This thesis, “Empirical Asset Pricing and Investment Strategies”, examines a number of topics related to portfolio choice, asset pricing, and strategic and tactical asset allocation. The first two papers treat the predictability of asset returns. Since at least the mid-1980s until quite recently, the conventional wisdom has been that it is possible to predict the return on, for example, an index of stocks. However, a series of recent papers have challenged this conventional wisdom. I answer this challenge and show that it is possible to predict returns if structural changes in the underlying economy are taken into account. The third paper examines the comovement between stocks and bonds. I show how it is possible to improve the composition of a portfolio consisting of these two asset classes by taking into account how the comovement changes over time. All three papers are self-contained and can therefore be read in any order. The first paper is entitled “Structural Breaks in Asset Return Predictability: Can They Be Explained?” Here I investigate whether predictability has changed over time and, if so, whether it is possible to tie the change to any underlying economic variables. Dividend yield and the short interest rate are often used jointly as instruments to predict the return on stocks, but several researchers present evidence that the relation has undergone a structural break. I use a model that extends the conventional structural breaks models to allow both for smooth transitions from one state to another (with a break as a special case), and for transitions that depend on a state variable other than time. The latter allows me to directly test whether, for example, the business cycle influences how the instruments predict returns. The results suggest that this is not the case. However, I do find evidence of a structural change primarily in how the instruments predict returns for large firms. The change differs from a break in that it appears to be an extended non-linear transition during the period 1993—1997. After the change, the short rate does not predict returns at all. Dividend yield, on the other hand, is strongly significant, and the return has become more sensitive to it. In the second paper, “Restoring the Predictability of Equity Returns,” I take another perspective on predictability and structural shifts. Several recent papers have questioned the predictability of equity returns, potentially implying serious negative consequences for investment decision-making. With return data including the 1990s, variables that previously predicted returns, such as the dividend yield, are no longer significant and results of out-of-sample tests are often weak. A possible reason is that the underlying structure of the economy has changed. I use an econometric model that allows for regime shifts over time as well as due to changes in a state variable, in this case the price-earnings ratio. This makes it possible to separate influences from these two sources and to determine whether one or both sources have affected return predictability. The results indicate that, first, a structural change occurred during the 1990s, and, second, that the unusually high level of price earnings in the late 1990s and early 2000s temporarily affected predictability at the 12-month horizon. In the third paper, “Coupling and Decoupling: Changing Relations between Stock and Bond Market Returns,” I investigate stock-bond comovement. The correlation between stocks and bonds has changed dramatically over the last ten years, introducing a new type of risk for portfolio managers, namely, correlation risk. I use GARCH estimates of stock volatility, simple regressions, and regime-switching econometric models to assess whether level of volatility, or changes in volatility, can be used to explain some of the changes in comovement in seven different countries. As regards volatility level, strong support is found in almost all countries to suggest that high volatility predicts lower, or negative, comovement. I argue that this can be evidence of a market-timing type of behavior. As for changes in volatility, the results are more mixed. Only for the U.S. market do I find strong support to conclude that large changes tend to coincide with lower, or negative, comovement. This could be evidence of a flight-to-quality (or cross-market hedging) type of behavior. / <p>Diss. Stockholm : Handelshögskolan, 2007</p>

Cet article étudie la sensibilité des estimations de certaines variables explicatives de la croissance économique dans des régressions en coupe transversale sur un ensemble de pays. Il applique un modèle modifié de l’analyse de sensibilité de Leamer (1983, 1985). Mes résultats confirment la conclusion de Levine and Renelt (1992), toutefois, je montre que plus de variables sont solidement corrélées à la croissance économique. Entre 1990-2010, je trouve que huit sur vingt cinq variables ont des coefficients significatifs et sont solidement corrélées à la croissance de long terme, notamment, les parts de l’investissement et des dépenses étatiques dans le PIB, la primauté du droit et une variable dichotomique pour les pays subsahariens. Je trouve aussi une preuve empirique solide de l'hypothèse de la convergence conditionnelle, ce qui est cohérent avec le modèle de croissance néoclassique. / This paper examines the robustness of explanatory variables in cross-country growth regressions. It employs a variant of Leamer’s (1983, 1985) extreme-bounds analysis. My results confirm Levine and Renelt’s (1992) conclusion, but identify more variables to be robustly correlated with economic growth. Of 25 explanatory variables tested, I find 8 to be significantly and robustly correlated with long-term growth over the 1990-2010 period. The strongest evidence is for the investment ratio, government consumption share in GDP, the rule of law, and the Sub-Saharan dummy. I also find strong empirical evidence for conditional convergence, which is consistent with the neoclassical growth model.

Submitted by Kym Marcel Martins Ardison (kymmarcel@gmail.com) on 2015-04-06T19:04:20Z No. of bitstreams: 1 Tail Risk - Original.pdf: 817189 bytes, checksum: 02561a6a7cb94d1480a4f78933486df4 (MD5) / Approved for entry into archive by BRUNA BARROS (bruna.barros@fgv.br) on 2015-04-28T12:21:10Z (GMT) No. of bitstreams: 1 Tail Risk - Original.pdf: 817189 bytes, checksum: 02561a6a7cb94d1480a4f78933486df4 (MD5) / Approved for entry into archive by Marcia Bacha (marcia.bacha@fgv.br) on 2015-05-04T12:33:49Z (GMT) No. of bitstreams: 1 Tail Risk - Original.pdf: 817189 bytes, checksum: 02561a6a7cb94d1480a4f78933486df4 (MD5) / Made available in DSpace on 2015-05-04T12:37:02Z (GMT). No. of bitstreams: 1 Tail Risk - Original.pdf: 817189 bytes, checksum: 02561a6a7cb94d1480a4f78933486df4 (MD5) Previous issue date: 2015-02-12 / This paper proposes a new novel to calculate tail risks incorporating risk-neutral information without dependence on options data. Proceeding via a non parametric approach we derive a stochastic discount factor that correctly price a chosen panel of stocks returns. With the assumption that states probabilities are homogeneous we back out the risk neutral distribution and calculate five primitive tail risk measures, all extracted from this risk neutral probability. The final measure is than set as the first principal component of the preliminary measures. Using six Fama-French size and book to market portfolios to calculate our tail risk, we find that it has significant predictive power when forecasting market returns one month ahead, aggregate U.S. consumption and GDP one quarter ahead and also macroeconomic activity indexes. Conditional Fama-Macbeth two-pass cross-sectional regressions reveal that our factor present a positive risk premium when controlling for traditional factors.

Toppeffekter används av elnätsbolag för att dimensionera elnätet, vilket blir allt viktigare för varje år. Fler och fler invånare och företag ökar sin elkonsumtion och förväntar sig en driftsäker och stabil elförsörjning. Det finns två vanliga metoder att beräkna toppeffekter. Första sättet är Velanders formel som är en enkel metod för att uppskatta toppeffekter. Velanders formel behöver bara årsenergi och vetskap om kundkategori med tillhörande Velanderkonstanter för beräkning av uppskattad toppeffekt. Sedan finns den mer komplexa typkurvemetoden som behöver flera olika parametrar, t.ex. graddagtal, dygnsmedeltemperatur, gränssannolikhet och kundkategori. Detta examensarbete undersöker en enkel metod för att ta fram konstanter till Velanders formel för beräkning av toppeffekter. Detta genomfördes med hjälp av regressionsanalys av historiska elanvändningsdata från Mälarenergi Elnät AB:s (MEE) kunder från 12 olika kundkategorier. Detta på grund av att MEE önskade att utveckla en metod för att ta fram konstanter till Velanders formel baserad på historiska elanvändningsdata. Metoden för att ta fram konstanter till Velanders formel går ut på att med hjälp av MATLAB utföra en regressionsanalys på simulerade kundgrupper skapade från timvis historiska elanvändningsdata. En kurva baserad på Velanders formel tas sedan fram som beskriver den övre gränsen till toppeffekterna för de simulerade kundgrupperna. Från kurvan fås sedan de Velanderkonstanter som söks. Resultaten av den undersökta metoden presenteras i form av grafer och tabeller för tre utvalda kundkategorier. Alla kategorier och deras resultat finns som bilagor till rapporten. Valideringen av resultaten och metoden gjordes med hjälp av korsvalidering och jämförelse mot heterogena simulerade kundgrupper. Känslighetsanalysen visar att den undersökta metoden var känslig för flera faktorer såsom kategorisering av kunder, tidsspann för historiska elanvändningsdata, antal simulerade kundgrupper och kundantal. Med tillräcklig dimensionering av dessa faktorer bedömdes metoden vara användbar. Resultaten visade på att de framtagna Velanderkonstanterna gav en god uppskattning av toppeffekter för de kundkategorier som undersökts. Jämförelse av de uppskattade toppeffekterna och de observerade visade på att det fanns en viss differens mellan dem. Detta var dock förväntat eftersom de uppskattade toppeffekterna ska avspegla den övre toppeffektsgränsen. / This degree project has examined a simple method aiming to obtain coefficients for Velanders formula which purpose is to calculate peak loads. This was done by using regression analysis on historical data on consumption of electricity from 12 different customer categories acquired from Mälarenergi Elnät AB (MEE). The reason being that MEE wanted to examine a method which could obtain coefficients for Velanders formula based on hourly historical electricity consumption data. The method for obtaining Velander coefficients uses MATLAB to do regression analysis on simulated customer groups, created from hourly historical electricity consumption data. The Velander coefficients are then obtained from a regression curve based on Velanders formula. Results from the evaluation of the method is presented with the help of plots and tables for three chosen customer categories. Validation of the method was done by cross-validation and comparison against heterogeneous customer groups. Sensitivity analysis showed the examined method to be sensitive to several factors such as categorization of customers, the timespan of historical electricity consumption data, the number of simulated customer groups that were used and how many customers a category contained. By dimensioning these factors carefully, the method examined was assessed to be viable. The results indicated that the obtained Velander coefficients gave a good estimation of the peak loads for the chosen customer categories. Comparison between the estimated and observed peak loads indicated that there was a certain difference between them. This was to be expected since the estimated peak loads are to reflect the upper peak load limit.

No description available.

Dans cette thèse, nous introduisons des modèles de régression ”Gini-PLS”. Les algorithmes proposés combinent les propriétés des estimateurs relatifs aux régressions Gini et PLS. Les quatre modèles construits dans cette thèse permettent de résoudre simultanément les problèmes : de valeurs extrêmes (”outliers”), de multi-colinéarité, de faible taille de l’échantillon, de données manquantes, d’erreurs de mesure et d’endogénéité. En présence des problèmes cités, les modèles uni-variés (Gini-PLS1) sont robustes pour estimer une variable dépendante en fonction d’une ou plusieurs variables explicatives ; tandis que les modèles multi-variés (Gini-PLS2) servent à estimer une matrice de variables dépendantes en fonction d’une matrice de variables explicatives.Notre application dans le cadre de la thèse concerne l’estimation de contributions des variables technico-économiques aux inégalités des rémunérations pour les pays européens adhérents à la Politique Agricole Commune.Nous proposons deux approches de régressions basées sur les modèles Gini-PLS (RISD-Gini-PLS) pour estimer les contributions des variables technico-économiques (sources de revenus, superficies, main d’œuvre, etc.) aux inégalités des revenus agricoles pour les pays de l’union européenne avant et après les réformes de Mac Sharry et de l’accord de Luxembourg. / In this thesis we propose ”Gini-PLS” regressions. The proposed algorithms combine the properties of the estimators related to the Gini and PLS regressions. The four models built in this thesis solve simultaneously the problems of : extreme values (outliers), multicollinearity, small sample, missing data, measurement errors,and endogeneity. In presence of these problems, the univariate models (Gini-PLS1) are robust to estimate a dependent variable with one or more explanatory variables. While, the multivariate models (Gini-PLS2) are used to estimate a matrix of dependent variables with a matrix of explanatory variables.Our application in this thesis is the estimation of the contributions of technico-economic variables to the whole inequality of farm’s income for European countries acceding to the Common Agricultural Policy. We also propose Gini-PLS regressions approaches based on income source decomposition (RISD-Gini-PLS) to estimate the contributions of techno-economic variables (income sources, areas, labor, etc.) to the incomei nequalies of productions (total output crops and output livestock) for european countries.

Cette thèse porte sur l’étude des inégalités dans un cadre macroéconomique, d’un point de vue théorique ainsi qu’empirique. Dans un premier chapitre, j’écris et simule un modèle basé-agents capable de répliquer les distributions fat-tailed des richesses observées empiriquement dans les économies développées. Dans un second chapitre, je prolonge ce modèle théorique pour étudier l’impact économique des discriminations interpersonnelles et institutionnelles. Lorsque les discriminations institutionnelles cessent, l’état final des inégalités dépend de l’économie au moment de la fin de ces discriminations : plus l’économie est organisée, plus le temps nécessaire à une égalisation des revenus et richesses entre ethnies est long, voire infini. Dans un troisième chapitre empirique, j’étudie l’évolution des inégalités de salaire entre Noirs et Blancs aux États-Unis entre 1960 et 2015, en me concentrant sur la période 2000-2015. Je traite les biais de sélection liés à l’asymétrie raciale envers l’emprisonnement, et montre que l’écart - en conditionnant par l'âge et les diplômes - entre salaires médians des Noirs et des Blancs atteint un maximum en 2012. En utilisant la méthode de régression quantiles non-conditionnelles conjointement avec la décomposition de Blinder-Oaxaca, j’établis que la part non-expliquée de cet écart reste stable durant la Grande Récession. Enfin, dans une post-face, en utilisant les métadonnées de RePEC, j’établis que la part des articles scientifiques consacrés à l’étude des crises augmente significativement après 2008 pour 13 des 30 « top journals » en économie. / This PhD dissertation focuses on wealth and wage inequality, and the macro-economy. In a first chapter, I write and run a small macro agent-based model (M-ABM) in which I study the resultant distribution of wealth among households. I show that this model generates fat- tailed distributions of wealth in the household sector, as empirically observed in advanced economies. In a second chapter, I extend this model to study the macroeconomics of interpersonal and institutional discriminations against racial minorities. When discrimination is at work, racial disparities in income and wealth arise. The effect of the abolition of institutional discrimination is path-dependant: the more the economy is organized when this institutional change occurs, the more time it takes to get back to the counter-factual situation where no institutional discrimination was set up in the first place. In a third chapter, I study the evolution of the difference of median log-annual earnings between Blacks and Whites in the US between 1960 and 2015, focusing on the 2008 crisis. I control for selection arising from racial differentials in institutionalised population, and find that the unconditional racial wage gap attains a maximum in 2012. Controlling for age and education, I obtain the same result. Using unconditional quantile regressions, I show that the unexplained part of the unconditional racial wage gap has not increased during the crisis. Finally, in an afterword, I use metadata from RePEC to show that the share of economics papers published in the 13 of the 30 "top" journals containing "crisis" in their titles and/or abstracts has significantly increased in 2008.

Building new homes and oÿces are vital for the well-being in a country from both an economic sense and from a viewpoint that a growing population needs more housing. For construction companies to be able to meet their objectives, an important issue is the capital structure choice. The discussion of capital structure and company value became one of the most contentious areas in finance in the decades following the publication of the famous paper by Modigliani and Miller. Since then, there has been a lot of work exploring the optimal capital structure for firms in di˙erent situations, however the work has been rather limited in Sweden. This study tested the pecking order theory of capital structure on publicly traded Swedish construction firms between 1995 to 2019. The study had a focus on how well the pecking order theory can account for financial decisions made by Swedish construction firms through a series of tests. The purpose is to understand what factors are the most important, with regards to the capital structure, for listed firms in the Swedish construction industry. The result of the tests showed that the pecking order theory failed to outperform the conventional leverage model. Therefore, the study was unsuccessful in finding support for the hypothesis that the pecking order theory would be the dominant financial theory to explain capital structure decisions. / Att bygga nya bostäder och kontor är avgörande för välfärden i ett land ur både ekonomisk mening och ur en synvinkel att en växande befolkning behöver fler bostäder. För att byggföretag ska kunna nå sina mål är valet av kapitalstruktur en viktig fråga. Diskussionen om kapitalstruktur och företagsvärde blev ett av de mest debatterade områdena inom finansiell ekonomi under årtiondena efter den berömda publiceringen av Modigliani och Miller. Sedan dess har det gjorts mycket arbete med att utforska den optimala kapitalstrukturen för företag i olika situationer, däremot är forskningen något begränsat i Sverige. Denna studie testade pecking order teorin om kapitalstruktur hos börsnoterade svenska byggföretag mellan 1995 och 2019. Studien hade ett fokus på hur väl pecking order teorin kan förklara ekonomiska beslut som fattats av svenska byggföretag genom en serie av tester. Syftet är att förstå vilka faktorer som är de viktigaste med avseende på kapitalstrukturen för börsnoterade företag i den svenska byggbranschen. Resultatet av testerna visade att pecking order teorin inte överträ˙ade den konventionella modellen av finansiell hävstång. Därmed hittades inte stöd för hypotesen att pecking order teorin skulle vara den dominerande finansiella teorin för att förklara beslut av kapitalstruktur.

This research was geared towards the investigation of management strategies (factors) that affect the performance ofMSMEs in Kenya. Many developed countries record a time in history when entrepreneurial activities led to revival of economical growth after decline. This implies MSMEs is a very vital sector especially for a developing country like Kenya. MSMEs stagnate and their performance is uncertain according to writers such as Namusonge, Management inadequacies have been suggested in several studies. The objectives of this research was to, 1. To identifY the critical management factors affecting the performance of MSMEs in Kenya; ii. To establish the process through which managerial factors affect the performance of a MSMEs in Kenya ; m. To determine the integrative effect of various management factors in the MSMES in Kenya; IV. To establish the effect of demographics and management factors on performance, v. To establish effects of external environment on internal management factors A conceptual model was formulated from the literature review showing relationships of the management strategies and the environment they operate in. These relationships became the basis for the hypotheses which were later tested. In chapter 4, a mini research (pilot study) was conducted in May 2007,whose main aim was to test the reliability and validity of the research instruments. The 36 questionnaires returned were analysed through descriptive method. Results obtained indicated the instruments were reliable and the results valid. A few corrections suggested were made. The major correction was addition of question 35 to collect financial information. The data collection was done between mid August and mid October 2007.In chapter 5, the researcher analysesd the results of the survey after receiving 180 questionnaires. Time was a constraint. In chapter 6, the hypotheses and conceptual model were analysed and the results obtained suggested that, most strategies did not affect the profitability separately but severally. The integrated effect of the management strategies and the associated factors had a higher impact on performance of the MSMES than any individual strategies. In chapter 7, the conclusions, summaries and Recommendations are given. / Business Management / D. Com. (Business Management and Policy)

近幾年來，國人自殺死亡率不斷提高，且自殺死亡從1997年起已連續多年列於國人十大死亡原因之一，所以自殺防治工作刻不容緩。本研究採用自殺防治中心在桃園縣六家居家服務單位(龍祥、中國、仁愛、紅十字、家輔及寬福)所做之問卷調查資料，目的在於找出何種特性者，BSRS5 (The Five-Item Brief Symptom Rating Scale)分數及自殺意念分數可能較高。本研究屬於時序性追蹤資料，自民國96年5月份起，由居服人員針對受測對象進行訪談，大約每隔兩週收集一次，總共進行四次。 針對問卷進行基本敘述性統計、單項排名分析以及交叉分析後發現，在人口特質方面，男女性比例相當，年齡層主要皆在65~84歲，教育程度以不識字及國小為主；在BSRS5五題排名方面，以第一題「睡眠困難(難以入睡或早醒)」的平均分數最高，第四題「覺得比不上別人」平均分數最低；由交叉分析的結果發現身體狀況為一個重要的變數，身體狀況差的人BSRS5總分6分以上或自殺意念2分以上明顯較多。 對資料配適廣義估計方程式及Alternating Logistic Regressions的結果，發現在反應變數為BSRS5總分時，女性、身體狀況差及曾經看過精神科者BSRS5分數達到6分以上的可能性較高。若反應變數為自殺意念時，無論是利用廣義估計方程式或Alternating Logistic Regressions，從模型配適的結果發現只有BSRS5的效應顯著。不管利用BSRS5總分或是各題分開來看，BSRS5對自殺意念是一個相當有效的檢測工具，BSRS5分數愈高則自殺意念2分以上的機會也愈高。此外利用多層結構分析方法配適廣義估計方程式，針對BSRS5與受測次數間的關聯性分析，發現與配適傳統unstructured相關性矩陣的估計結果差異不大，但是可以減少許多參數估計，並且在電腦計算時間上是較快速的。 / In Taiwan, suicide has been among the top ten causes of death since 1997, and suicide prevention has thus attracted much attention since. Using the data provided by Taiwan Suicide Prevention Center (TSPC), this study is aimed to find out possible personal characteristics that might have some impacts on the BSRS5 (the Five-Item Brief Symptom Rating Scale) and suicide ideation scores The data come from a longitudinal study in which subjects from six elderly home service centers in Taoyuan County, Taiwan were visited four times between May and July, 2007, about two weeks between each visit. The total number of subjects is 1981. The proportions of male and female are nearly the same, the age range is from 65 to 84, and most of them have only an elementary school degree. Preliminary analyses indicate that among the five items in BSRS5, insomnia (the first item) is ranked the highest, and inferiority (the fourth item) is the lowest. In addition, health status is highly correlated to the BSRS5 and suicide ideation scores, the worse the health status, the higher the BSRS5 and suicide ideation scores. Fitting the data with Generalized Estimating Equation (GEE) and Alternating Logistic Regressions models with respect to the BSRS5 score, we further find that female, those who have bad health status, and those who have ever consulted a psychiatrist have higher probability that the BSRS5 score is greater than 6. As far as the suicide ideation score is concerned, the BSRS5 score is the only covariate that is statistically significant, an indication that BSRS5 is a useful tool for screening subjects at risk of committing suicide. While the conclusions stay the same whether the data are analyzed through GEE with commonly used unstructured correlation structure or newly developed multiblock and multilayer correlation structure, the latter approach reduces the computer time significantly.