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Sources: Financial Statements and Price Data – CapitalIQ & CoreData - Calculations – LCRT Platform
THE CONCEPT OF VALUE MANAGEMENTTHE CONCEPT OF VALUE MANAGEMENT A strong correlation exists between enterprise value
and the spread between CER (cash economic return) and cost of capital
Econometric DCF models can be built and validated against historical data to quantify this correlation and identify the key operating drivers which most significantly impact value
Managements can use these models to analyze their own corporate performance and to improve their decision making and value generation
Portfolio managers can use these models for buy / sell decisions
Sources: Financial Statements and Price Data – CapitalIQ & CoreData - Calculations – LCRT Platform
UTILIZATION OF ECONOMIC RATE OF UTILIZATION OF ECONOMIC RATE OF RETURN BASED DCF VALUATIONSRETURN BASED DCF VALUATIONS
Academic finance teaches that corporations create shareholder value when investing in projects which produce rates of return above the cost of capital
Yet, most professional money managers primarily employ P/E’s, EPS surprises and other metrics which fail to relate directly to the above fundamental finance principle
Why don’t most all portfolio managers utilize rate of return on capital based DCF techniques as their primary (or even exclusive) criteria for investment decisions?
Hypothesis Academics and practitioner oriented vendors have failed to
demonstrate conceptually sound, overwhelming empiricalempirical evidence that either EVA® or DCF intrinsic valuation techniques based on corporate rate of return spreads over the cost of capital are superior to simple multiples in explaining stock price levels and total shareholder returns.
Sources: Financial Statements and Price Data – CapitalIQ & CoreData - Calculations – LCRT Platform
OTHER HYPOTHESES FOR THE DISCONNECT BETWEEN OTHER HYPOTHESES FOR THE DISCONNECT BETWEEN CAPITAL BUDGETING PRINCIPLES AND PORTFOLIO CAPITAL BUDGETING PRINCIPLES AND PORTFOLIO
DECISIONSDECISIONS
Failure to decompose the problem into separable component pieces– Solve the price level = PV of cash flows empirically first, before attacking the
price change problem (academics usually employ multiple regression techniques of price changes related to other variables)
– Separate the validity of the cash flow forecast from the empirical validity of the terminal value structure
– Separate the migration of price toward intrinsic value and intrinsic value toward next year’s price
– Separate technical (behavioral finance sentiment) pressures from intrinsic valuations as anchors – wide-spread academic belief in the strong form instantaneous efficient markets precludes their openness to consider counter evidence
Failure to develop measures of goodness which enable comparative empirical testing of different models and associated parameters
– Measure the empirical accuracy of intrinsic value models against actual stock price levels (without analyst intervention)
– Measure the differences between “Winner” and “Losers” – their means and their distributional “risk” characteristics
VERSUSVERSUSVALUATION AND STOCK SELECTION QUANTITATIVE MODELSVALUATION AND STOCK SELECTION QUANTITATIVE MODELS
0102030405060708090
100110
0 10 20 30 40 50 60 70 80 90 100 110
Valuation and Stock Selection Quantitative Models (%)
Ind
ivid
ua
l Fir
m S
ec
uri
ty
An
aly
sis
(%
)
Zacks, First Call
Morgan Stanley
Merrill Lynch
CSFB HOLT & AFG
LifeCycle Returns
SchwabRetail
“Sweet Spot” ?
Hypothesis: Moving from heavy individual security analysis in the upper left toward more model based valuations in the lower right may enable the security
analysis function to add more value and become more scaleable, IF the valuation model employed is
more robust, accurate, and predictive. Analysts spend more time on material valuation issues and
Sources: Financial Statements and Price Data – CapitalIQ & CoreData - Calculations – LCRT Platform
LCRT SIMPLIFIED VIEW OF THE LCRT SIMPLIFIED VIEW OF THE ROLES FOR SECURITY ANALYSTSROLES FOR SECURITY ANALYSTS
Simplified Value added Roles in the Investment Process– Override historical raw financial data and selected drivers of
cash economic return and debt to properly reflect economics and valuation of each firm
– Forecast discontinuities of performance between history and the future based on an assessment of competitive strategy
– Employ empirically validated most accurate structure of valuation models as the terminal values in the forecasts
Properly implemented, these simplified roles promise the possibility of both increasing the value added of the security analysis function and its scalability from 20-25 to 75-100 firms per security analyst
– Encourages the security analyst to focus on the most value relevant issues
Sources: Financial Statements and Price Data – CapitalIQ & CoreData - Calculations – LCRT Platform
How Many Resources Does Your Institution Devote to Reduce the Model How Many Resources Does Your Institution Devote to Reduce the Model Risk* of Your DCF Terminal Value Assumptions Through Empirical Risk* of Your DCF Terminal Value Assumptions Through Empirical
Validation? How Do those Resources Compare to Its Valuation Impact?Validation? How Do those Resources Compare to Its Valuation Impact?
Typical % Valuation Impact
85
15 TerminalValue(DCF orMultiple)
Forecast
Typical % Resources Devoted to Accurate Forecasts
85
1
14Forecast
DCF TerminalValueMultipleTerminal Value
*Susan Mangiero, “The Risks of Ignoring Model Risk (New),” Chapter 5B, in Risk Management for Pensions, Endowments, and Foundations, Wiley, Forthcoming November 2004, pp. 5B•1-4.Susan Mangiero, “Financial Model Risk Looms Large,” The Investment Lawyer, November 2002, pp. 1-6.
Sources: Financial Statements and Price Data – CapitalIQ & CoreData - Calculations – LCRT Platform
SIMILARITIES BETWEEN STERN SIMILARITIES BETWEEN STERN STEWART AND LCRTSTEWART AND LCRT
GAAP Income, accounting rates of return, EPS growth and value expressed in simple multiples fail to reflect the fundamental economics of companies
Fundamental economics require comparing the rate of return on operating assets which a business achieves to its cost of capital
– Returns on Total Capital (Debt and Equity) are more appropriate than leveraged returns on equity for non-financial firms
– Valuation models should focus on enterprise values, subtract debt, and divide by shares to determine equity value per share; they should not attempt to estimate equity values directly
Excess returns over the cost of capital do not last forever Both methods produce a rate of return and a change in intrinsic
Sources: Financial Statements and Price Data – CapitalIQ & CoreData - Calculations – LCRT Platform
CONCEPTUAL DIFFERENCES BETWEEN STERN CONCEPTUAL DIFFERENCES BETWEEN STERN STEWART AND LCRTSTEWART AND LCRT
Stern Stewart Company rate of return based on
(RONA)1
– Net Assets Include Goodwill Traditional CAPM Nominal Weighed
Average Cost of Capital EVA®2 = (RONA – CAPM Cost of
Capital) * Depreciated H$ Net Assets Excess returns continue for “T” years,
after which spread over the cost of capital drops to zero
Stream of EVA®’s produces a current intrinsic value
LCRT CER3 =
– Gross Assets Exclude Goodwill4
Real Market Derived Investor’s Discount Rate
Cash Value Added = (CER – Market Derived Discount Rate) * C$ Gross Invested Capital
Returns fade toward a company specific CER Fade-To
DCF produces a current intrinsic value
1 Equivalently, Total Capital Employed = Debt + Equity = Net Assets
2 EVA® is a registered Trademark of Stern Stewart.
3The ratio version of CER with sinking fund depreciation closely parallels the IRR version for positive cash flows, but, unlike the IRR version, continues to calculate for start-ups and firms in financial distress, when the gross cash flow becomes negative. Sound return performance measures must calculate from boundary to boundary of the universe.
4Effect of Goodwill included in the valuation as the increase in debt assumed or shares exchanged. Including Goodwill in the C$ Gross Assets biases the operating return and likely returns on incremental investments. Goodwill does not require cash to replenish it as with other operating assets.
Net Operating Profit After Tax
Depreciated Historical Dollar Net Assets
Operating Gross Cash Flow - Sinking Fund Depreciation
Sources: Financial Statements and Price Data – CapitalIQ & CoreData - Calculations – LCRT Platform
EMPIRICAL DIFFERENCES BETWEEN EMPIRICAL DIFFERENCES BETWEEN STERN STEWART AND LCRTSTERN STEWART AND LCRT
Stern Stewart Empirical Evidence relies on Market
Value Added versus EVA® scatter correlations on Russell 3,000, both on individual company basis and portfolio of companies basis
LCRT Empirical Evidence relies on tracking
error of intrinsic spot value versus actual price @ Fiscal Year + 3 Months to compare multiple models and various parameters for each model with full transparent audit trails on entire universe of about 30,000 company-years
– LCRT 1st Generation– LCRT without enhancements– LCRT without non-recurring add-back– LCRT 2nd Generation Research Model5
– Residual Income (from joint research with Sally Webber from NIU, based on Quest for Value.)
– Free Cash Flow– Feltham-Ohlson
5Treats equity as an option on the returns, growth, size, and capital structure of each firm, based solely on historical data without analyst intervention. Since the LCRT research model places all the risk in the cash flows, it successfully employs a single discount rate each year for all firms in the super sector, without systematic model structural errors in the Susan Mangiero Model Risk sense.
Sources: Financial Statements and Price Data – CapitalIQ & CoreData - Calculations – LCRT Platform
IN A CAREFULLY IN A CAREFULLY CONTROLLED CONTROLLED
EXPERIMENT IN AN EXPERIMENT IN AN ECONOMICS ECONOMICS
LABORATORY, VERNON LABORATORY, VERNON SMITH et. al. SMITH et. al.
DEMONSTRATES DEMONSTRATES SIGNIFICANT SIGNIFICANT
DIFFERENCES OF TRADED DIFFERENCES OF TRADED PRICES FROM KNOWN PRICES FROM KNOWN
INTRINSIC VALUESINTRINSIC VALUES
Vernon L. Smith, Gerry L. Suchanek, and Arlington W. Williams, “Bubbles, Crashes, and Endogenous Expectations in Experimental Spot Asset Markets,” in Vernon Smith, Papers in Experimental Economics, Cambridge University Press, Cambridge, 1991, pp. 339-371, chart from p. 352.
Sources: Financial Statements and Price Data – CapitalIQ & CoreData - Calculations – LCRT Platform
NOTICE THE SAME PATTERN IN AN INTRINSIC VALUE CHART NOTICE THE SAME PATTERN IN AN INTRINSIC VALUE CHART WHICH ENABLES US TO VISUALIZE THE MEASUREMENT OF WHICH ENABLES US TO VISUALIZE THE MEASUREMENT OF
ACCURACY OF A DCF MODEL PRICE ACCURACY OF A DCF MODEL PRICE LEVEL LEVEL FOR HPFOR HPUSING ONLY ACTUAL REPORTED FINANCIAL DATA AND THE SAME GLOBAL USING ONLY ACTUAL REPORTED FINANCIAL DATA AND THE SAME GLOBAL
PARAMETERS ACROSS THE ENTIRE UNIVERSE TO DRIVE A MECHANICAL LIFE PARAMETERS ACROSS THE ENTIRE UNIVERSE TO DRIVE A MECHANICAL LIFE CYCLE FORECAST OF CASH FLOWS FOR EACH COMPANYCYCLE FORECAST OF CASH FLOWS FOR EACH COMPANY
Notice the large high low variation around the intrinsic valuations,
providing opportunity for profitable trading
The Absolute “Tracking” Error Intrinsic Value vs. Actual Equals the Absolute Geometric Mean Error
Between The Intrinsic Value Red Line And Closing Prices at Fiscal Year + 3 Months
Sources: Financial Statements and Price Data – CapitalIQ & CoreData - Calculations – LCRT Platform
FOR HEWLETT-PACKARD, A FREE CASH FLOW MODEL FOR HEWLETT-PACKARD, A FREE CASH FLOW MODEL DISPLAYS LOWER ACCURACY THAN LCRTDISPLAYS LOWER ACCURACY THAN LCRT
(OF COURSE, H-P IS ONLY A SAMPLE OF ONE)(OF COURSE, H-P IS ONLY A SAMPLE OF ONE)
Sources: Financial Statements and Price Data – CapitalIQ & CoreData - Calculations – LCRT Platform
COMPARISON OF FELTHAM-OHLSON COMPARISON OF FELTHAM-OHLSON AND FREE CASH FLOW PERPETUITYAND FREE CASH FLOW PERPETUITY
Feltham-Ohlson Based on market value of
equity/ operating assets regressed against return on assets, change in return on assets, and growth rate in assets
From Jing Liu and James A. Ohlson, “The Feltham-Ohlson Model: Empirical Implications,” Journal of Accounting, Auditing and Finance, 2000, v15 [3, Summer], pp. 321-331, especially p. 326-327.
Programmed with the aid of Sally Webber, Accounting Professor, Northern Illinois University
Free Cash Flow Perpetuity Based on growing free cash
flow for T years and capitalizing the terminal year’s free cash flow into perpetuity
Free cash flow = income after taxes + depreciation and amortization – non-operating items after tax – normalized capital expenditures – working capital additions
The terminal year’s cash flow is capitalized by a CAPM nominal discount rate less a nominal growth rate
From specifications by Dan Van Vleet of Willamette
Sources: Financial Statements and Price Data – CapitalIQ & CoreData - Calculations – LCRT Platform
COMPARISON OF RESIDUAL COMPARISON OF RESIDUAL INCOME AND LCRTINCOME AND LCRT
Residual Income From PV of growing excess
residual income (EVA®) for T years plus release of capital at terminal value employing a CAPM cost of capital
Bennett Stewart, The Quest for Value, Harper Business, 1991, especially p. 324-325.
Programmed with the aid of Sally Webber, Accounting Professor, Northern Illinois University
LifeCycle Returns (LCRT) From PV of net cash flows for
50+ years using a market derived discount rate
Net cash flows derive from fading growth rates and cash economic returns applied to constant dollar gross investment less replacement assets less growth in gross investment
See Bartley J. Madden, CFROI Valuation: A Total System Approach to Valuing the Firm, Butterworth-Heinemann, Oxford, 1999 and LCRT.com
Sources: Financial Statements and Price Data – CapitalIQ & CoreData - Calculations – LCRT Platform
TRADITIONAL ACCOUNTING MEASURES FIRST TRADITIONAL ACCOUNTING MEASURES FIRST UNDERSTATE AND THEN OVERSTATE ECONOMIC UNDERSTATE AND THEN OVERSTATE ECONOMIC
RETURNS AS ASSETS AGERETURNS AS ASSETS AGE(ASSUMING CONSTANT OUTPUT = CONSTANT DOLLAR LEVEL ANNUITY)(ASSUMING CONSTANT OUTPUT = CONSTANT DOLLAR LEVEL ANNUITY)
(A DESIRED ANNUAL PERFORMANCE MEASURE REFLECTS THE PROJECT IRR)(A DESIRED ANNUAL PERFORMANCE MEASURE REFLECTS THE PROJECT IRR)
NOTE: The Annual CER
each and every year precisely equals the IRR of the project.
Sources: Financial Statements and Price Data – CapitalIQ & CoreData - Calculations – LCRT Platform
CASH ECONOMIC RETURNS FADE (REGRESS) CASH ECONOMIC RETURNS FADE (REGRESS) TOWARD THE MEAN, BUT NOT ALL THE WAYTOWARD THE MEAN, BUT NOT ALL THE WAY
THE 10THE 10THTH DECILE FADES DOWN, BUT NOT ALL THE WAY; DECILE FADES DOWN, BUT NOT ALL THE WAY; THE 1THE 1STST DECILE FADES UP, BUT NOT ALL THE WAY DECILE FADES UP, BUT NOT ALL THE WAY
-10-505
10152025303540
1994 1995 1996 1997 1998 1999 2000 2001 2002 2003
Year
Ca
sh
Ec
on
om
ic R
etu
rn 1st2nd3rd4th5th6th7th8th9th10th
Median of Each DecileNote: Competitive Pressure Forces High
Returns Down; Investor and Debt Pressure ForcesLow Returns Up; Most All the Fade Occurs in 5 Years
1994-1999
Industrials Constant Dollar Gross Investment > $100 Million in 1994, N = 1,267
Sources: Financial Statements and Price Data – CapitalIQ & CoreData - Calculations – LCRT Platform
LCRT’S RESEARCH METHODOLOGY CONTRASTS LCRT’S RESEARCH METHODOLOGY CONTRASTS SHARPLY WITH THE TRADITIONAL VALUATION SHARPLY WITH THE TRADITIONAL VALUATION
APPROACHAPPROACH
Traditional Approach Forecasts 3-10 Years of Cash
Flows Applies Perpetuity or Multiple
for Terminal Value Discounts to Present (“plan
valuation”) Implicitly assumes the
structure and parameters of the terminal valuation are robust and accurate or “plugs” the parameters to explain current price
Fails to measure model risk (e.g. Susan Mangiero)
LCRT Methodology Employs only actual data to
empirically test robustness and accuracy of “spot intrinsic valuation” models and parameters
Extends the best models to use as terminal values in traditional “plan intrinsic valuations”
May eventually test the best models with forecast security analyst data
Sources: Financial Statements and Price Data – CapitalIQ & CoreData - Calculations – LCRT Platform
EMPIRICAL EVIDENCE:EMPIRICAL EVIDENCE: LCRT’s MODEL IS 28-67% MORE ACCURATE THAN LCRT’s MODEL IS 28-67% MORE ACCURATE THAN
OTHER MODELS (at 50OTHER MODELS (at 50thth Percentile) Percentile)
LOG2 of % Absolute Model Error versus Actual Price -
Fiscal Year +3 Months 1994-200247 63 79
67
Cumulative % of Universe
Sources:Financial Statements and Price Data – CapitalIQCalculations - LCRT’s PlatformConstant Dollar Gross Investment > $100 Million20,957 Company-Years; 1994-2002; Industrials
Sources:Financial Statements and Price Data – CapitalIQCalculations - LCRT’s PlatformConstant Dollar Gross Investment > $100 Million, Panel Data from 1994-2002, 17,697 Company-Years
Sources: Financial Statements and Price Data – CapitalIQ & CoreData - Calculations – LCRT Platform
FREE CASH FLOW AND LCRT INTRINSIC VALUES FREE CASH FLOW AND LCRT INTRINSIC VALUES PERFORM THE BEST TO SEPARATE “WINNERS” FROM PERFORM THE BEST TO SEPARATE “WINNERS” FROM
“LOSERS”“LOSERS”
Sources:Financial Statements and Price Data – CapitalIQCalculations - LCRT’s PlatformConstant Dollar Gross Investment > $100 Million20,957 Company-Years; 1994-2002; Industrials
Sources:Financial Statements and Price Data – CapitalIQCalculations - LCRT’s PlatformConstant Dollar Gross Investment > $100 Million, Panel Data from 1994-2002, 17,697 Company-Years
Sources: Financial Statements and Price Data – CapitalIQ & CoreData - Calculations – LCRT Platform
UNDER (OVER) INTRINSIC VALUATION VERSUS UNDER (OVER) INTRINSIC VALUATION VERSUS CER ILLUSTRATES EMPIRICAL VALUE AUDIT CER ILLUSTRATES EMPIRICAL VALUE AUDIT
ANALYSIS OF OUTLIERS AND PATTERNSANALYSIS OF OUTLIERS AND PATTERNSCER Fade-To
Sources: Financial Statements and Price Data – CapitalIQ & CoreData - Calculations – LCRT Platform
NEXT GENERATION LCRT MODELNEXT GENERATION LCRT MODEL Place all risk and other effects in the cash flows, so a singlesingle discount rate
applies to ALLALL firms in each super sector for each year (22,000-115,000+ company-years 1994-2003)
Treat equity as an option on the cash economic returns, growth, capital structure, and restructuring potential of the operating assets (using only disclosed historical data to drive the model’s cash flow forecast)
– Refine company CER Fade-To’s and Fade Rates to reflect empirical realities across the entire CER spectrum from boundary to boundary, using option functions; use a put function for start-up CER Fade-to’s
– Refine asset growth fade rates to reflect market expectations– Employ an option pricing function to quantify the deadweight loss of
bankruptcy and a [0,1] function to describe the loss in intrinsic value of the equity put for any debt
– Use a call option to describe the market expected increase in cash flows due to restructuring from excessive debt overhang (the Michael Jensen effect)
– Divide the intrinsic value employing one uniform discount rate for all firms into its debt and equity components
Sources: Financial Statements and Price Data – CapitalIQ & CoreData - Calculations – LCRT Platform
CONCEPUTAL COMPARISON OF CONCEPUTAL COMPARISON OF THREE LCRT MODELSTHREE LCRT MODELS
LCRT Research– Place all risk and other effects in the cash flows, so a singlesingle discount
rate applies to ALLALL firms in each super sector for each year (27,000 company-years 1994-2003)
– Treat equity as an option on the cash economic returns, growth, capital structure, and restructuring potential of the operating assets (using only disclosed historical data to drive the model’s cash flow forecast)
LCRT DCF– No option pricing functions– Fade CER’s to 35% of difference between current level and median for
universe– Discount rate adjusted for leverage, asset mix, and asset life
LCRT Without Enhancements– Fade CER’s to median for universe– Discount rate adjusted for leverage
Sources: Financial Statements and Price Data – CapitalIQ & CoreData - Calculations – LCRT Platform
ACROSS THE UNIVERSE OF ABOUT 30,000 COMPANY-ACROSS THE UNIVERSE OF ABOUT 30,000 COMPANY-YEARS 1994-2003, THE MEDIAN ACCURACY OF LCRT’S 2YEARS 1994-2003, THE MEDIAN ACCURACY OF LCRT’S 2NDND
GENERATION MODEL (RESEARCH) IS APPROXIMATELY 27% GENERATION MODEL (RESEARCH) IS APPROXIMATELY 27% GREATER THAN OTHER MODELS (BUT NOT GREATER THAN OTHER MODELS (BUT NOT
OVERWHELMING)OVERWHELMING)
LOG2 of % Absolute Model Error Versus Actual Price -
Fiscal Year +3 Months 1994-2003
Cumulative % of Universe
Sources:Financial Statements and Price Data – CoreDataCalculations - LCRT’s Platform29,488 Company-Years; 1994-2003; Non-Financials
•All Models derived from purely historical data without analyst intervention
•Note the simple 8 X EBITDA valuation is more accurate up to 30% of the Universe compared to Residual income, Feltham-Ohlson, and Free Cash Flow Perpetuity – No wonder security analysts and portfolio managers employ simple multiples
Sources: Financial Statements and Price Data – CapitalIQ & CoreData - Calculations – LCRT Platform
CASH ECONOMIC RETURN FADE TO’S RELY ON CASH ECONOMIC RETURN FADE TO’S RELY ON SMALL FIRM PUT, LARGE FIRM CALL, AND SMALL FIRM PUT, LARGE FIRM CALL, AND
MEDIUM SIZE STRADDLE FUNCTIONSMEDIUM SIZE STRADDLE FUNCTIONS
Sources: Financial Statements and Price Data – CapitalIQ & CoreData - Calculations – LCRT Platform
LCRT PLACES LEVERAGE RELATED RISK IN THE CASH LCRT PLACES LEVERAGE RELATED RISK IN THE CASH FLOWS INSTEAD OF THE DISCOUNT RATE IN ORDER TO FLOWS INSTEAD OF THE DISCOUNT RATE IN ORDER TO EMPLOY A UNIFORM DISCOUNT RATE FOR ALL FIRMS IN EMPLOY A UNIFORM DISCOUNT RATE FOR ALL FIRMS IN
THE SUPER SECTOR EACH YEARTHE SUPER SECTOR EACH YEAR
0
10
20
30
40
50
60
0 25 50 75 100 125 150
% Debt to Debt Capacity (PV of Cash Flows from Existing Assets)
% L
os
s o
f In
trin
sic
Va
lue
Small
Medium
Large
Deadweight Bankruptcy Cost of Higher Leverage[0,1] Function
Sources: Financial Statements and Price Data – CapitalIQ & CoreData - Calculations – LCRT Platform
SELECT LCRT … CHARTS … SELECT LCRT … CHARTS … INTRINSIC VALUE CHARTINTRINSIC VALUE CHART
Use the “Intrinsic Value” to determine whether the company is under/over valued. If the red Intrinsic Value “*” for the last year is above the closing price at Fiscal Year + 3 Months, the company is a “buy” candidate. If the “Intrinsic Value” is below the stock price, the opposite would be true.
Use the information in the lower right corner to determine the accuracy of the intrinsic value model. Look for a low “absolute error” and a low “signed error” along with a high “model robustness.” Absolute error measures the geometric mean of the absolute % difference between actual stock price (hollow dots) at Fiscal Year + 3 Months and the intrinsic value. Signed error measures the geometric mean of the % difference between the stock price and the intrinsic value. Model robustness measures the % of years where the model calculates a value.
Sources: Financial Statements and Price Data – CapitalIQ & CoreData - Calculations – LCRT Platform
SELECT LCRT … OVERRIDES TO ADD ANALYST SELECT LCRT … OVERRIDES TO ADD ANALYST ESTIMATES AND OTHER ANNUAL OVERIDESESTIMATES AND OTHER ANNUAL OVERIDES
Click on the tab marked “Forecasts” and enter values for the “current fiscal year forecast” and the “next fiscal year forecast“ for both sales and EPS. When completed, either click on one of the chart buttons at the bottom of the window or “Save – Exit” to return to the worksheet where your estimates appear. Note, the Nucleus stores the values entered for the next time you retrieve the particular company. Now when you view the “value chart”, the chart displays the forecasts. LCRT has programmed customized processes to include computer readable estimates from the client’s First Call, I/B/E/S, Stock/Val, Value Line or internal sources.
Sources: Financial Statements and Price Data – CapitalIQ & CoreData - Calculations – LCRT Platform
FOR HEWLETT-PACKARD, A FREE CASH FLOW MODEL FOR HEWLETT-PACKARD, A FREE CASH FLOW MODEL DISPLAYS LOWER ACCURACY THAN LCRTDISPLAYS LOWER ACCURACY THAN LCRT
(OF COURSE, HP IS ONLY A SAMPLE OF ONE)(OF COURSE, HP IS ONLY A SAMPLE OF ONE)
Sources: Financial Statements and Price Data – CapitalIQ & CoreData - Calculations – LCRT Platform
COMPANY RELATIVE WEALTH COMPANY RELATIVE WEALTH CHARTCHART
The Relative Wealth Chart provides a strategic overview of the company’s investment policy and results. The first panel on this chart identifies the trend of the company’s Cash Economic Return (CER) Look for positive trends to identify companies that are “buy/hold” candidates.
The second panel shows the “asset growth” for the company. For firms after their start-up period, companies with positive spreads of CER over the discount rate create shareholder value by growing their assets, while companies with negative spreads destroy shareholder value.
The third panel show the “relative wealth” of the company compared to the S&P 500.
Sources: Financial Statements and Price Data – CapitalIQ & CoreData - Calculations – LCRT Platform
Valuation Compliment:Valuation Compliment:Use the Valuation Control Center to test the sensitivity of company Use the Valuation Control Center to test the sensitivity of company
values to changing company inputs and Platform parameters.values to changing company inputs and Platform parameters.Click on the “LCRT” menu and choose “Valuation Control Center…”/Click on the “LCRT” menu and choose “Valuation Control Center…”/
Change any of the numbers in the “Override” column to see the impact at the bottom of the window and the effect on the charts displayed on the right side.
Notice the additional charts with tabs above the Value Chart.
Also view the “standard” value chart by clicking the “View Standard” button.
Use the “Save Overrides” button to save the overrides to re-display when viewing this company.
The display of an “audit trail” represents one of the strongest features of the LCRT Nucleus to show precisely the determination of the present value of cash flow results. Click on “view base audit trail” or “view override audit trail” to display all the calculations used to determine the results shown at the bottom of this window.
Sources: Financial Statements and Price Data – CapitalIQ & CoreData - Calculations – LCRT Platform
The display of an “audit trail” represents one of the strongest The display of an “audit trail” represents one of the strongest features of the LCRT Nucleus to show precisely the determination of features of the LCRT Nucleus to show precisely the determination of
the present value of cash flow results. Click on “view base audit the present value of cash flow results. Click on “view base audit trail” or “view override audit trail” to display all the calculations used trail” or “view override audit trail” to display all the calculations used
to determine the results shown at the bottom of this window.to determine the results shown at the bottom of this window.
Although CSFB explains calculations, HOLT does not provide full transparent audit trails in Excel or VB for every single calculation, every year, and every company! (FORTRAN precludes this.)
Sources: Financial Statements and Price Data – CapitalIQ & CoreData - Calculations – LCRT Platform
Finding a Report: The powerful Nucleus worksheet contains hundreds of reports and analyses of Finding a Report: The powerful Nucleus worksheet contains hundreds of reports and analyses of each company. To ease navigation, a “Go to” feature assists in locating and moving to a report in each company. To ease navigation, a “Go to” feature assists in locating and moving to a report in the worksheet. Click on the “LCRT” menu and choose “GoTo Report…”. A window appears the worksheet. Click on the “LCRT” menu and choose “GoTo Report…”. A window appears containing either a list of all the reports or a tree structure allowing you to locate the particular containing either a list of all the reports or a tree structure allowing you to locate the particular report. For this explanation, use the “Tree” structure. If the “Tree View” is not displayed, click on report. For this explanation, use the “Tree” structure. If the “Tree View” is not displayed, click on the tab marked “Tree View”.the tab marked “Tree View”.
Sources: Financial Statements and Price Data – CapitalIQ & CoreData - Calculations – LCRT Platform
Locate the “Comparison of Models Intrinsic Values Locate the “Comparison of Models Intrinsic Values Chart” and either double-click on the name or click Chart” and either double-click on the name or click
once and then click on the “Go” button at the once and then click on the “Go” button at the bottom of the window.bottom of the window.
Sources: Financial Statements and Price Data – CapitalIQ & CoreData - Calculations – LCRT Platform
This particular report compares the valuations and tracking errors of all the models in This particular report compares the valuations and tracking errors of all the models in the LCRT Nucleus. The ability to “trace” the source for all calculations represents one the LCRT Nucleus. The ability to “trace” the source for all calculations represents one
of the prime benefits of using Excel as the base for the LCRT Nucleus. To use this of the prime benefits of using Excel as the base for the LCRT Nucleus. To use this feature, move to the cell in question and click on “Tools”, “Formula Auditing” and feature, move to the cell in question and click on “Tools”, “Formula Auditing” and
“Trace Precedents”. Follow the lines up to the source of the values for the particular “Trace Precedents”. Follow the lines up to the source of the values for the particular cell.cell.
Sources: Financial Statements and Price Data – CapitalIQ & CoreData - Calculations – LCRT Platform
ADJUSTING USER LEVELADJUSTING USER LEVEL To display additional or less
detail for a company, modify your “level” by clicking on the “LCRT” menu and then clicking on “User Display Level”.
Choose the appropriate level of detail and then click “Set level”. This may take a few minutes to display the rows in the worksheet associated with the level you select. The Platform remembers your choice the next time you reference the worksheet.
Sources: Financial Statements and Price Data – CapitalIQ & CoreData - Calculations – LCRT Platform
USING THE LCRT DCF MODEL, 57% OF THE USING THE LCRT DCF MODEL, 57% OF THE APPROVED LIST IS OVER-VALUED AND 72% (100-APPROVED LIST IS OVER-VALUED AND 72% (100-28) IS MORE OVER-VALUED THAN THE UNIVERSE28) IS MORE OVER-VALUED THAN THE UNIVERSE
Any one of the following three hypotheses could be true:
– 1. Approved List may pick more “losers” than “winners”
– 2. OR Approved List may pick more “winners” than “losers”
– 3. OR Employing both the Approved List and LCRT’s valuation may pick more “winners” than “losers”
Empirical Tests to distinguish which Hypothesis of the three is most true
– Translate each dimension of the beliefs used to produce the Approved List into testable valuation models
– Back test each model’s accuracy and predictive capability
– Test combination of Approved List implicit valuation models and LCRT
Feedback from the empirical results will improve the stock selection PROCESS
Approved List
Universe
Median N Approved List -11.3 84Universe -6.2 1,000
Sources: Financial Statements and Price Data – CapitalIQ & CoreData - Calculations – LCRT Platform
A BETTER EXPLANATORY MODEL IS A BETTER EXPLANATORY MODEL IS MORE PREDICTIVEMORE PREDICTIVE
Accuracy: % Explanatory Price Level
1009080706050403020100
Acc
ura
cy:
% P
red
ictiv
e C
ap
ital G
ain
100
90
80
70
60
50
40
30
20
10
0
R2 = 0.473N = 2,752
OLS
Least AbsoluteDeviation
LCRT Intrinsic Value Model
These results support the intuition of HOLT’s clients, who in the late 1980’s said, “I only employ the model for buy/sell decisions when it tracks well.”
“Few strokes separate the best from the worst professional golfers.”
Like golf, lower scores indicate more accuracy.
This chart violates the instantaneously efficient market hypothesis. It represents an “anomaly” consistent with behavioral finance theory.