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 equilibrium methodology, whereby stock returns are forecasted using macroeconomic variables, in particular the dividend yield and price-earnings ratio. The forecasting exercise revealed the presence of non-linear predictability for all data periods considered, and confirmed an improvement of predictability for long-horizon data. Finally, the present value model approach is applied to the housing market, whereby the house price returns are forecasted using a price-earnings ratio as a measure of fundamental levels of prices. Findings revealed that the UK housing market appears to be characterised with asymmetric non-linear dynamics, and a clear preference for the asymmetric ESTAR model in terms of forecasting accuracy.

This thesis explores various aspects of long memory behaviour in African stock markets (ASMs). First, we examine long memory in both equity returns and volatility using the weak-form version of the efficient market hypothesis (EMH) as a criterion. The results show that these markets (largely) display a predictable component in returns; while evidence of long memory in volatility is mixed. In general, these findings contradict the precepts of the EMH and a variety of remedial policies are suggested. Next, we re-examine evidence of volatility persistence and long memory in light of the potential existence of neglected breaks in the stock return volatility data. Our results indicate that a failure to account for time-variation in the unconditional mean variance can lead to spurious conclusions. Furthermore, a modification of the GARCH model to allow for mean variation is introduced, which, generates improved volatility forecasts for a selection of ASMs. To further evaluate the quality of volatility forecasts we compare the performance of a number of long memory models against a variety of alternatives. The results generally suggest that over short horizons simple statistical models and the short memory GARCH models provide superior forecasts of volatility; while, at longer horizons, we find some evidence in favour of long memory models. However, the various model rankings are shown to be sensitive to the choice of error statistic used to assess the accuracy of the forecasts. Finally, a wide range of volatility forecasting models are evaluated in order to ascertain which method delivers the most accurate value-at-risk (VaR) estimates in the context of Basle risk framework. The results show that both asymmetric and long memory attributes are important considerations in delivering accurate VaR measures.

本文是以市場研究（market study）的方式，探討制定會計原則的權威機構所發佈之 新的會計原則公報是否具有資訊內涵（information content ）。亦即調查會計報表 的主要使用者一投資人，是否會因企業改變所採用的會計原則而改變其對該企業之評 價，進而使該企業之股價發生反常的（abcdrmal）變動。 本文共壹冊，約六萬字，分為五章：第一章為緒論，概括地說明研究動機、目的及預 期貢獻；第二章則在發展理論上的研究架構，包括與研究有關的文獻探討；第三章為 研究方法論，介紹所使用的市場模式（market model），說明樣本資料之蒐集、統計 分析方法上的限制。第四章則解釋並分析統計的結果，第五章將彙總研究之結果，並 作結論與建議。

股價的漲跌變化是由於證券市場中眾多不同投資人及其投資決策後所產生的結果。然而，影響股價變動的因素眾多且複雜，新聞也屬於其中一種，新聞事件不但是投資人用來得知該股票上市公司的相關營運資訊的主要媒介，同時也是影響投資人決定或變更其股票投資策略的主要因素之一。本研究提出以新聞文件做為股價漲跌預測系統的基礎架構，透過文字探勘技術及分類技術來建置出能預測當日個股收盤股價漲跌趨勢之系統。 本研究共提出三種分類模型，分別是簡易貝氏模型、k最近鄰居模型以及混合模型，並設計了三組實驗，分別是分類器效能的比較、新聞樣本資料深度的比較、以及新聞樣本資料廣度的比較來檢驗系統的預測效能。實驗結果顯示，本研究所提出的分類模型可以有效改善相關研究中整體正確率高但各個類別的預測效能卻差異甚大的情況。而對於影響投資人獲利與否的關鍵類別"漲"及類別"跌"的平均預測效能上，本研究所提出的這三種分類模型亦同時具有良好的成效，可以做為投資人進行投資決策時的有效參考依據。 / Stocks' closing price levels can provide hints about investors' aggregate demands and aggregate supplies in the stock trading markets. If the level of a stock's closing price is higher than its previous closing price, it indicates that the aggregate demand is stronger than the aggregate supply in this trading day. Otherwise, the aggregate demand is weaker than the aggregate supply. It would be profitable if we can predict the individual stock's closing price level. For example, in case that one stock's current price is lower than its previous closing price. We can do the proper strategies(buy or sell) to gain profit if we can predict the stock's closing price level correctly in advance. In this thesis, we propose and evaluate three models for predicting individual stock's closing price in the Taiwan stock market. These models include a naïve Bayes model, a k-nearest neighbors model, and a hybrid model. Experimental results show the proposed methods perform better than the NewsCATS system for the "UP" and "DOWN" categories.

This thesis extends the 52-week high momentum literature, which was first published by George and Hwang in 2004, by stressing the parameters of the trading strategy to investigate its robustness. George and Hwang, in their seminal paper, find that the ratio of a stock’s close price to its 52-week high price is a good predictor of future returns. The thesis stresses various parameters of the strategy - such as the percent of total stocks bought and sold each period – and applies the strategy over different time periods – such as bull and bear markets. The study finds that the strategy is more profitable over the later half of the data set due to underperformance in bear markets such as the 1929 market crash and subsequent Great Depression. The results also show a significant difference in profitability between bull and bear market periods. The second half of the thesis looks at a new area in momentum, the absolute 52-week high. The strategy buys stocks whose price has increased over the previous six months, and who also close to their 52-week high price. Stocks are only bought (sold) if their price has increased (decreased) over the past six months and is close to (far from) the 52-week high price. The aim is to cut out stocks that are considered to be underperforming in the 52-week high momentum strategy, leaving only true winner and loser stocks. This strategy was found to increase the strength of the 52-week high momentum strategy, and the results show that there is no longer a significant difference between bull and bear market returns.

商業銀行是以借貸為主的金融機構，銀行獲利的主要來源，是從存款大眾手中取得短期資金，再將資金貸放給政府或企業進行長期投資。銀行「借短貸長」的業務，常使得其資產與負債產生存續期間不一致的問題，當利率非預期變動時，會改變資產與負債的真實價值，進而影響到銀行的淨值及股票報酬率。此外，匯率變動的風險也是銀行常常面臨的問題，尤其是當銀行涉足國際業務時，匯率的變動常常會使銀行所持有的外幣部位價值改變，進而影響到銀行的真實價值。另外一個會影響到銀行資產與負債價值的因素，就是信用風險的問題，總體經濟環境的信用品質變動，常常會影響銀行放款的還款機率，進而改變銀行放款的實質價值。 本文採用過去學者們所研究過的銀行股價三因子模型，即市場因子、債券因子、匯率因子，並加入代表總體信用風險的第四個因子，以及代表抵押品價值變動的第五個因子，成為銀行股價五因子模型。以日本銀行業的股價報酬為研究對象，實證結果顯示:新加入的總體信用風險因子，對於銀行股價報酬率的確產生顯著的負向影響，也就是當借貸市場信用品質愈差（信用風險越高）時，整體銀行股價的報酬率下降。且在四種類型的銀行中，地方銀行所估計出的信用風險顯著的比例最高，代表資產規模較小、放款業務較集中的地方銀行，其信用風險確實較其他類型的銀行為高。另外，在日本泡沫經濟破滅以後的銀行危機時期，以股價多因子模型來衡量的銀行信用風險也有上升的現象。

本文的研究意旨在於探討企業所投入的研究發展支出及資本支出對經營績效及股價報酬產生何種影響，希望能提供給企業經營者在決定研發政策或資本支出決策時參考。 本論文以國內上市櫃公司（除金融服務業外）作為研究樣本，並以2001年至2011年間為實證期間，進行迴歸模型分析，探討研發支出、資本支出等重大支出對於公司經營績效及股價報酬所產生的效果，並探討國內電子次產業如半導體產業、光電產業、電腦周邊產業及電子零組件產業在研發與資本支出對經營績效與股價報酬的影響差異度；本論文在公司經營績效及市場價值的衡量指標，係以公司之資產報酬率、股東權益報酬率、營業毛利率、營業淨利率、營收成長率及公司Tobin’s Q值與股價報酬等作為衡量指標。 實證結果發現： 一、 就全體產業而言，研究發展支出對於企業之營業毛利率、營業淨利率及Tobin’s Q值有顯著正相關，但對於企業之營收成長率、資產報酬率、股東權益報酬率以及公司股價報酬率等項目並未出現顯著相關性；資本支出對企業之資產報酬率及股東權益報酬率則出現顯著負相關，同時資本支出對企業Tobin’s Q值及股價報酬率出現顯著負相關，但對於企業之營收成長率、營業毛利率、營業淨利率等未出現顯著相關性。 二、 針對電子次產業實證結果： 1. 針對半導體產業實證發現，研究發展支出對於公司資產報酬率出現顯著正相關，資本支出對於公司Tobin’s Q值及股價報酬率則呈現顯著負相關。 2. 針對光電產業的實證發現，研究發展支出對於企業經營績效指標包括公司營收成長率、營業毛利率、營業淨利率、資產報酬率及股東權益報酬率等，全數呈現顯著正相關；而資本支出對於公司Tobin’s Q值或股價報酬率呈現顯著正相關，但對於營業毛利率、營業淨利率、資產報酬率及股東權益報酬率等則呈現顯著負相關。 3. 針對電腦週邊產業的實證發現，研究發展支出對於公司營收成長率、營業淨利率、資產報酬率、股東權益報酬率及公司Tobin’s Q值等皆呈現顯著正相關；而資本支出則對於公司營收成長率出現顯著正相關。 4. 針對零組件產業的實證發現，研究發展支出對於公司營收成長率、營業毛利率、營業淨利率、資產報酬率、股東權益報酬率、公司Tobin’s Q值及股價報酬率等全數呈現顯著正相關；而資本支出對於公司營業毛利率、資產報酬率及股東權益報酬率等出現顯著負相關。 / This research mainly examines the related effect of R&D expenditure and capital investment on corporate performance and company’s stock price. The results of this study are trying to offer reference opinions to corporate executive officers that will make R&D or capital investment decisions. In this study, the database includes the listed companies in Taiwan Stock exchange except the finance industry from 2001 to 2011. We adopt R&D expenditure and capital investment as the independent variables of evaluating of corporate performance and company’s stock price, and also choose the growth rate of sales, the operating margin ratio, the net profit margin ratio, the return on total assets, the return on equity, Tobin's Q Ratio and company’s stock price as the dependent variables. The results of this investigation could be summarized as follows: 1. For all targeted industries, R&D expenditure had positive, significant influence on the operating margin ratio, the net profit margin ratio and Tobin's Q Ratio. Capital investment had negative, significant influence on the return on total assets, the return on equity, Tobin's Q Ratio and company’s stock price. 2. For Semiconductor industry, R&D expenditure had positive, significant influence on the return on total assets. Capital investment had negative, significant influence on Tobin's Q Ratio and company’s stock price. 3. For Optoelectronics industry, R&D expenditure had positive, significant influence on growth rate of sales, the operating margin ratio, the net profit margin ratio, the return on total assets, the return on equity. Capital investment had positive, significant influence on Tobin's Q Ratio and company’s stock price. 4. For Computer peripheral industry, R&D expenditure had positive, significant influence on growth rate of sales, the operating margin ratio, the net profit margin ratio, the return on total assets, the return on equity, and Tobin's Q Ratio. Capital investment had positive, significant influence on the growth rate of sales. 5. For Electronic components/material industry, R&D expenditure had positive, significant influence on growth rate of sales, the operating margin ratio, the net profit margin ratio, the return on total assets, the return on equity, Tobin's Q Ratio and company’s stock price. Capital investment had negative, significant influence on the operating margin ratio, the return on total assets and the return on equity.

本研究欲探究個股新聞影響台灣股票市場之關係，透過蒐集宏達電、台積電與鴻海等三間上市公司從2012年6月至2013年5月的歷史交易資料和個股新聞，使用文字探勘技術找出各新聞內容的特徵，再透過歷史資料、技術分析指標與kNN和2-way kNN演算法將新聞先做分類後分群，建立預測模型，分析新聞對股價漲跌的影響與程度，以及漲跌幅度較高之群集與股價漲跌和轉折的關係。 研究結果發現，加入技術分析指標後能夠提升分類的準確率，而漲跌類別內的分群能夠界定各群集與股價漲跌之間的關係，且漲跌幅度較高之群集的分析則能大幅提升投資準確率至80%左右，而股價轉折點之預測則能提供一個明確的投資進場時間點，並確保當投資人依照此預測模型的結果進行7交易日投資時，可以在風險極低的前提下，穩當且迅速的獲取2.82%至22.03%不等的投資報酬。 / This study investigated the relation that the stock news effect on Taiwan Stock Market. Through collected the historical transaction data and stock news from July, 2012 to May, 2013, and use text mining、kNN Classification and 2-Way kNN Clustering technique analyzing the stock news, build a forecast model to analyze the degree of news effect on the stock price, and find the relation between the cluster which has great degree and the reversal points of stock price. The result shows that using the change range and Technical Indicator rise classification’s accuracy, and clustering in the ”up” group and “down” group can identify the range stock price move, and rise the invested accuracy up to about 80 percent. The forecast of reversal points of stock price offers a specific time to invest, and insure the investors who execute a 7 trading day investment depend on this model can get 2.82 to 22.03 percent return reliably and quickly with low risk.

In this paper we examine the short and long-term relations between stock price, book value and residual income.  We employ a panel error correction model, estimated with Engle & Granger’s (1987) two-step procedure and the single equation methodology. The models are estimated with FE-OLS and the MG-estimator. We find that stock prices adjust previous periods equilibrium error. Further, we find that book value has short and long-term effects on stock prices. Finally, this paper finds mixed results regarding residual incomes impact on stock prices. The MG-estimator finds evidence for a short-term relationship, while the FE-OLS provides insignificant or weak support for short-term effects. FE-OLS and MG-estimator find insignificant or weak support regarding residual incomes long-term effects.

Syfte: Studiens syfte är att undersöka om Riksbankens tillkännagivanden av reporänteförändringar har en effekt på den svenska aktiemarknaden, samt om det råder skillnader mellan fyra branscher i Stockholmsbörsen. Studien syftar även till att undersöka om det kan urskönjas en skillnad mellan branschernas räntekänslighet. Metod: Undersökningen baseras på en eventstudie med ett estimeringsfönster på 60 dagar före tillkännagivandet av reporänteförändringen, och ett eventfönster på 11 dagar. Urvalet består samtliga reporänteförändringar mellan 2001-2015, och av följande branscher, Finans & Fastighet, Industrivaror, Hälsovård, Teknologi, som är inhämtade från Stockholmsbörsen. Teori: Den teoretiska utgångspunkten i studien är teorin om den effektiva marknadshypotesen och teorier om reporäntan. Det presenteras även teorier om diskonteringsräntans effekt samt pris- och inkomstelasticitet. Finansiell psykologi, som är en invändning mot effektiva marknadshypotesen, redogörs dessutom tillsammans med tidigare forskning som har legat till grund för undersökningen. Slutsats: Studien resulterar i att det inte råder ett entydigt samband mellan Riksbankens tillkännagivanden av reporänteförändringar och den svenska aktiekursen. Resultatet illustrerar att det råder en skillnad mellan de valda branschernas räntekänslighet. Det går inte direkt att fastställa att den svenska marknaden är effektiv. / Purpose: The purpose of this study is to examine if Sweden’s central bank announcements of the federal funds rate have an effect on the Swedish stock market, and whether there are differences between four sectors of the Stockholm Stock Exchange. The study also aims to investigate if there is a difference between the sectors interest rate sensitivity.  Method: The study is based on an event study with an estimation window of 60 days prior the announcement of the federal fund rate, and an event window of 11 days. The sample consists of all the announcement of the federal funds rate between 2001- 2015 and the following sectors, Finance & Real Estate, Industrials, Healthcare, Technology, who are acquired from the Stockholm Stock Exchange. Theory: The theoretical basis in this study is the theory of the efficient market hypothesis and theories about the federal funds rate. An introduction to theories about the discount rate and price and income elasticity is also presented in the study. Financial psychology, which is a statement of opposition against the efficient market hypothesis, is also introduced together with previous research which the examination is based on. Conclusion: The results show that there is no unambiguous correlation between Sweden’s central bank announcements of the federal funds rate and the Swedish stock price. The result illustrate that there is a difference between the selected sectors interest rate sensitivity. In summary, it’s established that the Swedish stock market cannot be seen as an efficient market.