Is EBITDA a Useful Metric? EBITDA: Earnings Before Interest, Taxes, - PowerPoint PPT Presentation

Jan 15, 2024 •435 likes •526 views

Is EBITDA a Useful Metric? EBITDA: Earnings Before Interest, Taxes, Depreciation & Amortization VERY common in valuations, LBOs, credit analysis But is it really accurate? Or are there problems with it? Are there ways to see

Is EBITDA a Useful Metric? • EBITDA: Earnings Before Interest, Taxes, Depreciation & Amortization • VERY common in valuations, LBOs, credit analysis… • But… is it really accurate? Or are there problems with it? Are there ways to see how accurate it is? • Yes! It’s called “Free Cash Flow Conversion Analysis”
Problems with EBITDA • EBITDA: Supposed to be a proxy for a company’s Cash Flow from Operations – just like CFO, D&A gets added back and CapEx is excluded • PROBLEMS:  What about taxes and interest? Could be huge!  Or Working Capital requirements?  And can you really just ignore CapEx? It impacts a company’s ability to repay debt…
FCF Conversion Analysis • Solution: Compare a company’s Free Cash Flow (CFO – CapEx) to its EBITDA Historical Projected Key Metrics and Ratios: Units FY10 FY11 FY12 FY13 FY14 FY15 FY16 FY17 Free Cash Flow Conversion Analysis: EBITDA: ¥ M ¥ 334.8 ¥ 396.5 ¥ 563.8 ¥ 748.2 ¥ 836.4 ¥ 921.6 ¥ 979.2 ¥ 1,045.0 Less: CapEx: ¥ M (425.6) (566.8) (546.2) (553.6) (466.0) (435.6) (395.0) (353.3) Less: Net Interest Expense: ¥ M 1.0 (1.0) (13.6) (38.4) (28.5) (15.7) (8.0) 1.3 Less: Taxes: ¥ M (35.8) (36.3) (67.5) (87.5) (102.7) (117.5) (126.7) (138.4) Plus/Less: Other Non-Cash Items: ¥ M (1.8) (3.7) (7.1) (9.1) (13.5) (14.9) (20.2) (21.9) Plus/Less: Change in WC: ¥ M 21.6 58.2 69.8 56.9 40.5 47.5 38.6 47.5 Free Cash Flow: ¥ M ¥ -105.9 ¥ -153.0 ¥ -0.9 ¥ 116.4 ¥ 266.3 ¥ 385.4 ¥ 467.9 ¥ 580.2 FCF Conversion %: % (31.6%) (38.6%) (0.2%) 15.6% 31.8% 41.8% 47.8% 55.5% FCF Yield %: % 3.1% 7.0% 10.1% 12.3% 15.2% • Goal: How close is a company’s EBITDA to its discretionary cash flow?
Interpreting FCF Conversion • Question: Is 100%, or over 100% FCF conversion “good”? It must be, right? • Truth: Depends on why it is that high… if it’s sustainable and based on high cash payments from customers upfront, sure… • But … if it’s based on one -time tax benefits, non- recurring items, weird Working Capital treatment, etc., not so positive
FCF Conversion Analysis • How can you use this analysis? • Method #1: Compare peer companies, and see which one has the highest conversion % (HomeAway)  higher conversion = higher valuation multiple? • Method #2: Use it to develop your investment thesis in a company (7 Days Inn) – do the numbers work because of improved FCF generation?
FCF Conversion Analysis • Method #3: Use it along with other credit stats/ratios to determine how much debt a company can take on • Median from Comps: 4x Debt / EBITDA, 50% FCF Conversion • This Company: 75% FCF Conversion • Implication: Maybe more than 4x Debt / EBITDA?
Recap and Summary • FCF Conversion: How much of a company’s EBITDA gets “converted” into its Free Cash Flow? • Higher percentages are generally more positive, if they are sustainable • Uses: Compare peer companies and valuation multiples, support investment/LBO theses, and use it in conjunction with credit stats and ratios

Recommend

Metric Spaces Definition If d is a metric on X , then the metric topology on X induced by d is

Metric Spaces Definition If d is a metric on X , then the metric topology on X induced by d is the topology generated by the basis = { B d ( X , ) : x X and > 0 } . The set X endowed with this topology is called the metric space (

52 views • 4 slides

Welcome back... Metric spaces. Approximate metric using a tree. Tree metric: 16 16 A metric

Welcome back... Metric spaces. Approximate metric using a tree. Tree metric: 16 16 A metric space X , d ( i , j ) where d ( i , j ) d ( i , k )+ d ( k , j ) , X is nodes of tree with edge weights d ( i , j ) = d ( j , i ) , and d ( i , j )

376 views • 4 slides

January 30, 2020 EBITDA (SEKm) and EBITDA margin Sales growth of 4% vs 2018 +1% +44%

January 30, 2020 EBITDA (SEKm) and EBITDA margin Sales growth of 4% vs 2018 +1% +44% Price/mix -8%, volume 11%, currency 3%, acq/div -2% 5,319 EBITDA up 1% vs 2018 5,252 - Lower selling prices + Higher pulp volumes + Positive

599 views • 37 slides

Multiwavelength UV-metric and pH-metric determination of the dissociation constants of the

Multiwavelength UV-metric and pH-metric determination of the dissociation constants of the hypoxia-inducible factor prolyl hydroxylase inhibitor Roxadustat * Milan Meloun 1 , Lucie Pilaov 1 , Milan Javrek 2 and Tom Pekrek 3 1

178 views • 15 slides

Metric Conversions Ladder Method T. Trimpe 2008 http://sciencespot.net/ Metric System The

Metric Conversions Ladder Method T. Trimpe 2008 http://sciencespot.net/ Metric System The metric system is based on a base unit that corresponds to a certain kind of measurement Length = meter Volume = liter Weight (Mass) =

293 views • 11 slides

0 EBITDA 3,269m, +13% YoY benefiting from gain on Naturgas disposal Recurring EBITDA (1)

0 EBITDA 3,269m, +13% YoY benefiting from gain on Naturgas disposal Recurring EBITDA (1) 2,711m, -4% YoY penalised by 52% decline YoY of hydro production in Iberia OPEX IV efficiency programme achieved savings of 103m in 9M17 (23% above

390 views • 26 slides

+6.4% 9.4BN UP SLIGHTLY ABOVE LAST YEAR +1.8% ORGANICALLY IN Q3 YTD Q3 GET/TDC NORWAY DEAL

INTERIM REPORT JANUARY SEPTEMBER 2018 JOHAN DENNELIND PRESIDENT & CEO ANOTHER GOOD QUARTER CASH FLOW REMAINS CASH FLOW REMAINS CONTINUED EBITDA GROWTH CONTINUED EBITDA GROWTH EBITDA OUTLOOK EBITDA OUTLOOK STRONG STRONG REVISED

299 views • 13 slides

Dynamical Systems Continuous maps of metric spaces We work with metric spaces, usually a

Dynamical Systems Continuous maps of metric spaces We work with metric spaces, usually a subset of R n with the Euclidean norm. A map of metric spaces F : X Y is continuous at x X if it preserves the limits of convergent sequences,

409 views • 17 slides

Some remarks about metric spaces, 1 Stephen William Semmes Of course various kinds of metric

Some remarks about metric spaces, 1 Stephen William Semmes Of course various kinds of metric spaces arise in various contexts and are viewed in various ways. In this brief survey we hope to give some modest indications of this. In particular,

566 views • 10 slides

INVESTOR PRESENTATION August 2020 2 measures. EBITDA is defined as earnings before interest

1 INVESTOR PRESENTATION August 2020 2 measures. EBITDA is defined as earnings before interest expense, provision for income taxes and depreciation and amortization. Adjusted EBITDA adjusts EBITDA to remove the effects of certain stock-based

422 views • 30 slides

Q3 2018 Results Orri Hauksson og skar Hauksson 31 October 2018 Highlights in Q3 2018 EBITDA

Q3 2018 Results Orri Hauksson og skar Hauksson 31 October 2018 Highlights in Q3 2018 EBITDA EBITDA ratio Cash 2.397 m.kr. 34,4% 570 m.kr. FINANCE Net debt / EBITDA * CAPEX Equity ratio 1,88 1.192 m.kr. 62,1% *EBITDA trailing twelve

843 views • 28 slides

Q1 2019 Results Orri Hauksson og skar Hauksson 30 April 2019 Highlights in Q1 2019 EBITDA

Q1 2019 Results Orri Hauksson og skar Hauksson 30 April 2019 Highlights in Q1 2019 EBITDA EBITDA ratio Cash 2.369 m.kr. 34,0% 966 m.kr. FINANCE Net debt / EBITDA* CAPEX Equity ratio 1,75 1.147 m.kr. 55,4% *EBITDA trailing twelve

379 views • 24 slides

Shortest Path Similar Routing 2 A New Metric A new metric path- based metric that can use used

R outing S tate D istance: A Path-based Metric for Network Analysis Gonca Grsun joint work with joint work with Natali Ruchansky, Evimaria Terzi, Mark Crovella Distance Metrics for Analyzing Routing Shortest Path Similar Routing 2 A New

1.43k views • 48 slides

Information Theoretic Metric Learning Instructor: Sham Kakade 1 Metric Learning In k -nearest

CSE 547/Stat 548: Machine Learning for Big Data Lecture by Adam Gustafson Information Theoretic Metric Learning Instructor: Sham Kakade 1 Metric Learning In k -nearest neighbors ( k -nn) and other classification algorithms, one crucial choice

221 views • 8 slides

Q3 2019 Results Orri Hauksson and skar Hauksson 30 October 2019 Highlights in Q3 2019 EBITDA

Q3 2019 Results Orri Hauksson and skar Hauksson 30 October 2019 Highlights in Q3 2019 EBITDA EBITDA ratio Cash 2.817 m.kr. 39,7% 557 m.kr. FINANCE Net debt / EBITDA* CAPEX Equity ratio 1,57 2.115 m.kr. 55,4% *EBITDA trailing

664 views • 27 slides

PRESENTATION 1Q2019 April 23, 2019 Highlights in 1Q2019 Results improved in Revenues, EBITDA and

EARNINGS PRESENTATION 1Q2019 April 23, 2019 Highlights in 1Q2019 Results improved in Revenues, EBITDA and EBITDA margin compared to 1Q18 Revenues increased 5.4% (yoy) in reporting currency, registering growth in most regions EBITDA

491 views • 24 slides

GENERAL RULES OF MEASUREMENT All measurements are METRIC! Use the correct piece of

November 05, 2015 GENERAL RULES OF MEASUREMENT All measurements are METRIC! Use the correct piece of equipment All measurements are METRIC! Make all readings at eye level All measurements are METRIC! If your measurement

287 views • 6 slides

2019/20 PRESS CONFERENCE J u n e 3 , 2 0 2 0 HIGHLIGHTS EBITDA EBITDA GROWTH: +53% (in

2019/20 PRESS CONFERENCE J u n e 3 , 2 0 2 0 HIGHLIGHTS EBITDA EBITDA GROWTH: +53% (in m) +53% 420 275 Revenues +1.2% to 4.5 billion o Average sugar price EU: 334 ( -0.6%), Average sugar price NY11: 12.6 cts (+3%) 2018/19

399 views • 39 slides

69,782 +7.0 % BACKLOG (1) Adjusted by FX (Forex) impact (2) EBITDA Net financial expenses and

1H18 Key figures Figures in million YoY Var. Like for Like Var. 1 17,777 SALES +2,2 % +10,1 % +8.7 % 1,248 +2.0 % EBITDA +11.9 % 946 +5.1 % EBIT +13.3 % 447 +7.4 % NET PROFIT 1,605 +24.1 % LTM Net Operating Cash Flow - 1,596 mn

385 views • 14 slides

70,329 +7.7 % BACKLOG (1) Adjusted by FX (Forex) impact (2) EBITDA Net financial expenses and

9M18 Key figures Figures in million Like for Like Var. (1) YoY Var. 27,091 SALES +5.2 % +11,4 % +12.3 % 1,806 +5.5 % EBITDA +16.4 % 1,350 +9.3 % EBIT +20.9 % 691 +14.6 % NET PROFIT 1,927 +24.7 % LTM Operating Cash Flow (2) - 1,544

253 views • 14 slides

Distance Metric Learning: Beyond 0/1 Loss Praveen Krishnan CVIT, IIIT Hyderabad June 14, 2017 1

Distance Metric Learning: Beyond 0/1 Loss Praveen Krishnan CVIT, IIIT Hyderabad June 14, 2017 1 Outline Distances and Similarities Distance Metric Learning Mahalanobis Distances Metric Learning Formulation Mahalanobis metric for clustering

716 views • 44 slides

The Metric Coalescent joint with David Aldous Daniel Lanoue University of California, Berkeley

Introduction The Metric Coalescent The Metric Coalescent joint with David Aldous Daniel Lanoue University of California, Berkeley June 25, 2014 Daniel Lanoue The Metric Coalescent Introduction FMIE Processes The Metric Coalescent The

862 views • 33 slides

The Elusive Metric for The Elusive Metric for Low- -Power Architecture Power Architecture Low

The Elusive Metric for The Elusive Metric for Low- -Power Architecture Power Architecture Low Research Research Hsien- -Hsin Hsin Sean Sean Lee Lee Joshua B. Fryman Hsien A. Utku Diril Yuvraj S. Dhillon Center for

225 views • 22 slides

SIMILARITY SEARCH The Metric Space Approach Pavel Zezula, Giuseppe Amato, Vlastislav Dohnal,

SIMILARITY SEARCH The Metric Space Approach Pavel Zezula, Giuseppe Amato, Vlastislav Dohnal, Michal Batko Table of Contents Part I: Metric searching in a nutshell Foundations of metric space searching Survey of existing approaches Part

1.28k views • 95 slides