Financial time series analysis : Chaos and neurodynamics approach

This work aims at combining the Chaos theory postulates and Artificial Neural Networks classification and predictive capability, in the field of financial time series prediction. Chaos theory, provides valuable qualitative and quantitative tools to decide on the predictability of a chaotic system. Quantitative measurements based on Chaos theory, are used, to decide a-priori whether a time series, or a portion of a time series is predictable, while Chaos theory based qualitative tools are used to provide further observations and analysis on the predictability, in cases where measurements provide negative answers. Phase space reconstruction is achieved by time delay embedding resulting in multiple embedded vectors. The cognitive approach suggested, is inspired by the capability of some chartists to predict the direction of an index by looking at the price time series. Thus, in this work, the calculation of the embedding dimension and the separation, in Takens‘ embedding theorem for phase space reconstruction, is not limited to False Nearest Neighbor, Differential Entropy or other specific method, rather, this work is interested in all embedding dimensions and separations that are regarded as different ways of looking at a time series by different chartists, based on their expectations. Prior to the prediction, the embedded vectors of the phase space are classified with Fuzzy-ART, then, for each class a back propagation Neural Network is trained to predict the last element of each vector, whereas all previous elements of a vector are used as features.

Do crude oil price changes affect economic growth of India, Pakistan and Bangladesh? : A multivariate time series analysis

This paper analyzes empirically the effect of crude oil price change on the economic growth of Indian-Subcontinent (India, Pakistan and Bangladesh). We use a multivariate Vector Autoregressive analysis followed by Wald Granger causality test and Impulse Response Function (IRF). Wald Granger causality test results show that only India’s economic growth is significantly affected when crude oil price decreases. Impact of crude oil price increase is insignificantly negative for all three countries during first year. In second year, impact is negative but smaller than first year for India, negative but larger for Bangladesh and positive for Pakistan.

Forecasting with Vector Nonlinear Time Series Models

This work concerns forecasting with vector nonlinear time series models when errorsare correlated. Point forecasts are numerically obtained using bootstrap methods andillustrated by two examples. Evaluation concentrates on studying forecast equality andencompassing. Nonlinear impulse responses are further considered and graphically sum-marized by highest density region. Finally, two macroeconomic data sets are used toillustrate our work. The forecasts from linear or nonlinear model could contribute usefulinformation absent in the forecasts form the other model.

Common Features in Vector Nonlinear Time Series Models

This thesis consists of four manuscripts in the area of nonlinear time series econometrics on topics of testing, modeling and forecasting nonlinear common features. The aim of this thesis is to develop new econometric contributions for hypothesis testing and forecasting in these area. Both stationary and nonstationary time series are concerned. A definition of common features is proposed in an appropriate way to each class. Based on the definition, a vector nonlinear time series model with common features is set up for testing for common features. The proposed models are available for forecasting as well after being well specified. The first paper addresses a testing procedure on nonstationary time series. A class of nonlinear cointegration, smooth-transition (ST) cointegration, is examined. The ST cointegration nests the previously developed linear and threshold cointegration. An Ftypetest for examining the ST cointegration is derived when stationary transition variables are imposed rather than nonstationary variables. Later ones drive the test standard, while the former ones make the test nonstandard. This has important implications for empirical work. It is crucial to distinguish between the cases with stationary and nonstationary transition variables so that the correct test can be used. The second and the fourth papers develop testing approaches for stationary time series. In particular, the vector ST autoregressive (VSTAR) model is extended to allow for common nonlinear features (CNFs). These two papers propose a modeling procedure and derive tests for the presence of CNFs. Including model specification using the testing contributions above, the third paper considers forecasting with vector nonlinear time series models and extends the procedures available for univariate nonlinear models. The VSTAR model with CNFs and the ST cointegration model in the previous papers are exemplified in detail,and thereafter illustrated within two corresponding macroeconomic data sets.

An analysis of linkage between foreign direct investment and GDP per Capita in Pakistan : A time series analysis

This study aims to investigate the relation between foreign direct investment (FDI) and per capita gross domestic product (GDP) in Pakistan. The study is based on a basic Cobb-Douglas production function. Population over age 15 to 64 is used as a proxy for labor in the investigation. The other variables used are gross capital formation, technological gap and a dummy variable measuring among other things political stability. We find positive correlation between GDP per capita in Pakistan and two variables, FDI and population over age 15 to 64. The GDP gap (gap between GDP of USA and GDP of Pakistan) is negatively correlated with GDP per capita as expected. Political instability, economic crisis, wars and polarization in the society have no significant impact on GDP per capita in the long run.

DDR: an index method for large time-series datasets

The tree index structure is a traditional method for searching similar data in large datasets. It is based on the presupposition that most sub-trees are pruned in the searching process. As a result, the number of page accesses is reduced. However, time-series datasets generally have a very high dimensionality. Because of the so-called dimensionality curse, the pruning effectiveness is reduced in high dimensionality. Consequently, the tree index structure is not a suitable method for time-series datasets. In this paper, we propose a two-phase (filtering and refinement) method for searching time-series datasets. In the filtering step, a quantizing time-series is used to construct a compact file which is scanned for filtering out irrelevant. A small set of candidates is translated to the second step for refinement. In this step, we introduce an effective index compression method named grid-based datawise dimensionality reduction (DRR) which attempts to preserve the characteristics of the time-series. An experimental comparison with existing techniques demonstrates the utility of our approach.

Competitive interactions between the Australian native fish Galaxiasmaculatus and the exotic mosquitofish Gambusiaholbrooki,in a series of laboratory experiments

Competitive interactions between Galaxias maculatus, native to southeastern Australia, and Gambusia holbrooki, an exotic pest, were examined in relation to two types of artificial cover and a food source. Experiments were performed in an 800 l tank using photographic techniques. The relative distance of G. maculatus from cover or food source before and after the introduction of G. holbrooki were compared. Also, the proportions of the species were altered to examine the effects of unequal numbers on dominance behaviour. It was found that G. holbrooki was unable to out compete G. maculatus for either cover or food. The distance of G. maculatus from a food source was seen to increase following the introduction of G. holbrooki, when they outnumbered G. maculatus by 3 to 1. Although the distance from the food of G.maculatus increased following the introduction of G. holbrooki, in all cases the mean distance of G.␣maculatus from cover or food was less than that of G. holbrooki. Significant intra-species competition appeared to occur between G. maculatus and it may be that this competition had a greater effect than the competitive pressure G. holbrooki was able to place on the natives. This study revealed that the exotic pest species, G. holbrooki, could not out compete a small native Australian fish species.

Modifying the bitterness of selected oral pharmaceuticals with cation and anion series of salts

Purpose. NaCl has proven to be an effective bitterness inhibitor, but the reason remains unclear. The purpose of this study was to examine the influence of a variety of cations and anions on the bitterness of selected oral pharmaceuticals and bitter taste stimuli: pseudoephedrine, ranitidine, acetaminophen, quinine, and urea.
Method. Human psychophysical taste evaluation using a whole mouth exposure procedure was used.
Results. The cations (all associated with the acetate anion) inhibited bitterness when mixed with pharmaceutical solutions to varying degrees. The sodium cation significantly (P < 0.003) inhibited bitterness of the pharmaceuticals more than the other cations. The anions (all associated with the sodium cation) also inhibited bitterness to varying degrees. With the exception of salicylate, the glutamate and adenosine monophosphate anions significantly (P < 0.001) inhibited bitterness of the pharmaceuticals more than the other anions. Also, there were several specific inhibitory interactions between ammonium, sodium and salicylate and certain pharmaceuticals.
Conclusions. We conclude that sodium was the most successful cation and glutamate and AMP were the most successful anions at inhibiting bitterness. Structure forming and breaking properties of ions, as predicted by the Hofmeister series, and other physical-chemical ion properties failed to significantly predict bitterness inhibition.

The first 50 years of the annual endowed accounting research lecture series at the University of Melbourne

Carnegie and Edwards (2001) suggest that the formation of an organisational body is just one of the 'signals of movement' within the dynamic process of professionalisation of an occupation and they list the sponsoring of professorial posts and research activities at universities as further examples. While the literature on this process in Australia does refer to the sponsorship of chairs of accounting (Carnegie & Williams, 2001), little has been written identifying the range of other areas of sponsorship by the organised accounting bodies. This paper presents details of the first fifty years presentations of the Annual Accounting Research Lectures held at The University of Melbourne, Australia. They have been presented continuously since 1940, when they were inaugurated with sponsorship from the Commonwealth Institute of Accountants. The paper presents the first complete listing of details relating to the presenter (including name, gender, residency and occupational area), title of the paper, date of presentation (where known) and details of publication (where appropriate). The initial and subsequent motivation for the presentation of the series and the influence of the lectures in promoting research and fostering relations between the professional bodies and the university, during a period of great significance in the development of accounting education and the professionalisation of accounting in Australia, is also discussed.

Post-extinction brachiopod faunas from the late Permian Wuchiapingian coal series of South China

This paper describes fourteen brachiopod species in eleven genera from the Late Permian Wuchiapingian Coal Series (Lungtan Formation) of South China. Of these, the shell bed fauna from the basal Lungtan Formation is interpreted to represent the onset of the recovery of shelly faunas in the aftermath of the Guadalupian/Lopingian (G/L) mass extinction in South China. The post-extinction brachiopod faunas in the Wuchiapingian are characterized by the presence of numerous Lazarus taxa, survivors, and newly originating taxa. These elements capable of adapting their life habits were relatively more resistant to the G/L crisis. The post-extinction faunas, including survivors and the elements originating in the recovery period, have no life habit preference, but they were all adapted to a variety of newly vacated niches in the Late Permian oceans. Two new species, Meekella beipeiensis and Niutoushania chongqingensis, are described, and two Chinese genera, Niutoushania and Chengxianoproductus, are emended based on re-examination of the type specimens and new topotype materials from the Lungtan Formation.