15 resultados para Investment Model

em Doria (National Library of Finland DSpace Services) - National Library of Finland, Finland


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The suitable timing of capacity investments is a remarkable issue especially in capital intensive industries. Despite its importance, fairly few studies have been published on the topic. In the present study models for the timing of capacity change in capital intensive industry are developed. The study considers mainly the optimal timing of single capacity changes. The review of earlier research describes connections between cost, capacity and timing literature, and empirical examples are used to describe the starting point of the study and to test the developed models. The study includes four models, which describe the timing question from different perspectives. The first model, which minimizes unit costs, has been built for capacity expansion and replacement situations. It is shown that the optimal timing of an investment can be presented with the capacity and cost advantage ratios. After the unit cost minimization model the view is extended to the direction of profit maximization. The second model states that early investments are preferable if the change of fixed costs is small compared to the change of the contribution margin. The third model is a numerical discounted cash flow model, which emphasizes the roles of start-up time, capacity utilization rate and value of waiting as drivers of the profitable timing of a project. The last model expands the view from project level to company level and connects the flexibility of assets and cost structures to the timing problem. The main results of the research are the solutions of the models and analysis or simulations done with the models. The relevance and applicability of the results are verified by evaluating the logic of the models and by numerical cases.

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Työn tavoitteena oli tutkia robotti-investointia ja muodostaa siitä investointimalli, jossa selvitetään sen aiheuttamat kustannukset ja tuotot investointilaskelmien avulla. Investointimalli tehtiin siten, että sillä pystytään tutkimaan myös tulevia investointihankkeita. Robotti-investointi on luonteeltaan korvausinvestointi, joten sen toteuttamisessa on huomioitu tarkoin sille asetetut vaatimukset. Näiden perusteilla lähdettiin etsimään sopivaa laitetoimittajaa, joka pystyisi täyttämään annetut vaatimukset. Robottiaseman suunnittelu ja kehittäminen tehtiin vahvassa yhteistyössä laitetoimittajien kanssa, joilta saatiin myös tarvittavaa aineistoa teknisistä ominaisuuksista ja käytöstä aiheutuvista kustannuksista. Investoinnin kannattavuutta arvioitiin laskentamallin avulla, jonka tärkeimpinä kannattavuuden mittareina pidettiin takaisinmaksuaikaa ja nykyarvoa. Laskelmien tuloksiin liittyvää epävarmuutta arvioitiin herkkyysanalyysillä, jossa tutkittiin nykyarvon kehitystä eri tapauksissa. Investointia tutkittiin myös muista, kuin taloudellisista näkökulmista, joka vaikutti lopulliseen päätöksentekoon. Investointi muodostui erittäin kannattavaksi.

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Tämän työn tavoitteena oli selvittää sähkön jakeluverkkotoiminnan valvontamenetelmien muutoksien vaikutuksia Loiste Sähköverkko Oy:n talouteen neljännellä ja viidennellä valvontajaksolla. Tarkastelua varten tehtiin talousmalli, joka mallintaa verkkoyhtiön taloutta vuoteen 2040 asti. Talousmallissa mallinnettiin kaikkien kannustimien vaikutus paitsi innovaatio- ja toimitusvarmuuskannustimien vaikutus. Talousmallinnuksen perusperiaate oli, että mitä ei pystytä kattamaan siirtotuloilla, rahoitetaan vieraalla pääomalla, kun kassavirran minimitaso ja investointitaso ovat valittu. Talousmallilla tarkasteltiin neljää erilaista verkostoskenaariota. Tarkasteltavat verkostoskenaariot olivat kehittämissuunnitelman mukainen skenaario, nopeutettu kehittämissuunnitelman mukainen skenaario, kaapelointipainotteinen skenaario ja kunnossapitopainotteinen skenaario. Verkon arvon kehittyminen verkostoskenaarioissa mallinnettiin Loiste Sähköverkko Oy:n investointimallilla ja kuvattiin talousmallinnusta varten jälleenhankinta-arvon, nykykäyttöarvon, investointien ja tasapoistojen kehittymisellä vuoteen 2029 asti. Työn tulosten perusteella kehittämissuunnitelman mukaisessa skenaariossa vieraan pääoman määrä pysyy kohtuullisena ja mahdollistaa kohtuullisen kassavirran tarkastelujakson lopussa. Nopeutetussa kehittämissuunnitelman mukaisessa skenaariossa ja kaapelointipainotteisissa skenaariossa vieraan pääoman määrä kasvaa merkittävästi, mikä voi lisätä liiketaloudellisia riskejä, mutta toisaalta mahdollistavat korkeamman kassavirran tarkastelujakson lopussa. Kunnossapitopainotteisessa skenaariossa vieraan pääoman määrä on matala, mutta kassavirta myös pysyy matalana tarkastelujakson loppuun asti.

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This research report illustrates and examines new operation models for decreasing fixed costs and transforming them into variable costs in the field of paper industry. The report illustrates two cases - a new operation model for material logistics in maintenance and an examination of forklift truck fleet outsourcing solutions. Conventional material logistics in maintenance operation is illustrated and some problems related to conventional operation are identified. A new operation model that solves some of these problems is presented including descriptions of procurement and service contracts and sources of added value. Forklift truck fleet outsourcing solutions are examined by illustrating the responsibilities of a host company and a service provider both before and after outsourcing. The customer buys outsourcingservices in order to improve its investment productivity. The mechanism of how these services affect the customer company's investment productivity is illustrated.

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The evaluation of investments in advanced technology is one of the most important decision making tasks. The importance is even more pronounced considering the huge budget concerning the strategic, economic and analytic justification in order to shorten design and development time. Choosing the most appropriate technology requires an accurate and reliable system that can lead the decision makers to obtain such a complicated task. Currently, several Information and Communication Technologies (ICTs) manufacturers that design global products are seeking local firms to act as their sales and services representatives (called distributors) to the end user. At the same time, the end user or customer is also searching for the best possible deal for their investment in ICT's projects. Therefore, the objective of this research is to present a holistic decision support system to assist the decision maker in Small and Medium Enterprises (SMEs) - working either as individual decision makers or in a group - in the evaluation of the investment to become an ICT's distributor or an ICT's end user. The model is composed of the Delphi/MAH (Maximising Agreement Heuristic) Analysis, a well-known quantitative method in Group Support System (GSS), which is applied to gather the average ranking data from amongst Decision Makers (DMs). After that the Analytic Network Process (ANP) analysis is brought in to analyse holistically: it performs quantitative and qualitative analysis simultaneously. The illustrative data are obtained from industrial entrepreneurs by using the Group Support System (GSS) laboratory facilities at Lappeenranta University of Technology, Finland and in Thailand. The result of the research, which is currently implemented in Thailand, can provide benefits to the industry in the evaluation of becoming an ICT's distributor or an ICT's end user, particularly in the assessment of the Enterprise Resource Planning (ERP) programme. After the model is put to test with an in-depth collaboration with industrial entrepreneurs in Finland and Thailand, the sensitivity analysis is also performed to validate the robustness of the model. The contribution of this research is in developing a new approach and the Delphi/MAH software to obtain an analysis of the value of becoming an ERP distributor or end user that is flexible and applicable to entrepreneurs, who are looking for the most appropriate investment to become an ERP distributor or end user. The main advantage of this research over others is that the model can deliver the value of becoming an ERP distributor or end user in a single number which makes it easier for DMs to choose the most appropriate ERP vendor. The associated advantage is that the model can include qualitative data as well as quantitative data, as the results from using quantitative data alone can be misleading and inadequate. There is a need to utilise quantitative and qualitative analysis together, as can be seen from the case studies.

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The aim of this master’s thesis is to analyze the effects of Foreign Direct Investments on growth in selected Central and Eastern European transition countries. The theoretical part of this thesis, introduces growth theories and how FDI is covered in those theories. In addition, the results from previous studies, which have studied FDI’s effect on growth, are presented in this master’s thesis. This work introduces also the economical progress during the transition period in selected countries. In the empirical part’s regression model, it will be searched for the direct effect of FDI on growth with panel data collected from nine transition countries.

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Purpose of this study is to analyze the effect of Russia's economic environment changes in the total return indexes of Finnish companies. The research data consisted of Finnish publicly listed companies, which have made physical investments to Russia, and operating in the area. The study used six different variables to model the Russian operating environment. The data consists of total return indexes of Finnish companies. From those we calculated the monthly mean interval between timeline of 1 January 2000 to 31 December 2009. Sample period is divided into two different parts. Variables impact on companies' total return indices is tested by regression analysis. By F-test we tested significance of model and squared coefficient correlation told us how much model explains from changes. Goodness of the β-coefficient is tested in the model by t-test. The research results shows that the Russian operating environment, or changes in which the active Finnish companies in total return indices. On partial sample periods results were not so significant.

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This thesis examined both domestic and international forest investment options for a Finnish non-industrial private forest investor. The focus was on forest-based investment instruments. The influence of movements of currency exchange rates on foreign returns were also taken into account. Annual data from 1995 to 2011 was used. The main portfolio optimization model in this study was the Mean-Variance model but the results were also validated by using the Value at Risk and Expected Shortfall models. In addition, the exchange rate risk hedging was established by using one-week-maturity forward contracts. The results suggested that 75 % of the total wealth should be invested in Finnish private forests and the rest, 25 %, to a US REIT, in this case Rayonier. With hedging, the total return on the portfolio was 7.21 % (NIPF 5.3%) with the volatility of 6.63 % (NIPF 7.9%). Taxation supported US investments in this case. As a conclusion, a Finnish private forest investor may, as evidenced, benefit in diversifying a portfolio using REITs in the US.

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This research report illustrates and examines new operation models for decreasing fixed costs and transforming them into variable costs in the field of paper industry. The report illustrates two cases – a new operation model for material logistics in maintenance and an examination of forklift truck fleet outsourcing solutions. Conventional material logistics in maintenance operation is illustrated and some problems related to conventional operation are identified. A new operation model that solves some of these problems is presented including descriptions of procurement and service contracts and sources of added value. Forklift truck fleet outsourcing solutions are examined by illustrating the responsibilities of a host company and a service provider both before and after outsourcing. The customer buys outsourcing services in order to improve its investment productivity. The mechanism of how these services affect the customer company’s investment productivity is illustrated.

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The objective of this Master’s thesis is to create a calculation model for working capital management in value chains. The study has been executed using literature review and constructive research methods. Constructive research methods were mainly modeling. The theory in this thesis is founded in research articles and management literature. The model is developed for students and researchers. They can use the model for working capital management and comparing firms to each other. The model can also be used to cash management. The model tells who benefits and who suffers most in the value chain. Companies and value chains cash flows can be seen. By using the model can be seen are the set targets really achieved. The amount of operational working capital can be observed. The model enables user to simulate the amount of working capital. The created model is based on cash conversion cycle, return on investment and cash flow forecasting. The model is tested with carefully considered figures which seem to be though realistic. The modeled value chain is literally a chain. Implementing this model requires from the user that he/she have some kind of understanding about working capital management and some figures from balance sheet and income statement. By using this model users can improve their knowledge about working capital management in value chains.

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The thesis aims to build a theoretical model to explain consumer investment intentions in stocks and investment funds. The model examines the relationships between subjective investment knowledge, expected sacrifice, expected investment value, compatibility, perceived behavioral control and investment intentions. The data was collected via web-based survey and consisted of 45- to 65-year-old Finnish consumers (n=154). Confirmatory factor analysis (CFA), structural equation modeling (SEM) and t-tests were applied in analyzing the data. The results suggest that among average household consumers expected investment value consists of three dimensions, namely, economic, functional, and emotional, whereas expected sacrifice consists of effort, financial risk, source risk, and psychological risk. Two structural models were assessed, one for stock investments and one for investment funds. Whereas the models presented somewhat different outcomes, in both models compatibility had an essential role in explaining consumer investment intentions. Compatibility was affected by expected investment value and expected sacrifice. Subjective investment knowledge impacted consumers’ evaluations of the value and sacrifices. The effect of perceived behavioral control on investment intentions was rather small, however significant. Moreover, the results suggest that there are significant differences between consumers with no investment experience and consumers with investment experience in subjective investment knowledge, the dimensions of expected sacrifices and expected investment value, perceived behavioral control, compatibility and investment intentions.

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This thesis discusses the basic problem of the modern portfolio theory about how to optimise the perfect allocation for an investment portfolio. The theory provides a solution for an efficient portfolio, which minimises the risk of the portfolio with respect to the expected return. A central feature for all the portfolios on the efficient frontier is that the investor needs to provide the expected return for each asset. Market anomalies are persistent patterns seen in the financial markets, which cannot be explained with the current asset pricing theory. The goal of this thesis is to study whether these anomalies can be observed among different asset classes. Finally, if persistent patterns are found, it is investigated whether the anomalies hold valuable information for determining the expected returns used in the portfolio optimization Market anomalies and investment strategies based on them are studied with a rolling estimation window, where the return for the following period is always based on historical information. This is also crucial when rebalancing the portfolio. The anomalies investigated within this thesis are value, momentum, reversal, and idiosyncratic volatility. The research data includes price series of country level stock indices, government bonds, currencies, and commodities. The modern portfolio theory and the views given by the anomalies are combined by utilising the Black-Litterman model. This makes it possible to optimise the portfolio so that investor’s views are taken into account. When constructing the portfolios, the goal is to maximise the Sharpe ratio. Significance of the results is studied by assessing if the strategy yields excess returns in a relation to those explained by the threefactormodel. The most outstanding finding is that anomaly based factors include valuable information to enhance efficient portfolio diversification. When the highest Sharpe ratios for each asset class are picked from the test factors and applied to the Black−Litterman model, the final portfolio results in superior riskreturn combination. The highest Sharpe ratios are provided by momentum strategy for stocks and long-term reversal for the rest of the asset classes. Additionally, a strategy based on the value effect was highly appealing, and it basically performs as well as the previously mentioned Sharpe strategy. When studying the anomalies, it is found, that 12-month momentum is the strongest effect, especially for stock indices. In addition, a high idiosyncratic volatility seems to be positively correlated with country indices on stocks.

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Over time the demand for quantitative portfolio management has increased among financial institutions but there is still a lack of practical tools. In 2008 EDHEC Risk and Asset Management Research Centre conducted a survey of European investment practices. It revealed that the majority of asset or fund management companies, pension funds and institutional investors do not use more sophisticated models to compensate the flaws of the Markowitz mean-variance portfolio optimization. Furthermore, tactical asset allocation managers employ a variety of methods to estimate return and risk of assets, but also need sophisticated portfolio management models to outperform their benchmarks. Recent development in portfolio management suggests that new innovations are slowly gaining ground, but still need to be studied carefully. This thesis tries to provide a practical tactical asset allocation (TAA) application to the Black–Litterman (B–L) approach and unbiased evaluation of B–L models’ qualities. Mean-variance framework, issues related to asset allocation decisions and return forecasting are examined carefully to uncover issues effecting active portfolio management. European fixed income data is employed in an empirical study that tries to reveal whether a B–L model based TAA portfolio is able outperform its strategic benchmark. The tactical asset allocation utilizes Vector Autoregressive (VAR) model to create return forecasts from lagged values of asset classes as well as economic variables. Sample data (31.12.1999–31.12.2012) is divided into two. In-sample data is used for calibrating a strategic portfolio and the out-of-sample period is for testing the tactical portfolio against the strategic benchmark. Results show that B–L model based tactical asset allocation outperforms the benchmark portfolio in terms of risk-adjusted return and mean excess return. The VAR-model is able to pick up the change in investor sentiment and the B–L model adjusts portfolio weights in a controlled manner. TAA portfolio shows promise especially in moderately shifting allocation to more risky assets while market is turning bullish, but without overweighting investments with high beta. Based on findings in thesis, Black–Litterman model offers a good platform for active asset managers to quantify their views on investments and implement their strategies. B–L model shows potential and offers interesting research avenues. However, success of tactical asset allocation is still highly dependent on the quality of input estimates.