logging in or signing up Altman - Z-score-PRINTOUT-VERSION srikrishnak Download Post to : URL : Related Presentations : Share Add to Flag Embed Email Send to Blogs and Networks Add to Channel Uploaded from authorPOINT lite Insert YouTube videos in PowerPont slides with aS Desktop Copy embed code: (To copy code, click on the text box) Embed: URL: Thumbnail: WordPress Embed Customize Embed The presentation is successfully added In Your Favorites. Views: 125 Category: Business & Fin.. License: All Rights Reserved Like it (0) Dislike it (0) Added: December 07, 2011 This Presentation is Public Favorites: 0 Presentation Description No description available. Comments Posting comment... Premium member Presentation Transcript PowerPoint Presentation: ALTMAN Z-SCORE Where lies its value in corporate M&A Presented to ICPAS “toward a new era in Corporate M&A” 27 March 2004 Dr Raymond Ting, CPA Nucleus Capital Ltd Nucleus Capital Ltd. All rights reserved .PowerPoint Presentation: Z score basics Accounting ratios Case study Rating for a best fit Forensic Nucleus Capital Ltd. All rights reserved . AgendaPowerPoint Presentation: Z score – a multiple discriminant analysis technique, developed as a powerful diagnostic tool measuring solvency – with ability to identify bankrupt firms, 12 months in advance, at an accuracy rate of approximately 95% Professor Edward Altman, Stern School of Business, New York UniversityPowerPoint Presentation: Z = 1.2 x1 + 1.4 x2 + 3.3 x3 + 0.6 x4 + 0.99 x5 Z = overall index of corporate health x1 = working capital/total assets x2 = retained earnings/total assets x3 = earnings before interest and taxes/total assets x4 = market value equity/book value of total liabilities x5 = sales/total assetsPowerPoint Presentation: Total debt / total assetsPowerPoint Presentation: Working capital / total assetsPowerPoint Presentation: Cash flow / total debtPowerPoint Presentation: Net income / total assetsPowerPoint Presentation: Current ratioPowerPoint Presentation: multiple discriminant analysis Altman (1968) built a linear discriminant model based only on financial ratios, matched sample (by year, industry, size) Z = 1.2 X 1 + 1.4 X 2 + 3.3 X 3 +0.6 X 4 + 1.0 X 5 X 1 = working capital / total assets X 2 = retained earnings / total assets X 3 = earning before interest and taxes / total assets X 4 = market value of equity / book value of total liabilities X 5 = sales / total assetsPowerPoint Presentation: Prediction accuracy of the Z score Year prior to failure Accuracy rate 1 95% 2 72% 3 48% 4 29% 5 36% Trade-off Between Robustness and Accuracy While accuracy may be an academic pursuit, for cost and practicality purposes, a trend analysis (by years) of the Z score should suffice for the purpose of M&APowerPoint Presentation: Caveat emptor - a company appearing financially fit may in fact be insolvent or become a bankrupt within a few short months. Beware of the “living dead” companies Completeness of business model – are you acquiring just a shelf?PowerPoint Presentation: By convention, an individual with a BMI of 30 or more is considered obese. This ratio applies to both men and women. Ratios do not fluctuate wildly. It is also not so easy to manipulate ratios. Trend analysis using z score has predictive value.PowerPoint Presentation: Most M&A due diligence approach consider the use a combination of :- Financial; and Non financial factors Financial Factors Non-financial Factors Debt service coverage Size and age of company Leverage Industry sector Profitability Age/experience managers Liquidity Location Net worth Market position Share price Judgement Z score Business synergies/strategiesPowerPoint Presentation: Important assumption underlying the use of financial ratios to control for the size differences is the so-called proportionality between the numerator and denominator Strict proportionality implicates that there should exist a linear relationship between the numerator and denominator of the ratioPowerPoint Presentation: Deviations from strict proportionality assumption Earnings Earnings Sales Earnings Sales Earnings Sales Sales 1. Proportionality without constant 3. Non-proportionality without constant 2. Proportionality with constant 4. Non-proportionality with constantPowerPoint Presentation: Actual Outcome Predicted Outcome Bankrupt Nonbankrupt Bankrupt Correct Error: Type II Cost: Small 0-10% Nonbankrupt Error: Type Cost: Large Up to 100% Correct Error Rate = false negatives + false positives Note that you may care very differently about the two error types Cost of Type I usually considerably higher (e.g. 15 to 1)PowerPoint Presentation: ALTMAN Z-SCORE Ratio analysis Nucleus Capital Ltd. All rights reserved .PowerPoint Presentation: ACCOUNTING EQUATION A = L + OE – R + E Balance sheet Profit and loss Debit Credit Debit Credit CreditPowerPoint Presentation: Criterion (Ecology) Adaptation of Lens Model to the study of human judgment Judgment Relationship of features to criterion Utilization of features by judge Multiple Features Brunswick lens model – quality and accuracy of human judgement Z scorePowerPoint Presentation: ALTMAN Z-SCORE Singapore case study Nucleus Capital Ltd. All rights reserved .PowerPoint Presentation: Audited accounts clean No mention of going concern problems Raised funds via placements and rights issues cum warrant Company is dying in 1995 Insolvent by 1997 Company in “living dead” status by 1998 – continues to look for strategic investment partners Post mortem status in 2003PowerPoint Presentation: 2000 - 2000 2001 - Profit margin affected severe 2002 – marketing strategies successful with new product launching 2003 – major acquisition (goodwill purchased = 50% of NTA)PowerPoint Presentation: 1993 – private company 1995 – solicit for potential investor 1995 – secured private investor (end 1995) 1996 – duplicated sales scheme boosts sales revenue and profit 1997 – story telling sessions/excuses 1998 – blame it on the Asian crises 1999 – investor remove management 2000 – fraud and creative accounting discoveredPowerPoint Presentation: Investigation ? Cost > benefit face value management time If in doubt, walk away . If you know what is going on, devise investment schemes that will mitigate the concerns/contingenciesPowerPoint Presentation: ALTMAN Z-SCORE Internal rating – looking for a good fit in an M&A Nucleus Capital Ltd. All rights reserved .PowerPoint Presentation: CREDIT RISK LEVEL PD (bp) S&P GRADES 1 Minimal 0-1 AAA 2 Modest 2-4 AA 3 Average 5-10 A 4 Acceptable 11-50 BBB 5 Acceptable with care 51-200 BB 6 Management Attention 201-1000 B 7 Special Mention 1000+ CCC 8 Substandard Interest Suspense CCC / CC 9 Doubtful Provision CC / C 10 Loss Default / Loss DPowerPoint Presentation: Belkaoui (1983)PowerPoint Presentation: AAA Extremely low credit risk AA+ Very low credit risk AA Relatively low credit risk A+ Low credit risk A Moderate credit risk B Above average credit risk C Credit risk is very high Z > = 10 Z > = 2.9 Z =< 2.9 Z > = 4PowerPoint Presentation: ALTMAN Z-SCORE Forensic tool for M&A Nucleus Capital Ltd. All rights reserved .PowerPoint Presentation: Z score spread < 1.8 Z score >2.9PowerPoint Presentation: Normal - Unbounded both sides =============== 2.9 Gray areas :- Creative accounting Fraudulent accounting Unreliable records MisrepresentationPowerPoint Presentation: The company results is incomplete. The company is controlled externally. The strong positive z-score reveals a monopoly position supporting the company. This support may be temporary and unreliable due to inconsistency in z-score shows poor financial management and a lack of consistency. In order to assess the company more meaningfully, we need a complete evaluation of the way businesses are conducted. Valuation of the company is not meaningful at this stage.PowerPoint Presentation: Normal - Unbounded both sides ========================= > 8 Z score >8, some observation:- Monopoly – high margins Not competitive – too slow External “guardian” factor Long term z score below 1:- Conduit type arrangement Ask to see true picturePowerPoint Presentation: Thank you You do not have the permission to view this presentation. In order to view it, please contact the author of the presentation.
Altman - Z-score-PRINTOUT-VERSION srikrishnak Download Post to : URL : Related Presentations : Share Add to Flag Embed Email Send to Blogs and Networks Add to Channel Uploaded from authorPOINT lite Insert YouTube videos in PowerPont slides with aS Desktop Copy embed code: (To copy code, click on the text box) Embed: URL: Thumbnail: WordPress Embed Customize Embed The presentation is successfully added In Your Favorites. Views: 125 Category: Business & Fin.. License: All Rights Reserved Like it (0) Dislike it (0) Added: December 07, 2011 This Presentation is Public Favorites: 0 Presentation Description No description available. Comments Posting comment... Premium member Presentation Transcript PowerPoint Presentation: ALTMAN Z-SCORE Where lies its value in corporate M&A Presented to ICPAS “toward a new era in Corporate M&A” 27 March 2004 Dr Raymond Ting, CPA Nucleus Capital Ltd Nucleus Capital Ltd. All rights reserved .PowerPoint Presentation: Z score basics Accounting ratios Case study Rating for a best fit Forensic Nucleus Capital Ltd. All rights reserved . AgendaPowerPoint Presentation: Z score – a multiple discriminant analysis technique, developed as a powerful diagnostic tool measuring solvency – with ability to identify bankrupt firms, 12 months in advance, at an accuracy rate of approximately 95% Professor Edward Altman, Stern School of Business, New York UniversityPowerPoint Presentation: Z = 1.2 x1 + 1.4 x2 + 3.3 x3 + 0.6 x4 + 0.99 x5 Z = overall index of corporate health x1 = working capital/total assets x2 = retained earnings/total assets x3 = earnings before interest and taxes/total assets x4 = market value equity/book value of total liabilities x5 = sales/total assetsPowerPoint Presentation: Total debt / total assetsPowerPoint Presentation: Working capital / total assetsPowerPoint Presentation: Cash flow / total debtPowerPoint Presentation: Net income / total assetsPowerPoint Presentation: Current ratioPowerPoint Presentation: multiple discriminant analysis Altman (1968) built a linear discriminant model based only on financial ratios, matched sample (by year, industry, size) Z = 1.2 X 1 + 1.4 X 2 + 3.3 X 3 +0.6 X 4 + 1.0 X 5 X 1 = working capital / total assets X 2 = retained earnings / total assets X 3 = earning before interest and taxes / total assets X 4 = market value of equity / book value of total liabilities X 5 = sales / total assetsPowerPoint Presentation: Prediction accuracy of the Z score Year prior to failure Accuracy rate 1 95% 2 72% 3 48% 4 29% 5 36% Trade-off Between Robustness and Accuracy While accuracy may be an academic pursuit, for cost and practicality purposes, a trend analysis (by years) of the Z score should suffice for the purpose of M&APowerPoint Presentation: Caveat emptor - a company appearing financially fit may in fact be insolvent or become a bankrupt within a few short months. Beware of the “living dead” companies Completeness of business model – are you acquiring just a shelf?PowerPoint Presentation: By convention, an individual with a BMI of 30 or more is considered obese. This ratio applies to both men and women. Ratios do not fluctuate wildly. It is also not so easy to manipulate ratios. Trend analysis using z score has predictive value.PowerPoint Presentation: Most M&A due diligence approach consider the use a combination of :- Financial; and Non financial factors Financial Factors Non-financial Factors Debt service coverage Size and age of company Leverage Industry sector Profitability Age/experience managers Liquidity Location Net worth Market position Share price Judgement Z score Business synergies/strategiesPowerPoint Presentation: Important assumption underlying the use of financial ratios to control for the size differences is the so-called proportionality between the numerator and denominator Strict proportionality implicates that there should exist a linear relationship between the numerator and denominator of the ratioPowerPoint Presentation: Deviations from strict proportionality assumption Earnings Earnings Sales Earnings Sales Earnings Sales Sales 1. Proportionality without constant 3. Non-proportionality without constant 2. Proportionality with constant 4. Non-proportionality with constantPowerPoint Presentation: Actual Outcome Predicted Outcome Bankrupt Nonbankrupt Bankrupt Correct Error: Type II Cost: Small 0-10% Nonbankrupt Error: Type Cost: Large Up to 100% Correct Error Rate = false negatives + false positives Note that you may care very differently about the two error types Cost of Type I usually considerably higher (e.g. 15 to 1)PowerPoint Presentation: ALTMAN Z-SCORE Ratio analysis Nucleus Capital Ltd. All rights reserved .PowerPoint Presentation: ACCOUNTING EQUATION A = L + OE – R + E Balance sheet Profit and loss Debit Credit Debit Credit CreditPowerPoint Presentation: Criterion (Ecology) Adaptation of Lens Model to the study of human judgment Judgment Relationship of features to criterion Utilization of features by judge Multiple Features Brunswick lens model – quality and accuracy of human judgement Z scorePowerPoint Presentation: ALTMAN Z-SCORE Singapore case study Nucleus Capital Ltd. All rights reserved .PowerPoint Presentation: Audited accounts clean No mention of going concern problems Raised funds via placements and rights issues cum warrant Company is dying in 1995 Insolvent by 1997 Company in “living dead” status by 1998 – continues to look for strategic investment partners Post mortem status in 2003PowerPoint Presentation: 2000 - 2000 2001 - Profit margin affected severe 2002 – marketing strategies successful with new product launching 2003 – major acquisition (goodwill purchased = 50% of NTA)PowerPoint Presentation: 1993 – private company 1995 – solicit for potential investor 1995 – secured private investor (end 1995) 1996 – duplicated sales scheme boosts sales revenue and profit 1997 – story telling sessions/excuses 1998 – blame it on the Asian crises 1999 – investor remove management 2000 – fraud and creative accounting discoveredPowerPoint Presentation: Investigation ? Cost > benefit face value management time If in doubt, walk away . If you know what is going on, devise investment schemes that will mitigate the concerns/contingenciesPowerPoint Presentation: ALTMAN Z-SCORE Internal rating – looking for a good fit in an M&A Nucleus Capital Ltd. All rights reserved .PowerPoint Presentation: CREDIT RISK LEVEL PD (bp) S&P GRADES 1 Minimal 0-1 AAA 2 Modest 2-4 AA 3 Average 5-10 A 4 Acceptable 11-50 BBB 5 Acceptable with care 51-200 BB 6 Management Attention 201-1000 B 7 Special Mention 1000+ CCC 8 Substandard Interest Suspense CCC / CC 9 Doubtful Provision CC / C 10 Loss Default / Loss DPowerPoint Presentation: Belkaoui (1983)PowerPoint Presentation: AAA Extremely low credit risk AA+ Very low credit risk AA Relatively low credit risk A+ Low credit risk A Moderate credit risk B Above average credit risk C Credit risk is very high Z > = 10 Z > = 2.9 Z =< 2.9 Z > = 4PowerPoint Presentation: ALTMAN Z-SCORE Forensic tool for M&A Nucleus Capital Ltd. All rights reserved .PowerPoint Presentation: Z score spread < 1.8 Z score >2.9PowerPoint Presentation: Normal - Unbounded both sides =============== 2.9 Gray areas :- Creative accounting Fraudulent accounting Unreliable records MisrepresentationPowerPoint Presentation: The company results is incomplete. The company is controlled externally. The strong positive z-score reveals a monopoly position supporting the company. This support may be temporary and unreliable due to inconsistency in z-score shows poor financial management and a lack of consistency. In order to assess the company more meaningfully, we need a complete evaluation of the way businesses are conducted. Valuation of the company is not meaningful at this stage.PowerPoint Presentation: Normal - Unbounded both sides ========================= > 8 Z score >8, some observation:- Monopoly – high margins Not competitive – too slow External “guardian” factor Long term z score below 1:- Conduit type arrangement Ask to see true picturePowerPoint Presentation: Thank you