Teuer Furniture Case Study

Teuer Furniture A

Memorandum

Teuer Furniture’s valuation per share based on our discounted forecast cash flow methodology is $31.03. The discounted cash flow methodology is based on forecasting the free cash flows for two time periods (2013-2018) and thereafter in perpetuity.

Estimating free cash flow involves forecasting variables across the three main financial statements (Income statement, Balance Sheet and Cash flow statement). The variables are segregated by the treatment and ordered in priority of its impact on the final forecast. Sales growth at an individual cohort level (i.e – break sales by new store sales by year and old store sales by year), the rate of new store openings, and inventory assumptions have a disproportionate impact on the forecast methodology.

In particular, high inventory levels mean that higher sales growth actually hurts the Company’s free cash flow in the short run, due to the increase in net working capital, and opening too many stores too quickly can eat up all the Company’s free cash flow through the projection period.

Factor

Treatment

  • Consolidated at a store cohort level (see Exh 1) based on the growth profile of each existing and new store
  • Assumes high growth in initial years following opening, tapering off to flat growth on an individual level (all growth in out years is driven by macro factors)
  • We used the furniture industry growth rate as our primary macro factor, unadjusted for GDP or inflation
  • We multiplied the individual cohort revenues each of the post-2010 cohorts by a “macro index” that was constructed in a compounding fashion from the furniture industry growth rate
  • We drove this at a % of sales level, based on the historical margins various cohorts exhibited between 2004 and 2012
  • SGA excluding depreciation and advertising (% sales)
  • We drove this at a % of sales level, based on the historical margins various cohorts exhibited between 2004 and 2012
  • We drove this at a % of sales level, based on the historical margins various cohorts exhibited between 2004 and 2012
  • Accounts Receivable (% sales)
  • We drove this at a % of sales level, based on the historical margins various cohorts exhibited between 2004 and 2012
  • Inventory (% current year CGS)
  • We drove this at a % of CGS level, based on the historical relationship various cohorts exhibited between 2004 and 2012
  • Accounts Payable (% current year CGS)
  • We drove this at a % of CGS level, based on the historical relationship various cohorts exhibited between 2004 and 2012
  • Accrued expenses (% current year advertising + SGA)
  • We drove this at a % of advertising and SGA level, based on the historical relationship various cohorts exhibited between 2004 and 2012

For the following parameters we made no change to the assumptions made by Teuer’s finance team

  • Rate of new store openings
  • We accepted management’s plans to open two new stores per year through 2015
  • We assumed a 5 year straight line depreciation on capital expenditures, with zero residual value
  • We assumed a 70% refresh cost rate vis a vis original capex required to start up the store that occurred 8 years after store opening – this led us to revise management’s estimations of refresh cost for stores that opened prior to 2012
  • We assumed a 40% tax rate on pre-tax profit
  • We assumed 5% margin on corporate expenses
  • We assumed 12.1% as the cost of capital
  • We assumed a long-term growth rate of 3.5%.  We felt this was reasonable as it was less than GDP growth of 5%
  • The Company had 9.945M shares outstanding
  • We assumed the company would lease all of its square footage at a cost of $20.88 per square foot in 2013, and this cost would increase by 2% per square foot thereafter.
  • We accepted management’s estimation of capital expenditures excluding refresh costs

Our share price calculation process is described below:

  1. Calculate individual store cohort P&Ls using above assumptions
  2. Calculate individual store cohort balance sheets using above assumptions
  3. Consolidate 1 and 2
  4. Derive a net income figure from the consolidated IS: NI = Sales – CGS – SG&A – Depreciation - Advertising – Tax Rate x Pretax Profit
  5. Derive non-cash items and cash outflows from the consolidated balance sheet and total capex from individual store cohort balance sheets
  6. Calculate the FCF as follows: FCF = NI – capex – ΔNWC + Depreciation
  7. Use the FV of the final FCF in 2019 to calculate a perpetuity value for the business assuming 12.1% cost of capital and 3.5% growth rate
  8. Add the perpetuity value to the FV of the final FCF
  9. Discount all FCFs to present value using 12.1% cost of capital
  10. Add all discounted values together to get value of businesses operating assets through the NPV of their future cash flows
  11. Subtract debt and add cash to get equity value of business. In this case, both were zero as the firm did not raise capital since 2008 and the firm’s cash flow in excess of its investments always returns to the shareholders each year in the form of dividends. so they did not impact our analysis
  12. Divide equity value by number of shares outstanding to get final value of $31.03 per share

Note: Sales projection is one of the most critical activities in valuing the company. We understand that given the nature of the industry, (high end furniture) it is highly sensitive to GDP growth. In an ideal scenario given resources, we would like to build a co-relation model, which would derive an elasticity metric w.r.t GDP. This would  in turn give us an indexed sales number that would be more realistic. However, given our limitations, we have segmented the Sales numbers by new store sales by year (Eg: rate of growth of a new store in year 1, year 2 and so on) and used that to project for future sales.

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Author Bio

Mitchell Petersen is the Glen Vasel Professor of Finance. He has published widely in finance and economics. Professor Petersen's research is in the area of empirical corporate finance—the questions of how firms evaluate potential investment projects and how they fund such projects. His recent writing focuses on the funding of small firms and how such funding has been altered by technology and changes in the financial (banking) market. He was awarded the Smith-Breeden Prize for Outstanding Paper in the Journal of Finance in 1995 (for his paper “The Benefits of Lending Relationships: Evidence from Small Business Data”) and the Michael Brennan Award for Best Paper in the Review of Financial Studies in 1998 (for his paper “Trade Credit: Theories and Evidence”). He was runner-up for the Brennan Award in 2008 (for his paper “Does the Source of Capital Affect Capital Structure”) and 2010 (for his paper “Estimating Standard Errors in Finance Panel Data Sets: Comparing Approaches”).

He has been a member of the editorial board of various journals, including the Journal of Finance, Financial Management, Review of Financial Studies and the Journal of Financial Intermediation. He is also a research associate with the National Bureau of Economic Research (NBER) and is a member of the Moody's Academic Advisory and Research Committee and served on the Board of Directors of L.R. Nelson. Professor Petersen was awarded the Sidney J. Levy Teaching Award in 1996, 1999, 2001, 2003, 2006, 2008, 2010, and 2012 and was voted the Kellogg Professor of the Year in 2000, the Executive MBA Outstanding Professor in 2008, 2010, and 2011, and Kellogg Alumni Professor of the Year in 2010. He received his Ph.D. in Economics from the Massachusetts Institute of Technology. Prior to joining Kellogg Professor Petersen taught at the University of Chicago.

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