Thesis (M.Com.)(Hons.) -- University of Western Sydney, Nepean, 1999. / Bibliography : p. [105-111].

Thesis (Ph. D.)--Columbia University, 1941. / Lithoprinted. Vita. Bibliography: p. 257-263.

Thesis (M.B.A.)--University of Hong Kong, 1995. / Includes bibliographical references.

Thesis (M.M.S.)--Carleton University, 1999. / Also available in electronic format on the Internet.

Στην παρούσα εργασία γίνεται μια ανασκόπηση της μεθόδου μέτρησης κινδύνου Value at Risk (VaR). Παρουσιάζουμε μερικούς βασικούς τρόπους μέτρησης του Value at Risk και εφαρμόζουμε σε δεδομένα ενός χαρτοφυλακίου συναλλαγματικών ισοτιμιών και στον γενικό δείκτη του χρηματιστηρίου Αθηνών διαφορετικά μοντέλα GARCH (IGARCH, TGARCH, EGARCH, GARCH) για την εκτίμηση του VaR με ορίζοντα μιας ημέρας (1- day ahead). Εφαρμόζουμε διαφορετικές υποθέσεις για την κατανομή των αποδόσεων (normal, student's-t, ged), χρησιμοποιούμε διαφορετικά μεγέθη δείγματος (250, 500, 750, 1000) και επίπεδα εμπιστοσύνης για το VaR (95% και 99%). Στην συνέχεια τα αποτελέσματα τού κάθε μοντέλου ελέγχονται με βάση τον έλεγχο του Kupiec για την καταλληλότητα τους. / In the present diplomatic essay we present a review of the method for risk measurement Value at Risk (VaR). We present a few basic ways of measuring Value at Risk and apply to data of an exchange rates portfolio and Athens stock exchange index different GARCH (IGARCH, TGARCH, EGARCH, GARCH) models for the estimation of the 1-day ahead VaR. We use various assumptions for the distribution of the returns (normal, student's-t, ged), various sample sizes (250, 500, 750, 1000) and VaR confidence levels (95% and 99%). Then the results of each model are tested using Kupiec test for their performance.

This diploma thesis deals with the comparison of equity and debt financing the development of the company according to pre-defined criteria such as cost, PR and marketing, debt and autonomy. Attention is also paid to the underpricing on the Czech capital market. The result of the work will assess the appropriate way of financing a particular company. It will also be calculated above underpricing the selected company on the basis of two selected methods.

This paper examines bubbles on the JSE All Share Index as well as the critical time of the stock market crash from 2/01/ 2004 – 27/03/2014. The underlying hypothesis define bubbles as extreme and begin as a group of small events which grow in a super exponential form explained by a log periodic power law model (LPPL model). The hypothesis is based on the assumption of investors’ herding behavior, where investors collude by making investment decision correlated with their counterparties. The paper implements a Savitzky Golary Algorithm to detect peaks and calculate the critical time of the crash from the peaks. An Ordinary Least Squares (OLS) method is used to determine both the value of stock market price index at the critical time and the increase in the stock market price index over the time before the crash. The remaining parameters of the LPPL model are estimated using a Maximum Likelihood Estimation method. On the empirical results; 68 peaks were detected, and the LPPL model at the critical crash time is estimated 34736.586. Five bubbles are detected; the 15/8/2005 bubble, 28/5/2013 bubble, 23/8/2013 bubble, 5/11/2013, and 1/20/2014.

This study analyses whether historically defensive sectors on the JSE have – with respect to the market – proven to be defensive during the recent global financial crisis. By withstanding the shocks of market volatility, defensive industries (such as pharmaceuticals and consumer staples) are renowned for their consistent performance throughout the business cycle. Using daily data for the period 2000–2009, the study compares the descriptive statistics of sector returns before and during the crisis. The volatility of each sector relative to the market index is calculated using the CAPM beta and a simplified volatility ratio. The same comparison is extended to the conditional volatilities of each of the sectors, which is estimated using the GARCH model and two of its extensions: the EGARCH and GJR GARCH models. While no sector experienced a positive mean return during the financial crisis, Healthcare, Consumer Goods, Consumer Services and Industrials all proved less volatile than the market. Surprisingly, Telecommunications proved more volatile than the market and experienced leverage effects during the financial crisis. Since the timing of a recession is difficult to predict, defensive securities were found to be a useful investment tool for protection against adverse movements in the stock market.

Este trabalho descreve o comportamento do Judiciário brasileiro com relação aos derivativos. Para tanto, exploramos decisões dos Tribunais de Justiça entre os anos de 2006 e 2010, conforme metodologia específica. Como suporte da pesquisa jurimétrica, analisamos os aspectos financeiros (utilidade e risco, espécies e estratégias, locais de negociação) e as características jurídicas (jogo e aposta, natureza contratual, valores mobiliários) dos derivativos. / This paper describes the position of the Brazilian courts on derivatives. For this purpose, we examine decisions rendered by the Courts of Appeals between the years of 2006 and 2010, in accordance with a specific methodology. As a foundation for jurimetrics research, we analyse the financial aspects (utility and risk, species and strategies, trade environment) and the legal characteristics (gambling, contractual nature, securities) of derivatives.

The aim of this work is to compare the rentability and risk of the shares and to find out which strategy would be the best to use to evaluate the money invested into selected companies from chosen branches of Paris stock exchange. The introduction of this work briefly describes the history, recent state and description of financial markets. In Czech conditions, this market is not suitable for similar comparison and analysis, therefore the analytic part of this work concentrates only on French stock exchange. Several statistic indicators are used for possible analysis of lucrativeness and risk rate (standard deviation, coefficient alpha, coefficient beta, variation coefficient), range of historical dates from the internet and other information. Historical dates, statistical markers, analysis and tests were used to establish and compare strategies used in investment in Paris stock exchange. Also used in the work are the findings of Czech and foreign authors who deal with the question. The aim of the practical part of this work is to put to use the theoretical knowledge and to find out which branches are best to invest into and vice-versa and which strategy to choose in order to make the most money or to loose as little money as possible.