907 resultados para Stock markets


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The nature and organisation of creative industries and the creative economy has received increased attention in recent academic and policy literatures (Florida 2002; Grabher 2002; Scott 2006a). Constituted as one variant on new economy narratives, creativity, alongside knowledge, has been presented as a key competitive asset, Such industries – ranging from advertising, to film and new media – are seen as not merely expanding their scale and scope, but as leading edge proponents of a more general trend towards new forms of organization and economic coordination (Davis and Scase 2000). The idea of network forms (and the consequent displacement of markets and hierarchies) has been at the heart of attempts to differentiate the field economically and spatially. Across both the discussion of production models and work/employment relations is the assertion of the enhanced importance of trust and non-market relations in coordinating structures and practices. This reflects an influential view in sociological, management, geography and other literatures that social life is ‘intrinsically networked’ (Sunley 2008: 12) and that we can confidently use the term ‘network society’ to describe contemporary structures and practices (Castells 1996). Our paper is sceptical of the conceptual and empirical foundations of such arguments. We draw on a number of theoretical resources, including institutional theory, global value chain analysis and labour process theory (see Smith and McKinlay 2009) to explore how a more realistic and grounded analysis of the nature of and limits to networks can be articulated. Given space constraints, we cannot address all the dimensions of network arguments or evidence. Our focus is on inter and intra-firm relations and draws on research into a particular creative industry – visual effects – that is a relatively new though increasingly important global production network. Through this examination a different model of the creative industries and creative work emerges – one in which market rules and patterns of hierarchical interaction structure the behaviour of economic actors and remain a central focus of analysis. The next section outlines and unpacks in more detail arguments concerning the role and significance of networks, markets and hierarchies in production models and work organisation in creative industries and the ‘creative economy’.

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The creative industries are important because they are clustered at the point of attraction for a billion or more young people around the world. They're the drivers of demographic, economic and political change. They start from the individual talent of the creative artist and the individual desire and aspiration of the audience. These are the raw materials for innovation, change and emergent culture, scaled up to form new industries and coordinated into global markets based on social networks.

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The paper investigates if there are any discernible trends in the U.S. and Australian commercial property public debt markets with the onset of the global financial crisis (GFC). Commercial mortgage-backed securities and unsecured bonds issued by real estate investment trusts for the period 2000 to Q3:2009 are reviewed. It is shown that events in the equity markets have an impact on the pricing of these two instruments. Furthermore, the impact of subdued activity in these financing instruments on the commercial property market is discussed.

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Financial processes may possess long memory and their probability densities may display heavy tails. Many models have been developed to deal with this tail behaviour, which reflects the jumps in the sample paths. On the other hand, the presence of long memory, which contradicts the efficient market hypothesis, is still an issue for further debates. These difficulties present challenges with the problems of memory detection and modelling the co-presence of long memory and heavy tails. This PhD project aims to respond to these challenges. The first part aims to detect memory in a large number of financial time series on stock prices and exchange rates using their scaling properties. Since financial time series often exhibit stochastic trends, a common form of nonstationarity, strong trends in the data can lead to false detection of memory. We will take advantage of a technique known as multifractal detrended fluctuation analysis (MF-DFA) that can systematically eliminate trends of different orders. This method is based on the identification of scaling of the q-th-order moments and is a generalisation of the standard detrended fluctuation analysis (DFA) which uses only the second moment; that is, q = 2. We also consider the rescaled range R/S analysis and the periodogram method to detect memory in financial time series and compare their results with the MF-DFA. An interesting finding is that short memory is detected for stock prices of the American Stock Exchange (AMEX) and long memory is found present in the time series of two exchange rates, namely the French franc and the Deutsche mark. Electricity price series of the five states of Australia are also found to possess long memory. For these electricity price series, heavy tails are also pronounced in their probability densities. The second part of the thesis develops models to represent short-memory and longmemory financial processes as detected in Part I. These models take the form of continuous-time AR(∞) -type equations whose kernel is the Laplace transform of a finite Borel measure. By imposing appropriate conditions on this measure, short memory or long memory in the dynamics of the solution will result. A specific form of the models, which has a good MA(∞) -type representation, is presented for the short memory case. Parameter estimation of this type of models is performed via least squares, and the models are applied to the stock prices in the AMEX, which have been established in Part I to possess short memory. By selecting the kernel in the continuous-time AR(∞) -type equations to have the form of Riemann-Liouville fractional derivative, we obtain a fractional stochastic differential equation driven by Brownian motion. This type of equations is used to represent financial processes with long memory, whose dynamics is described by the fractional derivative in the equation. These models are estimated via quasi-likelihood, namely via a continuoustime version of the Gauss-Whittle method. The models are applied to the exchange rates and the electricity prices of Part I with the aim of confirming their possible long-range dependence established by MF-DFA. The third part of the thesis provides an application of the results established in Parts I and II to characterise and classify financial markets. We will pay attention to the New York Stock Exchange (NYSE), the American Stock Exchange (AMEX), the NASDAQ Stock Exchange (NASDAQ) and the Toronto Stock Exchange (TSX). The parameters from MF-DFA and those of the short-memory AR(∞) -type models will be employed in this classification. We propose the Fisher discriminant algorithm to find a classifier in the two and three-dimensional spaces of data sets and then provide cross-validation to verify discriminant accuracies. This classification is useful for understanding and predicting the behaviour of different processes within the same market. The fourth part of the thesis investigates the heavy-tailed behaviour of financial processes which may also possess long memory. We consider fractional stochastic differential equations driven by stable noise to model financial processes such as electricity prices. The long memory of electricity prices is represented by a fractional derivative, while the stable noise input models their non-Gaussianity via the tails of their probability density. A method using the empirical densities and MF-DFA will be provided to estimate all the parameters of the model and simulate sample paths of the equation. The method is then applied to analyse daily spot prices for five states of Australia. Comparison with the results obtained from the R/S analysis, periodogram method and MF-DFA are provided. The results from fractional SDEs agree with those from MF-DFA, which are based on multifractal scaling, while those from the periodograms, which are based on the second order, seem to underestimate the long memory dynamics of the process. This highlights the need and usefulness of fractal methods in modelling non-Gaussian financial processes with long memory.

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As the ultimate corporate decision-makers, directors have an impact on the investment time horizons of the corporations they govern. How they make investment decisions has been profoundly influenced by the expansion of the investment chain and the increasing concentration of share ownership in institutional hands. By examining agency in light of legal theory, we highlight that the board is in fact sui generis and not an agent of shareholders. Consequently, transparency can lead to directors being 'captured' by institutional investor objectives and timeframes, potentially to the detriment of the corporation as a whole. The counter-intuitive conclusion is that transparency may, under certain conditions, undermine good corporate governance and lead to excessive short-termism.

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This paper studies the incentives for credence goods experts to invest effort in diagnosis if effort is both costly and unobservable, and if they face competition by discounters who are not able to perform a diagnosis. The unobservability of diagnosis effort and the credence characteristic of the good induce experts to choose incentive compatible tariff structures. This makes them vulnerable to competition by discounters. We explore the conditions under which honestly diagnosing experts survive competition by discounters; we identify situations in which experts misdiagnose consumers in order to prevent them from free-riding on experts' advice; and we discuss policy options to solve the free-riding consumers–cheating experts problem.

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We examine the nature and extent of statutory executive stock option (ESO) disclosures by Australian listed companies over the 2001 to 2004 period, and the influence of corporate governance mechanisms on these disclosures. Our results show a progressive increase in overall compliance from 2001 to 2004. However, despite the improved compliance, the results reveal managements’ continued reluctance to disclose more sensitive ESO information. Factors associated with good internal governance, including board independence, audit committee independence and effectiveness, and compensation committee independence and effectiveness are found to contribute to improved compliance. Similarly, certain external governance factors are associated with improved disclosure, including external auditor quality, shareholder activism (as proxied by companies identified as poor performers by the Australian Shareholders’ Association), and regulatory intervention.

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In this paper, we propose a multivariate GARCH model with a time-varying conditional correlation structure. The new double smooth transition conditional correlation (DSTCC) GARCH model extends the smooth transition conditional correlation (STCC) GARCH model of Silvennoinen and Teräsvirta (2005) by including another variable according to which the correlations change smoothly between states of constant correlations. A Lagrange multiplier test is derived to test the constancy of correlations against the DSTCC-GARCH model, and another one to test for another transition in the STCC-GARCH framework. In addition, other specification tests, with the aim of aiding the model building procedure, are considered. Analytical expressions for the test statistics and the required derivatives are provided. Applying the model to the stock and bond futures data, we discover that the correlation pattern between them has dramatically changed around the turn of the century. The model is also applied to a selection of world stock indices, and we find evidence for an increasing degree of integration in the capital markets.

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This paper examines the relationship between the volatility implied in option prices and the subsequently realized volatility by using the S&P/ASX 200 index options (XJO) traded on the Australian Stock Exchange (ASX) during a period of 5 years. Unlike stock index options such as the S&P 100 index options in the US market, the S&P/ASX 200 index options are traded infrequently and in low volumes, and have a long maturity cycle. Thus an errors-in-variables problem for measurement of implied volatility is more likely to exist. After accounting for this problem by instrumental variable method, it is found that both call and put implied volatilities are superior to historical volatility in forecasting future realized volatility. Moreover, implied call volatility is nearly an unbiased forecast of future volatility.

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This study employs a pairs trading investment strategy on daily commodity futures returns. The study reveals that pairs trading in similarly related commodity futures earns statistically significant excess returns with commensurate volatility. The excess returns from pairs trading in commodity futures are unrelated to conventional market risk factors and they are not associated with classic contrarian investing. The evidence of pairs trading reflect compensation to arbitrageurs for enforcing the law of one price in similarly related market efficiency.

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Credence goods markets are characterized by asymmetric information between sellers and consumers that may give rise to inefficiencies, such as under- and overtreatment or market break-down. We study in a large experiment with 936 participants the determinants for efficiency in credence goods markets. While theory predicts that either liability or verifiability yields efficiency, we find that liability has a crucial, but verifiability only a minor effect. Allowing sellers to build up reputation has little influence, as predicted. Seller competition drives down prices and yields maximal trade, but does not lead to higher efficiency as long as liability is violated.

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Theory predicts that efficiency prevails on credence goods markets if customers are able to verify which quality they receive from an expert seller. In a series of experiments with endogenous prices we observe that verifiability fails to result in efficient provision behaviour and leads to very similar results as a setting without verifiability. Some sellers always provide appropriate treatment even if own money maximization calls for over- or undertreatment. Overall our endogenous-price-results suggests that both inequality aversion and a taste for efficiency play an important role for experts’ provision behaviour. We contrast the implications of those two motivations theoretically and discriminate between them empirically using a fixed-price design. We then classify experimental experts according to their provision behaviour.

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A plethora of literature exists on irrigation development. However, only a few studies analyse the distributional issues associated with irrigation induced technological changes (IITC) in the context of commodity markets. Furthermore, these studies deal with only the theoretical arguments and to date no proper investigation has been conducted to examine the long-term benefits of adopting modern irrigation technology. This study investigates the long-term benefit changes of irrigation induced technological changes using data from Sri Lanka with reference to rice farming. The results show that (1) adopting modern technology on irrigation increases the overall social welfare through consumption of a larger quantity at a lower cost (2) the magnitude, sensitivity and distributional gains depend on the price elasticity of demand and supply as well as the size of the marketable surplus (3) non-farm sector gains are larger than farm sector gains (4) the distribution of the benefits among different types of producers depend on the magnitude of the expansion of the irrigated areas as well as the competition faced by traditional farmers (5) selective technological adoption and subsidies have a detrimental effect on the welfare of other producers who do not enjoy the same benefits (6) the short-term distributional effects are more severe than the long-term effects among different groups of farmers.

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Since the early 1990’s the United Arab Emirates has been actively seeking to diversify into non-oil sectors. The nation has set out to market itself as a hub for foreign and domestic companies; realizing to achieve these goals that it must provide appropriate e-business frameworks and infrastructures. While the nation itself is paving the way for other nations in the Middle East to undertake electronic business initiatives, the use of everyday e-business in the UAE appears to be somewhat stifled. An investigation into reasons for the apparent low levels of adoption of e-business by UAE inhabitants has been conducted using an autoethnographic research methodology coupled with qualitative interviews of selected stakeholders. Findings from this research may contribute to a better understanding of how e-business initiatives in specific regions need to take into account local cultural and other issues which may be irrelevant elsewhere.

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Digital production and distribution technologies may create new opportunities for filmmaking in Australia. A culture of new approaches to filmmaking is emerging driven by ‘next generation filmmakers’ who are willing to consider new business models: from online web series to short films produced for mobile phones. At the same time cultural representation itself is transforming within an interactive, social media driven environment. Yet there is very little research into next generation filmmaking. The aim of this paper is to scope and discuss three key aspects of next generation filmmaking, namely: digital trends in film distribution and marketing; processes and strategies of ‘next generation’ filmmakers; and case studies of viable next generation business models and filmmaking practices. We conclude with a brief examination of the implications for media and cultural policy which suggests the future possibility of a rapprochement between creative industries discourse and cultural policy.