Diagnostic Tests Based on Quantile Residuals for Nonlinear Time Series Models

This thesis studies quantile residuals and uses different methodologies to develop test statistics that are applicable in evaluating linear and nonlinear time series models based on continuous distributions. Models based on mixtures of distributions are of special interest because it turns out that for those models traditional residuals, often referred to as Pearson's residuals, are not appropriate. As such models have become more and more popular in practice, especially with financial time series data there is a need for reliable diagnostic tools that can be used to evaluate them. The aim of the thesis is to show how such diagnostic tools can be obtained and used in model evaluation. The quantile residuals considered here are defined in such a way that, when the model is correctly specified and its parameters are consistently estimated, they are approximately independent with standard normal distribution. All the tests derived in the thesis are pure significance type tests and are theoretically sound in that they properly take the uncertainty caused by parameter estimation into account. -- In Chapter 2 a general framework based on the likelihood function and smooth functions of univariate quantile residuals is derived that can be used to obtain misspecification tests for various purposes. Three easy-to-use tests aimed at detecting non-normality, autocorrelation, and conditional heteroscedasticity in quantile residuals are formulated. It also turns out that these tests can be interpreted as Lagrange Multiplier or score tests so that they are asymptotically optimal against local alternatives. Chapter 3 extends the concept of quantile residuals to multivariate models. The framework of Chapter 2 is generalized and tests aimed at detecting non-normality, serial correlation, and conditional heteroscedasticity in multivariate quantile residuals are derived based on it. Score test interpretations are obtained for the serial correlation and conditional heteroscedasticity tests and in a rather restricted special case for the normality test. In Chapter 4 the tests are constructed using the empirical distribution function of quantile residuals. So-called Khmaladze s martingale transformation is applied in order to eliminate the uncertainty caused by parameter estimation. Various test statistics are considered so that critical bounds for histogram type plots as well as Quantile-Quantile and Probability-Probability type plots of quantile residuals are obtained. Chapters 2, 3, and 4 contain simulations and empirical examples which illustrate the finite sample size and power properties of the derived tests and also how the tests and related graphical tools based on residuals are applied in practice.

Essays on the Modeling and Prediction of Volatility and Higher Moments of Stock Returns (summary section only)

One of the most fundamental and widely accepted ideas in finance is that investors are compensated through higher returns for taking on non-diversifiable risk. Hence the quantification, modeling and prediction of risk have been, and still are one of the most prolific research areas in financial economics. It was recognized early on that there are predictable patterns in the variance of speculative prices. Later research has shown that there may also be systematic variation in the skewness and kurtosis of financial returns. Lacking in the literature so far, is an out-of-sample forecast evaluation of the potential benefits of these new more complicated models with time-varying higher moments. Such an evaluation is the topic of this dissertation. Essay 1 investigates the forecast performance of the GARCH (1,1) model when estimated with 9 different error distributions on Standard and Poor’s 500 Index Future returns. By utilizing the theory of realized variance to construct an appropriate ex post measure of variance from intra-day data it is shown that allowing for a leptokurtic error distribution leads to significant improvements in variance forecasts compared to using the normal distribution. This result holds for daily, weekly as well as monthly forecast horizons. It is also found that allowing for skewness and time variation in the higher moments of the distribution does not further improve forecasts. In Essay 2, by using 20 years of daily Standard and Poor 500 index returns, it is found that density forecasts are much improved by allowing for constant excess kurtosis but not improved by allowing for skewness. By allowing the kurtosis and skewness to be time varying the density forecasts are not further improved but on the contrary made slightly worse. In Essay 3 a new model incorporating conditional variance, skewness and kurtosis based on the Normal Inverse Gaussian (NIG) distribution is proposed. The new model and two previously used NIG models are evaluated by their Value at Risk (VaR) forecasts on a long series of daily Standard and Poor’s 500 returns. The results show that only the new model produces satisfactory VaR forecasts for both 1% and 5% VaR Taken together the results of the thesis show that kurtosis appears not to exhibit predictable time variation, whereas there is found some predictability in the skewness. However, the dynamic properties of the skewness are not completely captured by any of the models.

Modeling Nonlinearities and Asymmetries in Asset Pricing

Financial time series tend to behave in a manner that is not directly drawn from a normal distribution. Asymmetries and nonlinearities are usually seen and these characteristics need to be taken into account. To make forecasts and predictions of future return and risk is rather complicated. The existing models for predicting risk are of help to a certain degree, but the complexity in financial time series data makes it difficult. The introduction of nonlinearities and asymmetries for the purpose of better models and forecasts regarding both mean and variance is supported by the essays in this dissertation. Linear and nonlinear models are consequently introduced in this dissertation. The advantages of nonlinear models are that they can take into account asymmetries. Asymmetric patterns usually mean that large negative returns appear more often than positive returns of the same magnitude. This goes hand in hand with the fact that negative returns are associated with higher risk than in the case where positive returns of the same magnitude are observed. The reason why these models are of high importance lies in the ability to make the best possible estimations and predictions of future returns and for predicting risk.

Climatic adaptation of Norway spruce (Picea abies (L.) Karsten) in Finland based on male flowering phenology.

Anthesis was studied at the canopy level in 10 Norway spruce stands from 9 localities in Finland from 1963 to 1974. Distributions of pollen catches were compared to the normal Gaussian distribution. The basis for the timing studies was the 50 per cent point of the anthesis-fitted normal distribution. Development up to this point was given in calendar days, in degree days (>5 °C) and in period units. The count of each parameter began on March 19 (included). Male flowering in Norway spruce stands was found to have more annual variation in quantity than in Scots pine stands studied earlier. Anthesis in spruce in northern Finland occurred at a later date than in the south. The heat sums needed for anthesis varied latitudinally less in spruce than in pine. The variation of pollen catches in spruce increased towards north-west as in the case of Scots pine. In the unprocessed data, calendar days were found to be the most accurate forecast of anthesis in Norway spruce both for a single year and for the majority of cases of stand averages over several years. Locally, the period unit could be a more accurate parameter for the stand average. However, on a calendar day basis, when annual deviations between expected and measured heat sums were converted to days, period units were narrowly superior to days. The geographical correlations respect to timing of flowering, calculated against distances measured along simulated post-glacial migration routes, were stronger than purely latitudinal correlations. Effects of the reinvasion of Norway spruce into Finland are thus still visible in spruce populations just as they were in Scots pine populations. The proportion of the average annual heat sum needed for spruce anthesis grew rapidly north of a latitude of ca. 63° and the heat sum needed for anthesis decreased only slighty towards the timberline. In light of flowering phenology, it seems probable that the northwesterly third of Finnish Norway spruce populations are incompletely adapted to the prevailing cold climate. A moderate warming of the climate would therefore be beneficial for Norway spruce. This accords roughly with the adaptive situation in Scots pine.

Differences in the climatic adaptation of silver birch (Betula pendula) and downy birch (B. pubescens) in Finland based on male flowering phenology.

Male flowering was studied at the canopy level in 10 silver birch (Betula pendula Roth) stands from 8 localities and in 14 downy birch (B. pubescens Ehrh.) stands from 10 localities in Finland from 1963 to 1973. Distributions of cumulative pollen catches were compared to the normal Gaussian distribution. The basis for the timing of flowering was the 50 per cent point of the anthesis-fitted normal distribution. To eliminate effects of background pollen, only the central, normally distributed part of the cumulative distribution was used. Development up to the median point of the distribution was measured and tested in calendar days, in degree days (> 5 °C) and in period units. The count of each parameter began on and included March 19. Male flowering in silver birch occurred from late April to late June depending on latitude, and flowering in downy birch took place from early May to early July. The heat sums needed for male flowering varied in downy birch stands latitudinally but there was practically no latitudinal variation in heat sums needed for silver birch flowering. The amount of male flowering in stands of both birch species were found to have a large annual variation but without any clear periodicity. The between years pollen catch variation in stands of either birch species did not show any significant latitudinal correlation in contrast to Norway spruce stands. The period unit heat sum gave the most accurate forecast of the timing of flowering for 60 per cent of the silver birch stands and for 78.6 per cent of the for downy birch stands. Calendar days, however, gave the best forecast for silver birch in 25 per cent of the cases, while degree days gave the best forecast for downy birch in 21.4 per cent of the cases. Silver birch seems to have a local inclination for a more fixed flowering date compared to downy birch, which could mean a considerable photoperiodic influence on flowering time of silver birch. Silver birch and downy birch had different geographical correlations. Frequent hybridization of birch species occurs more often in northern Finland in than in more southern latitudes. The different timing in flowering caused increasing scatter in flowering times in the north, especially in the case of downy birch. The chance of simultaneous flowering of silver birch and downy birch so increased northwards due to a more variable climate and also higher altitudinal variations. Compared with conifers, the reproduction cycles of both birch species were found to be well protected from damage by frost.

Distribution and adhesion-promoting activity of alpha4 and alpha5 chain laminins in human endothelia and carcinomas

Basement membranes are specialized sheets of extracellular matrix found in contact with epithelia, endothelia, and certain isolated cells. They support tissue architecture and regulate cell behaviour. Laminins are among the main constituents of basement membranes. Due to differences between laminin isoforms, laminins confer structural and functional diversity to basement membranes. The first aim of this study was to gain insights into the potential functions of the then least characterized laminins, alpha4 chain laminins, by evaluating their distribution in human tissues. We thus created a monoclonal antibody specific for laminin alpha4 chain. By immunohistochemistry, alpha4 chain laminins were primarily localized to basement membranes of blood vessel endothelia, skeletal, heart, and smooth muscle cells, nerves, and adipocytes. In addition, alpha4 chain laminins were found in the region of certain epithelial basement membranes in the epidermis, salivary gland, pancreas, esophagus, stomach, intestine, and kidney. Because of the consistent presence of alpha4 chain laminins in endothelial basement membranes of blood vessels, we evaluated the potential roles of endothelial laminins in blood vessels, lymphatic vessels, and carcinomas. Human endothelial cells produced alpha4 and alpha5 chain laminins. In quantitative and morphological adhesion assays, human endothelial cells barely adhered to alpha4 chain-containing laminin-411. The weak interaction of endothelial cells with laminin-411 appeared to be mediated by alpha6beta1 integrin. The alpha5 chain-containing laminin-511 promoted endothelial cell adhesion better than laminin-411, but it did not promote the formation of cell-extracellular matrix adhesion complexes. The adhesion of endothelial cells to laminin-511 appeared to be mediated by Lutheran glycoprotein together with beta1 and alphavbeta3 integrins. The results suggest that these laminins may induce a migratory phenotype in endothelial cells. In lymphatic capillaries, endothelial basement membranes showed immunoreactivity for laminin alpha4, beta1, beta2, and gamma1 chains, type IV and XVIII collagens, and nidogen-1. Considering the assumed inability of alpha4 chain laminins to polymerize and to promote basement membrane assembly, the findings may in part explain the incomplete basement membrane formation in these vessels. Lymphatic capillaries of ovarian carcinomas showed immunoreactivity also for laminin alpha5 chain and its receptor Lutheran glycoprotein, emphasizing a difference between normal and ovarian carcinoma lymphatic capillaries. In renal cell carcinomas, immunoreactivity for laminin alpha4 chain was found in stroma and basement membranes of blood vessels. In most tumours, immunoreactivity for laminin alpha4 chain was also observed in the basement membrane region of tumour cell islets. Renal carcinoma cells produced alpha4 chain laminins. Laminin-411 did not promote adhesion of renal carcinoma cells, but inhibited their adhesion to fibronectin. Renal carcinoma cells migrated more on laminin-411 than on fibronectin. The results suggest that alpha4 chain laminins have a counteradhesive function, and may thus have a role in detachment and invasion of renal carcinoma cells.