The purpose of financial reporting is to provide information that is useful for decision making. Recently, however, there has been a systematic decline in the usefulness of such information. Indeed, the current reporting model seems to be no longer sufficient mainly due to the fact that it ignores many of the nonfinancial intangible factors which are increasingly becoming important in determining corporate value and performance. That is, there is a need for the traditional reporting model to be modified or at least broadened to reflect Intangible Assets (IA) in order to enhance the usefulness of information being provided to different stakeholders. In the absence of mandatory reporting requirements, one alternative way of disseminating information regarding IA is to engage in voluntary disclosure practices. It has also been suggested that companies which would benefit the most from such practice are those originating from emerging economies looking to expand into international markets. While there exists an array of empirical studies which have examined the voluntary disclosure practices of corporations from developed economies, less considered are the reporting practices of emerging market companies regarding their IA. The purpose of this thesis is to examine the voluntary disclosure practices of the top 200 emerging market companies regarding the variety, nature and extent of IA and to consider some of the factors that may be associated with the level of such disclosure. Using a disclosure index based on the Value Chain Scoreboard??? (Lev, 2001), narrative sections of the 2002 annual reports of the top 200 emerging market companies are analysed. The findings indicate that emerging market companies engage in voluntary disclosure practices in order to disseminate different varieties of mainly quantitative IA information to their global stakeholders. Further, the variety and the extent of IA disclosure are associated with corporate specific factors such as leverage, adoption of IFRS/US GAAP, industry type, and price to book ratio. Contrary to the existing literature on voluntary disclosure, however, firm size and ownership concentration are not found to be associated with the IA disclosure level. Country specific factors such as the level of risks associated with economic policy and legal system are also found to be significantly associated with the IA voluntary disclosure level.

The rural land market in Australia is a very complex property market. This complexity is not limited to the volatility of the returns in the rural land market, but also those factors that influence the change inland prices within specific rural property markets. Rural land returns – over the period 1975-1996, there has been higher than the returns achieved from residential and commercial real estate in respective rural areas: traditional farming areas have not provided the same level of returns as developing and marginal farming areas. Economic and financial factors and rural land prices – there is significant correlation between rural land price trends in adjoining areas with similar land use and level of farming development: as the distance between specific rural area increases the correlation between changes in land price decreases. Modelling rural land values – relationship between change in rural land prices and the change in economic factors is more significant in the developing and marginal cropping areas compared to the traditional cropping areas: there is a more significant association between rural land prices and rural economic factors when the economic factors are lagged, rather than contemporaneous. Rural property and valuation implications – rural land sales in one location are generally not an accurate measure of changing prices in another location: factors other than rural economic factors have a greater impact on rural land prices in areas which are closer settled or where alternate non agricultural land uses are available / Master of Commerce (Hons.)

Licensed valuers in the State of Victoria, Australia currently appraise rural land using manual techniques. Manual techniques typically involve site visits to the property, liaison with property owners through interview, and require a valuer experienced in agricultural properties to determine a value. The use of manual techniques typically takes longer to determine a property value than for valuations performed using automated techniques, providing appropriate data are available. Manual methods of valuation can be subjective and lead to bias in valuation estimates, especially where valuers have varying levels of experience within a specific regional area. Automation may lend itself to more accurate valuation estimates by providing greater consistency between valuations. Automated techniques presently in use for valuation include artificial neural networks, expert systems, case based reasoning and multiple regression analysis. The latter technique appears mo st widely used for valuation. The research aimed to develop a conceptual rural property valuation model, and to develop and evaluate quantitative models for rural property valuation based on the variables identified in the conceptual model. The conceptual model was developed by examining peer research, Valuation Best Practice Standards, a standard in use throughout Victoria for rating valuations, and rural property valuation texts. Using data that are only available digitally and publicly, the research assessed this conceptualisation using properties from four LGAs in the Wellington and Wimmera Catchment Management Authority (CMAs) areas in Victoria. Cluster analysis was undertaken to assess if the use of sub-markets, that are determined statistically, can lead to models that are more accurate than sub-markets that have been determined using geographically defined areas. The research is divided into two phases; the 'available data phase' and the 'restricted data phase'. The 'available data phase' used publicly available digital data to build quantitative models to estimate the value of rural properties. The 'restricted data phase' used data that became available near the completion of the research. The research examined the effect of using statistically derived sub-markets as opposed to geographically derived ones for property valuation. Cluster analysis was used during both phases of model development and showed that one of the clusters developed in the available data phase was superior in its model prediction compared to the models produced using geographically derived regions. A number of limitations with the digital property data available for Victoria were found. Although GIS analysis can enable more property characteristics to be derived and measured from existing data, it is reliant on having access to suitable digital data. The research also identified limitations with the metadata elements in use in Victoria (ANZMETA DTD version 1). It is hypothesised that to further refine the models and achieve greater levels of price estimation, additional properties would need to be sourced and added to the current property database. It is suggested that additional research needs to address issues associated with sub-market identification. If results of additional modelling indicated significantly different levels of price estimation, then these models could be used with manual techniques to evaluate manually derived valuation estimates.

Valuation of R&D projects is quite complex due to the substantial uncertainties in a project's life-cycle phases. The sequential nature of R&D projects continuously provides decision-makers with choices regarding whether and when to undertake future potential investment opportunities. This means that when valuing R&D projects decision-makers should take these factors into account. But R&D project usually takes long time to complete processes for commercialization. If the time to complete is longer, it is easier to trigger the crisis for capital shortage. So it seems very important modeling the capital shortage risk to induce the probability of failure in the pricing model. In this thesis we try to apply the analogy of financial securities subject to credit risk of Jarrow & Turnbull (1995) and attempt to value patents with capital shortage risk in an arbitrage free environment using the martingale measure technique. Furthermore, derive closed form formula for patents valuation which makes application easier than that of the theoretic option model. The major findings are: (1) when considering the effect of the failure frequency (capital shortage risk), the patent value will grow rapidly and then converge in the short run, no matter how other parameters incorporated into the robust analysis; (2) when increasing in the volatility of market revenues with synchronized higher volatility of investment cost, the volatility curve will be distorted to be U-shaped. Meanwhile, lower failure frequency could aggravate the decreasing in the option value. Another issue is when the manager exercises the project with multiple underlying assets, where the assets returns are of non-linear correlation particularly in the non-Normal environment. Non-parametric dependence measures may better employed when explaining co-movement. We focus on the value of a (such as resources development) project in general depends on the price of the multiple products; these are usually correlated to some extent. So the project was treated as having a rainbow option, whose underlying asset prices correlate with each other, and also as having uncertainties that decrease according to the project stage. Based on Cherubini and Luciano’s framework (2002), the risk-neutral copula models are derived to figure decision flexibilities out easily. The main framework studies the valuation of a project (call on Max) by determining the joint risk-neutral distribution of the underlying assets (products) using copulas. Monte-Carlo simulations show that the higher default risk and association among the assets and the expected cost to completion contributes the higher risk premium in our model with dependence structure of Archimedean copula family than traditional Black-Scholes environment. / Valuation of R&D projects is quite complex due to the substantial uncertainties in a project's life-cycle phases. The sequential nature of R&D projects continuously provides decision-makers with choices regarding whether and when to undertake future potential investment opportunities. This means that when valuing R&D projects decision-makers should take these factors into account. But R&D project usually takes long time to complete processes for commercialization. If the time to complete is longer, it is easier to trigger the crisis for capital shortage. So it seems very important modeling the capital shortage risk to induce the probability of failure in the pricing model. In this thesis we try to apply the analogy of financial securities subject to credit risk of Jarrow & Turnbull (1995) and attempt to value patents with capital shortage risk in an arbitrage free environment using the martingale measure technique. Furthermore, derive closed form formula for patents valuation which makes application easier than that of the theoretic option model. The major findings are: (1) when considering the effect of the failure frequency (capital shortage risk), the patent value will grow rapidly and then converge in the short run, no matter how other parameters incorporated into the robust analysis; (2) when increasing in the volatility of market revenues with synchronized higher volatility of investment cost, the volatility curve will be distorted to be U-shaped. Meanwhile, lower failure frequency could aggravate the decreasing in the option value. Another issue is when the manager exercises the project with multiple underlying assets, where the assets returns are of non-linear correlation particularly in the non-Normal environment. Non-parametric dependence measures may better employed when explaining co-movement. We focus on the value of a (such as resources development) project in general depends on the price of the multiple products; these are usually correlated to some extent. So the project was treated as having a rainbow option, whose underlying asset prices correlate with each other, and also as having uncertainties that decrease according to the project stage. Based on Cherubini and Luciano’s framework (2002), the risk-neutral copula models are derived to figure decision flexibilities out easily. The main framework studies the valuation of a project (call on Max) by determining the joint risk-neutral distribution of the underlying assets (products) using copulas. Monte-Carlo simulations show that the higher default risk and association among the assets and the expected cost to completion contributes the higher risk premium in our model with dependence structure of Archimedean copula family than traditional Black-Scholes environment.

Biotechnology generated solutions have been hailed as potential cures to many of the problems facing the world today. New therapeutics will eradicate disease, new agricultural products will solve food shortages, and industrial application will improve productivity with reduced environmental impact. Despite the much anticipated benefits of biotechnology, the industry faces significant challenges that must be overcome in the coming decades. Biotechnology is an inherently complex field with a high degree of uncertainty and associated risks. In addition to the risk associated with project development and delivery, businesses looking to extract an economic return from the provision of biotechnology products and services face significant financial risk. This is exacerbated by the long lead times in biotechnology product development and the expensive nature of research and development. This thesis looks investigates the multi faceted problem of biotechnology valuation in Australia using a multi method approach designed to provide greater insight into the valuation challenges facing the industry and identify key value drivers. The approach incorporates a broad qualitative investigation, complimented by more focused quantitative studies into specific valuation issues surrounding IPO and project valuation. Australian biotechnology firms face a significant challenge to raise sufficient capital in order to remain internationally competitive. The current industry structure and funding mechanisms encourage creation of small firms with narrow pipelines, exacerbating the risk of company failure and acting as an impediment to sustainability and, therefore, investment in the sector. Despite the challenges facing the Australian biotechnology industry, the nation possesses a competitive advantage in the strength of local science which, if fully leveraged, should see the development of an internationally competitive industry. Through improved funding mechanisms which encourage the creation of sustainable business models, increased investor participation in the industry should see a greater portion of the value generated through biotechnology retained by local participants. An IPO is likely the largest single capital raising in a company's history. A quantitative investigation into the factors influencing the amount of underpricing and money left on the table for Australian biotechnology IPOs found that the amount of money left on the table was more critical than the level of underpricing. Additionally the impact of market sentiment on biotechnology IPOs was investigated with increased media coverage found to be positively related to the amount of money left on the table. Using project valuation models, the drivers of value over the life of a typical biotechnology project were identified. Key drivers of biotechnology value are commercial viability, coupled with development cost and time. The ability of management to control these elements is crucial. Analysis of project valuations using a traditional DCF model found value estimates exhibited a greater level of uncertainty than those calculated using more contemporary methods of decision tree and real option analysis. Additionally, incorporation of management flexibility into valuation assessment using real options techniques increased the perceived value of biotechnology projects. The value of management flexibility was found to be most relevant for early stage projects where the option to abandon was found to greatly influence values.

<p>The Private equity industry is receiving a lot of attention in the daily news. The Private equity firms are acquiring other companies through a Leverage buyout transaction (LBO). The ownership period is short with an average ownership of five to seven years. The business strategy of the PE firms is only focusing on generating the highest possible profit in a resale over this period. The PE firms’ target companies are companies they think have potential to grow or improve under their management. In the daily press these improvements is often associated with cost-cutting to improve efficiency (Mills 2006).</p><p>This business strategy seems to be contradicting general Merger and Acquisition motives defined in theory, as the theories are mainly focusing on long term integration and achieving synergies. Additionally, the focus on profit should lead one to believe that PE firms are highly focused on the financial aspects of the acquired company, hence heavily relying on financial valuation methods. These naïve conditions have lead to this research.</p><p>Theorists argue that an acquisition is a homogenous process where every step in the process affects the final outcome. Nevertheless most research in merger and acquisitions often focus on integration and synergies of the post-deal. These theories often neglect the more basic financial criteria that have to be met for the acquisition to be feasible in the first place. Other schools of theories are focused on the financial valuation of an LBO and the financing of it, excluding other aspects than financial.</p><p>The purpose of this thesis will be, from an academic point of view, to explain the transaction process of an LBO leading the way for the final acquisition by PE firms. This will be facilitated by drawing from and combing the more general Merger and Acquisition process theory with the more financial valuation theory.</p><p>A holistic framework is created, based on and by combining Haspeslagh & Jemison’s (1991) process model and the Watson Wyatt Deal Flow Model in (Galpin & Herndon 2000), this created framework identifies, where in the LBO process the valuation and due diligence takes place. The framework aims at identifying and explaining from an academic point of view, how the transaction process is constructed. Through this framework it will be evident what methods are attributed, by scholars, to the financial valuation in regard to a successive outcome. The created framework will be compared to the qualitative data collected through interviews with professionals from the industry. It will with an explorative angle be tried proven, whether the created framework has any explanatory value, relating theory perspectives with the practical LBO transaction as seen in the examples.</p><p>Based on the research and the findings, conclusions are made. It is apparent that the accepted general Merger and Acquisition theory is not fully applicable with the actual LBO transaction as identified in this research process, and that the methods used for valuation, is not utilized in the same manor as the theorist predict</p>

<p>Background: Tougher demands from regulators on drugs efficiency and safety,governmental cost cutting and more complex areas of research, has led to that the importance of the pharmaceutical industry’s research pipelines are increasing. Even though the capital markets views on the pharmaceutical industry and its valuation is changing, the authors is not aware of any prior research that has been conducted on the topic of how the market reacts to clinical trial results or how security analysts valuates product pipelines.</p><p>Aim: This thesis aims to explain how security analysts valuate research pipelines and analyze whether the publication of clinical trial results significantly affects the pricing of multinational pharmaceutical companies.</p><p>Methodology: Three econometric models using an aggregate daily data sample of 27 years for five of the world’s largest pharmaceutical firms distinguish the price effects related to the publication of clinical trial results. Three interviews with security analysts map how security analysts value pharmaceutical research.</p><p>Results: Security analysts’ uses a combination of DCF and relative valuation when analyzing pharmaceutical firms. All interviewed analysts uses a risk adjusted net present value approach which is closely linked to the DCF approach, however, financial theory suggests that pipelines should be valuated with contingent claim models Analysts recognize that all compounds in Phase III and some Phase II projects has a impact on firm value. Clinical trials have a significant short-term impact on firm value. Phase III projects shows significant share price influence whilst early stage clinical trials do not, which shows that analysts are correct in focusing their valuation to later stage clinical trials. However, not all areas of therapy have a significant impact on firm value. Oncology is the only area of therapy where successes raises firm value, whilst failures in oncology and cardiovascular/gastrointestinal significantly lower firm value. Negative news about the research portfolio also tends to have a larger impact than positive news.</p>

The standard way of representing numbers on computers gives rise to errors which increase as computations progress. Using p-adic valuations can reduce error accumulation. Valuation theory tells us that p-adic and standard valuations cannot be directly compared. The p-adic valuation can, however, be used in an indirect way. This gives a method of doing arithmetic on a subset of the rational numbers without any error. This exactness is highly desirable, and can be used to solve certain kinds of problems which the standard valuation cannot conveniently handle. Programming a computer to use these p-adic numbers is not difficult, and in fact uses computer resources similar to the standard floating-point representation for real numbers. This thesis develops the theory of p-adic valuations, discusses their implementation, and gives some examples where p-adic numbers achieve better results than normal computer computation. / Graduation date: 1994

Problem: The online betting industry has erased the importance of national borders and opened up the world, which has lead to a more diversified perspective of the company. In this master thesis we wanted to broaden and develop the topic of corporate valuation with regard to the on-line gambling industry. In order to do that, a case study of the on-line betting firm Unibet and its core betting activities has been carried out. Purpose: The study aims to identify factors in the strategic, SWOT and financial analysis that will be used in the cash flow valuation model in order to derive the company value. Method: A case study has been chosen to collect empirical data to our study. Conclusion: A cash flow valuation in different scenarios was carried out. With the assumptions made in the “probable” scenario a value of approximately GBP 85 million was reached, which was significantly lower than the listed value. This is mainly due to the fact that we believe that the increased competition will make it difficult for Unibet to maintain its strong growth in sales in the future. The assumptions have been based on the information gained from the strategic analysis, the SWOT analysis and the development in financial ratios.

Bakgrund Majoriteten av alla svenska företag är familjeföretag. Forskning inom området har inte bedrivits i någon större utsträckning förrän på senare år. Därtill kommer att forskning inom värdering av familjeföretag är närmast obefintlig. Familjeföretag skiljer sig på många sätt från icke-familjeföretag, t.ex. när det gäller kultur, ägande och ledning. Härav finns det anledning att tro att familjeföretag värderas annorlunda än icke-familjeföretag. Syfte med uppsatsen Syftet med denna uppsats är att beskriva hur värdering av familjeföretag går till från ett uppköpande företags synvinkel. Metod För att utföra denna uppsats har ett kvalitativt, hermeneutiskt tillvägagångssätt använts för att förstå helheten av fenomenet familjeföretags värdering. Vi har genomfört en fallstudie bestående av tre familjeföretags uppköp gjorda av Företag X som noggrant har studerats. Slutsats När ett familjeföretag värderas är det avgörande att ha erfarenhet, branschkännedom, intuition och framför allt kunskap och erfarenhet om familjeföretag. De immateriella tillgångarna i ett familjeföretag, som till exempel rykte, kultur och kunskap bidrar tillsammans med olika värderingsmodeller till ett rättvist värde av familjeföretaget. / Background The vast majority of all Swedish companies are family businesses. Research within the field of family businesses has not until recent years been developed. Moreover, the research regarding valuation of family businesses is close to non-existing. Family businesses differ in many ways from non-family businesses, for example when it comes to culture, ownership and management. Hence, there is a possibility that family businesses are valuated differently from non-family businesses. Purpose of this thesis The purpose with this thesis is to describe how valuation of family businesses is done from the perspective of an acquiring company. Method For this thesis a qualitative, hermeneutic approach was applied in order to understand the whole picture of the valuation of the family business phenomenon. A case study approach was carried out by carefully studying three acquisitions of small private family businesses in the service sector made by Company X. Conclusions The crucial skills to possess are experience, industry knowledge, intuition and most of all family business knowledge and experience when determining a fair value of a family business. The intangible assets of a family business, for instance reputation, culture and knowledge, together with different valuation methods contribute to the estimation of the value of a family business.