131 |
Mixture time series models and their applications in volatility estimation and statistical arbitrage tradingCheng, Xixin., 程細辛. January 2008 (has links)
published_or_final_version / Statistics and Actuarial Science / Master / Master of Philosophy
|
132 |
台灣股票價格之變化與投資決策之研究林和本 Unknown Date (has links)
No description available.
|
133 |
台灣證券上市發行公司股票價格變動分析賴永華 Unknown Date (has links)
No description available.
|
134 |
Does Fundamental Analysis Lead to a Rudimentary Momentum Strategy for the Inexperienced Investor? Evidence from a Student Investment FundLillie, Nicholas J 01 January 2017 (has links)
Using the Student Investment Fund at Claremont McKenna College as a proxy for inexperienced investors, I demonstrate that inexperienced investors using fundamental analysis produce momentum-like buying patterns. The results show that the Student Investment Fund is on average buying stocks that outperform Carhart’s four-factor asset pricing model in the year before purchase. As a result, the Student Investment Fund has, on average, underperformed the S&P500 by .48% per year since 1996. My thesis explores why the Student Investment Fund may have adopted momentum-like purchasing patterns and what steps can be taken to remedy it.
|
135 |
The Gladiators of the OMXSPI : What are the key drivers trailing the durable performance?Cullhed, Jakob, Olsson, Fredrik January 2019 (has links)
Background and problem: The impact on the stock market of macroeconomic factors have been analyzed in several earlier studies. These are forces constantly changing and thereby they contribute to changing the supply and demand of stocks. The fact that macroeconomic variables have affected the top performing stocks of the OMXSPI during 2004 – 2018, in terms of performance, plays an important part of the study. Different authors have recognized different factors to affect the stock price development and there has not yet been established an explanation of the determinants of stock prices. Purpose: The purpose of the study was to identify the stocks that continuously have had a development superior to the OMXSPI, and therefore have contributed the most to the development of the OMXSPI during 2004 – 2018. Moreover, the study analyzes the drivers that have contributed to the performance of these stocks. Furthermore, the study clarifies which factors that have contributed to the development of the P/E and the EV/EBITDA of the top performers. Methodology: The study followed a quantitative and deductive approach. The Swedish stock market was analyzed with a focus on the OMXSPI were the top performing stocks of this index were identified through a screening process. Moreover, the top performers were put against the OMXSPI in different time periods to compare the performance. Furthermore, multiples of these top performers and the sectors which they trade in were calculated in order to compare the multiples to each other, with the purpose of analyzing them relative to each other in different time periods. Conclusion: From the findings it could be established very similar patterns between the top performers and the OMXSPI. The difference mainly being that the top performers in every sequence experienced a superior development than the OMXSPI, but also greater declines during short sequences. Moreover, the tables displayed remarkable returns of the top performers and the aggregated top performers traded at premium levels in all analyzed time periods.
|
136 |
Evaluating efficiency of ensemble classifiers in predicting the JSE all-share index attitudeRamsumar, Shaun January 2017 (has links)
A research report submitted to the Faculty of Commerce, Law and Management, University
of the Witwatersrand, Johannesburg, in partial fulfillment of the requirements for the degree
of Master of Management in Finance and Investment.
Johannesburg, 2016 / The prediction of stock price and index level in a financial market is an interesting
but highly complex and intricate topic. Advancements in prediction models leading
to even a slight increase in performance can be very profitable. The number of studies
investigating models in predicting actual levels of stocks and indices however, far
exceed those predicting the direction of stocks and indices. This study evaluates the
performance of ensemble prediction models in predicting the daily direction of the
JSE All-Share index. The ensemble prediction models are benchmarked against three
common prediction models in the domain of financial data prediction namely, support
vector machines, logistic regression and k-nearest neighbour. The results indicate that
the Boosted algorithm of the ensemble prediction model is able to predict the index
direction the best, followed by k-nearest neighbour, logistic regression and support
vector machines respectively. The study suggests that ensemble models be considered
in all stock price and index prediction applications. / MT2017
|
137 |
Modeling and forecasting stock return volatility in the JSE Securities ExchangeMasinga, Zamani Calvin January 2016 (has links)
Thesis (M.M. (Finance & Investment))--University of the Witwatersrand, Faculty of Commerce, Law and Management, Wits Business School, 2016 / Modeling and forecasting volatility is one of the crucial functions in various fields of financial engineering, especially in the quantitative risk management departments of banks and insurance companies. Forecasting volatility is a task of any analyst in the space of portfolio management, risk management and option pricing. In this study we examined different GARCH models in Johannesburg Stock Exchange (JSE) using univariate GARCH models (GARCH (1, 1), EGARCH (1, 1), GARCH-M (1, 1) GJR-GARCH (1, 1) and PGARCH (1, 1)).
Daily log-returns were used on JSE ALSH, Resource 20, Industrial 25 and Top 40 indices over a period of 12 years. Both symmetric and asymmetric models were examined. The results showed that GARCH (1, 1) model dominate other models both in-sample and out-of-sample in modeling the volatility clustering and leptokurtosis in financial data of JSE sectoral indices.
The results showed that the JSE All Share Index and all other indices studied here can be best modeled by GARCH (1, 1) and out-of-sample for JSE All Share index proved to be best for GARCH (1, 1). In forecasting out-of-sample EGARCH (1, 1) proved to outperformed other forecasting models based on different procedures for JSE All Share index and Top 40 but for Resource 20 RJR-GARCH (1, 1) is the best model and Industrial 25 data suggest PGARCH (1, 1) / DM2016
|
138 |
The stock market as a leading indicator of economic activity: time-series evidence from South AfricaSayed, Ayesha January 2016 (has links)
A 50% research report to be submitted in partial fulfilment for the degree of:
MASTER OF COMMERCE (FINANCE)
UNIVERSITY OF THE WITWATERSRAND / Several studies have assessed the forward-looking characteristic of share prices and confirmed their resultant capability as leading indicators of economic activity, especially in advanced economies. Contention however exists when evaluating the role of stock markets as leading indicators for less developed countries. This study examines the validity of the stock market as a leading indicator of economic activity in South Africa using quarterly time-series data for the period January 1992 to June 2014. Causality and cointegration between the JSE All Share Index against Real GDP and Real Industrial Production is evaluated by employing Granger-causality tests and the Johansen cointegration procedure. The empirical investigation indicates that unidirectional causality exists between the nominal and real stock indices and economic activity in South Africa, and confirms a long-run relationship between the JSE and GDP and Industrial Production. Therefore, similar to the study by Auret and Golding (2012), in a South African context, the stock market is in fact a leading indicator of economic activity. / MT2017
|
139 |
An in-depth validation of momentum as a dominant explanatory factor on the Johannesburg Stock ExchangePage, Moshe Daniel January 2017 (has links)
A thesis submitted to the Faculty of Commerce, Law and Management, University of the Witwatersrand, in fulfilment of the requirements for the degree of Doctor of Philosophy (Ph.D), September 2016 / This study considers momentum in share prices, per Jegadeesh and Titman (1993, 2001), on the cross-section of shares listed on the JSE. The key research objective is to define whether momentum is significant, independent and priced. ‘Significant’ implies that momentum produces significantly positive nominal and risk-adjusted profits, ‘independent’ means that momentum is independent of other non-momentum stylistic factor premiums and finally, ‘priced’ suggests that momentum is a priced factor on the JSE and thereby contributes to the cross-sectional variation in share returns. In order to determine the significance of the momentum premium on the JSE, univariate momentum sorts are conducted that consider variation in portfolio estimation and holding periods, weighting methodologies as well as liquidity constraints, price impact and microstructure effects. The results of the univariate sorts clearly indicate that momentum on the JSE is both significant and profitable assuming estimation and holding periods between three and twelve months. Furthermore, consistent with international and local literature, momentum profits reverse assuming holding periods in excess of 24 months. In order to determine whether momentum is independent, bivariate sorts and time-series attribution regressions are conducted using momentum and six non-momentum factors, namely: Size, Value, Liquidity, Market Beta, Idiosyncratic Risk and Currency Risk. The results of the bivariate sorts and time-series attribution regressions clearly indicate that momentum on the JSE is largely independent of the nonmomentum stylistic factors considered. Lastly, cross-sectional panel regressions are conducted where momentum is applied, in conjunction with the considered non-momentum factors, as an independent variable in order assess the relationship between the factors and expected returns on a share-by-share basis. The results of the panel data cross-sectional regressions clearly indicate that momentum produces a consistently significant and independent premium, conclusively proving that momentum is a priced factor that contributes to the cross-sectional variation in share returns listed on the JSE. / XL2018
|
140 |
The impact of mergers and acquisitions announcements on the share price performance of acquiring companies: South African listed companiesNdlovu, Mthabisi January 2017 (has links)
Thesis submitted in fulfilment of the requirements for the degree of
Master of Management in Finance & Investment
in the Faculty of Commerce, Law and Management Wits Business School at the University of the Witwatersrand
2017 / This thesis empirically examines the stock market reaction to mergers and acquisitions (M&A) announcements in South Africa, and also analyses the effects of the method payment. Data was collected from 34 acquisitions, consisting of acquirer and target companies in the same industry listed on the Johannesburg Stock Exchange, (JSE). The transactions were of mergers and acquisitions for the period 2003 – 2013. The event study methodology was used to calculate cumulative average abnormal returns for the acquiring companies over the total event window. Parametric t-tests were then applied to test the significance of the cumulative average abnormal returns, and a comparison of the pre and post-announcement returns was done over the event window. A comparison is also done for cash and share acquisitions over the entire event window (-10, +10). From the findings, it is clear that there were no significant abnormal returns or significant differences between the pre and post announcement returns. Comparing the two payment methods (cash and share payments), the results also show that there were no significant differences between these methods. The study therefore concluded that merger and acquisition announcements did not create any value for shareholders of acquiring companies during and around the announcement period. / MT2017
|
Page generated in 0.0324 seconds