran on Valuation Security Analysis for Investment and Corporate Finance, by Ashwath Damodaran, Wiley Finance)A publicly traded peer is identified and compared to the company beneath consideration in terms of various valuation parameters like legal injury to Earnings, P strain to watchword, Price to Sales, Enterprise Value / EBITDA which ever is applicable and accordingly the value of the company/security under consideration can be calculated, e.g. If a comparable company is traded at 15 times its earnings, the earnings of the company under consideration are multiplied by 15 to calculate its value.The approach is fairly simple, however, the challenge lies in finding an exact comparable. There can be many differentiating factors, and some of them could be quite stark.The pricing of the publicly traded peer would also be influenced by many non-objective factors like frequent market perception, promoter re putation, adverse market rumors, low liquidity in specific stock, low level of public holding, etc.In igniter of these, many analysts and industry experts use industry-average multiples, on a stand-alone basis as well as to moderate/rationalize multiples of an individual or group of comparables.This brings us to the questions which the article intends to ponder overWhich bench-mark should be used? Every industry has two or three common benchmarks, which appropriately capture financial and operative strengths, such as the tea gardens are valued at certain times of their sales, so are football game clubs. Manufacturing industries are valued at certain time of their EBITDA or splash as the case may be. However, if an industry average is to be used, lofty degree of variability in the multiple will compromise its reliability. other question is what drives a companys valuation. The range in multiples in many industries tends to be quite laid-back. Some tangible financial factor cou ld be an important driver/differentiator for a company. Which would be the driver in a particular industry?The article attempts to answer these questions via an exercise on 214 companies in 8 different industries. The author hasChosen 8 industries based on his past work experienceSelected different publicly listed companies in individually industryDerived their multiples and financial parameters from various databasesChecked the variability of industry averages of multiples by using the statistical tool co-efficient of transformation to answer the first question (most reliable benchmark)Run correlation in the midst of a particular industry relevant bench-mark such as 5 year growth, margins, etc. and the multiple e.g. correlation between P/E ratios and book size in banking industry to answer the second question.The breakup of companies crosswise industries is as follows slacken 1 arenas and number of companies used in analysisIndustryNo of companiesPrivate sector banks14Public sector banks23General food processing16Agri Inputs8 nourishment Oil17Rice7Sugar17Plantations (tea, coffee, flowers)17 cable car-components85 pith214The following multiples were usedMarket Capitalisation (MCap) / Profit After Tax, Enterprise Value (EV) / Earnings Before Interest Taxes Depreciation and Ammortisation (EBITDA), MCap/Book Value, MCap/Sales. Mcap/ water tap is similar to more commonly used Price to Earnings per share (P/E), and Mcap/Book Value is similar to Price to Book value per share (P/B).The following financial performance parameters were selected for analysis receiptss of latest available financial year, 5 year revenue growth, margins ( ditch margin for banks and EBITDA margins for others), total assets, provisions, Return on Equity (hard roe), Net worthAnalysisPrivate Sector argotsThe following banks were analysed within clandestine sector banksHDFC swear Ltd., ICICI rim Limited, Axis till Limited, IndusInd Bank Limited, Yes Bank Ltd, Federal Bank Limited, ING Vysya Bank Limited, The Jammu Kashmir Bank Limited, Karur Vysya Bank Ltd., South Indian Bank Limited, City Union Bank Ltd., Karnataka Bank Ltd, Development Credit Bank Ltd., Lakshmi Vilas Bank Limited. elude 2 Results of clubby sector banksBanks (private)Multiple disputationMcap/PATMcap/AssetsMcap/SalesMcap/Book ValueMean8.400.090.881.19StdEv5.430.080.820.93Coeff of translation0.650.990.930.78 coefficient of correlation between multiple parameter revenue enhancement0.100.080.090.09Past 5 year growth0.200.340.360.48 bound0.320.590.610.63Total Assets0.070.060.060.07 nutrition-0.05-0.10-0.09-0.07 roe0.010.320.340.43Net Worth0.180.180.180.16MCap/PAT, similar to Price to Earnings instituteed upper limit stability. Margin (calculated as PAT/Revenue) showed maximum correlation with MCap/PAT, followed by high growth rate. The MCap/Book value Price to Book in popular parlance and Return On Equity showed the maximum correlation crossways all multiples and parameters.Margin and ROE show ed maximum correlation with MCap/PAT.Public Sector BanksPublic sector banks tend to have different operating objectives and are often valued differently compared to private sector banks. Mcap/PAT of public sector banks is 5.41 v/s 8.40 as detect in private sector banks. The following public sector banks were analysedIndian Overseas Bank, Andhra Bank, familiarity Bank, Central Bank Of India, UCO Bank, Dena Bank, Bank of Maharashtra, State Bank of Bikaner and Jaipur, State Bank of Travancore, State Bank of Mysore, United Bank of India, Punjab Sind Bank.Table 3 Results of public sector banksBanks (public)Multiple line of reasoningMcap/PATMcap/AssetsMcap/SalesMcap/Book ValueMean5.410.040.450.69StdEv1.360.010.150.16Coeff of interpretation0.250.290.320.23Correlation between multiple parameterRevenue0.340.610.650.60Past 5 year growth-0.050.120.130.07Margin-0.460.790.810.76Total Assets0.310.620.700.63 feed0.440.510.500.46ROE-0.640.570.570.69Net Worth0.290.700.750.65Public sector banks showed a different trend in variability of multiples. The book value multiple seems to show the least variation around mean as compared to Mcap/PAT sight in private banks. indoors the book value multiple, margins show the highest correlation of 0.76 followed by ROE, 0.69. intellectual nourishment processingFood processing falls into manufacturing domain. EV/EBITDA multiple is introduced in place of the Total Assets multiple is relevant to the banking and NBFC company wherein income is primarily driven by book size. EV/EBITDA is one of the most popular multiples in manufacturing sector. It captures the operating strength of a company (EBITDA) v/s Enterprise Value. Enterprise value is a debt and cash indifferent metric, calculated by Market Capitalisation + Debt Cash.Table 4 Results of food processing (general)Food ProcessingMultipleParameterMcap/PATEV/EBITDAMcap/SalesMcap/Book ValueMean18.509.390.974.21StdEv14.096.641.617.36Coeff of Variation0.760.711.651.75Correlation between mu ltiple parameterRevenue0.390.640.490.75Past 5 year growth-0.34-0.27-0.17-0.14EBITDA Margin0.020.200.570.26ROE0.500.800.750.90Net Worth0.060.310.340.34EV/EBITDA shows the lowest variation around mean (0.71). ROE is the most important driver for this multiple (0.8 correlation), followed by revenue.The following companies were considered for analysis in food processingHatson Agro Products REI Agro, inheritance Foods, KSE Limited, Nestle India Ltd., Glaxo SmithKline, Britannia Industries, Zydus Wellness, DFM Foods Ltd., Vadilal Industries, Himalya International, ADF Foods, Anik Industries, Srinivasa Hatcheries, Flex Foods, Bambino Agro, Foods and Inns, Tasty Bite Eatables, Freshtrop Fruits, Temptation Foods, Chordia Food Products. Vadilal Enterprises, Sita Shree Food Products, Simran Farms,Venkys (India), Waterbase.The companies belonged to multiple sub-sectors like dairy, poultry, consumer goods, ice creams, frozen food, etc .Agri InputsAgri inputs included seed, special fertilizers a nd some special input companies in food processing industries. The big fertilizer companies, which fall more into chemicals domain were not considered. The following companies were anlysedSukhjit amylum Chemicals, Narmada Gelatines, Sakuma Exports, Vidhi Dyestuffs, Saboo Sodium Chloro, Kaveri Seed, Advanta India, Basant Agro Tech.In agri inputs also, EV/EBITDA showed maximum stability, followed by MCap/PAT. EBITDA margin showed highest correlation with EV/EBITDA.Table 5 Results of specialised agri inputsAgri InputMultipleParameterMcap/PATEV/EBITDAMcap/SalesMcap/Book ValueMean11.278.530.981.68StdEv9.645.111.281.87Coeff of Variation0.860.601.301.11Correlation between multiple parameterRevenue-0.360.250.040.11Past 5 year growth-0.180.250.260.40EBITDA Margin-0.88-0.080.710.11ROE0.02-0.030.400.48Net Worth0.330.660.480.53Edible OilEdible oil is a special segment within food processing. The sector is characterized by high level of imports, benchmarking with international prices, low re gulations compared to commodities like rice and pulses, etc. The following companies were anlysedRuchi Soya Industries, Sanwaria Agro Oils, Rasoya Proteins, Gujarat Ambuja Exports, Jayant Agro-Organics, JVL Agro Industries, Vippy Industries Limited, Vimal Oil Foods, Raj Oil Mills, BCL Industries, Hind Industries, Kriti Nutrients, Vijay Solvex, Sam Industries, Modi Naturals, Natraj Proteins, Poona Dal Oil IndustriesTable 6 Results of nutriment oilEdible OilMultipleParameterMcap/PATEV/EBITDAMcap/SalesMcap/Book ValueMean11.106.430.211.53StdEv9.774.180.272.20Coeff of Variation0.880.651.311.44Correlation between multiple parameterRevenue0.43-0.12-0.12-0.03Past 5 year growth-0.28-0.360.99-0.20EBITDA Margin-0.01-0.030.510.16ROE-0.20-0.120.580.61Net Worth0.38-0.14-0.11-0.04EV/EBITDA showed the maximum stability, however, none of the parameters showed any reasonable correlation with the parameter. EV/EBITDA was followed by Mcap/PAT with 0.88 coefficient of variation. This factor showed r elatively high correlation with revenue followed by Net Worth.RiceRice is also a typical sector within food processing. Most of the publicly traded rice companies have focused on basmati rice. Basmati is a famous variety of aromatic rice and has queen-size export market in the middle east, Europe and US. The following companies were analysedKhushi Ram Behari La, Usher Agro, LT Food, Lakshmi talent and Foods, Emmsons International, Chaman Lal Setia Exports, GRM Overseas.The sector showed better stability of Mcap/PAT followed by Mcap/Book Value. Within Mcap/PAT EBITDA margin showed the highest correlation at 0.86.Table 7 Results of riceRiceMultipleParameterMcap/PATEV/EBITDAMcap/SalesMcap/Book ValueMean6.127.940.160.68StdEv2.273.950.130.30Coeff of Variation0.370.500.830.44Correlation between multiple parameterRevenue0.420.680.160.17Past 5 year growth-0.700.47-0.92-0.98EBITDA Margin0.86-0.600.59-0.25ROE-0.770.120.110.73Net Worth1.00-0.170.55-0.30SugarSugar is one of the largest orga nized sectors in agri processing. The sector has many large companies like Renuka Sugars, Bajaj Hindustan, etc. The sector also has some typical features like minimum procurement price, cyclical production, concentrate production in Asia and South America, etc. The following companies were analysedE.I.D. Parry, Bajaj Hindusthan, Bannari Amman Sugars, Triveni Engineering, Andhra Sugars, Dhampur Sugar Mills, KCP Sugar, Ponni Sugars (Erode), Ugar Sugar Works, Dalmia Bharat Sugar, Thiru Arooran Sugars, Sri Chamundeswari, Piccadily Agro, Vishnu Sugar Mills, Kesar Enterprises, Piccadily Sugars, Indian SucroseEV/EBITDA showed lowest co-efficient of variation (0.44). The multiple showed highest correlation with net worth, followed by revenue.Table 8 Results of cacographySugarMultipleParameterMcap/PATEV/EBITDAMcap/SalesMcap/Book ValueMean14.386.900.350.80StdEv14.793.070.200.39Coeff of Variation1.030.440.560.48Correlation between multiple parameterRevenue-0.010.200.000.19Past 5 year growt h-0.26-0.04-0.420.23EBITDA Margin-0.51-0.430.490.18ROE-0.65-0.690.440.61Net Worth-0.010.440.080.01PlantationsTea and Coffee are another vary area in agri and food industries. The sector has stakes of many large FMCG companies like Tata Tea, Unilever, etc. This sector also has special policies, farming conditions, agonistic factors. For the purpose of this analysis, flowers have also been analysed together with tea and coffee. The following companies for part of this analysisKaruturi Global, Neha International, Pochiraju Industries, Tata Global Beverage, McLeod Russel India, Tata Coffee, CCL Products India, Warren Tea, Dhunseri Petrochem, Goodricke Group, Jayshree Tea, Assam Company India, Harrisons Malayalam, Russell India, United Nilgiri Tea, Joonktollee Tea, Diana Tea.Here also, EV/EBITDA showed minimum coefficient of variation, followed by Mcap/Sales. Revenue and net worth showed the highest correlation with EV/EBITDA.Table 9 Results of plantation (tea, coffee, flowers)Plantati on (tea, coffee flowers)MultipleParameterMcap/PATEV/EBITDAMcap/SalesMcap/Book ValueMean15.179.601.091.13StdEv13.195.700.810.87Coeff of Variation0.870.590.750.76Correlation between multiple parameterRevenue0.220.330.090.27Past 5 year growth-0.47-0.38-0.19-0.43EBITDA Margin-0.34-0.420.20-0.11ROE-0.37-0.270.200.54Net Worth0.180.290.160.21 gondola componentsAuto components industry comprises of a large number of specialized players cerebrate on different segments of auto industry. Major segments and their composition in total industry size areEngine parts 31% fix transmission and steering parts 19%Body and Chassis 12%Suspension and braking parts 12%Equipments 10%Electrical parts 9%Miscellaneous 7%The industry is estimated at USD 43.5 billion in FY 2011-12. (Auto Components Manufacturers knowledge of India)The following companies were anlaysed in the industryBosch, Cummins India, Exide Industries, Motherson Sumi Systems, WABCO, Amtek India, Kirloskar, Amtek Auto Limited, Federa l-Mogul, Sundram Fasteners, Wheels India, Shanthi Gears, NRB Bearings, Automotive Axles, Mahindra Forgings, Commercial Engineers, Banco Products, Jamna Auto Industries, Fairfield Atlas, Gabriel India, Lumax Industries, Sundaram-Clayton, India Motor Parts, Saint-Gobain, Steel Strips Wheels,Setco Automotive, Minda Industries, Suprajit Engineering, Rane Holdings, ZF Steering Gear, Munjal Showa, Sona Koyo Steering, Munjal Auto, Lumax Auto Technology, Autoline Industries, India Nippon, FIEM Industries, L. G. Balakrishnan, Subros, Pricol, Hindustan Composites, Ucal Fuel Systems, Rane Madras, Rico Auto Industries, Jay Bharat Maruti, Shivam Autotech, Omax Autos, IST, Bimetal Bearings, Rane Engine Valves, REIL Electricals, Rane Brake Lining, Precision Pipes, Automotive Stampings, Harita Seating, JMT Auto, Alicon Castalloy, JBM Auto, Bharat Gears, Menon Pistons, Talbros Automotive, Triton Valves, Aunde India, appreciation Auto, Pix Transmissions, Bharat Seats, Lakshmi Precision, Menon Bearin gs, Simmonds Marshall, Kar Mobiles, IP Rings, Jay Ushin, Gujarat Automotive, Competent Automobile, Lumax Automotive Systems, Autolite India, ANG Industries, Hindustan Hardy, Raunaq Automotive, Remsons Industries, Porwall Auto Components, Spectra Industries,Kew Industries, Jagan Lamps, Coventry Coil-O Matic.In this industry again, EV/EBITDA is the most stable multiple. EV/EBITDA shows maximum correlation with revenue and net-worth.Table 10 Results of auto-componentsAuto ComponentsMultipleParameterMcap/PATEV/EBITDAMcap/SalesMcap/Book ValueMean12.476.040.671.62StdEv13.094.650.931.67Coeff of Variation1.050.771.401.03Correlation between multiple parameterRevenue0.190.350.180.31Past 5 year growth-0.040.05-0.050.09EBITDA Margin0.030.060.470.12ROE-0.310.040.210.45Net Worth0.130.350.300.24InferencesThe most stable multiples across different industries and their respective coefficients of correlations with different financial parameters were as followsTable 11 Summary of trendsCoefficient of variationCorrelationIndustryCo-efficient of VariationMultipleHighestCorrelationSecond highestCorrelationPrivate sector banks0.65MCAP/PATMargin0.32Past 5 year growth0.20Public sector banks0.23P/BMargin0.76ROE0.69General food processing0.71EV/EBITDAROE0.80Revenue0.64Agri Inputs0.60EV/EBITDANet worth0.66Revenue0.25Edible Oil0.88MCAP/PATRevenue0.43Net worth0.38Rice0.37MCAP/PATNet worth1.00EBITDA margin0.86Sugar0.44EV/EBITDANet worth0.44Revenue0.20Plantations (tea, coffee, flowers)0.59EV/EBITDARevenue0.33Revenue0.29Auto-components0.77EV/EBITDARevenue0.35Revenue0.35*In edible oil, lower coefficient was observed in EV/EBITDA. P/E was chosen because EV/EBITDA showed no correlation with any of the parameters studied.Co-efficient of variation was minimum in public sector banks and highest in auto-components. Industry multiple of public sector banks, hence, stands as the most reliable industry multiple among the industries observed. The co-efficient would be high if there is considerable hete rogeneity within the industry in terms of size, profitability, product portfolio, promoter background, etc.Earnings based multiples EV/EBITDA and P/E showed minimum coefficient of variation in all industries, except public sector banks, which showed Mcap to Book Value as the most stable multiple.Considering the correlations observed with the most stable multiple, we can infer thatnet margins are the main drivers of multiples in banks (both public and private) among the parameters observed,ROE was most powerful in food processing and edible oilplantations and auto-components seem to be driven by revenue vis--vis other parameters observedand agri inputs, rice and dinero were influenced by net-worth of respective companies.The following table shows the maximum correlation observed in a particular industry.Table 12 Maximum correlations across industriesIndustryMaximum CorrelationRelationshipsPrivate sector banks0.63ROE and Mcap/Book ValuePublic sector banks0.81PAT Margin and Mcap/Boo k ValueGeneral food processing0.90ROE and Mcap/Book ValueAgri Inputs0.71EBITDA margin and Mcap/SalesEdible Oil0.995 year growth and Mcap/SalesRice1.00Net-worth and Mcap/PATSugar0.61ROE and Mcap/Book ValuePlantations (tea, coffee, flowers)0.54ROE and Mcap/Book ValueAuto-components0.47EBITDA margin and Mcap/SalesROE and Mcap/Book Value showed highest correlation in four out of nine industries, followed by EBITDA margin and Mcap/Sales. The results were quite intuitive a company generating higher returns on invested capital (ROE), or a company operating at a higher margin should be valued more than its peers.Table 13 Results of general correlation analysisParameterMcap/PAT