Modeling Asymmetries in Financial Data with Multiplicative Error Models

This thesis addresses modeling of financial time series, especially stock market returns and daily price ranges. Modeling data of this kind can be approached with so-called multiplicative error models (MEM). These models nest several well known time series models such as GARCH, ACD and CARR models. They are able to capture many well established features of financial time series including volatility clustering and leptokurtosis. In contrast to these phenomena, different kinds of asymmetries have received relatively little attention in the existing literature. In this thesis asymmetries arise from various sources. They are observed in both conditional and unconditional distributions, for variables with non-negative values and for variables that have values on the real line. In the multivariate context asymmetries can be observed in the marginal distributions as well as in the relationships of the variables modeled. New methods for all these cases are proposed. Chapter 2 considers GARCH models and modeling of returns of two stock market indices. The chapter introduces the so-called generalized hyperbolic (GH) GARCH model to account for asymmetries in both conditional and unconditional distribution. In particular, two special cases of the GARCH-GH model which describe the data most accurately are proposed. They are found to improve the fit of the model when compared to symmetric GARCH models. The advantages of accounting for asymmetries are also observed through Value-at-Risk applications. Both theoretical and empirical contributions are provided in Chapter 3 of the thesis. In this chapter the so-called mixture conditional autoregressive range (MCARR) model is introduced, examined and applied to daily price ranges of the Hang Seng Index. The conditions for the strict and weak stationarity of the model as well as an expression for the autocorrelation function are obtained by writing the MCARR model as a first order autoregressive process with random coefficients. The chapter also introduces inverse gamma (IG) distribution to CARR models. The advantages of CARR-IG and MCARR-IG specifications over conventional CARR models are found in the empirical application both in- and out-of-sample. Chapter 4 discusses the simultaneous modeling of absolute returns and daily price ranges. In this part of the thesis a vector multiplicative error model (VMEM) with asymmetric Gumbel copula is found to provide substantial benefits over the existing VMEM models based on elliptical copulas. The proposed specification is able to capture the highly asymmetric dependence of the modeled variables thereby improving the performance of the model considerably. The economic significance of the results obtained is established when the information content of the volatility forecasts derived is examined.

Numerical computation of the module of a quadrilateral

The module of a quadrilateral is a positive real number which divides quadrilaterals into conformal equivalence classes. This is an introductory text to the module of a quadrilateral with some historical background and some numerical aspects. This work discusses the following topics: 1. Preliminaries 2. The module of a quadrilateral 3. The Schwarz-Christoffel Mapping 4. Symmetry properties of the module 5. Computational results 6. Other numerical methods Appendices include: Numerical evaluation of the elliptic integrals of the first kind. Matlab programs and scripts and possible topics for future research. Numerical results section covers additive quadrilaterals and the module of a quadrilateral under the movement of one of its vertex.

Yhteistoiminnallinen opetuspaketti lukion pitkän matematiikan Polynomifunktiot-kurssilla käytettäväksi

Tutkielmassa tarkastellaan yhteistoiminnallisen oppimisen soveltamismahdollisuuksia lukion pitkän matematiikan opettamiseen. Tutkielmassa on suunniteltu yhteistoiminnallinen opetuspaketti lukion pitkän matematiikan Polynomifunktiot-kurssille. Tutkielman ensimmäisessä teoriaosassa tarkastellaan yhteistoiminnallisen oppimisen periaatteita ja esitellään neljä yhteistoiminnallisen oppimisen menetelmää: rakenteellinen lähestymistapa, tiimioppiminen ryhmässä, ryhmäavusteinen yksilöllistäminen ja palapeli. Lisäksi teoriaosassa tuodaan esille niitä tekijöitä, jotka opettajan täytyy huomioida soveltaessaan esiteltyjä menetelmiä omaan opetukseensa sekä suunnitellessaan tehtäväkokonaisuuksia. Lopuksi tarkastellaan aiemmin tehtyjä tutkimuksia yhteistoiminnallisen oppimisen soveltamisesta matematiikan opetukseen. Tutkielman toisessa teoriaosassa esitellään klassisen algebran historiaa ja polynomifunktioihin liittyviä määritelmiä, lauseita ja niiden todistuksia sekä esimerkkejä. Opetuspaketti koostuu neljästä tehtäväkokonaisuudesta: epäyhtälön ratkaiseminen, polynomilaskennan kertaus, toisen asteen polynomifunktio ja -yhtälö sekä korkeamman asteen polynomifunktioiden tutkiminen. Lisäksi opetuspaketissa on yleinen esimerkki yhteistoiminnallisen oppitunnin rakenteesta. Opetuspaketin lopussa on raportti eräässä lukiossa suoritetusta testauksesta sekä sen tuloksista. Aiempien tutkimusten sekä tämän tutkielman yhteydessä tehdyn testauksen perusteella voidaan sanoa, että yhteistoiminnallinen oppiminen soveltuu lukion matematiikan opetukseen.