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Dissertations / Theses on the topic 'Econometrics. Stock price forecasting'

Author: Grafiati

Published: 4 June 2021

Last updated: 1 February 2022

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1

Dufour, Alfonso. "Essays on the econometrics of inter-trade durations and market liquidity /." Diss., Connect to a 24 p. preview or request complete full text in PDF format. Access restricted to UC campuses, 1999. http://wwwlib.umi.com/cr/ucsd/fullcit?p9944222.

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2

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.<br>Typescript. Bibliography: leaves 83-84. Also available online through University of New Brunswick, UNB Electronic Theses & Dissertations.

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3

Borneklint, Niklas. "Forecasting prices of Bitcoin and Google stock with ARIMA vs Facebook Prophet." Thesis, Högskolan Väst, Avd för juridik, ekonomi, statistik och politik, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:hv:diva-17345.

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In this thesis we have presented econometrics and forecasts of Bitcoin and Google (GOOG) prices. We have implemented two models, one traditional, “ARIMA” and a relatively new one, “Prophet model” by using Facebook Prophet (ML). Machine learning is still new in the economic field, it has been rewarding to learn its capability. We have evaluated the model’s performance by using root mean square error (RMSE) and compared the result which model performed better. We wanted to compare to different assets, volatile Bitcoin to considerable stable Google (GOOG), thus investigate our models performance

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4

Manganelli, Simone. "Conditional autoregressive value at risk and other essays in financial econometrics /." Diss., Connect to a 24 p. preview or request complete full text in PDF format. Access restricted to UC campuses, 2000. http://wwwlib.umi.com/cr/ucsd/fullcit?p9980049.

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5

Lewis, Kurt Frederick. "Robustness and information processing constraints in economic models." Diss., University of Iowa, 2007. http://ir.uiowa.edu/etd/159.

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6

Clayton, Maya. "Econometric forecasting of financial assets using non-linear smooth transition autoregressive models." Thesis, University of St Andrews, 2011. http://hdl.handle.net/10023/1898.

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Following the debate by empirical finance research on the presence of non-linear predictability in stock market returns, this study examines forecasting abilities of nonlinear STAR-type models. A non-linear model methodology is applied to daily returns of FTSE, S&P, DAX and Nikkei indices. The research is then extended to long-horizon forecastability of the four series including monthly returns and a buy-and-sell strategy for a three, six and twelve month holding period using non-linear error-correction framework. The recursive out-of-sample forecast is performed using the present value model

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7

Hakim, Abdul. "Modelling the interactions across international stock, bond and foreign exchange markets." UWA Business School, 2009. http://theses.library.uwa.edu.au/adt-WU2009.0202.

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[Truncated abstract] Given the theoretical and historical evidence that support the benefit of investing internationally. there is Iittle knowledge available of proper international portfolio construction in terms of how much should be invested in foreign countries, which countries should be targeted, and types of assets to be included in the portfolio. The prospects of these benefits depend on the market volatilities, cross-country correlations, and currency risks to change in the future. Another important issue in international portfolio diversification is the growth of newly emerging market

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8

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).<br>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 wit

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9

Serra, Rodrigo Moreira. "Cryptocurrency price forecasting : an empirical application." Master's thesis, Instituto Superior de Economia e Gestão, 2020. http://hdl.handle.net/10400.5/21015.

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Mestrado em Econometria Aplicada e Previsão<br>A presente dissertação é desenvolvida no âmbito dos modelos Autorregressivo Integrado de Médias Móveis (ARIMA) e de Alisamento Exponencial, tendo como principal objetivo realizar uma comparação de métodos de previsão. Em particular, as previsões serão feitas usando essas diferentes classes de métodos e serão realizados exercícios de validação cruzada para encontrar o modelo de previsão mais adequado. O objeto de estudo serão ativos financeiros; especificamente, cinco criptomoedas (criptoativos) - Bitcoin, Ether, Litecoin, XRP e Bitcoin Cash - esco

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10

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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11

Martin, Stephen D. "Aspects of expectations, investment and price changes." Thesis, University of York, 1990. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.238695.

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12

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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13

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

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14

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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15

Gallagher, Liam A. "Essays in macroeconomic and financial linkages." Thesis, University of Liverpool, 1997. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.364205.

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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 o

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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

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.<br>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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19

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.<br>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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20

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 (200

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21

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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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 i

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23

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 relat

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24

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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25

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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26

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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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

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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29

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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30

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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31

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

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32

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 re

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33

Shynkevich, Yauheniya. "Computational intelligence techniques for forecasting stock price movements from news articles and technical indicators." Thesis, Ulster University, 2016. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.701435.

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Forecasting the future behaviour of market prices is an important area of research, which is exploited in asset allocation, risk management and algorithmic trading. Market behaviour is complex and influenced by many factors whose relationships are non-linear. The amount of financial data available for analysis is increasing substantially due to increased volumes of electronic trading, and market participants who are capable of extracting influential information from these massive amounts of data successfully benefit from using it in trading and investments. Computational intelligence technique

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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 p

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35

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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36

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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37

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.<br>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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38

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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39

Diale, Tumelo K. "Interaction between macroeconomic fundamentals and energy prices: evidence from South Africa." Thesis, 2017. http://hdl.handle.net/10539/23079.

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This write-up is submitted in partial fulfilment of the Master of Management Degree in Finance and Investments Degree.<br>Growth in commodity exporting economies, such as South Africa, is highly dependent on the revenue generated from exports. It is thus evident that as commodity prices fluctuate, income and the balance of payments will be accordingly impacted. This is further exacerbated by strong dependence on the imports of certain commodities. Oil is one such commodity on whose imports South Africa is highly dependent. Although natural gas is also imported, it is in lower quantities and is

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40

Chandrashekar, Satyajit. "Three new perspectives for testing stock market efficiency." Thesis, 2006. http://hdl.handle.net/2152/3757.

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41

Turk, George Watson Song Kaisheng Peterson David R. "Scale mixture modeling and shape parameter estimation of security returns new theories and analyses /." 2006. http://etd.lib.fsu.edu/theses/available/etd-07102006-171906.

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Thesis (Ph. D.)--Florida State University, 2006.<br>Advisor: Kai-Sheng Song, Florida State University,College of Arts and Sciences, Dept. of Statistics; David R. Peterson, Florida State University, College of Business, Dept. of Finance. Title and description from dissertation home page (viewed Sept. 27, 2006). Document formatted into pages; contains ix, 147 pages. Includes bibliographical references.

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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<br>國立高雄大學<br>亞太工商管理學系碩士班<br>104<br>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 l

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43

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<br>國立高雄應用科技大學<br>資訊管理研究所碩士班<br>102<br>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(Ne

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44

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<br>國立雲林科技大學<br>財務金融系<br>106<br>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. T

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45

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<br>國立臺中科技大學<br>資訊管理系碩士班<br>100<br>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

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46

Yang, Jheng-Dar, and 楊政達. "Stock Price Forecasting Using MARS-The Case Study of Formosa Regent Stock." Thesis, 2012. http://ndltd.ncl.edu.tw/handle/63057236463441061141.

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碩士<br>輔仁大學<br>統計資訊學系應用統計碩士班<br>100<br>The research uses a new statistical method –Multivariate Adaptive Regression Spline (MARS) to forecast stock price changes rather than the often used artificial neural network(ANN), which is unable to determine the variable importance and need much more training time. The objective of this study is to investigate the stock price changes taking FORMOSA Regent stock for example. Comparison with past researches using few financial or economic variables, this study sets up MARS model based on forty financial, economic, and other stock variables to forecast

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47

Chung, Jen-Ming, and 鍾任明. "Forecasting Intraday Stock Price Trends with Text Mining Techniques." Thesis, 2005. http://ndltd.ncl.edu.tw/handle/58168719801079876058.

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碩士<br>中原大學<br>資訊管理研究所<br>93<br>Investors will look for probable investment information from numerous electronic publishing that to make investment decision. More and more news presented by electronic format in the information age. The immediate news includes investment information besides will response to stock market. How to deal with the mass unstructured data efficiently is an important issue. Stock price trend forecasting based on structured data enjoys great popularity, but no matter using the statistics methods or machine learning algorithms still use structured numerical data. Though ha

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48

Liu, Mei Chi, and 劉美琦. "A STUDY ON THE TAIWAN STOCK PRICE FORECASTING MODELS." Thesis, 2000. http://ndltd.ncl.edu.tw/handle/48785443252117071678.

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博士<br>淡江大學<br>管理科學學系<br>88<br>The performance of a country’s economy is strongly related to the performance of its stock market. According studies indicated that the economic factors influenced stock prices. If we can use the economic factors in the forecasting stock price model, we will reduce the economic crisis to our country. The purpose of the study is to explore the trend of the Taiwan stock price. We will conduct five forecasting models for Taiwan stock price. Models considered include the one equation, which is the Box-Jenkins ARIMA, the transfer function model and the regre

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49

CHEN, HAO-WEI, and 陳浩瑋. "A Study on Stock Price Forecasting by Deep Learning." Thesis, 2017. http://ndltd.ncl.edu.tw/handle/xa9tc2.

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碩士<br>國立高雄第一科技大學<br>資訊管理系碩士班<br>105<br>It has long been an interesting research direction for scholars and financial experts to conduct the prediction of stock price. Nevertheless, a bunch of noise together with non-linear data have created a tough hurdle in the assessment process with many uncertainties. Therefore, in this study, we will try to find an effective way to solve this problem through the deep learning technology, a prevalence of artificial intelligence in recent years. We first collect and extract the stock market data to provide the training data set based on technical analysis i

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50

LIU, TYNG-SHI, and 劉亭希. "The Effective of Feature Scaling in Stock Price Forecasting." Thesis, 2019. http://ndltd.ncl.edu.tw/handle/v9g4f9.

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碩士<br>世新大學<br>財務金融學研究所(含碩專班)<br>107<br>In order to explore the relationship between the feature scaling methods in data preprocessing step, including standardization, normalization, and none (means do nothing on the data). We categorized the raw data into two types for stock prices forecasting. One is multi-class classification, a classification with more than two classes which present more difficult challenge than binary classes classification, classifying a set of targets of stock prices into three classes; and the other is regression, using 20 days ahead close prices of a stock be the input

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