792 resultados para Financial Analysis


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In Queensland, Australia, there is presently a high level of interest in long-rotation hardwood plantation investments for sawlog production, despite the consensus in Australian literature that such investments are not financially viable. Continuing genetics, silviculture and processing research, and increasing awareness about the ecosystem services generated by plantations, are anticipated to make future plantings profitable and socio-economically desirable in many parts of Queensland. Financial and economic models of hardwood plantations in Queensland are developed to test this hypothesis. The economic model accounts for carbon sequestration, salinity amelioration and other ecosystem service values of hardwood plantations. A carbon model estimates the value of carbon sequestered, while salinity and other ecosystem service values are estimated by the benefit transfer method. Where high growth rates (20-25 m(3) ha(-1) year(-1)) are achievable, long-rotation hardwood plantations are profitable in Queensland Hardwood Regions 1, 3 and 7 when rural land values are less than $2300/ha. Under optimistic assumptions, hardwood plantations growing at a rate of 15 in 3 ha-1 year 1 are financially viable in Hardwood Regions 2, 4 and 8, provided land values are less than $1600/ha. The major implication of the economic analysis is that long-rotation hardwood plantation forestry is socio-economically justified in most Hardwood Regions, even though financial returns from timber production may be negative. (c) 2003 Elsevier B.V. All rights reserved.

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We use a smooth transition logistic function to test for equity market integration in a sample of Asia-Pacific countries. This allows us to gauge the speed at which a market is becoming integrated. Of the countries we examine we find that Thailand has the fastest pace of global integration. When we examine the extent to which local integration is taking place, we find that Singapore is experiencing the fastest rise in market integration. © 2004 Published by Elsevier Inc.

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Feasibility studies of industrial projects consist of multiple analyses carried out sequentially. This is time consuming and each analysis screens out alternatives based solely on the merits of that analysis. In cross-country petroleum pipeline project selection, market analysis determines throughput requirement and supply and demand points. Technical analysis identifies technological options and alternatives for pipe-line routes. Economic and financial analysis derive the least-cost option. The impact assessment addresses environmental issues. The impact assessment often suggests alternative sites, routes, technologies, and/or implementation methodology, necessitating revision of technical and financial analysis. This report suggests an integrated approach to feasibility analysis presented as a case application of a cross-country petroleum pipeline project in India.

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Many papers claim that a Log Periodic Power Law (LPPL) model fitted to financial market bubbles that precede large market falls or 'crashes', contains parameters that are confined within certain ranges. Further, it is claimed that the underlying model is based on influence percolation and a martingale condition. This paper examines these claims and their validity for capturing large price falls in the Hang Seng stock market index over the period 1970 to 2008. The fitted LPPLs have parameter values within the ranges specified post hoc by Johansen and Sornette (2001) for only seven of these 11 crashes. Interestingly, the LPPL fit could have predicted the substantial fall in the Hang Seng index during the recent global downturn. Overall, the mechanism posited as underlying the LPPL model does not do so, and the data used to support the fit of the LPPL model to bubbles does so only partially. © 2013.

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This paper applies the vector AR-DCC-FIAPARCH model to eight national stock market indices' daily returns from 1988 to 2010, taking into account the structural breaks of each time series linked to the Asian and the recent Global financial crisis. We find significant cross effects, as well as long range volatility dependence, asymmetric volatility response to positive and negative shocks, and the power of returns that best fits the volatility pattern. One of the main findings of the model analysis is the higher dynamic correlations of the stock markets after a crisis event, which means increased contagion effects between the markets. The fact that during the crisis the conditional correlations remain on a high level indicates a continuous herding behaviour during these periods of increased market volatility. Finally, during the recent Global financial crisis the correlations remain on a much higher level than during the Asian financial crisis.

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We test for departures from normal and independent and identically distributed (NIID) log returns, for log returns under the alternative hypothesis that are self-affine and either long-range dependent, or drawn randomly from an L-stable distribution with infinite higher-order moments. The finite sample performance of estimators of the two forms of self-affinity is explored in a simulation study. In contrast to rescaled range analysis and other conventional estimation methods, the variant of fluctuation analysis that considers finite sample moments only is able to identify both forms of self-affinity. When log returns are self-affine and long-range dependent under the alternative hypothesis, however, rescaled range analysis has higher power than fluctuation analysis. The techniques are illustrated by means of an analysis of the daily log returns for the indices of 11 stock markets of developed countries. Several of the smaller stock markets by capitalization exhibit evidence of long-range dependence in log returns. © 2012 Elsevier Inc. All rights reserved.

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We report an empirical analysis of long-range dependence in the returns of eight stock market indices, using the Rescaled Range Analysis (RRA) to estimate the Hurst exponent. Monte Carlo and bootstrap simulations are used to construct critical values for the null hypothesis of no long-range dependence. The issue of disentangling short-range and long-range dependence is examined. Pre-filtering by fitting a (short-range) autoregressive model eliminates part of the long-range dependence when the latter is present, while failure to pre-filter leaves open the possibility of conflating short-range and long-range dependence. There is a strong evidence of long-range dependence for the small central European Czech stock market index PX-glob, and a weaker evidence for two smaller western European stock market indices, MSE (Spain) and SWX (Switzerland). There is little or no evidence of long-range dependence for the other five indices, including those with the largest capitalizations among those considered, DJIA (US) and FTSE350 (UK). These results are generally consistent with prior expectations concerning the relative efficiency of the stock markets examined. © 2011 Elsevier Inc.

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We formally compare fundamental factor and latent factor approaches to oil price modelling. Fundamental modelling has a long history in seeking to understand oil price movements, while latent factor modelling has a more recent and limited history, but has gained popularity in other financial markets. The two approaches, though competing, have not formally been compared as to effectiveness. For a range of short- medium- and long-dated WTI oil futures we test a recently proposed five-factor fundamental model and a Principal Component Analysis latent factor model. Our findings demonstrate that there is no discernible difference between the two techniques in a dynamic setting. We conclude that this infers some advantages in adopting the latent factor approach due to the difficulty in determining a well specified fundamental model.

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Financial literacy can explain a significant proportion of wealth inequality. Among the key components of financial literacy are numeracy and money management skills. Our study examines the relative importance of these components in the determination of consumer debt and household net worth among credit union members in socially disadvantaged areas. The main finding from our analysis is that money management skills are important determinants of financial outcomes but that numeracy has almost no role to play. This result adds to a recent US-based behavioural finance literature on the role of attention and planning in consumer finance. Findings are found to be robust when the sample is reduced to only those who have a clear role in household financial decision-making and also when controlling for potential endogeneity. Our findings have policy implications in the UK and elsewhere as credit unions across the world are important players in national financial literacy strategies.

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Finance is one of the fastest growing areas in modern applied mathematics with real world applications. The interest of this branch of applied mathematics is best described by an example involving shares. Shareholders of a company receive dividends which come from the profit made by the company. The proceeds of the company, once it is taken over or wound up, will also be distributed to shareholders. Therefore shares have a value that reflects the views of investors about the likely dividend payments and capital growth of the company. Obviously such value will be quantified by the share price on stock exchanges. Therefore financial modelling serves to understand the correlations between asset and movements of buy/sell in order to reduce risk. Such activities depend on financial analysis tools being available to the trader with which he can make rapid and systematic evaluation of buy/sell contracts. There are other financial activities and it is not an intention of this paper to discuss all of these activities. The main concern of this paper is to propose a parallel algorithm for the numerical solution of an European option. This paper is organised as follows. First, a brief introduction is given of a simple mathematical model for European options and possible numerical schemes of solving such mathematical model. Second, Laplace transform is applied to the mathematical model which leads to a set of parametric equations where solutions of different parametric equations may be found concurrently. Numerical inverse Laplace transform is done by means of an inversion algorithm developed by Stehfast. The scalability of the algorithm in a distributed environment is demonstrated. Third, a performance analysis of the present algorithm is compared with a spatial domain decomposition developed particularly for time-dependent heat equation. Finally, a number of issues are discussed and future work suggested.

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This paper aims to investigate the long-run impact of housing and financial wealth on consumption in Italy and the UK using two different estimation methods. The novelty of the paper is to consider the recent financial crisis when studying wealth effects. The dynamics of wealth effects is also evaluated by a rolling regression analysis. The results show that: i) housing wealth plays no role in Italy, whereas it is significant in the UK; ii) in both countries, the financial wealth exerts a positive and significant impact on aggregate consumption; iii) by and large, the housing wealth effect assumes relatively increasing importance over time in the UK, while for Italy this is true for the financial wealth effect

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Using a Markov switching unobserved component model we decompose the term premium of the North American CDX index into a permanent and a stationary component. We establish that the inversion of the CDX term premium is induced by sudden changes in the unobserved stationary component, which represents the evolution of the fundamentals underpinning the probability of default in the economy. We find evidence that the monetary policy response from the Fed during the crisis period was effective in reducing the volatility of the term premium. We also show that equity returns make a substantial contribution to the term premium over the entire sample period.

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Owing to the discrete disclosure practices of the Reserve Bank of Australia, this paper provides new evidence on the channels of monetary policy triggered by central bank actions (monetary policy announcements) and statements (explanatory minutes releases), in the Australian equity market. Both monetary policy announcements and explanatory minutes releases are shown to have a significant and comparable impact on the returns and volatility of the Australian equity market. Further, distinct from US and European studies that find strong evidence of the interest rate, bank loan and balance sheet channels and no evidence of the exchange rate channel following central bank actions, this paper finds that monetary policy impacts the Australian equity market via the exchange rate, interest rate and bank loan channels of monetary policy, with only weak evidence of the balance sheet channel of monetary policy. These channels are found to be operating irrespective of the trigger (monetary policy announcements or explanatory minutes releases), though results are somewhat weaker when examining the explanatory minutes releases. These results have important implications for central bank officials and financial market participants alike: by confirming a comparable avenue to affect monetary policy; and providing an explication of its impact on the Australian equity market.