In the context of Lindt & Sprüngli valuation a Sensitivity Analysis is presented to fully understand the impact of several variables namely the return on invested capital, weighted average cost of capital, risk free, market risk premium, capital structure, beta and terminal growth rate. This analysis was realized with the purpose of helping investors to make conscient decisions

Costa, Mariana De Barros Fernandes Ferreira Da

English

Repositório da Universidade Nova de Lisboa

A Work Project, presented as part of the requirements for the Award of a Master Degree in Finance from the NOVA – School of Business and Economics.       Lindt & Sprüngli Sensitivity Analysis         MARIANA DE BARROS FERNANDES FERREIRA DA COSTA & 34009             A Project carried out on the Master in Finance Program, under the supervision of:  Professor FILIPA FRADE DE CASTRO           03/01/2020     Abstract  In the context of Lindt & Sprüngli valuation a Sensitivity Analysis is presented to fully understand the impact of several variables namely the return on invested capital, weighted average cost of capital, rsk free, market risk premium, capital structure, beta and terminal growth rate. This analysis was realized with the purpose of helping investors to make conscient d cisions.            Keywords: Sensitivity Analysis, Three Scenarios, Beta                                This work used infrastructure and resources funded by Fundação para a Ciência e a Tecnologia (UID/ECO/00124/2013, UID/ECO/00124/2019 and Social Sciences DataLab, Project 22209), POR Lisboa (LISBOA-01-0145-FEDER-007722 and Social Scien es DataLab, Project 22209) and POR Norte (Social Sciences DataLab, Project 22209).   LINDT & SPRÜNGLI COMPANY REPORT      PAGE 33/40    Mariana’s Insight: Sensitivity Analysis  This insight aims to give a deeper perspective on hw the different assumptions undertaken in the model affect the final share price as well as the inv stors decision towards the stock (buy, hold, sell). In this sence, a Sensativity Analysis was computed with the main purpose of determining the impact of one or more independent variables on a dependent variable (share price). The variables were analysed under 3 scenarios, the assumptions considered for the base scenario are explained in detail under the sections 4.1.1 Market Dimension and 4.1.2 Market Share and Sales Analysis of the report. The assumptions for both the  best and worst case-scenario are described in the section 7. Scenario Analysis of the report. Initially the independent variables used were WACC and ROIC since they provide an aggreagated impact of several effects (beta, risk free, etc) on the final share price.          Considering the current values (ROIC of 3.9% and WACC of 3.26%) under the base (Table 1) and worst scenario the final output would be a hold. However, under the best scenario the output is a buy. As expected the value of the firm is maximized when the RONIC is maximized and the WACC is minimized. However to understand what variable impacts the WACC and the model the most a separate analysis of the variables was conducted in order to be more precise:      Sensitivity Analysis   terminal WACC   81929.6 3.18% 3.28% 3.26% 3.48% 3.58% ROIC 3.70% 77595.5 72969.7 72969.7 65705.7 62802.9 3.80% 81360.0 76392.9 76392.9 68593.0 65476.0 3.90% 84931.5 79640.6 79640.6 71332.2 68012.1 4.00% 88324.4 82725.9 82725.9 73934.4 70421.3 4.10% 91551.7 85660.6 85660.6 76409.7 72713.0 4.20% 94625.4 88455.7 88455.7 78767.2 74895.5 Table 1: Sensitivity Analysis using WACC and ROIC – Base Scenario Source: Author elaboration   LINDT & SPRÜNGLI COMPANY REPORT      PAGE 34/40    Source: Author elaboration Source: Author elaboration  Cost of Equity: Market Risk Premium (MRP)   The MRP was computed by taking the proportion of Lindt’s sales in each specific country as it is presented on Table 2 and corresponds to 6.39%.  Risk premium includes five main risks: (1) business risk, (2) financial risk, (3) liquidity risk, (4) exchange-rate risk, and (5) country risk. The last one, can be found on the column Damodaran ERP of Table 2.  The five types of risks vary with time and external events for eg. the impact of Brexit on the exchange rate of CHF/GBP that changed from 1.4459 in 2016 (before Brexit announcement) to an average of 1.27445 during 2018. This event impacts Lindt valuation since the UK represents 7% of Lindt’s sales in 2018 (see section 3.2.1 Political factors of the report for a detailed explanaition).  As we can see on tables 3.1, 3.2 and 3.3 below an increase in MRP increases WACC and therefore diminishes the value of the firm. Under the 3 scenarios the expected MRP corresponds to hold. However it is relevant to notice that if the MRP is e timated through the MSCI World Index, corresponding to a value of  7.92% the recommendation would therefore be sell under the 3 scenarios. For this reason its important to consider possible volatility in this variable.  Table 3.1: MRP – Base Case       Table 3.2: MRP – Best Case      Table 3.3: MRP– Worst Case  Cost of Equity: Risk Free For the risk free rate, the 10-year bond of the Swiss government was used since the valuation carried out in CHF, the current rate is (0.4)%. The fact that it is negative represents the overall instable  Table 2: Market Risk Premium    LINDT & SPRÜNGLI COMPANY REPORT      PAGE 35/40    Source: Author elaboration Source: Author elaboration market conditions as well as investors willingness to buy safety. If this conditions change the risk free rate might as well change and the impact of possible changes is presented bellow on tables 4.1, 4.2 and 4.3. Under the current rate in the three scenarios the recommendation is hold.   Table 4.1: Rf – Base Case         Table 4.2: Rf – Best Case          Table 4.3: Rf – Worst Case All in all, a small change in the Rf rate does not seam to have a huge impact on the final share price(Table 4). However, if the Rf rate stops being negative the recommendation becomes sell. This happens since an increase in the rf rate not only makes equity more expensive but usually also increases the cost of debt. Cost of Equity: Beta  To compute Lindt’s beta two approaches were used: historical beta and comparable companies. We opted for the historical beta given the lack of truly comparable companies for Lindt as it is explained in detail under the section 4.2 WACC of the report. The unlevered historical beta corresponds to 0.53 and the levered beta to 0.55. The analysis presented on tables 5.1, 5.2 and 5.3 was computed using the levered beta and under the three scenarios the current value corresponds to a hold. Table 5.1: Beta – Base Case           Table 5.2: Beta – Best Case       Table 5.3: Beta – Worst Case  Small difference in the leveraged beta have a huge impact in the share price, suggesting the model is very sensitive to changes in this variable. This is mainly caused by the capital structure of Lindt that has a debt portion of only 4% (D/(D+E)).    LINDT & SPRÜNGLI COMPANY REPORT      PAGE 36/40    Source: Author elaboration Source: Author elaboration  WACC: Capital Structure Regarding optimal capital structure, we used Lindt’s historical D/E ratio of 0.04 and the reasons for it are explained in detail under Gian’s Insight in the Apendix.  As well as in the beta analysis, a small variation in the capital structure also has a significant impact in the final share price, not being necessary a huge increase in the debt level for the analysis to change from an hold to a buy. This suggests that the firm might benefit from increasing the level of debt, meaning the firm has not yet reached the optimal debt level. Furthermore, under the three scenarios the current ratio represents a hold.  Table 6.1: D/E – Base Case         Table 6.2: D/E – Best Case           Table 6.3: D/E – Worst Case    Terminal Value: Terminal Growth rate The terminal growth rate expected has a value of 2.08% and is used to discount the cash flows from the terminal period. The sensitivity analysis done in the tables 7.1, 7.2 and 7.3 shows that changes in the growth rate don’t have a relevant impact on the share price. This suggests that the value derived from the terminal period has less impact on he valuation that the forecasted period which is a positive result.      Table 7.1: G – Base Case          Table 7.2: G – Best Case          Table 7.3: G – Worst Case     LINDT & SPRÜNGLI COMPANY REPORT      PAGE 37/40    Key Takeaways Overall, we can conclude that WACC has a higher impact on Lindt’s valuation than the terminal growth rate  and that the WACC’s variable that seam to have a bigger impact on the model is the Beta. For this reason the final analysis presented on the section 6. Sensitivity Analysis of the report instead of WACC is done with the Beta for a more precise output.  Table 8: Sensitivity Analysis using ROIC and Beta – Base Scenario     Sensitivity Analysis    Leveraged Beta   81929.6 0.37 0.46 0.51 0.55 0.60 ROIC 3.70% -2758011.4 130523.6 93336.6 75133.3 64348.2 3.80% -2963462.0 138193.2 98262.5 78716.1 67135.3 3.90% -3241964.5 148589.9 104939.9 83572.9 70913.4 4.00% -3343545.6 152382.0 107375.4 85344.4 72291.4 4.10% -3519681.9 158957.3 111598.5 88416.0 74680.9 4.20% -3687430.8 165219.5 115620.4 91341.4 76956.5   Additionally, it is important to highlight that the impact of the variables has been considered individually considering everything else remains constant (“Ceteris Paribus”) which is not always the case in real life and it’s important to keep this in mind for decision making.         Source: Author elaboration 

Lindt & sprüngli sensitivity analysis

https://run.unl.pt/bitstream/10362/113705/1/1239155957-16119_Mariana_De_Barros_Fernandes_Ferreira_Da_Costa_2019-20_S1_34009_16-Mariana_Costa_124450_1718878086.pdf

Lindt & sprüngli sensitivity analysis

Abstract

Similar works

Full text

Available Versions

Repositório da Universidade Nova de Lisboa