40 resultados para Stores or stock-room keeping


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The desire to create a statistical or mathematical model, which would allow predicting the future changes in stock prices, was born many years ago. Economists and mathematicians are trying to solve this task by applying statistical analysis and physical laws, but there are still no satisfactory results. The main reason for this is that a stock exchange is a non-stationary, unstable and complex system, which is influenced by many factors. In this thesis the New York Stock Exchange was considered as the system to be explored. A topological analysis, basic statistical tools and singular value decomposition were conducted for understanding the behavior of the market. Two methods for normalization of initial daily closure prices by Dow Jones and S&P500 were introduced and applied for further analysis. As a result, some unexpected features were identified, such as a shape of distribution of correlation matrix, a bulk of which is shifted to the right hand side with respect to zero. Also non-ergodicity of NYSE was confirmed graphically. It was shown, that singular vectors differ from each other by a constant factor. There are for certain results no clear conclusions from this work, but it creates a good basis for the further analysis of market topology.

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Research has highlighted the adequacy of Markov regime-switching model to address dynamic behavior in long term stock market movements. Employing a purposed Extended regime-switching GARCH(1,1) model, this thesis further investigates the regime dependent nonlinear relationship between changes in oil price and stock market volatility in Saudi Arabia, Norway and Singapore for the period of 2001-2014. Market selection is prioritized to national dependency on oil export or import, which also rationalizes the fitness of implied bivariate volatility model. Among two regimes identified by the mean model, high stock market return-low volatility regime reflects the stable economic growth periods. The other regime characterized by low stock market return-high volatility coincides with episodes of recession and downturn. Moreover, results of volatility model provide the evidence that shocks in stock markets are less persistent during the high volatility regime. While accelerated oil price rises the stock market volatility during recessions, it reduces the stock market risk during normal growth periods in Singapore. In contrast, oil price showed no significant notable impact on stock market volatility of target oil-exporting countries in either of the volatility regime. In light to these results, international investors and policy makers could benefit the risk management in relation to oil price fluctuation.

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Traditionally real estate has been seen as a good diversification tool for a stock portfolio due to the lower return and volatility characteristics of real estate investments. However, the diversification benefits of a multi-asset portfolio depend on how the different asset classes co-move in the short- and long-run. As the asset classes are affected by the same macroeconomic factors, interrelationships limiting the diversification benefits could exist. This master’s thesis aims to identify such dynamic linkages in the Finnish real estate and stock markets. The results are beneficial for portfolio optimization tasks as well as for policy-making. The real estate industry can be divided into direct and securitized markets. In this thesis the direct market is depicted by the Finnish housing market index. The securitized market is proxied by the Finnish all-sectors securitized real estate index and by a European residential Real Estate Investment Trust index. The stock market is depicted by OMX Helsinki Cap index. Several macroeconomic variables are incorporated as well. The methodology of this thesis is based on the Vector Autoregressive (VAR) models. The long-run dynamic linkages are studied with Johansen’s cointegration tests and the short-run interrelationships are examined with Granger-causality tests. In addition, impulse response functions and forecast error variance decomposition analyses are used for robustness checks. The results show that long-run co-movement, or cointegration, did not exist between the housing and stock markets during the sample period. This indicates diversification benefits in the long-run. However, cointegration between the stock and securitized real estate markets was identified. This indicates limited diversification benefits and shows that the listed real estate market in Finland is not matured enough to be considered a separate market from the general stock market. Moreover, while securitized real estate was shown to cointegrate with the housing market in the long-run, the two markets are still too different in their characteristics to be used as substitutes in a multi-asset portfolio. This implies that the capital intensiveness of housing investments cannot be circumvented by investing in securitized real estate.

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An investor can either conduct independent analysis or rely on the analyses of others. Stock analysts provide markets with expectations regarding particular securities. However, analysts have different capabilities and resources, of which investors are seldom cognizant. The local advantage refers to the advantage stemming from cultural or geographical proximity to securities analyzed. The research has confirmed that local agents are generally more accurate or produce excess returns. This thesis tests the investment value of the local advantage regarding Finnish stocks via target price data. The empirical section investigates the local advantage from several aspects. It is discovered that local analysts were more focused on certain sectors generally located close to consumer markets. Market reactions to target price revisions were generally insignificant with the exception to local positive target prices. Both local and foreign target prices were overly optimistic and exhibited signs of herding. Neither group could be identified as a leader or follower of new information. Additionally, foreign price change expectations were more in line with the quantitative models and ideas such as beta or return mean reversion. The locals were more accurate than foreign analysts in 5 out of 9 sectors and vice versa in one. These sectors were somewhat in line with coverage decisions and buttressed the idea of local advantage stemming from proximity to markets, not to headquarters. The accuracy advantage was dependent on sample years and on the measure used. Local analysts ranked magnitudes of price changes more accurately in optimistic and foreign analysts in pessimistic target prices. Directional accuracy of both groups was under 50% and target prices held no linear predictive power. Investment value of target prices were tested by forming mean-variance efficient portfolios. Parallel to differing accuracies in the levels of expectations foreign portfolio performed better when short sales were allowed and local better when disallowed. Both local and non-local portfolios performed worse than a passive index fund, albeit not statistically significantly. This was in line with previously reported low overall accuracy and different accuracy profiles. Refraining from estimating individual stock returns altogether produced statistically significantly higher Sharpe ratios compared to local or foreign portfolios. The proposed method of testing the investment value of target prices of different groups suffered from some inconsistencies. Nevertheless, these results are of interest to investors seeking the advice of security analysts.

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Since different stock markets have become more integrated during 2000s, investors need new asset classes in order to gain diversification benefits. Commodities have become popular to invest in and thus it is important to examine whether the investors should use commodities as a part for portfolio diversification. This master’s thesis examines the dynamic relationship between Finnish stock market and commodities. The methodology is based on Vector Autoregressive models (VAR). The long-run relationship between Finnish stock market and commodities is examined with Johansen cointegration while short-run relationship is examined with VAR models and Granger causality test. In addition, impulse response test and forecast error variance decomposition are employed to strengthen the results of short-run relationship. The dynamic relationships might change under different market conditions. Thus, the sample period is divided into two sub-samples in order to reveal whether the dynamic relationship varies under different market conditions. The results show that Finnish stock market has stable long-run relationship with industrial metals, indicating that there would not be diversification benefits among the industrial metals. The long-run relationship between Finnish stock market and energy commodities is not as stable as the long-run relationship between Finnish stock market and industrial metals. Long-run relationship was found in the full sample period and first sub-sample which indicate less room for diversification. However, the long-run relationship disappeared in the second sub-sample which indicates diversification benefits. Long-run relationship between Finnish stock market and agricultural commodities was not found in the full sample period which indicates diversification benefits between the variables. However, long-run relationship was found from both sub-samples. The best diversification benefits would be achieved if investor invested in precious metals. No long-run relationship was found from either sample. In the full sample period OMX Helsinki had short-run relationship with most of the energy commodities and industrial metals and the causality was mostly running from equities to commodities. During the first sub period the number of short-run relationships and causality shrunk but during the crisis period the number of short-run relationships and causality increased. The most notable result found was unidirectional causality from gold to OMX Helsinki during the crisis period.

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Tässä kauppatieteiden kandidaatintyössä tutkittiin millaisia vaikutuksia julkisesti noteerattujen yhtiöiden osakekurssissa tapahtuu, kun jo valmiiksi Helsingin pörssissä listattu yritys jakautuu kahdeksi uudeksi pörssiyritykseksi. Molempien yrityksien osakkeita voi tämän jakautumisen jälkeen vapaasti ostaa tai myydä. Aikaisempi tutkimus on pääsääntöisesti keskittynyt Yhdysvaltojen markkinoille ja näiden tutkimusten tuloksien perusteella on monessa tapauksessa havautta, että on mahdollista saavuttaa ylinormaaleja tuottoja, kun pörssiyritys jakautuu kahdeksi uudeksi pörssiyritykseksi. Tässä analyysissä jakautumiset ajallisesti tapahtuivat vuosien 1994 ja 2013 välisenä aikana Suomessa ja näitä jakautumia oli yhteensä 16 kappaletta. Tutkimuksessa on hyödynnetty tilastollisten menetelmien analyysiä sekä CAP-mallia, jotta voitaisiin löytää vastauksia seuraaviin kysymyksiin: Vaikuttaako pörssiyrityksen jakautuminen kahdeksi pörssiyritykseksi alkuperäisen yhtiön ja uuden yhtiön osakekursseihin? Onko vaikutus positiivinen, negatiivinen vai onko jakautumisella mitään havaittavaa vaikutusta? Tämän tutkimuksen tulokset antavat uutta tietoa tutkijoille, analyytikoille, opettajille, opiskelijoille, yrityksille ja yritysten johdolle sekä erityisesti sijoittajille. Tulosten mukaan on nähtävissä monia vaikutuksia osakekursseissa, kun pörssiyritys jakautuu. Vaikutus näyttää kuitenkin olevan jossain määrin yritys-riippuvainen. Kun sijoitetaan oikeaan aikaan, on monia jakautuvia yrityksiä, jotka antavat hyvän tuoton keskimäärin, mutta kuten tavallista ja tyypillistä osakemarkkinoille, on myös jakautuvia yhtiöitä, jotka antavat negatiivisia tuottoja tai tuotot ovat nollassa

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Various researches in the field of econophysics has shown that fluid flow have analogous phenomena in financial market behavior, the typical parallelism being delivered between energy in fluids and information on markets. However, the geometry of the manifold on which market dynamics act out their dynamics (corporate space) is not yet known. In this thesis, utilizing a Seven year time series of prices of stocks used to compute S&P500 index on the New York Stock Exchange, we have created local chart to the corporate space with the goal of finding standing waves and other soliton like patterns in the behavior of stock price deviations from the S&P500 index. By first calculating the correlation matrix of normalized stock price deviations from the S&P500 index, we have performed a local singular value decomposition over a set of four different time windows as guides to the nature of patterns that may emerge. I turns out that in almost all cases, each singular vector is essentially determined by relatively small set of companies with big positive or negative weights on that singular vector. Over particular time windows, sometimes these weights are strongly correlated with at least one industrial sector and certain sectors are more prone to fast dynamics whereas others have longer standing waves.

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An investor can either conduct independent analysis or rely on the analyses of others. Stock analysts provide markets with expectations regarding particular securities. However, analysts have different capabilities and resources, of which investors are seldom cognizant. The local advantage refers to the advantage stemming from cultural or geographical proximity to securities analyzed. The research has confirmed that local agents are generally more accurate or produce excess returns. This thesis tests the investment value of the local advantage regarding Finnish stocks via target price data. The empirical section investigates the local advantage from several aspects. It is discovered that local analysts were more focused on certain sectors generally located close to consumer markets. Market reactions to target price revisions were generally insignificant with the exception to local positive target prices. Both local and foreign target prices were overly optimistic and exhibited signs of herding. Neither group could be identified as a leader or follower of new information. Additionally, foreign price change expectations were more in line with the quantitative models and ideas such as beta or return mean reversion. The locals were more accurate than foreign analysts in 5 out of 9 sectors and vice versa in one. These sectors were somewhat in line with coverage decisions and buttressed the idea of local advantage stemming from proximity to markets, not to headquarters. The accuracy advantage was dependent on sample years and on the measure used. Local analysts ranked magnitudes of price changes more accurately in optimistic and foreign analysts in pessimistic target prices. Directional accuracy of both groups was under 50% and target prices held no linear predictive power. Investment value of target prices were tested by forming mean-variance efficient portfolios. Parallel to differing accuracies in the levels of expectations foreign portfolio performed better when short sales were allowed and local better when disallowed. Both local and non-local portfolios performed worse than a passive index fund, albeit not statistically significantly. This was in line with previously reported low overall accuracy and different accuracy profiles. Refraining from estimating individual stock returns altogether produced statistically significantly higher Sharpe ratios compared to local or foreign portfolios. The proposed method of testing the investment value of target prices of different groups suffered from some inconsistencies. Nevertheless, these results are of interest to investors seeking the advice of security analysts.

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Pairs trading is an algorithmic trading strategy that is based on the historical co-movement of two separate assets and trades are executed on the basis of degree of relative mispricing. The purpose of this study is to explore one new and alternative copula-based method for pairs trading. The objective is to find out whether the copula method generates more trading opportunities and higher profits than the more traditional distance and cointegration methods applied extensively in previous empirical studies. Methods are compared by selecting top five pairs from stocks of the large and medium-sized companies in the Finnish stock market. The research period includes years 2006-2015. All the methods are proven to be profitable and the Finnish stock market suitable for pairs trading. However, copula method doesn’t generate more trading opportunities or higher profits than the other methods. It seems that the limitations of the more traditional methods are not too restrictive for this particular sample data.

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Health Innovation Village at GE is one of the new communities targeted for startup and growth-oriented companies. It has been established at the premises of a multinational conglomerate that will promote networking and growth of startup companies. The concept combines features from traditional business incubators, accelerators, and coworking spaces. This research compares Health Innovation Village to these concepts regarding its goals, target clients, source of income, organization, facilities, management, and success factors. In addition, a new incubator classification model is introduced. On the other hand, Health Innovation Village is examined from its tenants’ perspective and improvements are suggested. The work was implemented as a qualitative case study by interviewing GE staff with connections to Health Innovation Village as well as startup entrepreneurs and employees’ working there. The most evident features of Health Innovation Village correspond to those of business incubators although it is atypical as a non-profit corporate business incubator. Strong network orientation and connections to venture capitalists are common characteristics of these new types of accelerators. The design of the premises conforms to the principles of coworking spaces, but the services provided to the startup companies are considerably more versatile than the services offered by coworking spaces. The advantages of Health Innovation Village are that there are first-class premises and exceptionally good networking possibilities that other types of incubators or accelerators are not able to offer. A conglomerate can also provide multifaceted special knowledge for young firms. In addition, both GE and the startups gained considerable publicity through their cooperation, indeed a characteristic that benefits both parties. Most of the expectations of the entrepreneurs were exceeded. However, communication and the scope of cooperation remain challenges. Micro companies spend their time developing and marketing their products and acquiring financing. Therefore, communication should be as clear as possible and accessible everywhere. The startups would prefer to cooperate significantly more, but few have the time available to assume the responsibility of leadership. The entrepreneurs also expected to have more possibilities for cooperation with GE. Wider collaboration might be accomplished by curation in the same way as it is used in the well-functioning coworking spaces where curators take care of practicalities and promote cooperation. Communication issues could be alleviated if the community had its own Intranet pages where all information could be concentrated. In particular, a common calendar and a room reservation system could be useful. In addition, it could be beneficial to have a section of the Intranet open for both the GE staff and the startups so that those willing to share their knowledge and those having project offers could use it for advertising.