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Journal articles on the topic "Finance Australia Econometric models":
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Ma, Le, Richard Reed, and Jian Liang. "Separating owner-occupier and investor demands for housing in the Australian states." Journal of Property Investment & Finance 37, no. 2 (March 4, 2019): 215–32. http://dx.doi.org/10.1108/jpif-07-2018-0045.
PurposeThere has been declining home ownership and increased acceptance of long-term renting in many western countries including Australia; this has created a problem when examining housing markets as there are dual demand and include both owner-occupiers and investors. The purpose of this paper is to examine the long-run relationship between house prices, housing supply and demand, and to estimate the effects of the two types of demand (i.e. owner-occupier and investor) on house prices.Design/methodology/approachThe econometric techniques for cointegration with vector error correction models are used to specify the proposed models, where the housing markets in the Australian states and territories illustrate the models.FindingsThe results highlight the regional long-run equilibrium and associated patterns in house prices, the level of new housing supply, owner-occupier demand for housing and investor demand for housing. Different types of markets were identified.Practical implicationsThe findings suggest that policies that depress the investment demand can effectively prevent the housing bubble from further building up in the Australian states. The empirical findings shed light in the strategy of maintaining levels of housing affordability in regions where owner-occupiers have been priced out of the housing market.Originality/valueThere has been declining home ownership and increased acceptance of long-term renting in many western countries including Australia; this has created a problem when examining housing markets as there are dual demand and include both owner-occupiers and investors. This research has given to the relationship between supply and dual demand, which includes owner-occupation and investment, for housing and the influence on house prices.
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MILLER, PAUL W. "ECONOMIC MODELS OF FERTILITY BEHAVIOUR IN AUSTRALIA*." Australian Economic Papers 27, no. 50 (June 1988): 65–82. http://dx.doi.org/10.1111/j.1467-8454.1988.tb00807.x.
Purpose – The purpose of this study is to examine factors influencing decisions to repurchase shares on-market in Australia. The present study also examines the role of board size, board independence and chief executive officer duality on the decision to repurchase shares on-market by Australian firms. Design/methodology/approach – This study blends the traditional motivations of share repurchases with the influences of governance. The sample consists of all non-financial firms included in the Australian All Ordinaries Index (AOI) for the period 2004-2010. The repurchase sample consists of 104 repurchases undertaken by 62 firms. A probit panel model is used to analyse the decision to repurchase shares on the market. To account for unobserved heterogeneity, random effects panel models are also used. Findings – Analyses of a sample of non-financial firms included in the AOI for the period 2004-2010 show that size is significantly positively correlated with the decision to repurchase shares, thus supporting the agency cost. Findings also support the undervaluation and signalling hypotheses. Similarly, there is evidence in support of the view that firms repurchase shares to reach their target optimal capital structure. The present study also finds a significant positive association between board independence and the decision to repurchase shares in Australia. Research limitations/implications – On-market share repurchases help firms to signal their future growth opportunities and resolve agency conflicts. Signals from repurchases also help markets discover the true fundamental values of firms. Governance plays an important role in improving the effectiveness of on-market share repurchases, as independent directors provide both monitoring and discipline which helps to ensure that firms have valid motivations in undertaking share repurchases. Practical implications – These findings have implications for capital restructuring and governance policies. Principle-based governance frameworks that prevail in countries like Australia work as well as rule-based governance. Originality/value – This study highlights the complementary roles that financial policies and corporate boards play in corporate governance. Independent boards ensure that firms pursue appropriate financial policies that help resolve agency conflicts and information asymmetry problems.
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West, Tracey, and Andrew C. Worthington. "Life Events and Portfolio Rebalancing of the Family Home." Journal of Financial Counseling and Planning 29, no. 1 (June 2018): 103–13. http://dx.doi.org/10.1891/1052-3073.29.1.103.
This article investigates the impacts of financial shocks on the role of the family home in asset portfolios of Australian households using longitudinal data from the Household, Income, and Labour Dynamics in Australia (HILDA) survey. The life events considered are serious illness or injury, death of a spouse, fired or made redundant, and separation from a spouse. We use a static and dynamic Tobit models to assess the impact and duration of the life events on the portfolio share of the family home. The insights gained from this study may be important for financial planners, as adverse wealth outcomes may be hedged through better financial education, insurance products, or general financial preparedness.
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Durack, Nick, Robert B. Durand, and Ross A. Maller. "A best choice among asset pricing models? The Conditional Capital Asset Pricing Model in Australia." Accounting and Finance 44, no. 2 (July 2004): 139–62. http://dx.doi.org/10.1111/j.1467-629x.2004.00107.x.
Reddy, Wejendra, David Higgins, and Ron Wakefield. "An investigation of property-related decision practice of Australian fund managers." Journal of Property Investment & Finance 32, no. 3 (April 1, 2014): 282–305. http://dx.doi.org/10.1108/jpif-02-2014-0014.
Purpose – In Australia, the A$2.2 trillion managed funds industry including the large pension funds (known locally as superannuation funds) are the dominant institutional property investors. While statistical information on the level of Australian managed fund investments in property assets is widely available, comprehensive practical evidence on property asset allocation decision-making process is underdeveloped. The purpose of this research is to identify Australian fund manager's property asset allocation strategies and decision-making frameworks at strategic level. Design/methodology/approach – The research was undertaken in May-August 2011 using an in-depth semi-structured questionnaire administered by mail. The survey was targeted at 130 leading managed funds and asset consultants within Australia. Findings – The evaluation of the 79 survey respondents indicated that Australian fund manager's property allocation decision-making process is an interactive, sequential and continuous process involving multiple decision-makers (internal and external) complete with feedback loops. It involves a combination of quantitative analysis (mainly mean-variance analysis) and qualitative overlay (mainly judgement, or “gut-feeling”, and experience). In addition, the research provided evidence that the property allocation decision-making process varies depending on the size and type of managed fund. Practical implications – This research makes important contributions to both practical and academic fields. Information on strategic property allocation models and variables is not widely available, and there is little guiding theory related to the subject. Therefore, the conceptual frameworks developed from the research will help enhance academic theory and understanding in the area of property allocation decision making. Furthermore, the research provides small fund managers and industry practitioners with a platform from which to improve their own property allocation processes. Originality/value – In contrast to previous property decision-making research in Australia which has mainly focused on strategies at the property fund investment level, this research investigates the institutional property allocation decision-making process from a strategic position involving all major groups in the Australian managed funds industry.
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Antioch, K. M., and M. K. Walsh. "Risk-adjusted capitation funding models for chronic disease in Australia: alternatives to casemix funding." European Journal of Health Economics 3, no. 2 (June 2002): 83–93. http://dx.doi.org/10.1007/s10198-002-0096-7.
PLUNKETT, BRADLEY, FABIO R. CHADDAD, and MICHAEL L. COOK. "Ownership structure and incentives to invest: dual-structured irrigation cooperatives in Australia." Journal of Institutional Economics 6, no. 2 (May 6, 2010): 261–80. http://dx.doi.org/10.1017/s1744137409990361.
Abstract:In the past decade, Australia has begun to privatize its irrigation system. Two general models have emerged: a single and a dual ownership structure. This paper examines the trade-offs, costs and benefits, and the attendant efficiencies regarding costs of ownership. In particular, we examine member capital investment incentives and resultant risk-bearing costs related to capital formation. The paper concludes that the dual ownership structure system has significant economic advantages relative to its single-structured counterpart.
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West, Tracey, and Andrew Worthington. "The impact of major life events on household asset portfolio rebalancing." Studies in Economics and Finance 36, no. 3 (July 26, 2019): 334–47. http://dx.doi.org/10.1108/sef-11-2017-0318.
Purpose This paper aims to model the asset portfolio rebalancing decisions of Australian households experiencing a severe life event shock. Design/methodology/approach The paper uses household longitudinal data from the Household, Income, and Labour Dynamics in Australia (HILDA) survey since 2001. The major life events are serious illness or injury, death of a spouse, job dismissal or redundancy and separation from a spouse. The asset classes are bank accounts, cash investments, equities, superannuation (private pensions), life insurance, trust funds, owner-occupied housing, investor housing, business assets, vehicles and collectibles. The authors use both static and dynamic Tobit models to assess the impact and duration of impact of the shocks. Findings Serious illness and injury, loss of employment, separation and spousal death cause households to rebalance portfolios in ways that can have detrimental effects on long-term wealth accumulation through poor market timing and the incurring of transaction costs. Research limitations/implications The survey results are only available since 2001, and the wealth module from which the asset data are drawn is self-reported and not available every year. Practical implications Relevant to policymakers working on the ongoing retirement of the “baby boomer” generation and for financial planners guiding household investment decisions. Originality/value Most research on shocks to household wealth concern a narrower range of assets and only limited shocks. Also, this is one of the few studies to use a random effects model to allow for unspecified heterogeneity among households.
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Yong, Jaime, and Anh Khoi Pham. "The long-term linkages between direct and indirect property in Australia." Journal of Property Investment & Finance 33, no. 4 (July 6, 2015): 374–92. http://dx.doi.org/10.1108/jpif-01-2015-0005.
Purpose– Investment in Australia’s property market, whether directly or indirectly through Australian real estate investment trusts (A-REITs), grew remarkably since the 1990s. The degree of segregation between the property market and other financial assets, such as shares and bonds, can influence the diversification benefits within multi-asset portfolios. This raises the question of whether direct and indirect property investments are substitutable. Establishing how information transmits between asset classes and impacts the predictability of returns is of interest to investors. The paper aims to discuss these issues.Design/methodology/approach– The authors study the linkages between direct and indirect Australian property sectors from 1985 to 2013, with shares and bonds. This paper employs an Autoregressive Fractionally Integrated Moving Average (ARFIMA) process to de-smooth a valuation-based direct property index. The authors establish directional lead-lag relationships between markets using bi-variate Granger causality tests. Johansen cointegration tests are carried out to examine how direct and indirect property markets adjust to an equilibrium long-term relationship and short-term deviations from such a relationship with other asset classes.Findings– The authors find the use of appraisal-based property data creates a smoothing bias which masks the extent of how information is transmitted between the indirect property sector, stock and bond markets, and influences returns. The authors demonstrate that an ARFIMA process accounting for a smoothing bias up to lags of four quarters can overcome the overstatement of the smoothing bias from traditional AR models, after individually appraised constituent properties are aggregated into an overall index. The results show that direct property adjusts to information transmitted from market-traded A-REITs and stocks.Practical implications– The study shows direct property investments and A-REITs are substitutible in a multi-asset portfolio in the long and short term.Originality/value– The authors apply an ARFIMA(p,d,q) model to de-smooth Australian property returns, as proposed by Bond and Hwang (2007). The authors expect the findings will contribute to the discussion on whether direct property and REITs are substitutes in a multi-asset portfolio.
Dissertations / Theses on the topic "Finance 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.
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.
[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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Shen, Gensheng University of Ballarat. "The determinants of capital structure in Chinese listed companies." University of Ballarat, 2008. http://archimedes.ballarat.edu.au:8080/vital/access/HandleResolver/1959.17/12728.
Traditional financial theories see capital structure as a result of mainly financial, tax and growth factors (Modigliani & Miller, 1958). But corporate governance theories (Jensen & Meckling, 1976) and business strategy theories (Barton & Gordon, 1988) suggest that ownership structure and ownership concentration, product diversification and asset specificity may also influence capital structure. Focusing on the examination of the determinants of capital structure in Chinese listed companies, this research goes beyond financial factors and considered business strategy and corporate governance approaches, and their impact on capital structure, in a transitioning Chinese context where institutions, expertise and regulatory processes are different to, but converging on, Western approaches. A panel data set of 1,098 Chinese listed companies for the period of 1991 to 2000 was collected from published sources, and conventional and innovative econometric methodologies were used to model a range of relationships between capital structure and its financial and non-financial determinants. The statistical approaches used in this study included Ordinary Least Squares Model and also Linear Mixed Model, which is a powerful tool to examine panel data where independence of explanatory variables is not assumed. The analysis also involved Hox’s model building procedures to measure model fit. The capital structure of listed companies in both the Shenzhen Stock Exchange and the Shanghai Securities Exchange is positively related to a firm’s tax rate, growth and capital intensity and negatively related to a firm’s profit and size. Other financial factors such as tangibility, risk and duration are non-significant. The capital structure of listed companies, particularly in the Shenzhen Stock Exchange, is positively related to product diversification and negatively related to asset specificity. The capital structure of listed companies in the Shanghai Securities Exchange is positively related to government ownership and ownership concentration of the largest shareholder and negatively related to legal person ownership and ownership concentration of the ten largest shareholders. The data and modelling support financial and non-financial determinants of capital structure. In particular, information asymmetry, business diversity and asset specificity have a significant impact on capital structure. In addition the empirical work in the study supports agency cost explanations of debt and equity. Finally the research demonstrates that the two main financial markets in China, Shenzhen and Shanghai, have operated differently but are converging towards a common norm. The research contributes to the general field of capital structure and provides valuable insights into the nature of the Chinese firm and the evolution of the Chinese financial system. Doctor of Philosophy
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Shen, Gensheng. "The determinants of capital structure in Chinese listed companies." University of Ballarat, 2008. http://archimedes.ballarat.edu.au:8080/vital/access/HandleResolver/1959.17/15395.
Traditional financial theories see capital structure as a result of mainly financial, tax and growth factors (Modigliani & Miller, 1958). But corporate governance theories (Jensen & Meckling, 1976) and business strategy theories (Barton & Gordon, 1988) suggest that ownership structure and ownership concentration, product diversification and asset specificity may also influence capital structure. Focusing on the examination of the determinants of capital structure in Chinese listed companies, this research goes beyond financial factors and considered business strategy and corporate governance approaches, and their impact on capital structure, in a transitioning Chinese context where institutions, expertise and regulatory processes are different to, but converging on, Western approaches. A panel data set of 1,098 Chinese listed companies for the period of 1991 to 2000 was collected from published sources, and conventional and innovative econometric methodologies were used to model a range of relationships between capital structure and its financial and non-financial determinants. The statistical approaches used in this study included Ordinary Least Squares Model and also Linear Mixed Model, which is a powerful tool to examine panel data where independence of explanatory variables is not assumed. The analysis also involved Hox’s model building procedures to measure model fit. The capital structure of listed companies in both the Shenzhen Stock Exchange and the Shanghai Securities Exchange is positively related to a firm’s tax rate, growth and capital intensity and negatively related to a firm’s profit and size. Other financial factors such as tangibility, risk and duration are non-significant. The capital structure of listed companies, particularly in the Shenzhen Stock Exchange, is positively related to product diversification and negatively related to asset specificity. The capital structure of listed companies in the Shanghai Securities Exchange is positively related to government ownership and ownership concentration of the largest shareholder and negatively related to legal person ownership and ownership concentration of the ten largest shareholders. The data and modelling support financial and non-financial determinants of capital structure. In particular, information asymmetry, business diversity and asset specificity have a significant impact on capital structure. In addition the empirical work in the study supports agency cost explanations of debt and equity. Finally the research demonstrates that the two main financial markets in China, Shenzhen and Shanghai, have operated differently but are converging towards a common norm. The research contributes to the general field of capital structure and provides valuable insights into the nature of the Chinese firm and the evolution of the Chinese financial system. Doctor of Philosophy
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Klongkratoke, Pittaya. "Econometric models in foreign exchange market." Thesis, University of Glasgow, 2016. http://theses.gla.ac.uk/7333/.
According to the significance of the econometric models in foreign exchange market, the purpose of this research is to give a closer examination on some important issues in this area. The research covers exchange rate pass-through into import prices, liquidity risk and expected returns in the currency market, and the common risk factors in currency markets. Firstly, with the significant of the exchange rate pass-through in financial economics, the first empirical chapter studies on the degree of exchange rate pass-through into import in emerging economies and developed countries in panel evidences for comparison covering the time period of 1970-2009. The pooled mean group estimation (PMGE) is used for the estimation to investigate the short run coefficients and error variance. In general, the results present that the import prices are affected positively, though incompletely, by the exchange rate. Secondly, the following study addresses the question whether there is a relationship between cross-sectional differences in foreign exchange returns and the sensitivities of the returns to fluctuations in liquidity, known as liquidity beta, by using a unique dataset of weekly order flow. Finally, the last study is in keeping with the study of Lustig, Roussanov and Verdelhan (2011), which shows that the large co-movement among exchange rates of different currencies can explain a risk-based view of exchange rate determination. The exploration on identifying a slope factor in exchange rate changes is brought up. The study initially constructs monthly portfolios of currencies, which are sorted on the basis of their forward discounts. The lowest interest rate currencies are contained in the first portfolio and the highest interest rate currencies are in the last. The results performs that portfolios with higher forward discounts incline to contain higher real interest rates in overall by considering the first portfolio and the last portfolio though the fluctuation occurs.
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Wongwachara, Warapong. "Essays on econometric errors in quantitative financial economics." Thesis, University of Cambridge, 2011. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.609240.
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.
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.
Emiris, Marina. "Essays on macroeconomics and finance." Doctoral thesis, Universite Libre de Bruxelles, 2006. http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/210764.
Venditti, Fabrizio. "Essays on models with time-varying parameters for forecasting and policy analysis." Thesis, Queen Mary, University of London, 2017. http://qmro.qmul.ac.uk/xmlui/handle/123456789/24868.
The aim of this thesis is the development and the application of econometric models with time-varying parameters in a policy environment. The popularity of these methods has run in parallel with advances in computing power, which has made feasible estimation methods that until the late '90s would have been unfeasible. Bayesian methods, in particular, benefitted from these technological advances, as sampling from complicated posterior distributions of the model parameters became less and less time-consuming. Building on the seminal work by Carter and Kohn (1994) and Jacquier, Polson, and Rossi (1994), bayesian algorithms for estimating Vector Autoregressions (VARs) with drifting coefficients and volatility were independently derived by Cogley and Sargent (2005) and Primiceri (2005). Despite their increased popularity, bayesian methods still suffer from some limitations, from both a theoretical and a practical viewpoint. First, they typically assume that parameters evolve as independent driftless random walks. It is therefore unclear whether the output that one obtains from these estimators is accurate when the model parameters are generated by a different stochastic process. Second, some computational limitations remain as only a limited number of time series can be jointly modeled in this environment. These shortcomings have prompted a new line of research that uses non-parametric methods to estimate random time-varying coefficients models. Giraitis, Kapetanios, and Yates (2014) develop kernel estimators for autoregressive models with random time-varying coefficients and derive the conditions under which such estimators consistently recover the true path of the model coefficients. The method has been suitably adapted by Giraitis, Kapetanios, and Yates (2012) to a multivariate context. In this thesis I make use of both bayesian and non-parametric methods, adapting them (and in some cases extending them) to answer some of the research questions that, as a Central Bank economist, I have been tackling in the past five years. The variety of empirical exercises proposed throughout the work testifies the wide range of applicability of these models, be it in the area of macroeconomic forecasting (both at short and long horizons) or in the investigation of structural change in the relationship among macroeconomic variables. The first chapter develops a mixed frequency dynamic factor model in which the disturbances of both the latent common factor and of the idiosyncratic components have time varying stochastic volatility. The model is used to investigate business cycle dynamics in the euro area, and to perform point and density forecast. The main result is that introducing stochastic volatility in the model contributes to an improvement in both point and density forecast accuracy. Chapter 2 introduces a nonparametric estimation method for a large Vector Autoregression (VAR) with time-varying parameters. The estimators and their asymptotic distributions are available in closed form. This makes the method computationally efficient and capable of handling information sets as large as those typically handled by factor models and Factor Augmented VARs (FAVAR). When applied to the problem of forecasting key macroeconomic variables, the method outperforms constant parameter benchmarks and large Bayesian VARs with time-varying parameters. The tool is also used for structural analysis to study the time-varying effects of oil price innovations on sectorial U.S. industrial output. Chapter 3 uses a bayesian VAR to provide novel evidence on changes in the relationship between the real price of oil and real exports in the euro area. By combining robust predictions on the sign of the impulse responses obtained from a theoretical model with restrictions on the slope of the oil demand and oil supply curves, oil supply and foreign productivity shocks are identified. The main finding is that from the 1980s onwards the relationship between oil prices and euro area exports has become less negative conditional on oil supply shortfalls and more positive conditional on foreign productivity shocks. A general equilibrium model is used to shed some light on the plausible reasons for these changes. Chapter 4 investigates the failure of conventional constant parameter models in anticipating the sharp fall in inflation in the euro area in 2013- 2014. This forecasting failure can be partly attributed to a break in the elasticity of inflation to the output gap. Using structural break tests and non-parametric time varying parameter models this study shows that this elasticity has indeed increased substantially after 2013. Two structural interpretations of this finding are offered. The first is that the increase in the cyclicality of inflation has stemmed from lower nominal rigidities or weaker strategic complementarity in price setting. A second possibility is that real time output gap estimates are understating the amount of spare capacity in the economy. I estimate that, in order to reconcile the observed fall in inflation with the historical correlation between consumer prices and the business cycle, the output gap should be wider by around one third.
Books on the topic "Finance Australia Econometric models":
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Karen, Wilson. The architecture of the system of national accounts: A three country comparison, Canada, Australia, and United Kingdom. Cambridge, MA: National Bureau of Economic Research, 2005.
Karagedikli, Özer. Do inflation targeting central banks behave asymmetrically?: Evidence from Australia and New Zealand. Wellington, N.Z: Economics Dept., Reserve Bank of New Zealand, 2004.
Merton, Robert C. The design of financial systems: Towards a synthesis of function and structure. Cambridge, MA: National Bureau of Economic Research, 2004.
Book chapters on the topic "Finance Australia Econometric models":
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Wu, Shu, and Yong Zeng. "An Econometric Model of the Term Structure of Interest Rates Under Regime-Switching Risk." In Hidden Markov Models in Finance, 55–83. Boston, MA: Springer US, 2014. http://dx.doi.org/10.1007/978-1-4899-7442-6_3.
Bramante, R., R. Colombo, and G. Gabbi. "Are Neural Network and Econometric Forecasts Good for Trading? Stochastic Variance Models as a Filter Rule." In Decision Technologies for Computational Finance, 417–24. Boston, MA: Springer US, 1998. http://dx.doi.org/10.1007/978-1-4615-5625-1_33.
Lehrer, Steven F., Tian Xie, and Guanxi Yi. "Do the Hype of the Benefits from Using New Data Science Tools Extend to Forecasting Extremely Volatile Assets?" In Data Science for Economics and Finance, 287–330. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-66891-4_13.
AbstractThis chapter first provides an illustration of the benefits of using machine learning for forecasting relative to traditional econometric strategies. We consider the short-term volatility of the Bitcoin market by realized volatility observations. Our analysis highlights the importance of accounting for nonlinearities to explain the gains of machine learning algorithms and examines the robustness of our findings to the selection of hyperparameters. This provides an illustration of how different machine learning estimators improve the development of forecast models by relaxing the functional form assumptions that are made explicit when writing up an econometric model. Our second contribution is to illustrate how deep learning can be used to measure market-level sentiment from a 10% random sample of Twitter users. This sentiment variable significantly improves forecast accuracy for every econometric estimator and machine algorithm considered in our forecasting application. This provides an illustration of the benefits of new tools from the natural language processing literature at creating variables that can improve the accuracy of forecasting models.
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Buckmann, Marcus, Andreas Joseph, and Helena Robertson. "Opening the Black Box: Machine Learning Interpretability and Inference Tools with an Application to Economic Forecasting." In Data Science for Economics and Finance, 43–63. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-66891-4_3.
AbstractWe present a comprehensive comparative case study for the use of machine learning models for macroeconomics forecasting. We find that machine learning models mostly outperform conventional econometric approaches in forecasting changes in US unemployment on a 1-year horizon. To address the black box critique of machine learning models, we apply and compare two variables attribution methods: permutation importance and Shapley values. While the aggregate information derived from both approaches is broadly in line, Shapley values offer several advantages, such as the discovery of unknown functional forms in the data generating process and the ability to perform statistical inference. The latter is achieved by the Shapley regression framework, which allows for the evaluation and communication of machine learning models akin to that of linear models.
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Gilli, Manfred, Dietmar Maringer, and Enrico Schumann. "Econometric Models." In Numerical Methods and Optimization in Finance, 445–503. Elsevier, 2011. http://dx.doi.org/10.1016/b978-0-12-375662-6.00014-6.
Gilli, Manfred, Dietmar Maringer, and Enrico Schumann. "Econometric models." In Numerical Methods and Optimization in Finance, 487–549. Elsevier, 2019. http://dx.doi.org/10.1016/b978-0-12-815065-8.00028-5.
"/ Nonparametric and Semiparametric Panel Econometric Models: Estimation and Testing." In Handbook of Empirical Economics and Finance, 474–517. Chapman and Hall/CRC, 2016. http://dx.doi.org/10.1201/b10440-20.
Harding, Don, and Adrian Pagan. "Accounting for Observed Cycle Features with a Range of Statistical Models." In The Econometric Analysis of Recurrent Events in Macroeconomics and Finance. Princeton University Press, 2016. http://dx.doi.org/10.23943/princeton/9780691167084.003.0007.
This chapter looks at observed features of the cycle in a variety of time series. It sets out these features for the United States and a number of other countries, and then asks whether these features can be replicated by the use of a particular statistical model—a linear autoregression. For such linear models it is possible to broadly account for the observed features using moments of the series for growth rates, and this strategy is employed in the chapter. It then uses a particular nonlinear statistical model to see if it can match all the features, and further looks at two other nonlinear models first dealt with in Chapter 4. The chapter concludes with an examination of whether the binary indicators summarizing the recurrent states can be used in the context of standard multivariate methods such as vector autoregressions. This turns out not to be straightforward owing to the nature of the binary variables.
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"Chapter 7. Accounting for Observed Cycle Features with a Range of Statistical Models." In The Econometric Analysis of Recurrent Events in Macroeconomics and Finance, 122–42. Princeton: Princeton University Press, 2016. http://dx.doi.org/10.1515/9781400880935-009.
Lavergne, Pascal, and Pierre E. Nguimkeu. "Uniform in Bandwidth Tests of Specification for Conditional Moment Restrictions Models." In Econometric Methods and Their Applications in Finance, Macro and Related Fields, 223–41. WORLD SCIENTIFIC, 2014. http://dx.doi.org/10.1142/9789814513470_0009.
