Modeling Energy Futures Returns With Markov Regime Switching Model

Financial time series have a tendency of abruptly changing their behavior and maintain this behavior for several consecutive periods, and commodity futures returns are not an exception. This quality proposes that nonlinear models, as opposed to linear models, can more accurately describe returns and volatility. Markov regime switching models are able to match this behavior and have become a popular way to model financial time series. This study uses Markov regime switching model to describe the behavior of energy futures returns on a commodity level, because studies show that commodity futures are a heterogeneous asset class. The purpose of this thesis is twofold. First, determine how many regimes characterize individual energy commodities’ returns in different return frequencies. Second, study the characteristics of these regimes. We extent the previous studies on the subject in two ways: We allow for the possibility that the number of regimes may exceed two, as well as conduct the research on individual commodities rather than on commodity indices or subgroups of these indices. We use daily, weekly and monthly time series of Brent crude oil, WTI crude oil, natural gas, heating oil and gasoil futures returns over 1994–2014, where available, to carry out the study. We apply the likelihood ratio test to determine the sufficient number of regimes for each commodity and data frequency. Then the time series are modeled with Markov regime switching model to obtain the return distribution characteristics of each regime, as well as the transition probabilities of moving between regimes. The results for the number of regimes suggest that daily energy futures return series consist of three to six regimes, whereas weekly and monthly returns for all energy commodities display only two regimes. When the number of regimes exceeds two, there is a tendency for the time series of energy commodities to form groups of regimes. These groups are usually quite persistent as a whole because probability of a regime switch inside the group is high. However, individual regimes in these groups are not persistent and the process oscillates between these regimes frequently. Regimes that are not part of any group are generally persistent, but show low ergodic probability, i.e. rarely prevail in the market. This study also suggests that energy futures return series characterized with two regimes do not necessarily display persistent bull and bear regimes. In fact, for the majority of time series, bearish regime is considerably less persistent. Rahoituksen aikasarjoilla on taipumus arvaamattomasti muuttaa käyttäytymistään ja jatkaa tätä uutta käyttäytymistä useiden periodien ajan, eivätkä hyödykefutuurien tuotot tee tähän poikkeusta. Tämän ominaisuuden johdosta lineaaristen mallien sijasta epälineaariset mallit pystyvät tarkemmin kuvailemaan esimerkiksi tuottojen jakauman parametreja. Markov regiiminvaihtomallit pystyvät vangitsemaan tämän ominaisuuden ja siksi niistä on tullut suosittuja rahoituksen aikasarjojen mallintamisessa. Tämä tutkimus käyttää Markov regiiminvaihtomallia kuvaamaan yksittäisten energiafutuurien tuottojen käyttäytymistä, sillä tutkimukset osoittavat hyödykefutuurien olevan hyvin heterogeeninen omaisuusluokka. Tutkimuksen tarkoitus on selvittää, kuinka monta regiimiä tarvitaan kuvaamaan energiafutuurien tuottoja eri tuottofrekvensseillä ja mitkä ovat näiden regiimien ominaisuudet. Aiempaa tutkimusta aiheesta laajennetaan määrittämällä regiimien lukumäärä tilastotieteellisen testauksen menetelmin sekä tutkimalla energiafutuureja yksittäin; ei indeksi- tai alaindeksitasolla. Tutkimuksessa käytetään päivä-, viikko- ja kuukausiaikasarjoja Brent-raakaöljyn, WTI-raakaöljyn, maakaasun, lämmitysöljyn ja polttoöljyn tuotoista aikaväliltä 1994–2014, siltä osin kuin aineistoa on saatavilla. Likelihood ratio -testin avulla estimoidaan kaikille aikasarjoille regiimien määrä,jonka jälkeen Markov regiiminvaihtomallia hyödyntäen määritetään yksittäisten regiimientuottojakaumien ominaisuudet sekä regiimien välinen transitiomatriisi. Tulokset regiimien lukumäärän osalta osoittavat, että energiafutuurien päiväkohtaisten tuottojen aikasarjoissa regiimien lukumäärä vaihtelee kolmen ja kuuden välillä. Viikko- ja kuukausituottojen kohdalla kaikkien energiafutuurien prosesseissa regiimien lukumäärä on kaksi. Kun regiimejä on enemmän kuin kaksi, on prosessilla taipumus muodostaa regiimeistä koostuvia ryhmiä. Prosessi pysyy ryhmän sisällä yleensä pitkään, koska todennäköisyys siirtyä ryhmään kuuluvien regiimien välillä on suuri. Yksittäiset regiimit ryhmän sisällä eivät kuitenkaan ole kovin pysyviä. Näin ollen prosessi vaihtelee ryhmän sisäisten regiimien välillä tiuhaan. Regiimit, jotka eivät kuulu ryhmään, ovat yleensä pysyviä, mutta prosessi ajautuu niihin vain harvoin, sillä todennäköisyys siirtyä muista regiimeistä niihin on pieni. Tutkimuksen tulokset osoittavat myös, että prosesseissa, joita ohjaa kaksi regiimiä, nämä regiimit eivät välttämättä ole pysyvät bull- ja bear-markkinatilanteet. Tulokset osoittavat sen sijaan, että bear-markkinatilanne on energiafutuureissa selvästi vähemmän pysyvä.

Predicting performance on fluid intelligence from speed of processing, working memory, and controlled attention

Fluid inteliigence has been defined as an innate ability to reason which is measured commonly by the Raven's Progressive Matrices (RPM). Individual differences in fluid intelligence are currently explained by the Cascade model (Fry & Hale, 1996) and the Controlled Attention hypothesis (Engle, Kane, & Tuholski, 1999; Kane & Engle, 2002). The first theory is based on a complex relation among age, speed, and working memory which is described as a Cascade. The alternative to this theory, the Controlled Attention hypothesis, is based on the proposition that it is the executive attention component of working memory that explains performance on fluid intelligence tests. The first goal of this study was to examine whether the Cascade model is consistent within the visuo-spatial and verbal-numerical modalities. The second goal was to examine whether the executive attention component ofworking memory accounts for the relation between working memory and fluid intelligence. Two hundred and six undergraduate students between the ages of 18 and 28 completed a battery of cognitive tests selected to measure processing speed, working memory, and controlled attention which were selected from two cognitive modalities, verbalnumerical and visuo-spatial. These were used to predict performance on two standard measures of fluid intelligence: the Raven's Progressive Matrices (RPM) and the Shipley Institute of Living Scales (SILS) subtests. Multiple regression and Structural Equation Modeling (SEM) were used to test the Cascade model and to determine the independent and joint effects of controlled attention and working memory on general fluid intelligence. Among the processing speed measures only spatial scan was related to the RPM. No other significant relations were observed between processing speed and fluid intelligence. As 1 a construct, working memory was related to the fluid intelligence tests. Consistent with the predictions for the RPM there was support for the Cascade model within the visuo-spatial modality but not within the verbal-numerical modality. There was no support for the Cascade model with respect to the SILS tests. SEM revealed that there was a direct path between controlled attention and RPM and between working memory and RPM. However, a significant path between set switching and RPM explained the relation between controlled attention and RPM. The prediction that controlled attention mediated the relation between working memory and RPM was therefore not supported. The findings support the view that the Cascade model may not adequately explain individual differences in fluid intelligence and this may be due to the differential relations observed between working memory and fluid intelligence across different modalities. The findings also show that working memory is not a domain-general construct and as a result its relation with fluid intelligence may be dependent on the nature of the working memory modality.

Dynamic Performance Evaluation of Canadian Fixed-Income Funds using Markov Regime Switching Models

This thesis examines the performance of Canadian fixed-income mutual funds in the context of an unobservable market factor that affects mutual fund returns. We use various selection and timing models augmented with univariate and multivariate regime-switching structures. These models assume a joint distribution of an unobservable latent variable and fund returns. The fund sample comprises six Canadian value-weighted portfolios with different investing objectives from 1980 to 2011. These are the Canadian fixed-income funds, the Canadian inflation protected fixed-income funds, the Canadian long-term fixed-income funds, the Canadian money market funds, the Canadian short-term fixed-income funds and the high yield fixed-income funds. We find strong evidence that more than one state variable is necessary to explain the dynamics of the returns on Canadian fixed-income funds. For instance, Canadian fixed-income funds clearly show that there are two regimes that can be identified with a turning point during the mid-eighties. This structural break corresponds to an increase in the Canadian bond index from its low values in the early 1980s to its current high values. Other fixed-income funds results show latent state variables that mimic the behaviour of the general economic activity. Generally, we report that Canadian bond fund alphas are negative. In other words, fund managers do not add value through their selection abilities. We find evidence that Canadian fixed-income fund portfolio managers are successful market timers who shift portfolio weights between risky and riskless financial assets according to expected market conditions. Conversely, Canadian inflation protected funds, Canadian long-term fixed-income funds and Canadian money market funds have no market timing ability. We conclude that these managers generally do not have positive performance by actively managing their portfolios. We also report that the Canadian fixed-income fund portfolios perform asymmetrically under different economic regimes. In particular, these portfolio managers demonstrate poorer selection skills during recessions. Finally, we demonstrate that the multivariate regime-switching model is superior to univariate models given the dynamic market conditions and the correlation between fund portfolios.

Human Endogenous Retrovirus (HERV) Insertional Polymorphisms

Human endogenous retroviruses (HERVs) are the result of ancient germ cell infections of human germ cells by exogenous retroviruses. HERVs belong to the long terminal repeat (LTR) group of retrotransposons that comprise ~8% of the human genome. The majority of the HERVs documented have been truncated and/or incurred lethal mutations and no longer encode functional genes; however a very small number of HERVs seem to maintain functional in making new copies by retrotranspositon as suggested by the identification of a handful of polymorphic HERV insertions in human populations. The objectives of this study were to identify novel insertion of HERVs via analysis of personal genomic data and survey the polymorphism levels of new and known HERV insertions in the human genome. Specifically, this study involves the experimental validation of polymorphic HERV insertion candidates predicted by personal genome-based computation prediction and survey the polymorphism level within the human population based on a set of 30 diverse human DNA samples. Based on computational analysis of a limited number of personal genome sequences, PCR genotyping aided in the identification of 15 dimorphic, 2 trimorphic and 5 fixed full-length HERV-K insertions not previously investigated. These results suggest that the proliferation rate of HERVKs, perhaps also other ERVs, in the human genome may be much higher than we previously appreciated and the recently inserted HERVs exhibit a high level of instability. Throughout this study we have observed the frequent presence of additional forms of genotypes for these HERV insertions, and we propose for the first time the establishment of new genotype reporting nomenclature to reflect all possible combinations of the pre-integration site, solo-LTR and full-length HERV alleles.

The effect of perturbation warning on attention switching abilities during dual-task performance in young and older adults

This study examined whether providing an auditory warning would facilitate attention switching abilities in older adults during dual-tasking. Fifteen young and 16 older adults performed a tracking task while recovering their balance from a support surface translation. For half of the trials, an auditory warning was presented to inform participants of the upcoming translation. Performance was quantified through electromyographic (EMG) recordings of the lower limb muscles, while the ability to switch attention between tasks was determined by tracking task error. Providing warning of an upcoming loss of balance resulted in both young and older adults increasing their leg EMG activity by 10-165% (p<0.05) in preparation for the upcoming translation. However, no differences in the timing of attention switching were observed with or without the warning (p=0.424). Together, these findings suggest that providing a perturbation warning has minimal benefits in improving attention switching abilities for balance recovery in healthy older adults.

Melanosomal targeting sequences from gp100 are essential for MHC class II-restricted endogenous epitope presentation and mobilization to endosomal compartments

CD4+ T lymphocytes play an important role in CD8+ T cell-mediated responses against tumors. Considering that about 20% of melanomas express major histocompatibility complex (MHC) class II, it is plausible that concomitant antigenic presentation by MHC class I and class II complexes shapes positive (helper T cells) or negative (regulatory T cells) anti-tumor responses. Interestingly, gp100, a melanoma antigen, can be presented by both MHC class I and class II when expressed endogenously, suggesting that it can reach endosomal/MHC class II compartments (MIIC). Here, we demonstrated that the gp100 putative amino-terminal signal sequence and the last 70 residues in carboxy-terminus, are essential for MIIC localization and MHC class II presentation. Confocal microscopy analyses confirmed that gp100 was localized in LAMP-1+ endosomal/MIIC. Gp100-targeting sequences were characterized by deleting different sections in the carboxy-terminus (residues 590 to 661). Transfection in 293T cells, expressing MHC class I and class II molecules, revealed that specific deletions in carboxy-terminus resulted in decreased MHC class II presentation, without effects on MHC class I presentation, suggesting a role in MIIC trafficking for these deleted sections. Then, we used these gp100-targeting sequences to mobilize the green fluorescent protein (GFP) to endosomal compartments, and to allow MHC class II and class I presentation of minimal endogenous epitopes. Thus, we concluded that these specific sequences are MIIC targeting motifs. Consequently, these sequences could be included in expression cassettes for endogenously expressed tumor or viral antigens to promote MHC class II and class I presentation and optimize in vivo T cell responses, or as an in vitro tool for characterization of new MHC class II epitopes.

The Seemingly Unrelated Dynamic Cointegration Regression Model and Testing for Purching Power Parity.

This paper studies seemingly unrelated linear models with integrated regressors and stationary errors. By adding leads and lags of the first differences of the regressors and estimating this augmented dynamic regression model by feasible generalized least squares using the long-run covariance matrix, we obtain an efficient estimator of the cointegrating vector that has a limiting mixed normal distribution. Simulation results suggest that this new estimator compares favorably with others already proposed in the literature. We apply these new estimators to the testing of purchasing power parity (PPP) among the G-7 countries. The test based on the efficient estimates rejects the PPP hypothesis for most countries.

Tests of Joint Hypotheses for Time Series Regression with a Unit Root

This Paper Studies Tests of Joint Hypotheses in Time Series Regression with a Unit Root in Which Weakly Dependent and Heterogeneously Distributed Innovations Are Allowed. We Consider Two Types of Regression: One with a Constant and Lagged Dependent Variable, and the Other with a Trend Added. the Statistics Studied Are the Regression \"F-Test\" Originally Analysed by Dickey and Fuller (1981) in a Less General Framework. the Limiting Distributions Are Found Using Functinal Central Limit Theory. New Test Statistics Are Proposed Which Require Only Already Tabulated Critical Values But Which Are Valid in a Quite General Framework (Including Finite Order Arma Models Generated by Gaussian Errors). This Study Extends the Results on Single Coefficients Derived in Phillips (1986A) and Phillips and Perron (1986).

Political Influence, Economic Interests and Endogenous Tax Structure in a Computable Equilibrium Framework: with Applicatioon to the United States, 1973 and 1983

A full understanding of public affairs requires the ability to distinguish between the policies that voters would like the government to adopt, and the influence that different voters or group of voters actually exert in the democratic process. We consider the properties of a computable equilibrium model of a competitive political economy in which the economic interests of groups of voters and their effective influence on equilibrium policy outcomes can be explicitly distinguished and computed. The model incorporates an amended version of the GEMTAP tax model, and is calibrated to data for the United States for 1973 and 1983. Emphasis is placed on how the aggregation of GEMTAP households into groups within which economic and political behaviour is assumed homogeneous affects the numerical representation of interests and influence for representative members of each group. Experiments with the model suggest that the changes in both interests and influence are important parts of the story behind the evolution of U.S. tax policy in the decade after 1973.

Testing Mean-Variance Efficiency in CAPM with Possibly Non-Gaussian Errors : An Exact Simulation-Based Approach

In this paper we propose exact likelihood-based mean-variance efficiency tests of the market portfolio in the context of Capital Asset Pricing Model (CAPM), allowing for a wide class of error distributions which include normality as a special case. These tests are developed in the frame-work of multivariate linear regressions (MLR). It is well known however that despite their simple statistical structure, standard asymptotically justified MLR-based tests are unreliable. In financial econometrics, exact tests have been proposed for a few specific hypotheses [Jobson and Korkie (Journal of Financial Economics, 1982), MacKinlay (Journal of Financial Economics, 1987), Gib-bons, Ross and Shanken (Econometrica, 1989), Zhou (Journal of Finance 1993)], most of which depend on normality. For the gaussian model, our tests correspond to Gibbons, Ross and Shanken’s mean-variance efficiency tests. In non-gaussian contexts, we reconsider mean-variance efficiency tests allowing for multivariate Student-t and gaussian mixture errors. Our framework allows to cast more evidence on whether the normality assumption is too restrictive when testing the CAPM. We also propose exact multivariate diagnostic checks (including tests for multivariate GARCH and mul-tivariate generalization of the well known variance ratio tests) and goodness of fit tests as well as a set estimate for the intervening nuisance parameters. Our results [over five-year subperiods] show the following: (i) multivariate normality is rejected in most subperiods, (ii) residual checks reveal no significant departures from the multivariate i.i.d. assumption, and (iii) mean-variance efficiency tests of the market portfolio is not rejected as frequently once it is allowed for the possibility of non-normal errors.

Finite-Sample Diagnostics for Multivariate Regressions with Applications to Linear Asset Pricing Models

In this paper, we propose several finite-sample specification tests for multivariate linear regressions (MLR) with applications to asset pricing models. We focus on departures from the assumption of i.i.d. errors assumption, at univariate and multivariate levels, with Gaussian and non-Gaussian (including Student t) errors. The univariate tests studied extend existing exact procedures by allowing for unspecified parameters in the error distributions (e.g., the degrees of freedom in the case of the Student t distribution). The multivariate tests are based on properly standardized multivariate residuals to ensure invariance to MLR coefficients and error covariances. We consider tests for serial correlation, tests for multivariate GARCH and sign-type tests against general dependencies and asymmetries. The procedures proposed provide exact versions of those applied in Shanken (1990) which consist in combining univariate specification tests. Specifically, we combine tests across equations using the MC test procedure to avoid Bonferroni-type bounds. Since non-Gaussian based tests are not pivotal, we apply the “maximized MC” (MMC) test method [Dufour (2002)], where the MC p-value for the tested hypothesis (which depends on nuisance parameters) is maximized (with respect to these nuisance parameters) to control the test’s significance level. The tests proposed are applied to an asset pricing model with observable risk-free rates, using monthly returns on New York Stock Exchange (NYSE) portfolios over five-year subperiods from 1926-1995. Our empirical results reveal the following. Whereas univariate exact tests indicate significant serial correlation, asymmetries and GARCH in some equations, such effects are much less prevalent once error cross-equation covariances are accounted for. In addition, significant departures from the i.i.d. hypothesis are less evident once we allow for non-Gaussian errors.

Exact Skewness-Kurtosis Tests for Multivariate Normality and Goodness-of-fit in Multivariate Regressions with Application to Asset Pricing Models

We study the problem of testing the error distribution in a multivariate linear regression (MLR) model. The tests are functions of appropriately standardized multivariate least squares residuals whose distribution is invariant to the unknown cross-equation error covariance matrix. Empirical multivariate skewness and kurtosis criteria are then compared to simulation-based estimate of their expected value under the hypothesized distribution. Special cases considered include testing multivariate normal, Student t; normal mixtures and stable error models. In the Gaussian case, finite-sample versions of the standard multivariate skewness and kurtosis tests are derived. To do this, we exploit simple, double and multi-stage Monte Carlo test methods. For non-Gaussian distribution families involving nuisance parameters, confidence sets are derived for the the nuisance parameters and the error distribution. The procedures considered are evaluated in a small simulation experi-ment. Finally, the tests are applied to an asset pricing model with observable risk-free rates, using monthly returns on New York Stock Exchange (NYSE) portfolios over five-year subperiods from 1926-1995.

Exact Multivariate Tests of Asset Pricing Models with Stable Asymmetric Distributions

In this paper, we propose exact inference procedures for asset pricing models that can be formulated in the framework of a multivariate linear regression (CAPM), allowing for stable error distributions. The normality assumption on the distribution of stock returns is usually rejected in empirical studies, due to excess kurtosis and asymmetry. To model such data, we propose a comprehensive statistical approach which allows for alternative - possibly asymmetric - heavy tailed distributions without the use of large-sample approximations. The methods suggested are based on Monte Carlo test techniques. Goodness-of-fit tests are formally incorporated to ensure that the error distributions considered are empirically sustainable, from which exact confidence sets for the unknown tail area and asymmetry parameters of the stable error distribution are derived. Tests for the efficiency of the market portfolio (zero intercepts) which explicitly allow for the presence of (unknown) nuisance parameter in the stable error distribution are derived. The methods proposed are applied to monthly returns on 12 portfolios of the New York Stock Exchange over the period 1926-1995 (5 year subperiods). We find that stable possibly skewed distributions provide statistically significant improvement in goodness-of-fit and lead to fewer rejections of the efficiency hypothesis.