860 resultados para Volatility Models, Volatility, Equity Markets
Resumo:
Traditional resource management has had as its main objective the optimization of throughput, based on parameters such as CPU, memory, and network bandwidth. With the appearance of Grid markets, new variables that determine economic expenditure, benefit and opportunity must be taken into account. The Self-organizing ICT Resource Management (SORMA) project aims at allowing resource owners and consumers to exploit market mechanisms to sell and buy resources across the Grid. SORMA's motivation is to achieve efficient resource utilization by maximizing revenue for resource providers and minimizing the cost of resource consumption within a market environment. An overriding factor in Grid markets is the need to ensure that the desired quality of service levels meet the expectations of market participants. This paper explains the proposed use of an economically enhanced resource manager (EERM) for resource provisioning based on economic models. In particular, this paper describes techniques used by the EERM to support revenue maximization across multiple service level agreements and provides an application scenario to demonstrate its usefulness and effectiveness. Copyright © 2008 John Wiley & Sons, Ltd.
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The Private Finance Initiative (PFI) is frequently portrayed as a vehicle for change for the UK construction sector. Significant change in the working practices of construction companies is predicted as new business models based on whole-life value creation emerge. This paper shifts the focus of discussion from projected ideals and possible developments to the current situation. More specifically, it focuses on the challenges that large firms participating in both PFI and traditional markets face. The analysis focuses on the relations between business units and on day-to-day challenges to greater long-term commitment, through life-service provision and increased integration between construction and service provision. The paper offers insights into the effects of PFI on construction practice and their implications for theorizing on organizational and strategic change. It suggests abandoning a simplistic model of the centralized, homogenous firm and instead capturing the dynamics of decentralized, large firms working in multiple markets on a variety of projects. This would assist in the provision of more realistic and fruitful models of how to realize the PFI vision.
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Global financial activity is heavily concentrated in a small number of world cities –international financial centers. The office markets in those cities receive significant flows of investment capital. The growing specialization of activity in IFCs and innovations in real estate investment vehicles lock developer, occupier, investment, and finance markets together, creating common patterns of movement and transmitting shocks from one office market throughout the system. International real estate investment strategies that fail to recognize this common source of volatility and risk may fail to deliver the diversification benefits sought.
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Volatility, or the variability of the underlying asset, is one of the key fundamental components of property derivative pricing and in the application of real option models in development analysis. There has been relatively little work on volatility in real terms of its application to property derivatives and the real options analysis. Most research on volatility stems from investment performance (Nathakumaran & Newell (1995), Brown & Matysiak 2000, Booth & Matysiak 2001). Historic standard deviation is often used as a proxy for volatility and there has been a reliance on indices, which are subject to valuation smoothing effects. Transaction prices are considered to be more volatile than the traditional standard deviations of appraisal based indices. This could lead, arguably, to inefficiencies and mis-pricing, particularly if it is also accepted that changes evolve randomly over time and where future volatility and not an ex-post measure is the key (Sing 1998). If history does not repeat, or provides an unreliable measure, then estimating model based (implied) volatility is an alternative approach (Patel & Sing 2000). This paper is the first of two that employ alternative approaches to calculating and capturing volatility in UK real estate for the purposes of applying the measure to derivative pricing and real option models. It draws on a uniquely constructed IPD/Gerald Eve transactions database, containing over 21,000 properties over the period 1983-2005. In this first paper the magnitude of historic amplification associated with asset returns by sector and geographic spread is looked at. In the subsequent paper the focus will be upon model based (implied) volatility.
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Following the attack on the World Trade Center on 9/11 volatility of daily returns of the US stock market rose sharply. This increase in volatility may reflect fundamental changes in the economic determinants of prices such as expected earnings, interest rates, real growth and inflation. Alternatively, the increase in volatility may simply reflect the effects of increased uncertainty in the financial markets. This study therefore sets out to determine if the effects of the attack on the World Trade Center on 9/11 had a fundamental or purely financial impact on US real estate returns. In order to do this we compare pre- and post-9/11 crisis returns for a number of US REIT indexes using an approach suggested by French and Roll (1986), as extended by Tuluca et al (2003). In general we find no evidence that the effects of 9/11 had a fundamental effect on REIT returns. In other words, we find that the effect of the attack on the World Trade Center on 9/11 had only a financial effect on REIT returns and therefore was transitory.
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This article expresses the price of a spread option as the sum of the prices of two compound options. One compound option is to exchange vanilla call options on the two underlying assets and the other is to exchange the corresponding put options. This way we derive a new closed form approximation for the price of a European spread option and a corresponding approximation for each of its price, volatility and correlation hedge ratios. Our approach has many advantages over existing analytical approximations, which have limited validity and an indeterminacy that renders them of little practical use. The compound exchange option approximation for European spread options is then extended to American spread options on assets that pay dividends or incur costs. Simulations quantify the accuracy of our approach; we also present an empirical application to the American crack spread options that are traded on NYMEX. For illustration, we compare our results with those obtained using the approximation attributed to Kirk (1996, Correlation in energy markets. In: V. Kaminski (Ed.), Managing Energy Price Risk, pp. 71–78 (London: Risk Publications)), which is commonly used by traders.
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The application of real options theory to commercial real estate has developed rapidly during the last 15 Years. In particular, several pricing models have been applied to value real options embedded in development projects. In this study we use a case study of a mixed use development scheme and identify the major implied and explicit real options available to the developer. We offer the perspective of a real market application by exploring different binomial models and the associated methods of estimating the crucial parameter of volatility. We include simple binomial lattices, quadranomial lattices and demonstrate the sensitivity of the results to the choice of inputs and method.
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The performance of various statistical models and commonly used financial indicators for forecasting securitised real estate returns are examined for five European countries: the UK, Belgium, the Netherlands, France and Italy. Within a VAR framework, it is demonstrated that the gilt-equity yield ratio is in most cases a better predictor of securitized returns than the term structure or the dividend yield. In particular, investors should consider in their real estate return models the predictability of the gilt-equity yield ratio in Belgium, the Netherlands and France, and the term structure of interest rates in France. Predictions obtained from the VAR and univariate time-series models are compared with the predictions of an artificial neural network model. It is found that, whilst no single model is universally superior across all series, accuracy measures and horizons considered, the neural network model is generally able to offer the most accurate predictions for 1-month horizons. For quarterly and half-yearly forecasts, the random walk with a drift is the most successful for the UK, Belgian and Dutch returns and the neural network for French and Italian returns. Although this study underscores market context and forecast horizon as parameters relevant to the choice of the forecast model, it strongly indicates that analysts should exploit the potential of neural networks and assess more fully their forecast performance against more traditional models.
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This paper assesses the impact of the monetary integration on different types of stock returns in Europe. In order to isolate European factors, the impact of global equity integration and small cap factors are investigated. European countries are sub-divided according to the process of monetary convergence. Analysis shows that national equity indices are strongly influenced by global market movements, with a European stock factor providing additional explanatory power. The global and European factors explain small cap and real estate stocks much less well –suggesting an increased importance of ‘local’ drivers. For real estate, there are notable differences between core and non-core countries. Core European countries exhibit convergence – a convergence to a European rather than a global factor. The non-core countries do not seem to exhibit common trends or movements. For the non-core countries, monetary integration has been associated with increased dispersion of returns, lower correlation and lower explanatory power of a European factor. It is concluded that this may be explained by divergence in underlying macro-economic drivers between core and non-core countries in the post-Euro period.
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This paper uses sales transaction data in order to examine whether flight from risk phenomena took place in the US office property investment market during the financial crisis of 2007-2009. The effect of the crisis on the pricing of property quality attributes, mainly summarized by the class category of each building, is investigated. In addition, the paper examines how turnover levels were affected by the market downturn and whether there were significant variations between different real estate quality types. The results of the hedonic regression models suggest that the price spread between Class, A, B and C grew significantly during the downturn. We also find that property attributes such as size, height and age are priced significantly different in ‘hot’ and ‘cold’ markets.
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There is widespread evidence that the volatility of stock returns displays an asymmetric response to good and bad news. This article considers the impact of asymmetry on time-varying hedges for financial futures. An asymmetric model that allows forecasts of cash and futures return volatility to respond differently to positive and negative return innovations gives superior in-sample hedging performance. However, the simpler symmetric model is not inferior in a hold-out sample. A method for evaluating the models in a modern risk-management framework is presented, highlighting the importance of allowing optimal hedge ratios to be both time-varying and asymmetric.
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If stock and stock index futures markets are functioning properly price movements in these markets should best be described by a first order vector error correction model with the error correction term being the price differential between the two markets (the basis). Recent evidence suggests that there are more dynamics present than should be in effectively functioning markets. Using self-exciting threshold autoregressive (SETAR) models, this study analyses whether such dynamics can be related to different regimes within which the basis can fluctuate in a predictable manner without triggering arbitrage. These findings reveal that the basis shows strong evidence of autoregressive behaviour when its value is between the two thresholds but that the extra dynamics disappear once the basis moves above the upper threshold and their persistence is reduced, although not eradicated, once the basis moves below the lower threshold. This suggests that once nonlinearity associated with transactions costs is accounted for, stock and stock index futures markets function more effectively than is suggested by linear models of the pricing relationship.
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This study focuses on the wealth-protective effects of socially responsible firm behavior by examining the association between corporate social performance (CSP) and financial risk for an extensive panel data sample of S&P 500 companies between the years 1992 and 2009. In addition, the link between CSP and investor utility is investigated. The main findings are that corporate social responsibility is negatively but weakly related to systematic firm risk and that corporate social irresponsibility is positively and strongly related to financial risk. The fact that both conventional and downside risk measures lead to the same conclusions adds convergent validity to the analysis. However, the risk-return trade-off appears to be such that no clear utility gain or loss can be realized by investing in firms characterized by different levels of social and environmental performance. Overall volatility conditions of the financial markets are shown to play a moderating role in the nature and strength of the CSP-risk relationship.
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Office returns in the City of London are more volatile than in other UK markets. This volatility may reflect fluctuations in capital flows associated with changing patterns of ownership and the growing linkage between real estate and financial markets in the City. Using current and historical data, patterns of ownership in the City are investigated. They reveal that overseas ownership has grown markedly since 1985, that owners are predominantly FIRE-sector firms and that there are strong links between ownership and occupation. This raises concerns about future volatility and systemic risk in a market strongly influenced by the cyclical behaviour and shocks of the international financial system.
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The creation of value is admittedly a critical task for marketers regardless of industry. This paper focuses on a type of value that has traditionally been perceived as irrelevant to industrial markets and argues that brand value facilitates the progression from goods and services value to relationship value. To address the limited amount of research on B2B branding from the suppliers' point of view, we complement insights gained from a literature review with ten exploratory interviews with B2B supplier managers, and develop a framework of brand value applicable to industrial markets. This identifies both the functional (i.e., quality, technology, capacity, infrastructure, after sales service, capabilities, reliability, innovation) and emotional qualities (i.e., risk reduction, reassurance, trust) important for the development of industrial brand equity. Situational (e.g. nature of the purchase) and environmental factors (e.g. the economic situation) affecting suppliers' perceptions of the importance of brand in a B2B context and the role of functional versus emotional brand qualities are discussed. The value of the brand as a driver for the development of business to business relationships is also highlighted. The framework provides a basis for B2B practitioners to build their brands in such a way as to make a functional as well as an emotional connection with buyers that is more likely to lead to a supplier–buyer relationship.