895 resultados para asset prices


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Cartel detection is one of the most basic and most complicated tasks of competition authorities. In recent years, however, variance filters have provided a fairly simple tool for rejecting the existence of price-fixing, with the added advantage that the methodology requires only a low volume of data. In this paper we analyze two aspects of variance filters: 1- the relationship established between market structure and price rigidity, and 2- the use of different benchmarks for implementing the filters. This paper addresses these two issues by applying a variance filter to a gasoline retail market characterized by a set of unique features. Our results confirm the positive relationship between monopolies and price rigidity, and the variance filter's ability to detect non-competitive behavior when an appropriate benchmark is used. Our findings should serve to promote the implementation of this methodology among competition authorities, albeit in the awareness that a more exhaustive complementary analysis is required.

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The analysis of price asymmetries in the gasoline market is one of the most studied in the energy economics literature. Nevertheless, the great variability of results makes it very difficult to extract conclusive results on the existence or not of asymmetries. This paper shows through a meta-analysis approach how the industry segment analysed, the quality and quantity of data, the estimator and the model used may explain this heterogeneity of results.

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The aim of this study is to collect and analyze variables that could have a relationship with the second-hand house prices in Barcelona, as much disaggregated as possible from 2008 to 2011 and make a statistical analysis. The study consists of two parts. The first part is the preliminary study of the data and the second part is the econometric analysis of the data to see if there is any relationship between the second-hand house prices and the variables chosen. Finally, we looked at if there was any atypical observation and if the model presented multicollinarity. With all this information, we extract some conclusions and then, we analyzed more deeply the information.

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In this paper we investigate the optimal choice of prices and/or exams by universities in the presence of credit constraints. We first compare the optimal behavior of a public, welfare maximizing, monopoly and a private, profit maximizing, monopoly. Then we model competition between a public and a private institution and investigate the new role of exams/prices in this environment. We find that, under certain circumstances, the public university may have an interest to raise tuition fees from minimum levels if it cares for global welfare. This will be the case provided that (i) the private institution has higher quality and uses only prices to select applicants, or (ii) the private institution has lower quality and uses also exams to select students. When this is the case, there are efficiency grounds for raising public prices

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Electricity spot prices have always been a demanding data set for time series analysis, mostly because of the non-storability of electricity. This feature, making electric power unlike the other commodities, causes outstanding price spikes. Moreover, the last several years in financial world seem to show that ’spiky’ behaviour of time series is no longer an exception, but rather a regular phenomenon. The purpose of this paper is to seek patterns and relations within electricity price outliers and verify how they affect the overall statistics of the data. For the study techniques like classical Box-Jenkins approach, series DFT smoothing and GARCH models are used. The results obtained for two geographically different price series show that patterns in outliers’ occurrence are not straightforward. Additionally, there seems to be no rule that would predict the appearance of a spike from volatility, while the reverse effect is quite prominent. It is concluded that spikes cannot be predicted based only on the price series; probably some geographical and meteorological variables need to be included in modeling.

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Last two decades have seen a rapid change in the global economic and financial situation; the economic conditions in many small and large underdeveloped countries started to improve and they became recognized as emerging markets. This led to growth in the amounts of global investments in these countries, partly spurred by expectations of higher returns, favorable risk-return opportunities, and better diversification alternatives to global investors. This process, however, has not been without problems and it has emphasized the need for more information on these markets. In particular, the liberalization of financial markets around the world, globalization of trade and companies, recent formation of economic and regional blocks, and the rapid development of underdeveloped countries during the last two decades have brought a major challenge to the financial world and researchers alike. This doctoral dissertation studies one of the largest emerging markets, namely Russia. The motivation why the Russian equity market is worth investigating includes, among other factors, its sheer size, rapid and robust economic growth since the turn of the millennium, future prospect for international investors, and a number of important major financial reforms implemented since the early 1990s. Another interesting feature of the Russian economy, which gives motivation to study Russian market, is Russia’s 1998 financial crisis, considered as one of the worst crisis in recent times, affecting both developed and developing economies. Therefore, special attention has been paid to Russia’s 1998 financial crisis throughout this dissertation. This thesis covers the period from the birth of the modern Russian financial markets to the present day, Special attention is given to the international linkage and the 1998 financial crisis. This study first identifies the risks associated with Russian market and then deals with their pricing issues. Finally some insights about portfolio construction within Russian market are presented. The first research paper of this dissertation considers the linkage of the Russian equity market to the world equity market by examining the international transmission of the Russia’s 1998 financial crisis utilizing the GARCH-BEKK model proposed by Engle and Kroner. Empirical results shows evidence of direct linkage between the Russian equity market and the world market both in regards of returns and volatility. However, the weakness of the linkage suggests that the Russian equity market was only partially integrated into the world market, even though the contagion can be clearly seen during the time of the crisis period. The second and the third paper, co-authored with Mika Vaihekoski, investigate whether global, local and currency risks are priced in the Russian stock market from a US investors’ point of view. Furthermore, the dynamics of these sources of risk are studied, i.e., whether the prices of the global and local risk factors are constant or time-varying over time. We utilize the multivariate GARCH-M framework of De Santis and Gérard (1998). Similar to them we find price of global market risk to be time-varying. Currency risk also found to be priced and highly time varying in the Russian market. Moreover, our results suggest that the Russian market is partially segmented and local risk is also priced in the market. The model also implies that the biggest impact on the US market risk premium is coming from the world risk component whereas the Russian risk premium is on average caused mostly by the local and currency components. The purpose of the fourth paper is to look at the relationship between the stock and the bond market of Russia. The objective is to examine whether the correlations between two classes of assets are time varying by using multivariate conditional volatility models. The Constant Conditional Correlation model by Bollerslev (1990), the Dynamic Conditional Correlation model by Engle (2002), and an asymmetric version of the Dynamic Conditional Correlation model by Cappiello et al. (2006) are used in the analysis. The empirical results do not support the assumption of constant conditional correlation and there was clear evidence of time varying correlations between the Russian stocks and bond market and both asset markets exhibit positive asymmetries. The implications of the results in this dissertation are useful for both companies and international investors who are interested in investing in Russia. Our results give useful insights to those involved in minimising or managing financial risk exposures, such as, portfolio managers, international investors, risk analysts and financial researchers. When portfolio managers aim to optimize the risk-return relationship, the results indicate that at least in the case of Russia, one should account for the local market as well as currency risk when calculating the key inputs for the optimization. In addition, the pricing of exchange rate risk implies that exchange rate exposure is partly non-diversifiable and investors are compensated for bearing the risk. Likewise, international transmission of stock market volatility can profoundly influence corporate capital budgeting decisions, investors’ investment decisions, and other business cycle variables. Finally, the weak integration of the Russian market and low correlations between Russian stock and bond market offers good opportunities to the international investors to diversify their portfolios.

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This article examines the effect on price of different characteristics of holiday hotels in the sun-and-beach segment. The effect on price is estimated under the hedonic function perspective by means of random effect models, known also as mixed or panel models. Some 82,000 prices were gathered between 1991 and 1998 from tour operator catalogues. The study reveals huge price differences between 4-star hotels and the rest, coupled with practically no difference between 1-star and 2-star hotels. Other attributes with a significant effect on price are town, hotel size, distance to the beach and availability of parking place. The results can assist hotel managers in shaping pricing and investment strategies

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Condition monitoring systems for physical assets are constantly becoming more and more common in the industrial sector. At the same time an increasing portion of asset monitoring systems are being remotely supported. As global competitors are actively developing solutions for condition monitoring and condition-based maintenance, which it enables, Wärtsilä too feels the pressure to provide customers with more sophisticated condition-based maintenance solutions. The main aim of this thesis study is to consider Wärtsilä remote condition monitoring solutions and how they relate to similar solutions from other suppliers and end customers’ needs, in the context of offshore assets. A theoretical study is also included in the thesis, where the concepts of condition monitoring, condition-based maintenance, maintenance management and physical asset management are introduced.

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Aim of the Thesis is to study and understand the theoretical concept of Metanational corporation and understand how the Web 2.0 technologies can be used to support the theory. Empiric part of the study compares the theory to the case company’s current situation Goal of theoretical framework is to show how the Web 2.0 technologies can be used in the three levels of the Metanational corporation. In order to do this, knowledge management and more accurately knowledge transferring is studied to understand what is needed from the Web 2.0 technologies in the different functions and operations of the Metanational corporation. Final synthesis of the theoretical framework is to present a model where the Web 2.0 technologies are placed on the levels of the Metanational corporation. Empirical part of the study is based on interviews made in the case company. Aim of the interviews is to understand the current state of the company related to the theoretical framework. Based on the interviews, the differences between the theoretical concept and the case company are presented and studied. Finally the study presents the found problem areas, and where the adoption of the Web 2.0 tools is seen as beneficiary, based on the interviews and theoretical framework.

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This diploma thesis has been done to international organization which takes care from the accounting actions of two major companies. In this organization are used three different purchasing tools which are used when new asset master data is wanted to input to SAP R/3- system. The aim of this thesis is to find out how much changing the user interface of one of these three e-procurement programs will affect to overall efficiency in asset accounting. As an addition will be introduced project framework which can be used in future projects and which help to avoid certain steps in the development process. At the moment data needs to be inputted manually with many useless mouse clicks and data needs to be searched from many various resources which slow down the process. Other organization has better tools at the moment than the myOrders system which is under investigation Research was started by exploring the main improvement areas. After this possible defects were traced. Suggested improvements were thought by exploring literature which has been written from usability design and research. Meanwhile also directional calculations from the benefits of the project were done alongside with the analysis of the possible risks and threats. After this NSN IT approved the changes which they thought was acceptable. The next step was to program them into tool and test them before releasing to production environment. The calculations were made also from implemented improvements and compared them to planned ones From whole project was made a framework which can be utilized also to other similar projects. The complete calculation was not possible because of time schedule of the project. Important observation in the project was that efficiency is not improved not only by changing the GUI but also improving processes without any programming. Feedback from end user should be also listened more in development process. End-user is after all the one who knows the best how the program should look like.

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The main objective of this Master’s thesis is to find out which one of the two pricing models is the most cost-effective. In this thesis there are two companies that have made an outsourcing contract, in which they have a possibility to choose between two different pricing models. The first model is so called FTE (Full Time Employee) -based. The total cost will be based on the amount of outsourced person-workyears. The second pricing model is the transaction-based, in which the price will be formed according to the amount of transactions. Changing the pricing model from FTE-based to the transaction-based will also incur other costs. It is very important that these other costs are also taken into consideration, so that it is possible to determine the total costs of the pricing models. These other costs are direct costs, indirect costs and performance related costs of outsourcing. Activity based-costing (ABC) was used in order to find out the trues indirect costs of the outsourced processes. Performance related costs are related to quality, so Pareto-analysis was used to analyse the costs. Based on all of that, a framework for service related cost analysis was developed. Quality costs were almost impossible to quantify, so quality had to be taken into consideration in a qualitative way. Furthermore, considering only the indirect and direct costs in a quantitative way and quality costs in a qualitative way, it was possible to find a conditional solution for the research question.

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The aim of this work is to compare two families of mathematical models for their respective capability to capture the statistical properties of real electricity spot market time series. The first model family is ARMA-GARCH models and the second model family is mean-reverting Ornstein-Uhlenbeck models. These two models have been applied to two price series of Nordic Nord Pool spot market for electricity namely to the System prices and to the DenmarkW prices. The parameters of both models were calibrated from the real time series. After carrying out simulation with optimal models from both families we conclude that neither ARMA-GARCH models, nor conventional mean-reverting Ornstein-Uhlenbeck models, even when calibrated optimally with real electricity spot market price or return series, capture the statistical characteristics of the real series. But in the case of less spiky behavior (System prices), the mean-reverting Ornstein-Uhlenbeck model could be seen to partially succeeded in this task.

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This study investigates futures market efficiency and optimal hedge ratio estimation. First, cointegration between spot and futures prices is studied using Johansen method, with two different model specifications. If prices are found cointegrated, restrictions on cointegrating vector and adjustment coefficients are imposed, to account for unbiasedness, weak exogeneity and prediction hypothesis. Second, optimal hedge ratios are estimated using static OLS, and time-varying DVEC and CCC models. In-sample and out-of-sample results for one, two and five period ahead are reported. The futures used in thesis are RTS index, EUR/RUB exchange rate and Brent oil, traded in Futures and options on RTS.(FORTS) For in-sample period, data points were acquired from start of trading of each futures contract, RTS index from August 2005, EUR/RUB exchange rate March 2009 and Brent oil October 2008, lasting till end of May 2011. Out-of-sample period covers start of June 2011, till end of December 2011. Our results indicate that all three asset pairs, spot and futures, are cointegrated. We found RTS index futures to be unbiased predictor of spot price, mixed evidence for exchange rate, and for Brent oil futures unbiasedness was not supported. Weak exogeneity results for all pairs indicated spot price to lead in price discovery process. Prediction hypothesis, unbiasedness and weak exogeneity of futures, was rejected for all asset pairs. Variance reduction results varied between assets, in-sample in range of 40-85 percent and out-of sample in range of 40-96 percent. Differences between models were found small, except for Brent oil in which OLS clearly dominated. Out-of-sample results indicated exceptionally high variance reduction for RTS index, approximately 95 percent.