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Over the last few years there has been a surge of activity within the physics community in the emerging field of Econophysics—the study of economic systems from a physicist's perspective. Physicists tend to take a different view than economists and other social scientists, being interested in such topics as phase transitions and fluctuations. In this dissertation two simple models of stock exchange are developed and simulated numerically. The first is characterized by centralized trading with a market maker. Fluctuations are driven by a stochastic component in the agents' forecasts. As the scale of the fluctuations is varied a critical phase transition is discovered. Unfortunately, this model is unable to generate realistic market dynamics. The second model discards the requirement of centralized trading. In this case the stochastic driving force is Gaussian-distributed "news events" which are public knowledge. Under variation of the control parameter the model exhibits two phase transitions: both a first- and a second-order (critical). The decentralized model is able to capture many of the interesting properties observed in empirical markets such as fat tails in the distribution of returns, a brief memory in the return series, and long-range correlations in volatility. Significantly, these properties only emerge when the parameters are tuned such that the model spans the critical point. This suggests that real markets may operate at or near a critical point, but is unable to explain why this should be. This remains an interesting open question worth further investigation. One of the main points of the thesis is that these empirical phenomena are not present in the stochastic driving force, but emerge endogenously from interactions between agents. Further, they emerge despite the simplicity of the modeled agents; suggesting complex market dynamics do not arise from the complexity of individual investors but simply from interactions between (even simple) investors. Although the emphasis of this thesis is on the extent to which multi-agent models can produce complex dynamics, some attempt is also made to relate this work with empirical data. Firstly, the trading strategy applied by the agents in the second model is demonstrated to be adequate, if not optimal, and to have some surprising consequences. Secondly, the claim put forth by Sornette et al. that large financial crashes may be heralded by accelerating precursory oscillations is also tested. It is shown that there is weak evidence for the existence of log-periodic precursors but the signal is probably too indistinct to allow for reliable predictions.

Diplominio darbo tikslas – atlikti Biržų ploto dirvožemių geocheminį rajonavimą pagal geologinius-geomorfologinius požymius, nustatyti jų geocheminio lauko skirtumus, įvertinti gamtinių veiksnių apspręstus cheminių elementų kaupimo skirtumus. Išvados 1. Biržų ploto dirvožemio ir grunto geocheminiam rajonavimui optimalu naudoti du kriterijus: a) technogeninės apkrovos laipsnį; b) litogenetinę-geomorfologinę dirvodarinių uolienų priklausomybę. Pagal technogeninės apkrovos laipsnį ploto teritorija suskirstyta į gamtinę (foninę) ir dvi urbanizuotas zonas: Pasvalio ir Biržų. Pagal litogenetinę-geomorfologinę priklausomybę gamtinėje zonoje išskirti 7 geocheminiai rajonai: Vaškų, Lauksodžio ir Žeimelio moreninių lygumų, Nemunėlio Radviliškio moreninės limnoglacialinės lygumos, Linkuvos moreninio kalvagūbrio, Pasvalio limnoglacialinės lygumos, Saločių limnoglacialinės lygumos, Pumpėnų moreninės lygumos, Likėnų, Satkūnų, Antašavos moreninių lygumų. 2. Svarbiausi faktoriai, sąlygojantys cheminių elementų akumuliaciją, yra litogeninis ir karbonatinis. Pirmasis susijęs su molio frakcijos dirvožemyje procentiniu kiekiu, antrasis – su karbonatų ir sunkiųjų mineralų santykiu aleurito frakcijoje. Su litogeniniu faktoriumi asocijuojasi tokie technogeniniai elementai kaip Cr, Ni, Co, Zn, mažiau – Cu, Sn (sorbuojami ant molio mineralų. Su karbonatiniu faktoriumi asocijuojasi Pb, Cu, Co, Zn (sudaro patvarius junginius ir nusėda šarminėje aplinkoje). 3. Pagal teigiamas arba neigiamas faktorių... [toliau žr. visą tekstą] / Objectives: to perform Biržai region soil geochemical regionalism in accordance with geological-geophormalogical evidence, to establish geochemical field differences, evaluate resistance to polution technogenous chemical elements. Goals: 1. Summarize experience gained in previously accomplished geochemical regionalism in Lithuania. 2. Familiarize with geochemical mapping of Biržai region . 3. To explore geological (quaternary), geomorphologic and anthropocentric pollution conditions in Biržai region, according to this distinguish appropriate areas of soil and establish their geochemical field differences, by employing mathematical-statistical methods to verify extrication validity. 4. Applying factoring analysis Compose informative factors factoring significance maps – both for natural soil and city priming. 5. Determine different soil regions resistance to technogenic pollution by technogenous elements (Pb, Zn, Ag, Sn, Cu, Cr etc.), which represent their accumulation or immunity. Findings: 1. Two criteria were applied to Biržai area soil and priming geochemical regionalism: a) technogenic load rate; b) lithogenetical-geomorphological dependence of dirvodarinių rocks In Accordance to technogenic load rate area is divided into natural and two urbanized zones: Pasvalys and Biržai. By lithogenetical-geomorphological subordination in natural zone, 7 regions were identified: Vaškai, Lauksodis and Žeimelis morainic plains, Nemunėlis Radviliškis morainic limnoglacial plains, Linkuva... [to full text]

Darbo tyrimo objektas – kolokacijos ir jų tyrimo metodai. Pagrindinis darbo tikslas – išanalizuoti statistiniais metodais nustatytų kolokacijų sąrašus, juos palyginti ir išnagrinėti atrinktų kolokacijų vertimo atitikmenis. Darbo aktualumas – kolokacijų analizė padės lingvistams ir kitiems kalbos specialistams pasirinkti tinkamą kolokacijų nustatymo metodą tiek anglų, tiek lietuvių kalbai. O kolokacijų vertimo proceso supratimas svarbus vertimo analizei, vertėjų darbui. Tyrimas susideda iš penkių dalių. Antrajame skyriuje pristatoma teorinė kolokacijos sąvoka. Pateikiama sudėtinga kolokacijų vertimo problematika ir keturių analizei pasirinktų statistinių metodų charakteristikos: Tarpusavio Informacija (angl. Mutual Information), T-lygmuo (angl. T-score), Lošimo kauliukų metodas (angl. Dice) ir Logaritminio tikėtinumo santykis (angl. Log-likelihood ratio). Trečiajame skyriuje, remiantis pagrindiniu analizės šaltiniu – lygiagrečiu grožinės literatūros tekstynu, nustatomi kolokacijų sąrašai. Paaiškėja, kad T-lygmens ir Logaritminio tikėtinumo santykio (LTS) metoduose išryškėjo gramatinės kolokacijos, o Tarpusavio Informacijos (TI) ir Lošimo kauliukų (LK) metoduose – leksinės. Parinktos ir apibrėžtos kolokacijų ribos bei metodų panašumo koeficientai. Ketvirtajame skyriuje pasirenkamas 200 geriausiųjų kolokacijų sąrašas ir atliekamas kiekvienos kalbos statistinių metodų palyginimas. Metodai lyginami poromis pagal panašumo kriterijus – LK su TI (leksinės kolokacijos) bei... [toliau žr. visą tekstą] / The main objective of the Master thesis is collocations and collocation extraction methods. The aim of the research is to analyze collocation lists extracted by statistical methods from the parallel corpus of fiction and determine the collocation equivalents. Relevance of the thesis – collocation analysis can help linguists and other language specialists choose the right collocaton extraction methods in both, English and Lithuanian, languages. What is more, understanding of collocation translation process is very important for the translation analysis and interpreters. Research consists of 5 parts. Chapter 2 presents the concept of collocation and possible collocation translation problems. The theoretical part also includes the characteristics of the four selected statistical methods: Mutual Information (MI), T-score, Dice and Log-likelihood ratio (LLR). In chapter 3, collocation lists for each language, English and Lithuanian, are extracted. The analysis reveal that T-score and LLR methods extract grammatical collocations, while MI and Dice – lexical ones. Futher in this chapter, collocation boundaries and the coefficients of each method are defined. Chapter 4 presents a list of top 200 collocations of each language and method. The methods with new collocation lists are compared in pairs according to similarity criteria - Dice with MI (lexical collocations) and T-score with LLR (grammatical). Another distribution of bigrams according to frequency is identified, and both... [to full text]

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