The Fashion Group

Fashion Group (SGF) is an Australian clothing retailer which functions primarily in the Women’s market. The company first came into operation under the name “Millers” In 1993 and hence since grown to house 5 additional brands under the group portfolio. This report was structured to first discuss the firms’ strategy In navigating the ever changing retail environment, before evaluating its’ current valuation. Following which a credit analysis was performed to determine if additional debt could be taken on to fund future strategic goals.

With the results of the credit analysis, a proposed acquisition deal was structured and finally a final recommendation on what SGF should do was made. For the valuation of SGF, a combination of 2 techniques were used which were the comparable companies and discounted cash flow analysis techniques. Analysis of the comparable companies data was used to arrive at an initial valuation range using trading multiples. Following which, FCC was forecasted for SGF and the values discounted back at the appropriate discount rates to arrive at an implied equity value.

This coupled with a sensitivity analysis based on forecasted growth rates allowed for a comparison with he range obtained from the comparable companies method. A credit analysis was performed to determine the creditworthiness of the company based on past historical financial and ratios. This was performed with the purpose of obtaining a higher loan facility than the current one for future strategic purposes such as a potential acquisition.

Based on the forecasted EBITDA numbers, a sensitivity analysis was performed and found that the new loan amount requested did not place the company at any high risk of default. With the approval of the new loan facility, a potential acquisition was proposed based on the firms’ future strategic goals. Ululation was performed to evaluate if the calculations was beneficial and to determine what price should be offered. Following which, a teaser document was generated summarizing the highlights of the proposed acquisition.

Since then it has transformed into the largest women’s fashion retailer in Australia, with 1091 stores in Australia, New Zealand and the United States (Specialty Fashion Group, 2013). Brands under the company include Millers, City Chic, Crossroads, Katie, Autograph and Rivers. With the exception of Rivers, the 5 other brands sell apparel catered exclusively for women. Business revenues for the past 4 years have been stagnant, with an average change of -0. 2%. Expenses such as rental and employee benefits have been increasing over the same period at an average of 4. 3% and 4. 5% respectively. The poor performance over the period has been attributed to discounting tactics employed to attract customers and the bad conditions facing the Australian retail market (Fishbowls, 2013).

The core strategies of the company include optimizing the supply chain, developing and enhancing customer interaction and increasing sales via different channels . To optimism the supply chain, the company increased the reapportion of products sourced directly from overseas suppliers. This coupled with closer relationships and a favorable exchange rate resulted in a 3. 76% increase in the gross margin for the financial year 2013 (Specialty Fashion Group, 2013). Online sales accounted for 3. 8% of total revenue which was 50% up from the previous year, With the recent acquisition of Rivers, the company reinforces their strategy of increasing their presence in the clothing retailing industry (Cannonading, 2013).

The acquisition also represented Gaff’s entry into the men’s footwear market, and the investment is expected to contribute $77. M to group revenue in the 2013-IFFY (Fishbowls, 2013). 1. 2 Clothing and retailing industry SGF operates within this industry, which excludes online-based retailers and departmental stores. The industry is noticeable for the intense competition between companies and a low market concentration (Manger, 2014). From Figure 1, the top 4 players in the industry capture only 20% of the market while the remaining 80% is shared among a large number of smaller players. It is of note that most players in the industry choose serve only one customer segment instead of targeting the entire market.

Figure 1: Industry concentration and market share of major players Key economic drivers that affect companies in the industry include real household disposable income, consumer sentiment, exchange rate of the Australian dollar and indirectly, consumer savings (Australian National Retailers Association, 2011). Other factors that have a huge impact on Australian retailers include international retailers entering the domestic market and the high rate at which Australians are embracing technology to aid in product search, price comparisons and to complete the purchase. This has led to overseas retailers such as London based SASS actively arresting online shoppers in Australia (Pearson, 2013). Besides online shopping, another significant factor that affects companies in the industry include the arrival of big name international retailers (Ezra, H and Unique) into Australia (Manger, 2014).

With experience and efficiency in managing the supply chain along with streamlining other operational processes, the international retailers have made competition tighter within the industry. Regulation and policy within this industry varies between states in Australia, with the Australian National Retailers Association (ANKARA) slighting that consumers bear the costs of the discrepancy (Australian National Retailers Association, AAA). Regulation regarding trading hours has caused domestic retailers to suffer competitively against online retailers (which do not face such regulations). Hence ANKARA is pushing towards complete deregulation of trading hours in all states (Bibb).

This move is expected to increase consumer demand for clothing and apparel (Manger, 2014). 2. 0 Valuation techniques In the following sections, the valuation techniques used to derive the valuation of SGF was elaborated upon. Acknowledging that each valuation technique is accompanied comparable companies was used to arrive at a valuation of SGF. 2. 1 Comparable companies (transaction multiples) This method was chosen as it provided a fast and convenient method to derive a valuation for SGF. The information required was readily obtained from public data which provided a valuation that was current, based on market perception and sentiment (Rosenberg & Pearl, 2009).

However as the method relies heavily on market data, the valuation derived can be biased during periods of unwarranted market optimism or bearishness. Some feel that by concentrating company information to derive a set of multiples, effect of different drivers on valuation can be hard to discern (Ouzos, Cooper, Sutherland & Eden, 2001). The following four Australian companies were chosen from the clothing retailing industry as comparable companies for SGF: Table 1: Comparable companies profile Comparable companies Core business Adjusted EBITDA margin gross profit margin Premier Investments Limited (MAP) Women’s fashion 12. 7% 61 Noon B Limited (N.B.) 4. 2% 59. 7% Routings Limited (OGLE) 13. 5% 63. % Country Road Limited (CITY) 9. 2% 64. 2% From Table 1, companies were chosen based on their business profile being players in the Australian women’s fashion market as well as employing a multi-channel approach to obtain sales. The financial profiles (EBITDA and gross profit margin) were also considered when making the selection for the comparable. These companies are likely to experience the same economic drivers as SGF, along with the adverse effects that could impact business performance such as revenues and costs. Financial information was analyses up to and including the 2013/2014 interim reports. Acclimatization was performed for Premier Investments Limited and

Routings as both had financial years that ended a month after the rest of the financial of the companies under analysis. The multiples for gross profit, EBITDA and revenue were computed for the 4 comparable and the results are displayed in Appendix 1 . Rental expense was added back to EBITDA, as companies in the retail industry have rent as a significant cost in their operations expense. Doing so would result in a multiple value that best represents the companies in the industries. The decision was made to focus on enterprise value based multiples as they are independent of capital structure. This eliminated any differences brought about by differing capital structures between the comparable.

From the results of the multiples calculations, the comparable were benchmark to the actual multiples of SGF. From the benchmarking of the 3 chosen multiples, N.B. and CITY were observed to be the closest comparable to SGF (Appendix 2). This provided a narrower range for analysis, from which the valuation range could be derived. From Appendix 3, the implied share prices were derived for each of the transaction multiples considered. A tighter valuation range was obtained by comparing the implied valuations from the transaction multiples. Figure 2: Valuation range of SGF derived from comparison of EVE/gross profit and EVE EBITDA From Figure 2, the implied share price of SGF was narrowed down to $0. 6 – $1. 31. 2. 2 Discounted cash flow (adjusted present value) The adjusted present value (PAP) technique is useful when valuing companies that have shifting Debt to Equity ratios and also provides more avenues to account for indirect debt costs. If the costs are not accurately reflected in the pre-tax cost of debt, PAP would provide a more conservative valuation than the weighted average cost of UAPITA (WAC) method (Dominant, 2005). However one of the potential drawbacks of using PAP is the effect of understating or ignoring of the costs of financial distress, which could lead to an overvaluation if the firm in question has high amounts of debt.

With SGF presenting shifting capital structure for the past 5 years, a shifting beta should be used to reflect the dynamic change in risk structure. However due to the constraints faced, the data from the last 3 years was used to determine a fixed beta. 2. 2. 1 Assumptions Historical period analyses (2011 to 2013) financial year, as it best reflects the current equines cycle post global financial crisis (SGF) Future growth rates obtained from IBIS world industry reports Standard deviation of future growth rates used to determine optimistic and pessimistic scenarios was 1. 2% Terminal growth rate used for the company was 0. 5% to reflect increasing competition from global competitors entering the Australian market An average cost of debt of 6. 7% was derived from the average of 2011 to 2013 borrowing facilities From the sliding capital structure over the analyses years and prior, it is clear that SGF has a very low preference of debt. This behavior was assumed to continue into the years ahead and appropriately factored into the valuation in the form of quick repayment (within 2 years) of any debt borrowed Based on the above assumption and the ability to honor its’ payable via scofflaws, the expected bankruptcy cost for the firm was proxy for the risk free rate as it best reflected the period over which the forecast was generated for Beta of 1. 57 and the market risk premium of 7% was used to calculate the cost of equity of 13. 03% using CAMP Forecasts of financial performance were made based on key performance drivers of the firm (expanded on in the next section) 2. 2. 2 Forecasting free cash flow (FCC) As retail companies often focus on sales (revenues) as a driver of growth, it would thus be expected that any forecasted growth should be supported by other related line items. Detailed explanations for each key line item forecasted can be found in Appendix 4. Items such as cost of goods sold (COGS), selling, general and administrative (SAGA) along with capital expenditure (Cape) and rental expense are related to sales, and hence projected margin rates were projected based on a trend line of historical figures.

An average of the individual margins was calculated and used to forecast the individual items (Appendix 5). This process was in line with the assumption that business performance was expected to be similar throughout the projection years. 2. 2. 3 Derivation of an implied share price for SGF Once the individual line items were forecasted, FCC for the respective years were calculated as represented in Table 2 below. For alignment with the company’s practices with regards to debt, the new debt absorbed from the acquisition of Rivers was assumed to be paid back within the immediate 2 years. This resulted in an interest tax shield of $4. Mm when discounted back at the cost of debt of 6. 47% (Appendix 6).

Table 2: Enterprise value derivation for SGF (in $ millions) 2014 2015 2016 2017 2018 Terminal Value BAIT (NONFAT) 14. 197 14. 551 14. 914 15. 14 14. 838 14. 5 Plus: Depreciation and amortization 26. 9 27. 5 28. 6 28. 1 Less: Capital Expenditure 23. 3 23. 9 24. 5 24. 9 24. 4 Less: Changes in NC 0. 495 -0. 772 -0. 794 -0. 486 0. 66 0. 161 FCC 17. 2 18. 9 19. 4 17. 9 139. 0 up of OFFS 157. 2 Plus: UP of interest tax shield 4. 3 Enterprise value 161 . 5 From Table 2, FCC for the respective years were discounted back at the cost of equity of 13. 403%. This resulted in a UP of Offs of $157. M, following which the effect of tax shields from debt were added back in to give an enterprise value of $161. Mm.

From Appendix 7, the equity value of SGF was then derived by adding cash and deducting debt to give $184. Mm. Divided by the number of shares outstanding, this resulted in an implied share price of $0. 90, which was within the range calculated of the transaction multiples result and identical to the current market price. 2. 2. 4 Sensitivity analysis The sensitivity range was selected based off historic standard deviation of growth share prices derived for SGF was $0. 76 – $1. 07. The results of the DC analysis was within the valuation range obtained from the comparable companies method.