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Published: 10 December 2022
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1

Kwan, Wai-ching Josephine. "Trend models for price movements in financial markets /." [Hong Kong] : University of Hong Kong, 1994. http://sunzi.lib.hku.hk/hkuto/record.jsp?B13841397.

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2

Yiu, Fu-keung. "Time series analysis of financial index /." Hong Kong : University of Hong Kong, 1996. http://sunzi.lib.hku.hk/hkuto/record.jsp?B18003047.

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3

Shan, Yaowen School of Banking &amp finance UNSW. "Analysts' forecasts and future stock return volatility: a firm-level analysis for NYSE Firms." Awarded by:University of New South Wales. School of Banking & finance, 2006. http://handle.unsw.edu.au/1959.4/26963.

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This study demonstrates that financial analysts significantly affect short-term stock prices, by examining how non-accounting information particularly contained in analysts' forecasts contributes to the fluctuation of future stock returns. If current non-accounting information of future earnings is more unfavourable or more volatile, we could observe a larger shift in the current stock return. The empirical evidence strongly supports these theoretical predictions that stem from the combination of the accounting version of Campbell-Shiller model (Campbell and Shiller (1988) and Vuolteenaho (2002)) and Ohlson????s information dynamics (1995). In addition, the results are also valid for measures of both systematic and idiosyncratic volatilities.
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4

Rank, Christian. "Forecasting stock price movements using neural networks." Master's thesis, University of Cape Town, 2006. http://hdl.handle.net/11427/4392.

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Includes bibliographical references (p. 99-101).
The prediction of security prices has shown to be one of the most important but most difficult tasks in financial operations. Linear approaches failed to model the non-linear behaviour of markets and non-linear approaches turned out to posses too many constraints. Neural networks seem to be a suitable method to overcome these problems since they provide algorithms which process large sets of data from a non-linear context and yield thorough results. The first problem addressed by this research paper is the applicability of neural networks with respect to markets as a tool for pattern recognition. It will be shown that markets posses the necessary requirements for the use of neural networks, i.e. markets show patterns which are exploitable.
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5

Zhang, Yuzhao. "Essays on return predictability and volatility estimation." Diss., Restricted to subscribing institutions, 2008. http://proquest.umi.com/pqdweb?did=1666139151&sid=3&Fmt=2&clientId=1564&RQT=309&VName=PQD.

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6

Zhang, Shaorong. "Essays on security issuance /." free to MU campus, to others for purchase, 2004. http://wwwlib.umi.com/cr/mo/fullcit?p3144472.

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7

Rangel, Jose Gonzalo. "Stock market volatility and price discovery three essays on the effect of macroeconomic information /." Connect to a 24 p. preview or request complete full text in PDF format. Access restricted to UC campuses, 2006. http://wwwlib.umi.com/cr/ucsd/fullcit?p3220417.

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Thesis (Ph. D.)--University of California, San Diego, 2006.
Title from first page of PDF file (viewed September 7, 2006). Available via ProQuest Digital Dissertations. Vita. Includes bibliographical references (p. 125-130).
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8

Chen, Gary. "Behavioural heterogeneity in ASX 200 a dissertation submitted to Auckland University of Technology in fulfilment of the requirements for the degree of Master of Business (MBus), 2009 /." Click here to access this resource online, 2009. http://hdl.handle.net/10292/758.

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9

Fodor, Bryan D. "The effect of macroeconomic variables on the pricing of common stock under trending market conditions." Thesis, Department of Business Administration, University of New Brunswick, 2003. http://hdl.handle.net/1882/49.

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Thesis (MBA) -- University of New Brunswick, Faculty of Administration, 2003.
Typescript. Bibliography: leaves 83-84. Also available online through University of New Brunswick, UNB Electronic Theses & Dissertations.
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10

Woodgate, Artemiza. "The impact of earnings management on price momentum /." Thesis, Connect to this title online; UW restricted, 2007. http://hdl.handle.net/1773/8755.

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11

Mathew, Prem George. "Long-horizon event study methodology and seasoned equity offering performance in the Pacific Rim financial markets /." free to MU campus, to others for purchase, 1999. http://wwwlib.umi.com/cr/mo/fullcit?p9953880.

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12

Chavarnakul, Thira. "The development of hybrid intelligent systems for technical analysis based equivolume charting." Diss., Rolla, Mo. : University of Missouri-Rolla, 2007. http://scholarsmine.umr.edu/thesis/pdf/Thira_Chavarnakul_Dissertation_2007_09007dcc803425db.pdf.

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Thesis (Ph. D.)--University of Missouri--Rolla, 2007.
Vita. The entire thesis text is included in file. Title from title screen of thesis/dissertation PDF file (viewed October 25, 2007) Includes bibliographical references.
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13

Law, Ka-chung, and 羅家聰. "A comparison of volatility predictions in the HK stock market." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 1999. http://hub.hku.hk/bib/B30163535.

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14

關惠貞 and Wai-ching Josephine Kwan. "Trend models for price movements in financial markets." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 1994. http://hub.hku.hk/bib/B31211513.

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15

Lin, Gang. "Nesting regime-switching GARCH models and stock market volatility, returns and the business cycle /." Diss., Connect to a 24 p. preview or request complete full text in PDF format. Access restricted to UC campuses, 1998. http://wwwlib.umi.com/cr/ucsd/fullcit?p9906497.

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16

Tsakou, Katina. "Essays on financial volatility forecasting." Thesis, University of Stirling, 2016. http://hdl.handle.net/1893/25403.

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The accurate estimation and forecasting of volatility is of utmost importance for anyone who participates in the financial market as it affects the whole financial system and, consequently, the whole economy. It has been a popular subject of research with no general conclusion as to which model provides the most accurate forecasts. This thesis enters the ongoing debate by assessing and comparing the forecasting performance of popular volatility models. Moreover, the role of key parameters of volatility is evaluated in improving the forecast accuracy of the models. For these purposes a number of US and European stock indices is used. The main contributions are four. First, I find that implied volatility can be per se forecasted and combining the information of implied volatility and GARCH models predict better the future volatility. Second, the GARCH class of models are superior to the stochastic volatility models in forecasting the one-, five- and twenty two-days ahead volatility. Third, when the realised volatility is modelled and forecast directly using time series, I find that the HAR model performs better than the ARFIMA. Finally, I find that the leverage effect and implied volatility significantly improve the fit and forecasting performance of all the models.
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17

Cheng, Xin. "Three essays on volatility forecasting." HKBU Institutional Repository, 2010. http://repository.hkbu.edu.hk/etd_ra/1183.

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18

Kot, Hung Wan. "Two essays in empirical finance /." View abstract or full-text, 2004. http://library.ust.hk/cgi/db/thesis.pl?FINA%202004%20KOT.

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19

Wong, Chun-mei May. "The statistical tests on mean reversion properties in financial markets /." [Hong Kong : University of Hong Kong], 1994. http://sunzi.lib.hku.hk/hkuto/record.jsp?B13705568.

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20

Hansen, Patrik, and Sandi Vojcic. "Stock Market Forecasting Using SVM With Price and News Analysis." Thesis, KTH, Skolan för elektroteknik och datavetenskap (EECS), 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-293854.

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Many machine learning approaches have been usedfor financial forecasting to estimate stock trends in the future. Thefocus of this project is to implement a Support Vector Machinewith price and news analysis for companies within the technologysector as inputs to predict if the price of the stock is going torise or fall in the coming days and to observe the impact on theprediction accuracy by adding news to the technical analysis.The price analysis is compiled of 9 different financial indicatorsused to indicate changes in price, and the news analysis uses thebag-of-words method to rate headlines as positive or negative.There is a slight indication of the news improving the resultsif the validation data is randomly sampled the testing accuracyincreases. When testing on the last fifth of the data of eachcompany, there was only a small difference in the results whenadding news to the calculation and such no clear correlation canbe seen. The resulting program has a mean and median testingaccuracy over 50 % for almost all settings. Complications whenusing SVM for the purpose of price forecasting in the stockmarket is also discussed.
Många metoder för maskininlärning har använts i syfte av finansiell prognos för att uppskatta aktie trender i framtiden. Fokus för detta projekt är att implementera en Support Vector Machine med pris- och nyhetsanalys för företag inom teknologisektorn som inmatning för att förutsäga om priset på aktien kommer att öka eller minska under de kommande dagarna och för att observera påverkan på förutsägelsens noggrannhet av att lägga till nyheter till den tekniska analysen. Prisanalysen består av 9 olika finansiella indikatorer som används för att indikera prisändringar, och nyhetsanalysen använder metoden bag-of-word för att betygsätta rubriker som positiva eller negativa. Det finns en liten indikation på att nyheterna förbättrar resultat där om valideringsdata stickas ur slumpmässigt provningsnoggrannheten ökar. När man testade den sista femte delen av inmatningsdatan från varje företag, fanns det bara en liten skillnad i resultaten när nyheterna beräknades vilket leder till att en tydlig korrelation kan inte ses. Det resulterande programmet har en genomsnittlig och median test nogrannhet över 50 % för nästan alla inställningar. Komplikationer när SVM används för prisprognoser på aktiemarknaden diskuteras också.
Kandidatexjobb i elektroteknik 2020, KTH, Stockholm
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21

Elsegai, Heba. "Network inference and data-based modelling with applications to stock market time series." Thesis, University of Aberdeen, 2015. http://digitool.abdn.ac.uk:80/webclient/DeliveryManager?pid=228017.

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The inference of causal relationships between stock markets constitutes a major research topic in the field of financial time series analysis. A successful reconstruction of the underlying causality structure represents an important step towards the overall aim of improving stock market price forecasting. In this thesis, I utilise the concept of Granger-causality for the identification of causal relationships. One major challenge is the possible presence of latent variables that affect the measured components. An instantaneous interaction can arise in the inferred network of stock market relationships either spuriously due to the existence of a latent confounder or truly as a result of hidden agreements between market players. I investigate the implications of such a scenario; proposing a new method that allows for the first time to distinguish between instantaneous interactions caused by a latent confounder and those resulting from hidden agreements. Another challenge is the implicit assumption of existing Granger-causality analysis techniques that the interactions have a time delay either equal to or a multiple of the observed data. Two sub-cases of this scenario are discussed: (i) when the collected data is simultaneously recorded, (ii) when the collected data is non-simultaneously recorded. I propose two modified approaches based on time series shifting that provide correct inferences of the complete causal interaction structure. To investigate the performance of the above mentioned method improvements in predictions, I present a modified version of the building block model for modelling stock prices allowing causality structure between stock prices to be modelled. To assess the forecasting ability of the extended model, I compare predictions resulting from network reconstruction methods developed throughout this thesis to predictions made based on standard correlation analysis using stock market data. The findings show that predictions based on the developed methods provide more accurate forecasts than predictions resulting from correlation analysis.
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22

Hassan, Mahamood Mahomed. "Testing the pricing and informational efficiency of the S&P 500 stock index futures market." Diss., The University of Arizona, 1989. http://hdl.handle.net/10150/184858.

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Three empirical studies are conducted examining the efficiency of S&P 500 futures prices and the pricing of these futures contracts. In the first study, the ability of futures prices to predict the realized spot S&P 500 index prices on the expiration date is examined for near term contracts. The futures prices are found to be unbiased predictors of the realized spot index prices for the nineteen quarterly contracts from 1982 to 1986. Previous studies report significant deviations in S&P SOO futures prices from theoretically determined Cost of Carry Model (CCM) prices. In the second study, it is found that the CCM using the federal funds rate, a proxy for the overnight repurchase rate, provides relatively better estimates of the S&P S(x) futures prices over the 1984-1986 period. The futures mispricing also reflects the weekend effect anomaly: futures prices are "over-priced" relative to CCM prices on Mondays, whereas the opposite occurs on Fridays. The futures over-pricing (under-pricing) is characterized by "bull" ("bear") financial markets and the extent of price changes are relatively greater in the futures market. The futures under-pricing is supported by strong future market volume and open-interest positions. The basis and changes in it over the futures contract period are measures of how well integrated the futures market and the underlying spot market are. In the third study, based on daily closing prices for the S&P 500 index and index futures for the 1984-1986 period, it is found that the basis decreases over the contract period but the rate of decrease is independent of the time to expiration. The change in basis on Mondays is generally positive which also reflects the weekend effect anomaly. The daily basis is negative on 107 days, which generally occurs during strong futures market trading volume and open interest positions. It is doubtful whether the negative basis can be attributed to a negative net financing cost, where the dividend yield 0.1 the spot index exceeds the cost of financing the spot index forward.
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23

Scott, Laurie Croslin Zeng Yong. "Bayesian inference via filtering of micro-movement multivariate stock price models with discrete noises." Diss., UMK access, 2006.

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Thesis (Ph. D.)--Dept. of Mathematics and Statistics and Dept. of Economics. University of Missouri--Kansas City, 2006.
"A dissertation in mathematics and economics." Advisor: Yong Zeng. Typescript. Vita. Title from "catalog record" of the print edition Description based on contents viewed Jan. 29, 2007. Includes bibliographical references (leaves 121-124). Online version of the print edition.
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24

Wu, Ruojun. "Essays on the predictability and volatility of returns in the stock market." Diss., Connect to a 24 p. preview or request complete full text in PDF format. Access restricted to UC campuses, 2008. http://wwwlib.umi.com/cr/ucsd/fullcit?p3316421.

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Thesis (Ph. D.)--University of California, San Diego, 2008.
Title from first page of PDF file (viewed Sept. 4, 2008). Available via ProQuest Digital Dissertations. Vita. Includes bibliographical references (p. 127-132).
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25

Gropp, Jeffrey. "Mean reversion in U.S. stock prices a panel approach /." Morgantown, W. Va. : [West Virginia University Libraries], 2000. http://etd.wvu.edu/templates/showETD.cfm?recnum=1357.

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Thesis (Ph. D.)--West Virginia University, 2000.
Title from document title page. Document formatted into pages; contains vii, 160 p. : ill. (some col.) Includes abstract. Includes bibliographical references (p. 154-160).
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26

Ma, Chin-wan Raymond. "A study on the beta coefficients of securities in Hong Kong." Click to view the E-thesis via HKUTO, 1989. http://sunzi.lib.hku.hk/hkuto/record/B31976050.

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27

Yiu, Fu-keung, and 饒富強. "Time series analysis of financial index." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 1996. http://hub.hku.hk/bib/B31267804.

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28

Shapiro, Adam. "Jim Cramer's Mad Money effects on stock returns /." Diss., Connect to the thesis, 2006. http://hdl.handle.net/10066/588.

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29

Aziz, Tariq. "Essays in empirical finance." Thesis, University of Aberdeen, 2016. http://digitool.abdn.ac.uk:80/webclient/DeliveryManager?pid=230103.

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This PhD dissertation research primarily aims to empirically investigate into two financial topics using annual and monthly data sets of market-capitalization based size portfolio returns from the US stock market for the period 1925 to 2012. Using size-based portfolio returns is a pioneering effort for both topics. The first empirical research using annual data is on short and long horizon stock return predictability using three widely selected ratios in terms of price-output, price-earnings and price-dividend. Using univariate and multivariate predictive regressions for horizons from one year to fifteen years for the full sample and three different sub-samples for comparison reasons with the previous research using aggregate stock market data, it is reported that both short and long horizon return predictability exists albeit with different predictive ability for different horizons. Among the three selected ratios, overall the price-output ratio is empirically favoured as a superior predictor of stock returns. The empirical findings refer to that this is robust across the three sub-samples investigated. It is empirically shown that size significantly matters in terms of return predictability. The second empirical research using monthly data is on the analysis of impact of macroeconomic volatility in terms of inflation and industrial production growth on asymmetric time-varying volatility of stock returns. Using a two-stage econometric methodology, first, based on estimation of asymmetric conditional volatilities of stock returns and macroeconomic variables, and then employing a vector autoregression methodology; it is reported that volatility of size-based portfolio returns are, in general, not significantly dependent on macroeconomic volatility. It is also shown that stock return volatility is more responsive to its own previous shocks as shown by the variance decomposition. It is also found that size does not matter in this specific case.
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30

Chen, Ching-peng. "The implications of earnings quality for market reactions to annual earnings announcements." Thesis, University of British Columbia, 1989. http://hdl.handle.net/2429/42009.

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This paper assesses the impact of earnings quality on market responses to annual earnings announcements. Earnings quality is measured by the ratio of earnings to funds from operations. The difference in the association between forecast errors and excess returns across the high/low quality earnings subsamples is found to be statistically significant; there is a greater market response to earnings announcements of high-quality firms than to low-quality firms. Hence, earnings quality as measured by the ratio of earnings to funds from operations, is found to have pricing implications. The results are robust across two regression models: OLS on returns ordered in announcement time and SUR/GLS on returns ordered in calendar time.
Business, Sauder School of
Graduate
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31

Lu, Qunfang Flora. "Bayesian forecasting of stock prices via the Ohlson model." Link to electronic thesis, 2005. http://www.wpi.edu/Pubs/ETD/Available/etd-050605-155155/.

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32

Venter, Rudolf Gerrit. "Pricing options under stochastic volatility." Diss., Pretoria : [s.n.], 2003. http://upetd.up.ac.za/thesis/available/etd09052005-120952.

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33

Lidén, Erik. "Essays on information and conflicts of interest in stock recommendations." Göteborg : Dept. of Economics, School of Economics and commercial law, Göteborg University, 2005. http://www.handels.gu.se/epc/archive/00004063/01/Liden_avhandl.pdf.

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34

Kışınbay, Turgut. "Predictive ability or data snopping? : essays on forecasting with large data sets." Thesis, McGill University, 2004. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=85018.

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This thesis examines the predictive ability of models for forecasting inflation and financial market volatility. Emphasis is put on evaluation of forecasts and the usage of large data sets. Variety of models are used to forecast inflation, including diffusion indices, artificial neural networks, and traditional linear regressions. Financial market volatility is forecast using various GARCH-type and high-frequency based models. High-frequency data are also used to obtain ex-post estimates of volatility, which is then used to evaluate forecasts. All forecast are evaluated using recently proposed techniques that can account for data snooping bias, nested, and nonlinear models.
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35

Ma, Chin-wan Raymond, and 馬展雲. "A study on the beta coefficients of securities in Hong Kong." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 1989. http://hub.hku.hk/bib/B31976050.

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36

Coetzee, G. J. "A comparison of the Philips price earnings multiple model and the actual future price earnings multiple of selected companies listed on the Johannesburg stock exchange." Thesis, Stellenbosch : Stellenbosch University, 2000. http://hdl.handle.net/10019.1/51561.

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Thesis (MBA)--Stellenbosch University, 2000.
ENGLISH ABSTRACT: The price earnings multiple is a ratio of valuation and is published widely in the media as a comparative instrument of investment decisions. It is used to compare company valuation levels and their future growth/franchise opportunities. There have been numerous research studies done on the price earnings multiple, but no study has been able to design or derive a model to successfully predict the future price earnings multiple where the current stock price and following year-end earnings per share is used. The most widely accepted method of share valuation is to discount the future cash flows by an appropriate discount rate. Popular and widely used stock valuation models are the Dividend Discount Model and the Gordon Model. Both these models assume that future dividends are cash flows to the shareholder. Thomas K. Philips, the chief investment officer at Paradigm Asset Management in New York, constructed a valuation model at the end of 1999, which he published in The Journal of Portfolio Management. The model (Philips price earnings multiple model) was derived from the Dividend Discount Model and calculates an implied future price earnings multiple. The Philips price earnings multiple model includes the following independent variables: the cost of equity, the return on equity and the dividend payout ratio. Each variable in the Philips price earnings multiple model is a calculated present year-end point value, which was used to calculate the implied future price earnings multiple (present year stock price divided by following year-end earnings per share). This study used a historical five year (1995-2000) year-end data to calculate the implied and actual future price earnings multiple. Out of 225, Johannesburg Stock Exchange listed companies studied, only 36 were able to meet the criteria of the Philips price earnings multiple model. Correlation and population mean tests were conducted on the implied and constructed data sets. It proved that the Philips price earnings multiple model was unsuccesful in predicting the future price earnings multiple, at a statistical 0,20 level of significance. The Philips price earnings multiple model is substantially more complex than the Discount Dividend Model and includes greater restrictions and more assumptions. The Philips price earnings multiple model is a theoretical instrument which can be used to analyse hypothetical (with all model assumptions and restrictions having been met) companies. The Philips price earnings multiple model thus has little to no applicability in the practical valuation of stock price on Johannesburg Stock Exchange listed companies.
AFRIKAANSE OPSOMMING: Die prysverdienste verhouding is 'n waarde bepalingsverhouding en word geredelik gepubliseer in die media. Hierdie verhouding is 'n maatstaf om maatskappye se waarde vlakke te vergelyk en om toekomstige groei geleenthede te evalueer. Daar was al verskeie navorsingstudies gewy aan die prysverdiensteverhouding, maar nog geen model is ontwikkel wat die toekomstige prysverdiensteverhouding (die teenswoordige aandeelprys en toekomstige jaareind verdienste per aandeel) suksesvol kon modelleer nie. Die mees aanvaarbare metode vir waardebepaling van aandele is om toekomstige kontantvloeie te verdiskonteer teen 'n toepaslike verdiskonteringskoers. Van die vernaamste en mees gebruikte waardeberamings modelle is die Dividend Groei Model en die Gordon Model. Beide modelle gebruik die toekomstige dividendstroom as die toekomstige kontantvloeie wat uitbetaal word aan die aandeelhouers. Thomas K. Philips, die hoof beleggingsbeampte by Paradigm Asset Management in New York, het 'n waardeberamingsmodel ontwerp in 1999. Die model (Philips prysverdienste verhoudingsmodei) was afgelei vanaf die Dividend Groei Model en word gebruik om 'n geïmpliseerde toekomstige prysverdiensteverhouding te bereken. Die Philips prysverdienste verhoudingsmodel sluit die volgende onafhanklike veranderlikes in: die koste van kapitaal, die opbrengs op aandeelhouding en die uitbetalingsverhouding. Elke veranderlike in hierdie model is 'n berekende teenswoordige jaareinde puntwaarde, wat gebruik was om die toekomstige geïmpliseerde prysverdiensteverhouding (teenswoordige jaar aandeelprys gedeel deur die toekomstige verdienste per aandeel) te bereken. In hierdie studie word vyf jaar historiese jaareind besonderhede gebruik om die geïmpliseerde en werklike toekomstige prysverdiensteverhouding te bereken. Van die 225 Johannesburg Effektebeurs genoteerde maatskappye, is slegs 36 gebruik wat aan die vereistes voldoen om die Philips prysverdienste verhoudingsmodel te toets. Korrelasie en populasie gemiddelde statistiese toetse is op die berekende en geïmpliseerde data stelle uitgevoer en gevind dat die Philips prysverdienste verhoudingsmodel, teen 'n statistiese 0,20 vlak van beduidenheid, onsuksesvol was om die toekomstige prysverdiensteverhouding vooruit te skat. Die Philips prysverdienste verhoudingsmodel is meer kompleks as die Dividend Groei Model met meer aannames en beperkings. Die Philips prysverdienste verhoudingsmodel is 'n teoretiese instrument wat gebruik kan word om hipotetiese (alle model aannames en voorwaardes is nagekom) maatskappye te ontleed. Dus het die Philips prysverdienste verhoudingsmodel min tot geen praktiese toepassingsvermoë in die werkilke waardasie van aandele nie.
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37

Wang, Fengyu. "The value of analyst recommendations evidence from China /." Click to view the E-thesis via HKUTO, 2009. http://sunzi.lib.hku.hk/hkuto/record/B42841379.

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38

"Tests on relative strength index trading rules in China stock market." 2002. http://library.cuhk.edu.hk/record=b5890950.

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by Leung Kwok Chu, Wong Cheuk Fung.
Thesis (M.B.A.)--Chinese University of Hong Kong, 2002.
Includes bibliographical references (leaves 54-55).
ABSTRACT --- p.ii
TABLE OF CONTENTS --- p.iv
ACKNOWLEDGMENTS --- p.vi
Chapter
Chapter I. --- INTRODUCTION --- p.1
Technical Analysis --- p.2
The Characteristics and Efficiency of China's Equity Markets --- p.3
Market Participants --- p.4
Transaction Costs and Tradability of Shares --- p.5
Availability of Information --- p.7
Implication on Weak Form Market Efficiency --- p.8
Relative Strength Index --- p.10
Chapter II. --- LITERATURE REVIEW --- p.12
Chapter III. --- METHODOLOGY --- p.15
Primary Research --- p.15
Source of Data --- p.15
Spreadsheet Calculation Procedure --- p.16
Hypothesis Testing --- p.18
The First Type of Tests --- p.18
The Second Type of Tests --- p.19
The Third Type of Tests --- p.20
Chapter IV. --- RESEARCH FINDINGS --- p.21
Abnormal Returns Obtained by Following RSI Trading Rules --- p.21
A-shares --- p.21
Buy signals --- p.21
Interpretations of buy signals in A-share markets --- p.22
Sell signals --- p.22
Interpretations of sell signals in A-share markets --- p.23
B-shares --- p.25
Buy signals --- p.25
Interpretations of buy signals in B-share markets --- p.25
Sell signals --- p.26
Interpretations of sell signals in B-share markets --- p.27
Chapter V. --- ADDITIONAL RESEARCHES ON B-SHARE MARKETS --- p.30
Findings on Additional Researches on B-share Markets --- p.30
Interpretations of Findings on Additional Researches on B-share Markets --- p.31
Chapter VI. --- ADDITIONAL RESEARCHES ON A-SHARE MARKETS --- p.32
Correlation between Abnormal Return and Volume Turnover --- p.33
Findings on Correlation between Abnormal Return and Volume Turnover --- p.33
Interpretations of Findings on Correlation between Abnormal Return and Volume Turnover --- p.33
Correlation between Abnormal Return and Market Value --- p.34
Findings on Correlation between Abnormal Return and Market Value --- p.34
Interpretations of Findings on Correlation between Abnormal Return and Market Value --- p.35
Chapter VII. --- CONCLUSIONS --- p.37
Chapter VIII. --- LIMITATIONS --- p.39
Chapter IX. --- FURTHER STUDIES RECOMMENDED --- p.42
APPENDIX --- p.44
BIBLIOGRAPHY --- p.54
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39

Ohn, Jonathan Kong. "Dynamics of the return generating process and mean reversion of the US stock prices /." Diss., 1997. http://gateway.proquest.com/openurl?url_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:dissertation&res_dat=xri:pqdiss&rft_dat=xri:pqdiss:9814980.

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40

Kwon, Ki-Yeol. "Stock price, volatility and volume : the profitability of technical trading rules using bootstrap methodology /." Diss., 1999. http://gateway.proquest.com/openurl?url_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:dissertation&res_dat=xri:pqdiss&rft_dat=xri:pqdiss:9935167.

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41

Migliorino, Angelo. "Econometric approach for forecasting stock indices price." Master's thesis, 2017. http://hdl.handle.net/10362/28421.

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This work proposes to build a profitable dynamic trading strategy. In order to do that it is necessary to forecast the future stock indices prices. First we exploit the forecast power of stock indices assuming that they follow a Geometric Brownian motion. Next, we present an alternative forecasting model that involves cross sectional regression between indices. The latter proves to be more profitable on average than the former.
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42

LIN, JI-YU, and 林碁域. "A Study on Stock Price Trends Forecasting." Thesis, 2016. http://ndltd.ncl.edu.tw/handle/47741054909695966393.

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碩士
國立高雄大學
亞太工商管理學系碩士班
104
Stock market is a complex, changeful and dynamic system, and stock price trends affect the interest of investors, thus it attracts investors’ attention widely. Because stock price is fluctuating, and investors encounter inevitable risk, forecasting and analysis of investment planning is very important. This research uses time series method to forecast the stock price of three Taiwan listed companies. Using time series to forecast the decreasing daily price trends is accurate. Comparing the accuracy of three stock price trends forecasting, the best one is less fluctuation in stock price. In simulating trading, one of the three objects is good performance. The empirical results provide the reference for investors, researchers, and policy makers.
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43

"An application of two forecasting models for predicting price movements of a number of selected stocks in Hong Kong." Chinese University of Hong Kong, 1986. http://library.cuhk.edu.hk/record=b5885605.

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44

Chiang, Min-Wei, and 江旻緯. "Using Par-v-SVC For Stock Price Forecasting." Thesis, 2014. http://ndltd.ncl.edu.tw/handle/96607272986322083315.

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碩士
國立高雄應用科技大學
資訊管理研究所碩士班
102
Stock has been a higher rate of return but a higher risk on investment in the market,so investors focus that how to get a great price forecasting model.In this study,we apply Support Vector Machine(par-v-SVC)to build prediction model by technical indicators (BIAS,PSY,RSI…).There are two parts of research in this study.First, dividing the reaction time of technical indicators into three parts(one,three,five days) and dividing the change rate of stock price into two parts(1%,3%).Second, comparing the accuracy with algorithms of different classification(Neural Networks, Naive Bayes Classifier, Decision tree).The result obtained by par-v-SVC is the best compared to the other classification algorithms. Experimental results show the forecast accuracy of change rate 3% is better than 1%.The reaction time of one day has the worst forecast accuracy in change rate 1% and the reaction time of one day has the best forecast accuracy in change rate 3%.
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45

WU, JIAN-ZHANG, and 吳健彰. "Application of Stock Price Forecasting in Technical Analysis." Thesis, 2018. http://ndltd.ncl.edu.tw/handle/m75dr4.

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碩士
國立雲林科技大學
財務金融系
106
In this study, we use FCVAR（fractionally cointegrated vector autoregressive） to forecast the high prices and low prices. The study sample is 45 of the Taiwan 50 constituent stocks in TWSE from 2000 to 2017. The empirical result show that the highest and lowest prices of stocks can be predicted. The study found that it is possible to find the buying and selling point by using the highest and lowest prices. When the buying signal appears, the opening price of the next day is used, and after the selling signal appears, the closing price of the next day is used. The study found that this method can get positive return. The buy-and-hold strategy was buy on the first day, and sold until the last trading day. It was found that the method had a better return than the moving average on the most stocks.
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46

Chen, Bo-Tsuen, and 陳柏村. "Forecasting Stock Price based on Fuzzy Time-Series." Thesis, 2012. http://ndltd.ncl.edu.tw/handle/96n5x3.

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碩士
國立臺中科技大學
資訊管理系碩士班
100
The prediction of stock markets is an important and widely research issue since it could be had significant benefits and impacts, and the fuzzy time-series models have been often utilized to be the forecast models to make reasonably accurate predictions. For promoting the forecasting performance of fuzzy time-series models, this thesis proposed a new model, which incorporates the concept of the entropy-based discretization partitioning, equal-width pre-partitioning and equal-depth pre-partitioning based on fuzzy time-series models. In order to evaluate our proposed approach, the source data was using actual trading data from Taiwan Stock Exchange (TAIEX), and the experimental period is selected from 1997 to 2003 as the datasets for verifications. Finally, the experimental results showed that our proposed approach was effective in improving the forecasting errors on forecasting stock price significantly. Furthermore, the performances in terms of root mean squared error (RMSE) indicate that the proposed model is superior to the compared models suggested by Chen (1996), Karaboga et al. (2009), Cheng et al. (2009) and Chang et al. (2011) earlier. It is evident that the proposed model is a good approach to improve the forecasting performance fuzzy time-series models.
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47

"Modeling and forecasting Hong Kong stock market return." 1999. http://library.cuhk.edu.hk/record=b5889916.

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by Wong Hiu Ming.
Thesis (M.Phil.)--Chinese University of Hong Kong, 1999.
Includes bibliographical references (leaves 74-79).
Abstracts in English and Chinese.
ACKNOWLEDGMENTS --- p.iii
LIST OF TABLES --- p.iv
LIST OF ILLUSTRATIONS --- p.v
CHAPTER
Chapter ONE --- INTRODUCTION --- p.1
Chapter TWO --- THE LITERATURE REVIEW --- p.5
ARCH/GARCH Models
Nonparametric Method
Chapter THREE --- METHODOLOGY --- p.14
ARCH Modeling
Semiparametric GARCH Modeling
Causality Test
Local Polynomial Model
Chapter FOUR --- DATA AND EMPIRICAL RESULTS --- p.37
Data
GARCH Modeling
Semiparametric GARCH Modeling
Causality Test
Local Polynomial Model
Chapter FIVE --- CONCLUSION --- p.52
TABLES --- p.56
ILLUSTRATIONS --- p.62
APPENDIX --- p.71
BIBLIOGRAPHY --- p.74
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48

Glushkov, Denys Vitalievich. "Two essays on market behavior." Thesis, 2006. http://hdl.handle.net/2152/2869.

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49

Rimer, Øyvinn Døhl. "The effect of optionability on underlying stock prices : a thesis submitted in partial fulfilment of the requirements for the degree of Master of Commerce in Finance, University of Canterbury, Christchurch, New Zealand /." 2006. http://library.canterbury.ac.nz/etd/adt-NZCU20070521.162814.

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Thesis (M. Com.)--University of Canterbury, 2006.
Typescript (photocopy). "Senior supervisor: Prof. Edwin Maberly, Co-supervisor: Dr. Raylene Pierce." Includes bibliographical references (leaves 78-81). Also available via the World Wide Web.
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50

Naidoo, Justin Rovian. "Index/sector seasonality in the South African stock market." Thesis, 2016. http://hdl.handle.net/10539/20938.

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This paper aims to investigate the apparent existence of two anomalies in the South African stock market based on regular strike action, namely the month of the year effect and seasonality across specific sectors of the Johannesburg Stock Exchange.
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