Linking the Ohlson (1995) model with Monte Carlo simulation

Monte Carlo simulation is a widely applied method in capital budgeting analysis and investment appraisals (e.g. Smith, 1994; Reed and Stephan, 2010), yet less focus has been incorporated to stock valuation in the topic’s academic research and literature.

According to Reed and Stephan (2010), Monte Carlo simulation allows a decision-maker to address which variables are the most important. As the key variables of the Ohlson (1995) model – earnings and book value of equity capital – have their own probability distributions, calculation of mean and standard deviation of the wanted outcome or the expected stock price may be difficult (Wagle, 1967) and thus advocates the use of Monte Carlo simulation. In respect of the Ohlson (1995) model, probability distribution and consistency of residual income (𝑅𝐼_𝑡) is rarely available in financial statements. However, the particular bottom-line items or the model’s key variables that compose the residual income may well have plausible and reliable means and variances. Imitating Smith (1994), Monte Carlo simulation involves the replacement of linear estimates of residual income for each year with probability distributions for the variables affecting the residual income, which reflects the uncertainty associated with the variable concerned. The probability distribution is also useful when the average present value is misleading because it is unlikely to occur (Pedersen, 2013).

Pedersen (2013) also points out that Monte Carlo simulation is a useful tool when the probability distributions are not possible to derive analytically, either because it is too complex or because the stochastic variables of the model are not from simple, well-behave probability distributions. As regards to the simulated Ohlson (1995) model, the probability distributions of the expected growth of the key variables are assumed to be normally distributed and thus considered quite simple and well-behaved, but due to other assumptions such as the temporary nature of losses (Hayn, 1995) discussed in more detail in the following chapter advocates the usage of Monte Carlo simulation. Additionally, Hull

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(2014) points out that Monte Carlo simulation tends to be numerically more efficient than other procedures when there are three or more stochastic variables. The conducted scenario analysis for the FY2015, which is based on the simulated Ohlson (1995) model as well, contains four different variables each of which has its own predetermined probability distribution. Additionally, according to Reed and Stephan (2010), simulation software permits the financial modeller to specify (positive or negative) correlations and quantify their effects on the probability of success of failure. The constructed simulation model does not contain specifications of correlations between the applied variables, but the practical functionality of the model was ensured for example by adding constraints so that the distribution of wealth cannot result in negative values.

In the following chapter, the thesis discusses the methodology of the conducted analyses in more detail.

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3 Methodologies, hypotheses and the case company

This chapter introduces some of the key features and figures of the case company KONE Corporation and its position in the elevator and escalator industry. After the brief company presentation, the chapter states the three hypotheses of this thesis and discusses the empirical methodology conducted in the studies.

Case company: KONE Corporation

The crown jewel of the current Finnish business environment, KONE, was founded in 1910. During its 100 years as an industrial engineering company, KONE has been involved in businesses as different as textile manufacture, medical technology and the design of hydraulic piping systems. The company’s main focus, however, has always been the elevator and escalator business. As for its core business activities, KONE Corporation currently manufactures, installs and services elevators, escalators and automatic building doors and integrated solutions in more than 1,000 regional offices in almost 60 countries worldwide whilst headquartered in Helsinki, Finland. It is now one of the global leaders in the elevator and escalator industry among its three main competitors Otis (part of the United Technologies group), Schindler Group and ThyssenKrupp elevator (part of the ThyssenKrupp group). On 1 June 2005, Kone Corporation demerged into two separately listed firms KONE Corporation and Cargotec Corporation.

On the right in Figure 2 is a summary of the historical stock prices of

KONE Corporation’s

class B shares from 1.6.2005 to year-to-date (YTD). The class B shares are listed on the OMX Helsinki Stock Exchange. In respect of the stock prices, the

company has shown steady growth since the demerger. According to Talouselämä 500, KONE Corporation was the 7th _{largest company in Finland in terms of net sales in 2014.}

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KONE Corporation is the largest family-owned business in Finland. The Chairman of the Board and the former CEO of the company is Mr. Antti Herlin, who owns 21.44 % of the company’s shares and 61.76 % of the voting shares (FY2014). The current CEO of KONE Corporation is the company’s former CFO Henrik Ehrnrooth. At the end of 2014, KONE Corporation employed more than 47,000 people of which 44 % were located in EMEA- region, 12 % in America and 44 % in APAC.

In the FY2014, new equipment or elevators and escalators accounted for 55 % of the total sales of €7,334.5 million. Maintenance (32 %) and modernization (13 %) accounted for the remaining part. In 2014, KONE’s market share was estimated at 19 % measured by new elevators and escalators.

KONE Corporation’s company performance and the key financial ratios are presented in the summary in figures below. The financials are from the period 2007-2014.

Table 1 KONE Corporation 2007-2014 – summary in figures

KONE Corporation was chosen as the case company for the thesis because the author considers its business-model both lucrative and sustainable, its corporate structure solid and financial position healthy and above all, its business easily understandable. Additionally, KONE Corporation is an attractive investment both in terms of growth in the share value and in terms of distribution of dividends.

Consolidated Statement of Income 2007 2008 2009 2010 2011 2012 2013 2014

Sales, MEUR 4 079 4 603 4 744 4 987 5 225 6 277 6 933 7 334 Operating income, MEUR 321 558 567 696 725 791 953 1 036 - as percentage of sales, % 7,9 12,1 12,0 14,0 13,9 12,6 13,7 14,1 Net income, MEUR 180 418 466 536 644 611 713 774

Consolidated Balance Sheet, MEUR 2007 2008 2009 2010 2011 2012 2013 2014

Non-current assets 1 083 1 178 1 218 1 423 175 1 937 1 938 2 169 Current assets 1 277 1 478 1 634 2 725 2 977 3 197 3 405 4 191 Total equity 749 1 036 1 339 1 601 2 034 1 834 1 725 2 062 Non-current liabilities 334 328 180 203 208 302 262 321 Provisions 87 50 100 99 89 136 139 137 Current liabilities 1 191 1 243 1 232 2 245 2 397 2 862 3 217 3 839 Total assets 2 360 2 657 2 852 4 148 4 727 5 134 5 343 6 360 Other Data 2007 2008 2009 2010 2011 2012 2013 2014

Average number of employees 30 796 33 935 34 276 33 566 34 769 38 477 41 139 45 161 Number of employees at end of period 32 544 34 831 33 988 33 755 37 542 39 851 43 298 47 064

Key Ratios 2007 2008 2009 2010 2011 2012 2013 2014

Return on equity, % 24,9 46,8 39,3 36,5 35,5 32,1 40,1 40,9 Return on capital employed, % 18,6 35,9 34,0 34,8 34,3 29,4 36,4 37,7 Total equity/total assets, % 31,7 39,0 47,0 49,3 54,0 47,1 43,7 43,6 Gearing, % 12,2 -5,6 -37,7 -46,8 -40,8 -31,3 -36,1 -44,2

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