We compare two time series models: an ARMA(1,1)-ACD(1,1)-NIG model against an ARMA(1,1)-GARCH(1,1)-NIG model. Their out-of-sample performance is of interest rather than their in-sample properties. The models produce one-day ahead forecasts which are evaluated using three statistical tests: VaR-test, VaRdur-test and Berkowitz-test. All three tests are concerned with the the tail events, since our time series models are often used to estimate downside risk. When the two models are applied to data on Canadian stock market returns, our three statistical tests point in the direction that the ACD model and the GARCH model perform similarly. The difference between the models is small. We finish with comments on the model uncertainty inherit in the comparison.

Thesis advisor: Pierluigi Balduzzi / This dissertation consists of two essays in empirical asset pricing. Chapter I, "Skewness and Co-skewness in Bond Returns," explores skewness and co-skewness in discrete-horizon bond returns. Using data for 1976-2005, we find bond skewness is comparable to that in equities, varies with the holding period and varies over time. Speculative-grade bonds and collateralized securities have substantial negative skewness. The sign of the price of co-skewness risk in fixed income market is in general consistent with the theoretical prediction of the three-moment CAPM. Co-skewness against the market portfolio is priced differently in various bond sectors: taking a unit of co-skewness risk is rewarded with 0.43% and 2.47% per month for corporate bonds and collateralized securities, respectively. Co-skewness risk helps explain the cross section of expected bond returns when state variables such as inflation, real activity, or short term interest rates are included, or when conditioning information is exploited. Chapter II, "Modern Portfolio Management with Conditioning Information," studies models in which active portfolio managers optimize performance relative to a benchmark and utilize conditioning information unavailable to their clients. We provide explicit solutions for the optimal strategies with multiple risky assets, with or without a risk free asset, and also consider various constraints on portfolio risk or on portfolio weights. The equilibrium implications of the models are discussed. A currency portfolio example shows that the optimal solutions improve the measured performance by 53% out of sample, compared with portfolios ignoring conditioning information. / Thesis (PhD) — Boston College, 2009. / Submitted to: Boston College. Carroll School of Management. / Discipline: Finance.

Yes / Researchers have recognized that the successive growth of mid-channel bar deposits can be entertained as the raison d’être for the initiation of the braiding process, which is closely interlinked with the growth, decay, and vertical distribution of fluvial turbulent kinetic energy (TKE). Thus, focused analysis on the underlying mechanics of turbulent flow structures in the proximity of a bar deposit occurring in the middle of the channel can afford crucial scientific clues for insight into the initiating fluvial processes that give rise to braiding. In the study reported herein, a physical model of a mid-channel bar is constructed in an experimental flume to analyze the turbulence parameters in a region close to the bar. Notably, the flow velocity plays an important role in understanding the flow behavior in the scour-hole location in the upstream flow divergence zone as well as near the downstream zone of flow convergence in a mid-channel bar. Therefore, the fluctuating components of turbulent flow velocity are herein discussed and analyzed for the regions located close to the bar. In the present study, the impact of the mid-channel bar, as well as its growth in turbulent flow, on higher-order velocity fluctuation moments are investigated. For near-bed locations, the results show the dominance of ejection events in upstream zones and the dominance of sweep events at locations downstream of the mid-channel bar. In scour-hole sections, the negative value of the stream-wise flux of turbulent kinetic energy and the positive value of the vertical flux of turbulent kinetic energy indicate energy transport in downward and forward directions, respectively. The downward and forward energy transport processes lead to scouring at these locations. The maximum turbulent production rate occurs in the wake region of the bar. The high rate of turbulence production has occurred in that region, which can be ascribed to the process of shedding turbulent vortices. The results show that the impact of the presence of the bar is mainly restricted to the lower layers of flow. The turbulent dissipation rate monotonically decreases with an increase in the vertical distance from the bed. The turbulent production rate first increases and then decreases with successive increases in the vertical distance from the bed. The paper concludes with suggestions for the future potential use of the present research for the practical purpose of examining braid bar occurrences in alluvial rivers to develop an appropriate response through training measures

Die auf Markowitz (1952) zurückgehende Portfoliotheorie ist ohne jeden Zweifel ein bedeutender Themenbereich der modernen finanzwirtschaftlichen Forschung. Zentral beschäftigt sich dieser Bereich mit der Frage, wie ein Anleger sein Vermögen auf unterschiedliche Anlagewerte verteilen soll. Als Ergebnis stellt sich ein optimales Verhältnis aus Rendite und Risiko heraus, wobei das Risiko ausschließlich durch die Varianz der Portfoliorendite erfasst wird. Konkrete Anwendungen dieses Konzeptes erzielen jedoch aufgrund von Schätzfehlern und Stationaritätsannahmen bei der Erwartungsbildung enttäuschende Resultate, speziell im Vergleich zu passiven Anlagestrategien. Die vorliegende Arbeit greift nun beide Aspekte parallel auf. Zum einem werden neben der Varianz auch weitere höhere Momente der Portfoliorenditeverteilung in der optimalen Asset Allokation berücksichtigt, zum anderen werden an Stelle von historischen Renditezeitreihen implizite Informationen aus dem Optionsmarkt für die Erwartungsbildung genutzt. Die Arbeit leistet hierzu methodische, theoretische und empirische Beiträge. Es wird aufgezeigt, wie implizite Informationen in der Asset Allokation mit höheren Momenten zur Anwendung kommen und, im Rahmen von umfangreichen empirischen Studien, dass im Vergleich zur Erwartungsbildung auf Basis historischer Renditezeitreihen implizite Informationen in der Asset Allokation vorzuziehen sind.

Pas de résumé / No summary

This thesis studies the role of higher moments, that is moments behind mean and variance, in continuous-time, or diffusion, processes, which are commonly used to model so-called high-frequency data. Thereby, the first part is devoted to the derivation of closed-form expression of general (un)conditional (co)moment formulas of the famous CIR process’s solution. A byproduct of this derivation will be a novel way of proving that the process’s transition density is a noncentral chi-square distribution and that its steady-state law is a Gamma distribution. In the second part, we use these moment formulas to derive a near-exact simulation algorithm to the Heston model, in the sense that our algorithm generates pseudo-random numbers that have the same first four moments as the theoretical diffusion process. We will conduct several in-depth Monte Carlo studies to determine which existing simulation algorithm performs best with respect to these higher moments under certain circumstances. We will conduct the same study for the CIR process, which serves as a diffusion for the latent spot variance in the Heston model. The third part discusses several estimation approaches to the Heston model based on high-frequency data, such as MM, GMM, and (pseudo/quasi) ML. For the GMM approach, we will use the moments derived in the first part as moment conditions. We apply the best methodology to actual high-frequency price series of cryptocurrencies and FIAT stocks to provide benchmark parameter estimates. / Die vorliegende Arbeit untersucht die Rolle von höheren Momenten, also Momente, welche über den Erwartungswert und die Varianz hinausgehen, im Kontext von zeitstetigen Zeitreihenmodellen. Solche Diffusionsprozesse werden häufig genutzt, um sogenannte Hochfrequenzdaten zu beschreiben. Teil 1 der Arbeit beschäftigt sich mit der Herleitung von allgemeinen und in geschlossener Form verfügbaren Ausdrücken der (un)bedingten (Ko-)Momente der Lösung zum CIR-Prozess. Mittels dieser Formeln wird auf einem alternativen Weg bewiesen, dass die Übergangsdichte dieses Prozesses mithilfe einer nichtzentralen Chi-Quadrat-Verteilung beschrieben werden kann, und dass seine stationäre Verteilung einer Gamma-Verteilung entspricht. Im zweiten Teil werden die zuvor entwickelten Ausdrücke genutzt, um einen nahezu exakten Simulationsalgorithmus für das Hestonmodell herzuleiten. Dieser Algorithmus ist in dem Sinne nahezu exakt, dass er Pseudo-Zufallszahlen generiert, welche die gleichen ersten vier Momente besitzen, wie der dem Hestonmodell zugrundeliegende Diffusionsprozess. Ferner werden Monte-Carlo-Studien durchgeführt, die ergründen sollen, welche bereits existierenden Simulationsalgorithmen in Hinblick auf die ersten vier Momente die besten Ergebnisse liefern. Die gleiche Studie wird außerdem für die Simulation des CIR-Prozesses durchgeführt, welcher im Hestonmodell als Diffusion für die latente, instantane Varianz dient. Im dritten Teil werden mehrere Schätzverfahren für das Hestonmodell, wie das MM-, GMM und pseudo- beziehungsweise quasi-ML-Verfahren, diskutiert. Diese werden unter Benutzung von Hochfrequenzdaten studiert. Für das GMM-Verfahren dienen die hergeleiteten Momente aus dem ersten Teil der Arbeit als Momentebedingungen. Um ferner Schätzwerte für das Hestonmodell zu finden, werden die besten Verfahren auf Hochfrequenzmarktdaten von Kryptowährungen, sowie hochliquider Aktientitel angewandt. Diese sollen zukünftig als Orientierungswerte dienen.

Submitted by Pablo F. Oliveira (pablo.perque@gmail.com) on 2012-02-29T12:36:59Z No. of bitstreams: 1 Dissertacao - Pablo Frisanco Oliveira -final.pdf: 1039827 bytes, checksum: 63d8e3ff3c6593d9ef449829e78e77c1 (MD5) / Approved for entry into archive by Gisele Isaura Hannickel (gisele.hannickel@fgv.br) on 2012-02-29T12:45:22Z (GMT) No. of bitstreams: 1 Dissertacao - Pablo Frisanco Oliveira -final.pdf: 1039827 bytes, checksum: 63d8e3ff3c6593d9ef449829e78e77c1 (MD5) / Made available in DSpace on 2012-02-29T12:55:43Z (GMT). No. of bitstreams: 1 Dissertacao - Pablo Frisanco Oliveira -final.pdf: 1039827 bytes, checksum: 63d8e3ff3c6593d9ef449829e78e77c1 (MD5) Previous issue date: 2012-01-30 / The aim of the present work is verify if, when the higher moments (skewness and kurtosis) are taken in consideration for carry trade portfolio allocation optimization, an investor can be better off than the traditional allocation, which prioritizes only the first two moments (mean and variance). The hypothesis of the research is that a carry trade currency exhibits non-Normal returns distribution, and its higher moments have a dynamic which can be modeled by GARCH-type model, in this specific case IC-GARCHSK. This model consists of one equation to each of the independent components’ conditional moments, named the returns, variance, the skewness, and the kurtosis. Another hypothesis is that a CARA (constant absolute risk aversion) utility function investor can have its function approximated by 4th order Taylor expansion. The work’s strategy is modelling the dynamics of the daily log-returns series’ moments of some carry trade currencies using the model above and dynamically estimate the optimal allocation which maximizes the investor’s expected utility function. The results show that the investor can benefit from taking in consideration the series’ higher moments, once this portfolio exhibited smaller opportunity cost than one that uses only mean and variance as criteria. / O objetivo do presente trabalho é verificar se, ao levar-se em consideração momentos de ordem superior (assimetria e curtose) na alocação de uma carteira de carry trade, há ganhos em relação à alocação tradicional que prioriza somente os dois primeiros momentos (média e variância). A hipótese da pesquisa é que moedas de carry trade apresentam retornos com distribuição não-Normal, e os momentos de ordem superior desta têm uma dinâmica, a qual pode ser modelada através de um modelo da família GARCH, neste caso IC-GARCHSK. Este modelo consiste em uma equação para cada momento condicional dos componentes independentes, explicitamente: o retorno, a variância, a assimetria, e a curtose. Outra hipótese é que um investidor com uma função utilidade do tipo CARA (constant absolute risk aversion), pode tê-la aproximada por uma expansão de Taylor de 4ª ordem. A estratégia do trabalho é modelar a dinâmica dos momentos da série dos logartimos neperianos dos retornos diários de algumas moedas de carry trade através do modelo IC-GARCHSK, e estimar a alocação ótima da carteira dinamicamente, de tal forma que se maximize a função utilidade do investidor. Os resultados mostram que há ganhos sim, ao levar-se em consideração os momentos de ordem superior, uma vez que o custo de oportunidade desta foi menor que o de uma carteira construída somente utilizando como critérios média e variância.