856 resultados para Finnish stock market


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Whilst financial markets are not strangers to academic and professional scrutiny, they still remain epistemologically contested. For individuals trying to profit by trading shares, this uncertainty is manifested in the varying trading styles which they are able to utilize. This paper examines one trading style commonly used by non-professional share traders-technical analysis. Using research data obtained from individuals who identify themselves as technical analysts, this paper seeks to explain the ways in which individuals understand and use the technique in an attempt to make trading profits. In particular, four distinct subcategories or ideal types of technical analysis can be identified, each providing an alternative perceptual form for participating in financial markets. Each of these types relies upon a particular method for seeing the market, these visualization techniques highlighting the existence of forms of professional vision (as originally identified by Goodwin (1994)) in the way the trading styles are comprehended and acted upon.

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We examine the short-term price reaction of 424 UK stocks to large one-day price changes. Using the GJR-GARCH(1,1), we find no statistical difference amongst the cumulative abnormal returns (CARs) of the Single Index, the Fama–French and the Carhart–Fama–French models. Shocks bigger or equal to 5% are followed by a significant one-day CAR of 1% for all the models. Whilst shocks smaller or equal to -5% are followed by a significant one-day CAR of -0.43% for the Single Index, the CARs are around -0.34% for the other two models. Positive shocks of all sizes and negative shocks maller or equal to -5% are followed by return continuations, whilst the market is efficient following larger negative shocks. The price reaction to shocks is unaffected when we estimate the CARs using the conditional covariances of the pricing variables.

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Purpose – The purpose of this paper is to investigate the impact of foreign exchange and interest rate changes on US banks’ stock returns. Design/methodology/approach – The approach employs an EGARCH model to account for the ARCH effects in daily returns. Most prior studies have used standard OLS estimation methods with the result that the presence of ARCH effects would have affected estimation efficiency. For comparative purposes, the standard OLS estimation method is also used to measure sensitivity. Findings – The findings are as follows: under the conditional t-distributional assumption, the EGARCH model generated a much better fit to the data although the goodness-of-fit of the model is not entirely satisfactory; the market index return accounts for most of the variation in stock returns at both the individual bank and portfolio levels; and the degree of sensitivity of the stock returns to interest rate and FX rate changes is not very pronounced despite the use of high frequency data. Earlier results had indicated that daily data provided greater evidence of exposure sensitivity. Practical implications – Assuming that banks do not hedge perfectly, these findings have important financial implications as they suggest that the hedging policies of the banks are not reflected in their stock prices. Alternatively, it is possible that different GARCH-type models might be more appropriate when modelling high frequency returns. Originality/value – The paper contributes to existing knowledge in the area by showing that ARCH effects do impact on measures of sensitivity.

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A two-factor no-arbitrage model is used to provide a theoretical link between stock and bond market volatility. While this model suggests that short-term interest rate volatility may, at least in part, drive both stock and bond market volatility, the empirical evidence suggests that past bond market volatility affects both markets and feeds back into short-term yield volatility. The empirical modelling goes on to examine the (time-varying) correlation structure between volatility in the stock and bond markets and finds that the sign of this correlation has reversed over the last 20 years. This has important implications far portfolio selection in financial markets. © 2005 Elsevier B.V. All rights reserved.

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We estimate the shape of the distribution of stock prices using data from options on the underlying asset, and test whether this distribution is distorted in a systematic manner each time a particular news event occurs. In particular we look at the response of the FTSE100 index to market wide announcements of key macroeconomic indicators and policy variables. We show that the whole distribution of stock prices can be distorted on an event day. The shift in distributional shape happens whether the event is characterized as an announcement occurrence or as a measured surprise. We find that larger surprises have proportionately greater impact, and that higher moments are more sensitive to events however characterised.

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Modern injection-moulding machinery which produces several, pairs of plastic footwear at a time brought increased production planning problems to a factory. The demand for its footwear is seasonal but the company's manning policy keeps a fairly constant production level thus determining the aggregate stock. Production planning must therefore be done within the limitations of a specified total stock. The thesis proposes a new production planning system with four subsystems. These are sales forecasting, resource planning, and two levels of production scheduling: (a) aggregate decisions concerning the 'manufacturing group' (group of products) to be produced in each machine each week, and (b) detailed decisions concerning the products within a manufacturing group to be scheduled into each mould-place. The detailed scheduling is least dependent on improvements elsewhere so the sub-systems were tackled in reverse order. The thesis concentrates on the production scheduling sub-systems which will provide most. of the benefits. The aggregate scheduling solution depends principally on the aggregate stocks of each manufacturing group and their division into 'safety stocks' (to prevent shortages) and 'freestocks' (to permit batch production). The problem is too complex for exact solution but a good heuristic solution, which has yet to be implemented, is provided by minimising graphically immediate plus expected future costs. The detailed problem splits into determining the optimal safety stocks and batch quantities given the appropriate aggregate stocks. It.is found that the optimal safety stocks are proportional to the demand. The ideal batch quantities are based on a modified, formula for the Economic Batch Quantity and the product schedule is created week by week using a priority system which schedules to minimise expected future costs. This algorithm performs almost optimally. The detailed scheduling solution was implemented and achieved the target savings for the whole project in favourable circumstances. Future plans include full implementation.

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We analyze detailed monthly data on U.S. open market stock repurchases (OMRs) that recently became available following stricter disclosure requirements. We find evidence that OMRs are timed to benefit non-selling shareholders. We present evidence that the profits to companies from timing repurchases are significantly related to ownership structure. Institutional ownership reduces companies' opportunities to repurchase stock at bargain prices. At low levels, insider ownership increases timing profits and at high levels it reduces them. Stock liquidity increases profits from timing OMRs.

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We examine contemporaneous jumps (cojumps) among individual stocks and a proxy for the market portfolio. We show, through a Monte Carlo study, that using intraday jump tests and a coexceedance criterion to detect cojumps has a power similar to the cojump test proposed by Bollerslev et al. (2008). However, we also show that we should not expect to detect all common jumps comprising a cojump when using such coexceedance based detection methods. Empirically, we provide evidence of an association between jumps in the market portfolio and cojumps in the underlying stocks. Consistent with our Monte Carlo evidence, moderate numbers of stocks are often detected to be involved in these (systematic) cojumps. Importantly, the results suggest that market-level news is able to generate simultaneous large jumps in individual stocks. We also find evidence of an association between systematic cojumps and Federal Funds Target Rate announcements. © 2013 Elsevier B.V.

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Purpose - The paper aims to examine the role of market orientation (MO) and innovation capability in determining business performance during an economic upturn and downturn. Design/methodology/approach - The data comprise two national-level surveys conducted in Finland in 2008, representing an economic boom, and in 2010 when the global economic crisis had hit the Finnish market. Partial least square path analysis is used to test the potential mediating effect of innovation capability on the relationship between MO and business performance during economic boom and bust. Findings - The results show that innovation capability fully mediates the performance effects of a MO during an economic upturn, whereas the mediation is only partial during a downturn. Innovation capability also mediates the relationship between a customer orientation and business performance during an upturn, whereas the mediating effect culminates in a competitor orientation during a downturn. Thus, the role of innovation capability as a mediator between the individual market-orientation components varies along the business cycle. Originality/value - This paper is one of the first studies that empirically examine the impact of the economic cycle on the relationship between strategic marketing concepts, such as MO or innovation capability, and the firm's business performance.

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Around 80% of the 63 million people in the UK live in urban areas where demand for affordable housing is highest. Supply of new dwellings is a long way short of demand and with an average annual replacement rate of 0.5% more than 80% of the existing residential housing stock will still be in use by 2050. A high proportion of owner-occupiers, a weak private rental sector and lack of sustainable financing models render England’s housing market one of the least responsive in the developed world. As an exploratory research the purpose of this paper is to examine the provision of social housing in the United Kingdom with a particular focus on England, and to set out implications for housing associations delivering sustainable community development. The paper is based on an analysis of historical data series (Census data), current macro-economic data and population projections to 2033. The paper identifies a chronic undersupply of affordable housing in England which is likely to be exacerbated by demographic development, changes in household composition and reduced availability of finance to develop new homes. Based on the housing market trends analysed in this paper opportunities are identified for policy makers to remove barriers to the delivery of new affordable homes and for social housing providers to evolve their business models by taking a wider role in sustainable community development.

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The purpose of this paper is to explain the notion of clustering and a concrete clustering method- agglomerative hierarchical clustering algorithm. It shows how a data mining method like clustering can be applied to the analysis of stocks, traded on the Bulgarian Stock Exchange in order to identify similar temporal behavior of the traded stocks. This problem is solved with the aid of a data mining tool that is called XLMiner™ for Microsoft Excel Office.

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Az árhatásfüggvények azt mutatják meg, hogy egy adott értékű megbízás mekkora relatív árváltozást okoz. Az árhatásfüggvény ismerete a piaci szereplők számára fontos szerepet játszik a jövőben benyújtandó ajánlataikhoz kapcsolódó árhatás előrejelzésében, a kereskedés árváltozásból eredő többletköltségének becslésében, illetve az optimális kereskedési algoritmus kialakításában. Az általunk kidolgozott módszer révén a piaci szereplők a teljes ajánlati könyv ismerete nélkül egyszerűen és gyorsan tudnak virtuális árhatásfüggvényt meghatározni, ugyanis bemutatjuk az árhatásfüggvény és a likviditási mértékek kapcsolatát, valamint azt, hogy miként lehet a Budapesti Likviditási Mérték (BLM) idősorából ár ha tás függ vényt becsülni. A kidolgozott módszertant az OTP-részvény idősorán szemléltetjük, és a részvény BLM-adatsorából a 2007. január 1-je és 2011. június 3-a közötti időszakra virtuális árhatás függvényt becsülünk. Empirikus elemzésünk során az árhatás függ vény időbeli alakulásának és alapvető statisztikai tulajdonságainak vizsgálatát végezzük el, ami révén képet kaphatunk a likviditás hiányában fellépő tranzakciós költségek múltbeli viselkedéséről. Az így kapott információk például a dinamikus portfólióoptimalizálás során lehetnek a kereskedők segítségére. / === / Price-effect equations show what relative price change a commission of a given value will have. Knowledge of price-effect equations plays an important part in enabling market players to predict the price effect of their future commissions and to develop an optimal trading algorithm. The method devised by the authors allows a virtual price-effect equation to be defined simply and rapidly without knowledge of the whole offer book, by presenting the relation between the price-effect equation and degree of liquidity, and how to estimate the price-effect equation from the time line of the Budapest Liquidity Measure (BLM). The methodology is shown using the time line for OTP shares and the virtual price-effect equation estimated for the 1 January 2007 to 3 June 2011 period from the shares BML data set. During the empirical analysis the authors conducted an examination of the tendency of the price-effect equation over time and for its basic statistical attributes, to yield a picture of the past behaviour of the transaction costs arising in the absence of liquidity. The information obtained may, for instance, help traders in dynamic portfolio optimization.

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Environmental protectionism and sustainable development has been gaining increased attention among governments, investors and consumers alike. As a result, firms are facing growing pressure from the various stakeholders to improve their environmental performance. This study is focusing on the food industry, which in recent years has been a subject of increased scrutiny due to their role in resource consumption, waste generation and unsustainable production practices. Our research is aiming to examine how the financial community evaluates the environmental stewardship of food industry companies as proxied by market reactions in response to environmental news. Are all company related environmental news items evaluated equally, and which financial and non-financial firm-specific attributes can influence market responses? Have there been changes in reactions on the stock exchange in the past two decades?