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Статті в журналах з теми "Stocks Australia Econometric models"
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Masouman, Ashkan, and Charles Harvie. "Forecasting, impact analysis and uncertainty propagation in regional integrated models: A case study of Australia." Environment and Planning B: Urban Analytics and City Science 47, no. 1 (April 16, 2018): 65–83. http://dx.doi.org/10.1177/2399808318767128.
Повний текст джерелаАнотація:
The integration of input–output and econometric models at regional level has gained popularity for its superior performance in forecasting employment and examining the impacts of policies. There are a number of approaches to integrate the two models. This paper examines the integration of input–output with econometric modelling using two merging methodologies, namely coupling and holistic embedding. Each methodology is analysed with respect to the accuracy of its results of total and sectoral employment forecasting. Both methodologies are applied to a regional economy in Australia. The methodology which shows superior forecasting accuracy is applied to examine the significance of sectors that generate the highest number of employments relative to other sectors.
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Zhu, Rong, Zuo Quan Zhang, Xiao Yue Li, Xuan Wu, and Su Zhang. "The Study on the Plasticity Theoretical Models of the Volatility of Stock Prices." Advanced Materials Research 518-523 (May 2012): 5963–67. http://dx.doi.org/10.4028/www.scientific.net/amr.518-523.5963.
Повний текст джерелаАнотація:
This paper analyzes the characteristics of the stock price fluctuation compared with elastic-plastic theory in mechanics and introduces the concept of stock equilibrium price, plasticity of stock price analogically. A basic model of the stock plasticity under the relationship between stock price fluctuation and trading volume changes is also built. Tested by 20 kinds of stocks from Shanghai and Shenzhen stock markets in China by using the econometric analysis software Eviews3.0 afterwards, the basic model is improved, and three developed models are built from it. Finally, this paper obtains more scientific and reasonable stock price plasticity model after the comparative analysis of the four previous models.
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Shi, Chao, and Xiaosheng Zhuang. "A Study Concerning Soft Computing Approaches for Stock Price Forecasting." Axioms 8, no. 4 (October 18, 2019): 116. http://dx.doi.org/10.3390/axioms8040116.
Повний текст джерелаАнотація:
Financial time-series are well known for their non-linearity and non-stationarity nature. The application of conventional econometric models in prediction can incur significant errors. The fast advancement of soft computing techniques provides an alternative approach for estimating and forecasting volatile stock prices. Soft computing approaches exploit tolerance for imprecision, uncertainty, and partial truth to progressively and adaptively solve practical problems. In this study, a comprehensive review of latest soft computing tools is given. Then, examples incorporating a series of machine learning models, including both single and hybrid models, to predict prices of two representative indexes and one stock in Hong Kong’s market are undertaken. The prediction performances of different models are evaluated and compared. The effects of the training sample size and stock patterns (viz. momentum and mean reversion) on model prediction are also investigated. Results indicate that artificial neural network (ANN)-based models yield the highest prediction accuracy. It was also found that the determination of optimal training sample size should take the pattern and volatility of stocks into consideration. Large prediction errors could be incurred when stocks exhibit a transition between mean reversion and momentum trend.
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Chlebus, Marcin, Michał Dyczko, and Michał Woźniak. "Nvidia's Stock Returns Prediction Using Machine Learning Techniques for Time Series Forecasting Problem." Central European Economic Journal 8, no. 55 (January 1, 2021): 44–62. http://dx.doi.org/10.2478/ceej-2021-0004.
Повний текст джерелаАнотація:
Abstract Statistical learning models have profoundly changed the rules of trading on the stock exchange. Quantitative analysts try to utilise them predict potential profits and risks in a better manner. However, the available studies are mostly focused on testing the increasingly complex machine learning models on a selected sample of stocks, indexes etc. without a thorough understanding and consideration of their economic environment. Therefore, the goal of the article is to create an effective forecasting machine learning model of daily stock returns for a preselected company characterised by a wide portfolio of strategic branches influencing its valuation. We use Nvidia Corporation stock covering the period from 07/2012 to 12/2018 and apply various econometric and machine learning models, considering a diverse group of exogenous features, to analyse the research problem. The results suggest that it is possible to develop predictive machine learning models of Nvidia stock returns (based on many independent environmental variables) which outperform both simple naïve and econometric models. Our contribution to literature is twofold. First, we provide an added value to the strand of literature on the choice of model class to the stock returns prediction problem. Second, our study contributes to the thread of selecting exogenous variables and the need for their stationarity in the case of time series models.
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Akbulaev, Nurkhodzha, Basti Aliyeva, and Shehla Rzayeva. "Analysis of the Influence of the Price of Raw Oil and Natural Gas on the Prices of Indices and Shares of the Turkish Stock Exchange." Pénzügyi Szemle = Public Finance Quarterly 66, no. 1 (2021): 151–66. http://dx.doi.org/10.35551/pfq_2021_1_8.
Повний текст джерелаАнотація:
This article is a review on the impact of prices and their dependence on the cost of oil and natural gas on the world stock markets. The main studies and results achieved in the field of the impact of prices on both the stock index and industrial stocks and the dependence on the level of oil prices are presented. The paper presents an econometric study on the choice of offers on the securities market that allows us to identify the main specifics of changes in prices for the stock index and industrial shares in the daily period from 13. 05. 2012 to 01. 12. 2019. The article uses methods for estimating the impact of the price of natural gas and WTI crude oil using the Gretl statistical program, taking into account the selection of the main correlation features of the price matrix. Of the 13 proposed research models, only one model showed its statistical insignificance. A paired linear model of the CocaCola share price dependence and its dependence on NGFO prices was presented and analyzed in detail. Based on the results of econometric modeling, linear regression models were constructed for the dependence of stock prices on the NGFO and WTISPOT prices. The Gretl environment allows you to evaluate the situation in the econometric environment and make a forecast based on the obtained models of the dependence of stock prices and make appropriate conclusions.
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Milon, J. Walter. "Travel Cost Methods for Estimating the Recreational Use Benefits of Artificial Marine Habitat." Journal of Agricultural and Applied Economics 20, no. 1 (July 1988): 87–101. http://dx.doi.org/10.1017/s0081305200025681.
Повний текст джерелаАнотація:
AbstractThe growing popularity of marine recreational fishing has created considerable interest in artificial marine habitat development to maintain and enhance coastal fishery stocks. This paper provides a comparative evaluation of travel cost methods to estimate recreational use benefits for new habitat site planning. Theoretical concerns about price and quality effects of substitute sites, corner solutions in site choice, and econometric estimation are considered. Results from a case study indicate that benefit estimates are influenced by the way these concerns are addressed, but relatively simple single site models can provide defensible estimates. Practical limitations on data collection and model estimation are also considered.
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Nautiyal, Neeraj, and P. C. Kavidayal. "Analysis of Institutional Factors Affecting Share Prices: The Case of National Stock Exchange." Global Business Review 19, no. 3 (March 14, 2018): 707–21. http://dx.doi.org/10.1177/0972150917713865.
Повний текст джерелаАнотація:
This study offers empirical findings on the impact of institutional variables on firm’s stock market price performance. In order to identify the influence of companies financial on NIFTY 50 Index, our sample consists of balanced panel of 30 actively traded companies (that becomes the study’s index representative) over a massive transition period, 1995–2014. Attempts have been made with a wide range of econometric models and estimators, from the relatively straightforward to (static) more complex (dynamic panel analyses) to deal with the relevant econometric issues. Results indicate that increasing debt in capital structure does not establish any significant relation with the stock prices. Earnings per share (EPS) shows a poor explanation of price variation. Economic value added (EVA) indicates a positive relation with current as well as previous year’s stock price performances. However, dividend payout (DIVP) and dividend per share (DPS) achieve negative relationship at moderately significant level. The present study confirms that performance of companies fundamental ratios will be essential and immensely helpful to investors and analysts in assessing the better stocks that belong to different industry groups.
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Ndayisaba, Gilbert, and Abdullahi D. Ahmed. "CEO remuneration, board composition and firm performance: empirical evidence from Australian listed companies." Corporate Ownership and Control 13, no. 1 (2015): 534–52. http://dx.doi.org/10.22495/cocv13i1c5p2.
Повний текст джерелаАнотація:
Classical economic theories establishing a relationship between CEO remuneration and firm performance has paid particular attention to solve conflict of interest between managerial team and firm shareholders, by designing an optimum CEO remuneration that motivate executives to work in the best interest of shareholders. Many international and less Australian empirical researches suggest that there is overwhelming evidence that firm performance is strongly linked with CEO remuneration. In this paper, we reassess the association of firm performance and CEO remuneration variables using dynamic econometric models and comprehensive data from Australian Stock Exchange (ASX). We find a positive and strong association between CEO pay of top 200 Australian public listed companies and company performance. Obtained findings are similar to USA, UK and Canada studies results. We further test the effect of board and ownership features on CEO remuneration–performance sensitivity in the top 200 Australian public companies listed on ASX. Specifically, for the period of 2003-2007, our results highlight the importance of ownership structure in influencing remuneration–performance relationship. Monitoring block holders boost the responsiveness of long term incentives (LTI) remuneration to performance, thus straightening shareholder and manager welfares. However, based on a short term investment horizon strategy, insider block holders increase (decrease) the sensitivity of short-term incentives remuneration (long term incentives pay). Surprisingly, for the period 2008-2013, our findings suggest that ownership and board features did not influence significantly CEO pay-performance sensitivities. Finally, we find that larger boards increase (decrease) the responsiveness of CEO’s known remuneration (long term incentives) to performance.
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Provenzano, Davide. "The migration–tourism nexus in the EU28." Tourism Economics 26, no. 8 (March 10, 2020): 1374–93. http://dx.doi.org/10.1177/1354816620909994.
Повний текст джерелаАнотація:
This study explores the nexus between tourism and migration on an intra-European scale over the period 2000–2015. Complex-network analysis and gravity models were the investigation methods preferred. For each year under study, we built two country-to-country networks to map and reveal the connections between states as shaped by migration stocks and tourism flows, respectively. Then, the main determinants of the correlation patterns between the two networks were investigated by several econometric analysis. Results point to a quite similar topological structure for the tourism and migration networks as well as to a significant and reciprocal direct influence between tourism and migration movements inside the European Union. No relevant indirect causal relationship is present in the tourism–migration nexus instead.
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Ewers Lewis, Carolyn J., Mary A. Young, Daniel Ierodiaconou, Jeffrey A. Baldock, Bruce Hawke, Jonathan Sanderman, Paul E. Carnell, and Peter I. Macreadie. "Drivers and modelling of blue carbon stock variability in sediments of southeastern Australia." Biogeosciences 17, no. 7 (April 16, 2020): 2041–59. http://dx.doi.org/10.5194/bg-17-2041-2020.
Повний текст джерелаАнотація:
Abstract. Tidal marshes, mangrove forests, and seagrass meadows are important global carbon (C) sinks, commonly referred to as coastal “blue carbon”. However, these ecosystems are rapidly declining with little understanding of what drives the magnitude and variability of C associated with them, making strategic and effective management of blue C stocks challenging. In this study, our aims were threefold: (1) identify ecological, geomorphological, and anthropogenic variables associated with 30 cm deep sediment C stock variability in blue C ecosystems in southeastern Australia, (2) create a predictive model of 30 cm deep sediment blue C stocks in southeastern Australia, and (3) map regional 30 cm deep sediment blue C stock magnitude and variability. We had the unique opportunity to use a high-spatial-density C stock dataset of sediments to 30 cm deep from 96 blue C ecosystems across the state of Victoria, Australia, integrated with spatially explicit environmental data to reach these aims. We used an information theoretic approach to create, average, validate, and select the best averaged general linear mixed effects model for predicting C stocks across the state. Ecological drivers (i.e. ecosystem type or ecological vegetation class) best explained variability in C stocks, relative to geomorphological and anthropogenic drivers. Of the geomorphological variables, distance to coast, distance to freshwater, and slope best explained C stock variability. Anthropogenic variables were of least importance. Our model explained 46 % of the variability in 30 cm deep sediment C stocks, and we estimated over 2.31 million Mg C stored in the top 30 cm of sediments in coastal blue C ecosystems in Victoria, 88 % of which was contained within four major coastal areas due to the extent of blue C ecosystems (∼87 % of total blue C ecosystem area). Regionally, these data can inform conservation management, paired with assessment of other ecosystem services, by enabling identification of hotspots for protection and key locations for restoration efforts. We recommend these methods be tested for applicability to other regions of the globe for identifying drivers of sediment C stock variability and producing predictive C stock models at scales relevant for resource management.
Дисертації з теми "Stocks Australia Econometric models"
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Eadie, Edward Norman. "Small resource stock share price behaviour and prediction." Title page, contents and abstract only, 2002. http://web4.library.adelaide.edu.au/theses/09CM/09cme11.pdf.
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Weier, Annette 1960. "Demutualisation in the Australian life insurance industry." Monash University, Dept. of Economics, 2000. http://arrow.monash.edu.au/hdl/1959.1/8371.
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Limkriangkrai, Manapon. "An empirical investigation of asset-pricing models in Australia." University of Western Australia. Faculty of Business, 2007. http://theses.library.uwa.edu.au/adt-WU2007.0197.
Повний текст джерелаАнотація:
[Truncated abstract] This thesis examines competing asset-pricing models in Australia with the goal of establishing the model which best explains cross-sectional stock returns. The research employs Australian equity data over the period 1980-2001, with the major analyses covering the more recent period 1990-2001. The study first documents that existing asset-pricing models namely the capital asset pricing model (CAPM) and domestic Fama-French three-factor model fail to meet the widely applied Merton?s zero-intercept criterion for a well-specified pricing model. This study instead documents that the US three-factor model provides the best description of Australian stock returns. The three US Fama-French factors are statistically significant for the majority of portfolios consisting of large stocks. However, no significant coefficients are found for portfolios in the smallest size quintile. This result initially suggests that the largest firms in the Australian market are globally integrated with the US market while the smallest firms are not. Therefore, the evidence at this point implies domestic segmentation in the Australian market. This is an unsatisfying outcome, considering that the goal of this research is to establish the pricing model that best describes portfolio returns. Given pervasive evidence that liquidity is strongly related to stock returns, the second part of the major analyses derives and incorporates this potentially priced factor to the specified pricing models ... This study also introduces a methodology for individual security analysis, which implements the portfolio analysis, in this part of analyses. The technique makes use of visual impressions conveyed by the histogram plots of coefficients' p-values. A statistically significant coefficient will have its p-values concentrated at below a 5% level of significance; a histogram of p-values will not have a uniform distribution ... The final stage of this study employs daily return data as an examination of what is indeed the best pricing model as well as to provide a robustness check on monthly return results. The daily result indicates that all three US Fama-French factors, namely the US market, size and book-to-market factors as well as LIQT are statistically significant, while the Australian three-factor model only exhibits one significant market factor. This study has discovered that it is in fact the US three-factor model with LIQT and not the domestic model, which qualifies for the criterion of a well-specified asset-pricing model and that it best describes Australian stock returns.
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Oliveira, Lima Jorge Claudio Cavalcante de. "Fractional integration and long memory models of stock price volatility : the evidence of the emerging markets." Thesis, McGill University, 2002. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=38164.
Повний текст джерелаАнотація:
Following the important work on unit roots and cointegration which started in the mid-1980s, a great deal of econometric works has been devoted to the study of the subtleties and varieties of near nonstationarity and persistence that characterize so many economic and financial time series. In recent years research activity has gained importance with outstanding contributions made on estimation and testing of a wide variety of long memory processes, together with many interesting and imaginative applications over a wide variety of different fields of economics and finance. For these reasons, this study provides empirical evidence to an aspect of fractional differencing and long memory processes, or the long memory of volatility. Evidence of long memory persistence is explored using stock price indices for eight emerging economies in both Asian and Latin American markets. The concern with the presence of long memory in higher moments of return series was first drawn by Ding, Granger and Engle (1993), using asset returns. Baillie, Bollerslev and Mikkelsen (1996) developed the fractionally integrated GARCH, or FIGARCH, process to represent long memory in volatility. The measure of long-memory persistence in the volatility is employed either using the original rescaled range statistic by Hurst (1951) and its modified version proposed by Lo (1991). Further analysis of the presence of long memory persistence is conducted using autocorrelation analysis. All the findings point in the same direction, that is, the existence of long memory in volatility irrespective of the measure chosen. Estimation of different models of volatility is undertaken beginning with the ARCH specification and until the FIGARCH model. The results show the effects to be higher in Latin American countries than in the Asian ones. This result seems consistent with the degree of intervention in the Latin American markets, known to be much higher.Other possible explanations for the occurrence of long term persistence are also pursued such as the Regime Switching modelisation proposed first by Hamilton and Susnel (1994) with the SWARCH approach. Results show that this approach can bring another possible explanation for persistence, specially in economies like Brazil that, have very different regimes for the period covered in this study.
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Marshall, Peter John 1960. "Rational versus anchored traders : exchange rate behaviour in macro models." Monash University, Dept. of Economics, 2001. http://arrow.monash.edu.au/hdl/1959.1/9048.
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Enzinger, Sharn Emma 1973. "The economic impact of greenhouse policy upon the Australian electricity industry : an applied general equilibrium analysis." Monash University, Centre of Policy Studies, 2001. http://arrow.monash.edu.au/hdl/1959.1/8383.
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Forrester, David Edward Economics Australian School of Business UNSW. "Market probability density functions and investor risk aversion for the australia-us dollar exchange rate." Awarded by:University of New South Wales. School of Economics, 2006. http://handle.unsw.edu.au/1959.4/27199.
Повний текст джерелаАнотація:
This thesis models the Australian-US Dollar (AUD/USD) exchange rate with particular attention being paid to investor risk aversion. Accounting for investor risk aversion in AUD/USD exchange rate modelling is novel, so too is the method used to measure risk aversion in this thesis. Investor risk aversion is measured using a technique developed in Bliss and Panigirtzoglou (2004), which makes use of Probability Density Functions (PDFs) extracted from option markets. More conventional approaches use forward-market pricing or Uncovered Interest Parity. Several methods of estimating PDFs from option and spot markets are examined, with the estimations from currency spot-markets representing an original application of an arbitrage technique developed in Stutzer (1996) to the AUD/USD exchange rate. The option and spot-market PDFs are compared using their first four moments and if estimated judiciously, the spot-market PDFs are found to have similar shapes to the option-market PDFs. So in the absence of an AUD/USD exchange rate options market, spot-market PDFs can act as a reasonable substitute for option-market PDFs for the purpose of examining market sentiment. The Relative Risk Aversion (RRA) attached to the AUD/USD, the US Dollar-Japanese Yen, the US Dollar-Swiss Franc and the US-Canadian Dollar exchange rates is measured using the Bliss and Panigirtzoglou (2004) technique. Amongst these exchange rates, only the AUD/USD exchange rate demonstrates a significant level of investor RRA and only over a weekly forecast horizon. The Bliss and Panigirtzoglou (2004) technique is also used to approximate a time-varying risk premium for the AUD/USD exchange rate. This risk premium is added to the cointegrating vectors of fixed-price and asset monetary models of the AUD/USD exchange rate. An index of Australia???s export commodity prices is also added. The out-of-sample forecasting ability of these cointegrating vectors is tested relative to a random walk using an error-correction framework. While adding the time-varying risk premium improves this forecasting ability, adding export commodity prices does so by more. Further, including both the time-varying risk premium and export commodity prices in the cointegrating vectors reduces their forecasting ability. So the time-varying risk premium is important for AUD/USD exchange rate modelling, but not as important as export commodity prices.
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Ji, Inyeob Economics Australian School of Business UNSW. "Essays on testing some predictions of RBC models and the stationarity of real interest rates." Publisher:University of New South Wales. Economics, 2008. http://handle.unsw.edu.au/1959.4/41441.
Повний текст джерелаАнотація:
This dissertation contains a series of essays that provide empirical evidence for Australia on some fundamental predictions of real business cycle models and on the convergence and persistence of real interest rates. Chapter 1 provides a brief introduction to the issues examined in each chapter and provides an overview of the methodologies that are used. Tests of various basic predictions of standard real business cycle models for Australia are presented in Chapters 2, 3 and 4. Chapter 2 considers the question of great ratios for Australia. These are ratios of macroeconomic variables that are predicted by standard models to be stationary in the steady state. Using time series econometric techniques (unit root tests and cointegration tests) Australia great ratios are examined. In Chapter 3 a more restrictive implication of real business cycle models than the existence of great ratios is considered. Following the methodology proposed by Canova, Finn and Pagan (1994) the equilibrium decision rules for some standard real business cycle are tested on Australian data. The final essay on this topic is presented in Chapter 4. In this chapter a large-country, small-country is used to try and understand the reason for the sharp rise in Australia??s share of world output that began around 1990. Chapter 5 discusses real interest rate linkages in the Pacific Basin region. Vector autoregressive models and bootstrap methods are adopted to study financial linkages between East Asian markets, Japan and US. Given the apparent non-stationarity of real interest rates a related issue is examined in Chapter 6, viz. the persistence of international real interest rates and estimation of their half-life. Half-life is selected as a means of measuring persistence of real rates. Bootstrap methods are employed to overcome small sample issues in the estimation and a non-standard statistical inference methodology (Highest Density Regions) is adopted. Chapter 7 reapplies the High Density Regions methodology and bootstrap half-life estimation to the data used in Chapters 2 and 5. This provides a robustness check on the results of standard unit root tests that were applied to the data in those chapters. Main findings of the thesis are as follows. The long run implications of real business cycle models are largely rejected by the Australia data. This finding holds for both the existence of great ratios and when the explicit decision rules are employed. When the small open economy features of the Australian economy are incorporated in a two country RBC model, a country-specific productivity boom seems to provide a possible explanation for the rise in Australia??s share of world output. The essays that examine real interest rates suggest the following results. Following the East Asian financial crisis in 1997-98 there appears to have been a decline in the importance of Japan in influencing developments in the Pacific Basin region. In addition there is evidence that following the crisis Korea??s financial market became less insular and more integrated with the US. Finally results obtained from the half-life estimators suggest that despite the usual findings from unit root tests, real interest rates may in fact exhibit mean-reversion.
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Kummerow, Max F. "A paradigm of inquiry for applied real estate research : integrating econometric and simulation methods in time and space specific forecasting models : Australian office market case study." Curtin University of Technology, School of Economics and Finance, 1997. http://espace.library.curtin.edu.au:80/R/?func=dbin-jump-full&object_id=11274.
Повний текст джерелаАнотація:
Office space oversupply cost Australia billions of dollars during the 1990-92 recession. Australia, the United States, Japan, the U.K., South Africa, China, Thailand, and many other countries have suffered office oversupply cycles. Illiquid untenanted office buildings impair investors capital and cash flows, with adverse effects on macroeconomics, financial institutions, and individuals. This study aims to develop improved methods for medium term forecasting of office market adjustments to inform individual project development decisions and thereby to mitigate office oversupply cycles. Methods combine qualitative research, econometric estimation, system dynamics simulation, and institutional economics. This research operationalises a problem solving research paradigm concept advocated by Ken Lusht. The research is also indebted to the late James Graaskamp, who was successful in linking industry and academic research through time and space specific feasibility studies to inform individual property development decisions. Qualitative research and literature provided a list of contributing causes of office oversupply including random shocks, faulty forecasting methods, fee driven deals, prisoners dilemma game, system dynamics (lags and adjustment times), land use regulation, and capital market issues. Rather than choosing among these, they are all considered to be causal to varying degrees. Moreover, there is synergy between combinations of these market imperfections. Office markets are complex evolving human designed systems (not time invariant) so each cycle has unique historical features. Data on Australian office markets were used to estimate office rent adjustment equations. Simulation models in spreadsheet and system dynamics software then integrate additional information with the statistical results to produce demand, supply, and rent forecasts. Results include ++models for rent forecasting and models for analysis related to policy and system redesign. The dissertation ends with two chapters on institutional reforms whereby better information might find application to improve market efficiency.Keywords. Office rents, rent adjustment, office market modelling, forecasting, system dynamics.
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Milunovich, George Economics Australian School of Business UNSW. "Modelling and valuing multivariate interdependencies in financial time series." Awarded by:University of New South Wales. School of Economics, 2006. http://handle.unsw.edu.au/1959.4/25162.
Повний текст джерелаАнотація:
This thesis investigates implications of interdependence between stock market prices in the context of several financial applications including: portfolio selection, tests of market efficiency and measuring the extent of integration among national stock markets. In Chapter 2, I note that volatility spillovers (transmissions of risk) have been found in numerous empirical studies but that no one, to my knowledge, has evaluated their effects in the general portfolio framework. I dynamically forecast two multivariate GARCH models, one that accounts for volatility spillovers and one that does not, and construct optimal mean-variance portfolios using these two alternative models. I show that accounting for volatility spillovers lowers portfolio risk with statistical significance and that risk-averse investors would prefer realised returns from portfolios based on the volatility spillover model. In Chapter 3, I develop a structural MGARCH model that parsimoniously specifies the conditional covariance matrix and provides an identification framework. Using the model to investigate interdependencies between size-sorted portfolios from the Australian Stock Exchange, I gain new insights into the issue of asymmetric dependence. My findings not only confirm the observation that small stocks partially adjust to market-wide news embedded in the returns to large firms but also present evidence that suggests that small firms in Australia fail to even partially adjust (with statistical significance) to large firms??? shocks contemporaneously. All adjustments in small capitalisation stocks occur with a lag. Chapter 4 uses intra-daily data and develops a new method for measuring the extent of stock market integration that takes into account non-instantaneous adjustments to overnight news. This approach establishes the amounts of time that the New York, Tokyo and London stock markets take to fully adjust to overnight news and then uses this This thesis investigates implications of interdependence between stock market prices in the context of several financial applications including: portfolio selection, tests of market efficiency and measuring the extent of integration among national stock markets. In Chapter 2, I note that volatility spillovers (transmissions of risk) have been found in numerous empirical studies but that no one, to my knowledge, has evaluated their effects in the general portfolio framework. I dynamically forecast two multivariate GARCH models, one that accounts for volatility spillovers and one that does not, and construct optimal mean-variance portfolios using these two alternative models. I show that accounting for volatility spillovers lowers portfolio risk with statistical significance and that risk-averse investors would prefer realised returns from portfolios based on the volatility spillover model. In Chapter 3, I develop a structural MGARCH model that parsimoniously specifies the conditional covariance matrix and provides an identification framework. Using the model to investigate interdependencies between size-sorted portfolios from the Australian Stock Exchange, I gain new insights into the issue of asymmetric dependence. My findings not only confirm the observation that small stocks partially adjust to market-wide news embedded in the returns to large firms but also present evidence that suggests that small firms in Australia fail to even partially adjust (with statistical significance) to large firms??? shocks contemporaneously. All adjustments in small capitalisation stocks occur with a lag. Chapter 4 uses intra-daily data and develops a new method for measuring the extent of stock market integration that takes into account non-instantaneous adjustments to overnight news. This approach establishes the amounts of time that the New York, Tokyo and London stock markets take to fully adjust to overnight news and then uses this
Книги з теми "Stocks Australia Econometric models"
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Lo, Andrew W. Econometric models of limit-order executions. Cambridge, MA: National Bureau of Economic Research, 1997.
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2
Engle, R. F. Execution risk. Cambridge, Mass: National Bureau of Economic Research, 2006.
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3
Lo, Ingrid. Order submission: The choice between limit and market orders. Ottawa: Bank of Canada, 2005.
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Hallock, Kevin F. The value of stock options to non-executive employees. Cambridge, Mass: National Bureau of Economic Research, 2006.
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Albuquerque, Rui. International equity flows and returns: A quantitative equilibrium approach. Ottawa: Bank of Canada, 2004.
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6
Chan-Lau, Jorge A. Asian flu or Wall Street virus?: Price and volatility spillovers of tech and non-tech sectors in the United States and Asia. [Washington, D.C.]: International Monetary Fund, International Capital Markets Department and Western Hemisphere Department, 2002.
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Wright, Jonathan H. Log-periodogram estimation of long memory volatility dependencies with conditionally heavy tailed returns. Washington, D.C: Federal Reserve Board, 2000.
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Santos, Tano. Cash-flow risk, discount risk, and the value premium. Cambridge, Mass: National Bureau of Economic Research, 2005.
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Antunovich, Peter. Do investors mistake a good company for a good investment? [New York, N.Y.]: Federal Reserve Bank of New York, 1999.
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Lin, Wen-Ling. Do bulls and bears move across borders?: International transmission of stock returns and volatility as the world turns. Cambridge, MA: National Bureau of Economic Research, 1991.
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