991 resultados para financial forecasting


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This thesis introduces heat demand forecasting models which are generated by using data mining algorithms. The forecast spans one full day and this forecast can be used in regulating heat consumption of buildings. For training the data mining models, two years of heat consumption data from a case building and weather measurement data from Finnish Meteorological Institute are used. The thesis utilizes Microsoft SQL Server Analysis Services data mining tools in generating the data mining models and CRISP-DM process framework to implement the research. Results show that the built models can predict heat demand at best with mean average percentage errors of 3.8% for 24-h profile and 5.9% for full day. A deployment model for integrating the generated data mining models into an existing building energy management system is also discussed.

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Globalization and interconnectedness in the worldwide sphere have changed the existing and prevailing modus operandi of organizations around the globe and have challenged existing practices along with the business as usual mindset. There are no rules in terms of creating a competitive advantage and positioning within an unstable, constantly changing and volatile globalized business environment. The financial industry, the locomotive or the flagship industry of global economy, especially, within the aftermath of the financial crisis, has reached a certain point trying to recover and redefine its strategic orientation and positioning within the global business arena. Innovation has always been a trend and a buzzword and by many has been considered as the ultimate answer to any kind of problem. The mantra Innovate or Die has been prevailing in any organizational entity in a, sometimes, ruthless endeavour to develop cutting-edge products and services and capture a landmark position in the market. The emerging shift from a closed to an open innovation paradigm has been considered as new operational mechanism within the management and leadership of the company of the future. To that respect, open innovation has been experiencing a tremendous growth research trajectory by putting forward a new way of exchanging and using surplus knowledge in order to sustain innovation within organizations and in the level of industry. In the abovementioned reality, there seems to be something missing: the human element. This research, by going beyond the traditional narratives for open innovation, aims at making an innovative theoretical and managerial contribution developed and grounded on the on-going discussion regarding the individual and organizational barriers to open innovation within the financial industry. By functioning across disciplines and researching out to primary data, it debunks the myth that open innovation is solely a knowledge inflow and outflow mechanism and sheds light to the understanding on the why and the how organizational open innovation works by enlightening the broader dynamics and underlying principles of this fascinating paradigm. Little attention has been given to the role of the human element, the foundational pre-requisite of trust encapsulated within the precise and fundamental nature of organizing for open innovation, the organizational capabilities, the individual profiles of open innovation leaders, the definition of open innovation in the realms of the financial industry, the strategic intent of the financial industry and the need for nurturing a societal impact for human development. To that respect, this research introduces the trust-embedded approach to open innovation as a new insightful way of organizing for open innovation. It unveils the peculiarities of the corporate and individual spheres that act as a catalyst towards the creation of productive open innovation activities. The incentive of this research captures the fundamental question revolving around the need for financial institutions to recognise the importance for organizing for open innovation. The overarching question is why and how to create a corporate culture of openness in the financial industry, an organizational environment that can help open innovation excel. This research shares novel and cutting edge outcomes and propositions both under the prism of theory and practice. The trust-embedded open innovation paradigm captures the norms and narratives around the way of leading open innovation within the 21st century by cultivating a human-centricity mindset that leads to the creation of human organizations, leaving behind the dehumanization mindset currently prevailing within the financial industry.

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The thesis explores how the business ecosystem of financial services has changed and what its drivers of change are. Existing literature in the field of financial industry is concerned with financial innovations and their features, determinants and factors, but also with how to organize innovation activities such as open innovation principles. Thus, there is a clear need for understanding changes in financial service ecosystem. First, the comprehensive theory framework is conducted in order to serve the reader’s necessary understanding of basic theoretical concepts that are related to ecosystem changes. Second, the research is carried out by using qualitative research methods; the data is collected by interviewing 11 experts from the field of financial services in Finland. According to the results of this thesis, the most significant changes in the financial service ecosystem are the new market players. They have increased competition, created new courses of action, set new requirements for financial services, and first and foremost, they have shifted customers into the heart of the whole ecosystem. These new market players have a willingness to cooperate with external partners, which means a shift towards the world of open innovation. In addition, the economic environment has changed which has resulted in tighter regulation for incumbents making them even unyielding. Technology change, together with digitalization, has lead new financial innovations and new digital service channels, which have challenged the traditional business models in the financial industry. They have improved transparency, openness and efficiency, but also lead to the fragmentation of financial services. Thus, customers search for financial services from different sources and different service providers, and finally combine them into a coherent whole, which meets their own needs. The change of customers’ behavior and social environment has enabled and boosted these changes in the financial ecosystem. All in all, the change of the financial ecosystem is not a result of one or a few change forces, but instead it is a combination of many different factors.

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This research examines the concept of social entrepreneurship which is a fairly new business model. In the field of business it has become increasingly popular in recent years. The growing awareness of the environment and concrete examples of impact created by social entrepreneurship have encouraged entrepreneurs to address social problems. Society’s failures are tried to redress as a result of business activities. The purpose of doing business is necessarily no longer generating just profits but business is run in order to make a social change with the profit gained from the operations. Successful social entrepreneurship requires a specific nature, constant creativity and strong desire to make a social change. It requires constant balancing between two major objectives: both financial and non-financial issues need to be considered, but not at the expense of another. While aiming at the social purpose, the business needs to be run in highly competitive markets. Therefore, both factors need equally be integrated into an organization as they are complementary, not exclusionary. Business does not exist without society and society cannot go forward without business. Social entrepreneurship, its value creation, measurement tools and reporting practices are under discussion in this research. An extensive theoretical basis is covered and used to support the findings coming out of the researched case enterprises. The most attention is focused on the concept of Social Return on Investment. The case enterprises are analyzed through the SROI process. Social enterprises are mostly small or medium sized. Naturally this sets some limitations in implementing measurement tools. The question of resources requires the most attention and therefore sets the biggest constraints. However, the size of the company does not determine all – the nature of business and the type of social purpose need to be considered always. The mission may be so concrete and transparent that in all cases any kind of measurement would be useless. Implementing measurement tools may be of great benefit – or a huge financial burden. Thus, the very first thing to carefully consider is the possible need of measuring value creation.

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The context of financial services has been characterised by changes in the regulatory, technological and societal landscape. Consumers are increasingly interested in mobile payments, crowdfunding and microfinance services, either for themselves or because collaborative consumption is viewed as a more sustainable. Retail branches are re-organised to further meet the expectations of customers, start-ups focusing on technology for financial services (i.e. Fintech) are ever growing and financial services companies reinforce their own innovation practices (e.g. creation of innovation labs or venture capital investment funds). The innovation ecosystem around financial services companies represents the many actors with whom they can co-create and co-produce innovative new services for their customers (or for themselves). The innovation process is no longer a closed internal effort but needs to include external actors from the innovation ecosystem. This topic is especially interesting in a small and open economy where the financial centre takes a prominent place in the economy. The research question is therefore “How does the innovation ecosystem influence the innovation process within financial services companies?”. The influence of the innovation ecosystem on the innovation process within financial service companies mainly comes from its social capital and value creation efforts. However learning to work and exchange in an innovation ecosystem is also expected to influence the innovation process in place. Realizing the potential of the innovation ecosystem requires sufficient capabilities to manage new information coming from the innovation ecosystem. The professional associations provide the necessary coordination among actors in the innovation ecosystem to co-create and appropriate value, while fostering co-evolution within the innovation ecosystem.

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The financial sector has been viewed traditionally as either providing the "oil" for the "wheels of commerce" or as a parasite on the real sector of the economy where real productivity gains provide for increasing real wages and per capita incomes. The present paper takes a different route and attempts to an analysis of financial institutions on a par with the production sector of the economy. It also develops a link which amalgamates "the knowledge-based" perspective on firms' operations with Schumpeterian financial leverage to exploit productivity enhancing innovations, and Minsky's tendency towards financial fragility. The analysis also leads to some policy recommendations concerning financial regulation, risk management and financial institution's building.

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Different axioms underlie efficient market theory and Keynes's liquidity preference theory. Efficient market theory assumes the ergodic axiom. Consequently, today's decision makers can calculate with actuarial precision the future value of all possible outcomes resulting from today's decisions. Since in an efficient market world decision makers "know" their intertemporal budget constraints, decision makers never default on a loan, i.e., systemic defaults, insolvencies, and bankruptcies are impossible. Keynes liquidity preference theory rejects the ergodic axiom. The future is ontologically uncertain. Accordingly systemic defaults and insolvencies can occur but can never be predicted in advance.

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The 2008 global financial crisis was the consequence of the process of financialization, or the creation of massive fictitious financial wealth, that began in the 1980s, and of the hegemony of a reactionary ideology, namely, neoliberalism, based on self-regulated and efficient markets. Although capitalism is intrinsically unstable, the lessons from the stock-market crash of 1929 and the Great Depression of the 1930s were transformed into theories and institutions or regulations that led to the "30 glorious years of capitalism" (1948-1977) and that could have avoided a financial crisis as profound as the present one. It did not because a coalition of rentiers and "financists" achieved hegemony and, while deregulating the existing financial operations, refused to regulate the financial innovations that made these markets even more risky. Neoclassical economics played the role of a meta-ideology as it legitimized, mathematically and "scientifically", neoliberal ideology and deregulation. From this crisis a new capitalism will emerge, though its character is difficult to predict. It will not be financialized but the tendencies present in the 30 glorious years toward global and knowledge-based capitalism, where professionals will have more say than rentier capitalists, as well as the tendency to improve democracy by making it more social and participative, will b e resumed.

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This work aims at presenting the challenges that inflation targeting central banks may face since uncertainties represent a harmful element for the effectiveness of monetary policy, and since financial instabilities may disturb the transmission mechanisms - in particular, the expectation channel - and thus the economic stability. Financial stability must not be considered as a simple goal of monetary policy, but a precondition for central banks operate their policies and reach the goals of inflation and output stability. The work identifies different sources of uncertainties that surround central banks' decisions; and approaches the role that inflation targeting central banks should play according to some basic principles that can serve as useful guides for central banks to help them achieve successful outcomes in their conduct of monetary policy.

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Already one-third of the human population uses social media on a daily basis. The biggest social networking site Facebook has over billion monthly users. As a result, social media services are now recording unprecedented amount of data on human behavior. The phenomenon has certainly caught the attention of scholars, businesses and governments alike. Organizations around the globe are trying to explore new ways to benefit from the massive databases. One emerging field of research is the use of social media in forecasting. The goal is to use data gathered from online services to predict offline phenomena. Predicting the results of elections is a prominent example of forecasting with social media, but regardless of the numerous attempts, no reliable technique has been established. The objective of the research is to analyze how accurately the results of parliament elections can be forecasted using social media. The research examines whether Facebook “likes” can be effectively used for predicting the outcome of the Finnish parliament elections that took place in April 2015. First a tool for gathering data from Facebook was created. Then the data was used to create an electoral forecast. Finally, the forecast was compared with the official results of the elections. The data used in the research was gathered from the Facebook walls of all the candidates that were running for the parliament elections and had a valid Facebook page. The final sample represents 1131 candidates and over 750000 Facebook “likes”. The results indicate that creating a forecast solely based on Facebook “likes” is not accurate. The forecast model predicted very dramatic changes to the Finnish political landscape while the official results of the elections were rather moderate. However, a clear statistical relationship between “likes” and votes was discovered. In conclusion, it is apparent that citizens and other key actors of the society are using social media in an increasing rate. However, the volume of the data does not directly increase the quality of the forecast. In addition, the study faced several other limitations that should be addressed in future research. Nonetheless, discovering the positive correlation between “likes” and votes is valuable information that can be used in future studies. Finally, it is evident that Facebook “likes” are not accurate enough and a meaningful forecast would require additional parameters.

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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.

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Contrasting with the 1929 great crisis, authorities intervened forcefully in 2008 to stop the disintegration of the financial system. Governments and central banks then sought to revise the prudential regulation in depth. It would be optimistic, however, to believe that prudential measures, alone, could deliver full economic recovery, at least in the countries that had been involved in the financial turmoil. Indeed, the collapse of the "state of confidence" and the negative effects of private debts on consumption and investment decisions have fed depressive forces and policy challenges which could hold for a while, even once the financial sector is made safe. On the one hand, the economic slowdown and the direct and indirect assistance provided by the governments to the private sectors are having a heavy impact on public finances, meanwhile, on the other hand, the massive amounts of money which artificially inflated the prices of housing and financial products could produce inflationary pressures in the post-crisis period, unless a new assets bubble is allowed for. Authorities could therefore be facing high unemployment in a damaged context of public deficits and inflationary pressures. The paper aims at discussing these new challenges. The inadequacy of inflation targets and fiscal orthodoxy in a depressed economy is emphasized, and the outlines of a Post Keynesian alternative policy are examined.

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The paper investigates the recent financial crisis within a historical and comparative perspective having in mind that it is ultimately a confidence crisis, initially associated to a chain of high risk loans and financial innovations that spread thorough the international system culminating with impressive wealth losses. The financial market will eventually recover from the crisis but the outcome should be followed by a different and more disciplined set of international institutions. There will be a change on how we perceive the widespread liberal argument that the market is always efficient, or at least, more efficient than any State intervention, overcoming the false perception that the State is in opposition to the market. A deep financial crisis brings out a period of wealth losses and an adjustment process characterized by price corrections (commodities and equity price deflation) and real effects (recession and lower employment), and a period of turbulences and end of illusions is in place.