本研究用金融傳導的角度，從散裝海運產業切入，利用標普高盛商品指數、加權遠期運費協議指數、波羅的海運費指數、道瓊全球航運指數以及美元指數，以傳遞熵與BEKK-GARCH模型，探討2008年3月至2016年3月之散裝海運產業金融傳導因子，在多次金融危機中，散裝海運產業金融傳導因子的領先落後關係、短期報酬外溢效果與長期波動傳遞效果，以及對航運類股之影響。 本研究成果可從投資策略與經濟意涵兩方面呈現，在投資策略上，根據實證結果，在金融危機期間，資訊從道瓊全球航運指數流向波羅的海乾散貨運價指數，再流向加權遠期運費協議指數，代表股票市場領先運費市場，而運費市場又領先遠期運費協議市場，而每個期間的加權遠期運費協議指數對波羅的海乾散貨運價指數皆為正向顯著關係，波羅的海乾散貨運價指數與道瓊全球航運指數間皆為雙邊正向顯著關係，本研究建議預測波羅的海乾散貨運價指數的散裝海運產業業者與投資人，可以道瓊全球航運指數與加權遠期運費協議指數作為先行指標。 在經濟意涵方面，根據實證結果，金融危機期間，金融市場動盪程度提高，連帶影響散裝海運運價價格波動劇烈，使得散裝海運產業業者與投資人的避險需求提升，由於波羅的海乾散貨運價指數為散裝海運產業業者的每日報價，並非金融市場交易之結果，故散裝海運產業業者與投資人可以參考商品市場、股票市場、外匯市場及運費市場的資訊進行避險操作。

This thesis consists of four self-contained papers related to the change of market structure and the quality of equity market. In Paper [I] we found, by using of a Flexible Dynamic Component Correlations (FDCC) model, that the creation of a common cross-border stock trading platform has increased the long-run trends in conditional correlations between foreign and domestic stock market returns. In Paper [II] we study whether the creation of a uniform Nordic and Baltic stock trading platform has affected weak-form information efficiency. The results indicate that the stock market consolidations have had a positive effect on the information efficiency and turnover for an average firm. The merger effects are, however, asymmetrically distributed in the sense that relatively large (small) firms located on relatively large (small) markets experience an improved (reduced) information efficiency and turnover. Although the results indicate that changes in the level of investor attention (measured by turnover) may explain part of the changes in information efficiency, they also lend support to the hypothesis that merger effects may partially be driven by changes in the composition of informed versus uninformed investors following a stock. Paper [III] analyzes whether the measured level of trust in different countries can explain bilateral stock market correlations. One finding is that generalized trust among nations is a robust predictor for stock market correlations. Another is that the trust effect is larger for countries which are close to each other. This indicates that distance mitigates the trust effect. Finally, we confirm the effect of trust upon stock market correlations, by using particular trust data (bilateral trust between country A and country B) as an alternative measurement of trust. In Paper [IV] we present the impact of the stock market mergers that took place in the Nordic countries during 2000 – 2007 on the probabilities for stock price jumps, i.e. for relatively extreme price movements. The main finding is that stock market mergers, on average, reduce the likelihood of observing stock price jumps. The effects are asymmetric in the sense that the probability of sudden price jumps is reduced for large and medium size firms whereas the effect is ambiguous for small size firms. The results also indicate that the market risk has been reduced after the stock market consolidations took place.

Thesis (MBA (Business Management))--University of Stellenbosch, 2009. / ENGLISH ABSTRACT: Econophysics is a relatively new branch of physics. It entails the use of models in physics applied to economics. The distributions of financial time series are the aspect most intensely studied by physicists. This study is based on a study by Kleinert and Chen who applied the Boltzmann distribution to stock exchange data to define a market temperature that may be used by investors to indicate an impending stock market crash. Most econophysicists’ analysed the tail regions of the distributions as the tails represent risk in financial data. This study’s focus of analysis, on the other hand is the characterisation of the central portion of the probability distribution. The Boltzmann distribution, a cornerstone in statistical physics, yields an exponential distribution. The objective of this study is to investigate the suitability of using a market volatility forecasting method from econophysics, namely the Boltzmann/market temperature method. As econometric benchmark the ARCH/GARCH method is used. Stock market indices are known to be non-normally (non-Gaussian) distributed. The distribution pattern of a stock market index of reasonable high sampling frequency (typically interday or intraday) is leptokurtic with heavy tails. Mesoscopic (interday) distributions of financial time series have been found to be exponential distributions. If the empirical exponential distribution is therefore interpreted as a Boltzmann distribution, then a market temperature can be calculated from the exponential distribution. Empirical data for this study is in the form of daily closing values of the Johannesburg Stock Exchange (JSE) All Share Index (ALSI) and the Standard & Poor 500 (S & P 500) index for the period 1995 through to 2008. The Kleinert and Chen study made use of intraday data obtained from established markets. This study differs from the Kleinert and Chen study in that interday data obtained from an emerging market, namely the South African stock market is used. Neither of the aforementioned two differences had a significant influence on the results of this study. The JSE ALSI log-return data displays non-Gaussian properties and the Laplace (double exponential) distribution fit the data well. A plot of the market temperature provided a clear indication of when stock market crashes occurred. Results of the econophysical (Boltzmann/market temperature) method compared well to results of the econometric (ARCH/GARCH) method and subject to certain improvements can be utilised successfully. A leptokurtic, non-Gaussian nature was established for daily log-returns of the JSE ALSI and the S & P 500 index. The Laplace (double exponential) distribution fit the annual logreturns of the JSE ALSI and S & P 500 index well. As a result of the good Laplace fit, annual market temperatures could be calculated for the JSE ALSI and the S & P 500 index. The market temperature method was effective in identifying market crashes for both indices, but a limitation of the method is that only annual market temperatures can be determined. The availability of intraday stock index data should improve the interval for which market temperature can be determined. / AFRIKAANSE OPSOMMING: Ekonofisika is ‘n relatiewe nuwe studieveld. Dit behels die toepassing van fisiese modelle op finansiële data. Die waarskynlikheidsversdelings van finansiële tydreekse is die aspek wat meeste deur fisisie bestudeer word. Hierdie studie is gebaseer op ‘n studie deur Kleinert en Chen. Hulle het die Boltzmann-verspreiding op ‘n aandele-indeks toegepas en ‘n mark-temperatuur bepaal. Hierdie mark-temperatuur kan deur ontleders gebruik word as waarskuwingsmeganisme teen moontlike aandelebeurs ineenstortings. Die meeste fisisie het die uiterste areas van die verspreidingskurwes geanaliseer omdat hierdie uiterste area risiko in finansiële data verteenwoordig. Die analitiese fokus van hierdie studie, aan die ander kant, is die karakterisering van die die sentrale areas van die waarskeinlikheidsverdeling. Die Boltzmann verspreiding, die hoeksteen van Statistiese Fisika lewer ‘n eksponensiële waarskynlikheidsverdeling. Die doel van hierdie studie is om ‘n ondersoek te doen na die geskiktheid van die gebruik van ‘n ekonofisiese, vooruitskattingsmetode, naamlik die Boltzmann/mark-temperatuur model. As ekonometriese verwysing is die “ARCH/GARCH” metode toegepas. Aandelemark indekse is bekend vir die nie-Gaussiese verspreiding daarvan. Die verspreidingspatroon van ‘n aandelemark indeks met‘n redelike hoë steekproef frekwensie (in die orde van ‘n dag of minder) is leptokurties met breë stert-dele. Mesoskopiese (interdag) verspreidings van finansiële tydreekse is getipeer as eksponensieël. Indien die empiriese eksponensiële-verspreiding as ‘n Boltzmann-verspreiding geinterpreteer word, kan ‘n mark-temperatuur daarvoor bereken word. Empiriese data vir die gebruik in hierdie studie is in die vorm van daaglikse sluitingswaardes van die Johannesburgse Effektebeurs (JSE) se Alle Aandele Indeks (ALSI) en die Standard en Poor 500 (S & P 500) indeks vir die periode 1995 tot en met 2008. Die Kleinert en Chen studie het van intradag data vanuit ‘n ontwikkelde mark gebruik gemaak. Hierdie studie verskil egter van die Kleinert en Chen studie deurdat van interdag data vanuit ‘n opkomende mark, naamlik die Suid-Afrikaanse aandelemark, gebruik is. Nie een van die twee voorafgaande verskille het ‘n beduidende invloed op die resultate van hierdie studie gehad nie. Die JSE ALSI se logaritmiese opbrengs data vertoon nie-Gaussiese eienskappe en die Laplace (dubbeleksponensiële) verspreiding beskryf die data goed. ‘n Grafiek van die mark-temperatuur vertoon duidelik wanneer aandelemarkineenstortings plaasgevind het. Resultate van die ekonofisiese (Boltzmann/mark-temperatuur) metode vergelyk goed met resultate van die ekonometriese (“ARCH/GARCH”) metode en onderhewig aan sekere verbeteringe kan dit met sukses toegepas word. ‘n Leptokurtiese, nie-Gaussiese aard is vir daaglike opbrengswaardes vir die JSE ALSI en die S & P 500 indeks vasgestel. ‘n Laplace (dubbel-eksponensiële) verspreiding kan goed op die jaarlikse logaritmiese opbrengste van die JSE ALSI en die S & P 500 indeks toegepas word. As gevolg van die goeie aanwending van die Laplace-verspreiding kan ‘n jaarlikse mark-temperatuur vir die JSE ALSI en die S & P 500 indeks bereken word. Die mark-temperatuur metode is effektief in die identifisering van aandelemarkineenstorings vir beide indekse, hoewel daar ‘n beperking is op die aantal mark-temperature wat bereken kan word. Die beskikbaarheid van intradag aandele indekswaardes behoort die interval waarvoor mark-temperature bereken kan word te verbeter.

於現今經濟情勢混沌不明，令人想起價值投資的投資策略方法，期望 在任何環境下，只要篩選出的股票是具有獲益潛力，則可趁勢進場，獲取 超額收益。本論文嘗試以基本面分析為主體建構三步驟的資產配置流程。 第一步驟使用比例交集法進行資產選擇，而多因子方法通常比單因子所篩 選的報酬率更優異，且加上月營收成長率作為篩選條件其報酬率更是亮眼。 再者，第二步驟透過風控管指標選股發現，當採用 GSR 做為資產選擇的條件時，可達到最佳的表現。最後於最適權重的配置之中，資產模型及目標函數會因為不同的資產組合而有不同的效果，其中，當 FCFY(0.1) & ROA(0.2)加上月營收成長率20%做為篩選條件並使用GSR進行二次篩選後，使用 ARMA(1,1)-GARCH(1,1)且目標函數為最大化夏普指標時可達最大報酬。

This thesis investigates systematic liquidity risk and short-term stock price reaction to large one-day price changes. We study 642 constituents of the FTSALL share index over the period from 1st July 1992 to 29th June 2007. We show that the US evidence of a priced systematic liquidity risk of Pastor and Stambaugh (2003) and Liu (2006) is not country-specific. Particularly, systematic liquidity risk is priced in the London Stock Exchange when Amihud's (2002) illiquidity ratio is used as a liquidity proxy. Given the importance of systematic liquidity risk in the asset pricing literature, we are interested in testing whether the different levels of systematic liquidity risk across stocks can explain the anomaly following large one-day price changes. Specifically, we expect that the stocks with high sensitivity to the fluctuations in aggregate market liquidity to be more affected by price shocks. We find that most liquid stocks react efficiently to price shocks, while the reactions of the least liquid stocks support the uncertain information hypothesis. However, we show that time-varying risk is more important than systematic liquidity risk in explaining the price reaction of stocks in different liquidity portfolios. Indeed, the time varying risk explains nearly all of the documented overreaction and underreaction following large one-day price changes. Our evidence suggests that the observed anomalies following large one-day price shocks are caused by the pricing errors arising from the use of static asset pricing models. In particular, the conditional asset pricing model of Harris et al. (2007), which allow both risk and return to vary systematically over time, explain most of the observed anomalies. This evidence supports the Brown et al. (1988) findings that both risk and return increase in a systematic fashion following price shocks.

一般研究外匯波動均以現貨的波動為主，但理論上衍生性金融商品由於成本低、市場限制較少，並且隱含波動度為「事前」波動度，隱含「預期」的意涵，因此衍生性金融商品的波動應該比現貨更能反映市場的資訊，市場資訊透過市場參與者的投資策略反映在市場，將會造成市場上的波動，且影響是不對稱和具有反轉現象的，所謂的「反轉」是指當價格變動幅度很大時，負向的價格變動比正向對波動度的影響要大，但當價格變動很小時，影響方向便會出現反轉 (reversal)，即小幅度的正向價格變動比負向價格變動對波動度的影響要大。 本研究以英磅、歐元、日圓及瑞士法郎四種外匯選擇權作為研究標的，探討外匯波動是否具有不對稱效果以及不對稱效果是否因價格變動幅度而有反轉現象，並且發展類似double-threshold GARCH模型的VS-VOLUME-GARCH模型，在控制交易量變數後，檢視不對稱及反轉的現象是否有所改變。實證結果發現市場訊息對英磅、歐元、日圓與瑞士法郎波動具有不對稱效果與反轉，但是方向與影響程度剛好與一般股市波動相反，即小幅度正向價格變動對波動度的影響較負向小，大幅度的正向價格變動對波動度的影響較負向大，其次，交易量的確可以用來解釋波動度不對稱及反轉但是僅能解釋部份原因，並且由實證結果可知交易量的確可以減輕波動度不對稱及反轉的程度，另外，實證結果也指出交易量只是造成不對稱及反轉效果的一個原因，除了交易量之外應該還存在其它重要因素。

本文選取台灣電子產業發行之11支海外存託憑證(Global Depositary Receipts，GDR)為樣本，其中10支於美國發行、1支於歐盟發行。研究目的分別為國內標的股報酬、存託憑證報酬是否受匯率報酬影響，以及國內、外投資人對匯率風險之看法是否相同。本文選取財務上最常用之估計非線性模型條件共變數之雙變量GARCH(1,1)模型(Bivariate GARCH Model)，經過AIC(Akaike Information Criteria)比較、及相關係數是否隨時間而改變之檢定後，得知所有樣本皆適用DCC(1,1)模型(Dynamic Conditional Correlation Model)，於估計存託憑證報酬與匯率報酬之條件共變數後，再運用多元迴歸模型，探討實證結果。實證結果顯示國內標的股均存在顯著之匯率風險，存託憑證則多數存在顯著之匯率風險。而國內、外投資人對匯率風險之看法異同方面，宏□、鴻海、茂矽、仁寶、錸德、台積電所發行之海外存託憑證，國內、外投資人對存託憑證、國內標的股匯率風險之看法無顯著不同，可歸因於其較其他存託憑證及標的股國際化。而華邦、智邦、旺宏之海外存託憑證，國內、外投資人對存託憑證匯率風險之看法顯著不同，本文又將匯率風險之來源，歸納為兩部分：一、由標的股產生，可歸因於標的股國際化程度；二、由換匯(foreign exchange)產生，可歸因於匯率變動程度；而華邦、智邦、旺宏實證顯示匯率風險皆由標的股產生，因其於美國或歐盟上市，美元或歐元又為強勢貨幣，故不存在換匯風險。

本研究資料期間自2004年1月2日至2005年12月13日止，擷取政府債券期貨收盤價及10年期最具流動性之政府債券收盤價資料進行整理，2004年1月2日~2005年6月30日為樣本內期間，2005年7月1日~2005年12月13日為樣本外期間。以簡單避險法、最小平方法（價格）模型、最小平方法（報酬）模型及GARCH 模型之避險比率，應用於樣本外期間的避險。實證結果如下：避險績效方面，日資料無論何種模型均未降低其報酬率之波動度，週資料而言各模型均可降低原公債現貨之報酬波動度，其中以OLS（return）較佳，但避險成效不彰。日資料避險比率最小為OLS（報酬）模型，週資料避險比率最小為OLS（價格）模型。就報酬而言，無論日資料及週資料，各種避險模型所作之避險，均降低其報酬率，換言之，未作避險動作之報酬率最佳。 / The main purpose of this paper is to examine the hedging effectiveness of the Taiwan government bond futures under several hedging models. These models are Naive, OLS-reward, OLS-level and GARCH. The daily data is from January 2004 to December 2005. The in-sample data is from January 2, 2004 to June 30,2005. The out-of-sample one is from July 1, 2005 to December 13,2005. The hedging porformance is measured by the decreasing degree of portfolio variance.The empirical results show as follows:1. OLS（return）model has the better hedge performance from weekly data. 2.The smallest hedge ratio is OLS（reward）from daily data, and it’s OLS（level）from weekly data. 3.The reward is highest without hedge

本研究探討台灣50指數成分股變動造成的異常報酬與超額交易量現象，提供投資人作為選股參考，由於台灣50指數編製依據為總市值，僅使用公開資訊，可以用來檢驗效率市場假說。不同於過去研究的貢獻，本文考慮金融資產報酬的波動群聚現象及模型係數的不穩定性，分別使用卡爾曼濾嘴法及GARCH(1,1) 模型修正，以期獲得較穩健的實證結果。本研究結果發現，新增股及剔除股在宣告日的下一個交易日及生效日的前一個交易日有顯著異常報酬；新增股的累積異常報酬可持續大約兩個工作星期，且新增股有持續的超額交易量情形；而剔除股僅在生效日及生效日的前一個交易日有超額交易量。上述實證結果顯示投資人可利用此公開資訊，獲得異常報酬，不支持效率市場假說。 / We study the price and volume effects following the Taiwan 50 Index revisions. Since the decision to include (exclude) a stock in (from) the index is based merely on market capitalization, it provides a unique opportunity to test the efficient market hypothesis. Our contribution to the existing literature lies in the fact that we employ the Kalman filter approach and the GARCH(1,1) model to allow the parameters instability and time-varying residual variance, and hence to produce more robust empirical results. The results suggest that the newly added stocks and the currently dropped stocks experience significant price changes right after the announcement day and right before the change day; the abnormal returns of the newly added stocks last about two weeks, these stocks also exhibit persistently excessive trading volume while the currently dropped stocks only have excessive trading volume on and right before the change day. These results indicate that investors can earn abnormal returns through public information, and invalidate the efficient market hypothesis.

雖然許多研究已針對認股權證評價進行調整，但是其價格低估的問題仍無法解決。因此，本文將探討認股權證發行對股價報酬動態過程的影響。本文將證實是否認股權證發行將影響其標的股價之動態過程，倘若股價報酬的動態過程已反應了認股權證發行的潛在稀釋效果，則進行充分調整的股權稀釋模型將低估認股權證的價格。為了確認在評價認購權證時充分調整稀釋效果的必要性，本文將檢測權證發行對股票報酬過程的影響。本文利用延伸Garch-M模型，導出四個檢驗稀釋效果的模型。實證結果顯示，在發行認股權證之後，股價報酬的變異數顯著降低，該結果在釐清股權稀釋效果與不對稱效果之後，該稀釋效果依然顯著。 / As the underestimation of warrants remains unsolved after many adjustments presented by previous researchers, we further investigate the impact of the warrant introduction on the underlying stock return processes. This research attempts to determine whether the introduction of warrants influences the return processes of underlying stocks. If the introduction creates a potential dilution effect in stock return processes, full dilution adjustment pricing models would lead to underestimation. To exam whether full dilution adjustments are required for warrant pricing, the GARCH-M model has been extended to derive four models for testing the dilution effect on stock return processes. Empirical results show that the volatilities of underlying stock return processes are significantly reduced following warrant introduction even after clarification and distinguishing dilution from asymmetric effect.