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In this dissertation, we are considering the following question: can the Rigidity Thesis (RT) be reduced to the Wide Scope Thesis (WT). According to the RT, proper names of natural language are rigid designators and most of the definite descriptions of natural language are not rigid designators. Thus, the Descriptive Theory of Proper Names (DTPN), according to which the semantic content of a proper name is a (set of) definite description(s), is false. According to WT, the semantic content of a sentence containing a proper name is given by a (set of) definite description(s) with wide scope (over intensional operators, modal operators included). Such a semantic content can explain the... 

In this research, trade and transportation trends of Asia-Europe-Africa, in the both intercontinental and intracontinental levels have been analyzed. With analyses which are done in this research, determinant factors for modeling and investigating international bilateral trade in these three continents have been recognized. The relevant time-series data were extracted from centralized and international databases. The examined database consists of 11 variables grouped in four categories: bilateral trade data, transportation, geographical and socio-economic characteristics. Transportation data is based on three different networks. The first network consisted of highway, rail and marine modes... 

Wishart processes are popular models for stochastic correlation and volatility of financial assets due to their convenient analytical properties. However, they cannot reproduce the sudden and sustained surges in correlation and volatility observed during market crises. Moreover, the Wishart process (like the CIR model) does not impose a positive lower bound on variances, allowing them to approach zero. This thesis introduces a new stochastic process, called the Markov-Modulated Shifted Wishart (MMSW) process, to address these shortcomings. The MMSW process extends the Wishart model by adding a constant “shift” matrix to keep variances away from zero and by using a Markov chain to switch...