本篇主要為原物料指數與總體經濟物價間動態關聯性的研究。由於近年來糧食價格高漲，本研究選取CRB現貨指數（Commodity Research Bureau）、CCI期貨指數（Continuous Commodity Index），與CRB農產品指數為原物料指數以觀察原物料價格對總體面物價影響的程度；研究期間為2001年10月至2011年3月；總經物價指標選擇生產者物價指數（PPI）、消費者物價指數（CPI）、再加上國內生產毛額（GDP）；選取的國家為美國、臺灣與中國。本研究以Johansen共整合、向量自我迴歸模型、向量誤差修正模型、Granger因果關係檢定及衝擊反應分析等方法，探討三項原物料指數與總體經濟指標的互動關係。 研究結果顯示，原物料指數與總體指標之間的長期均衡關係不明顯。因果檢定顯示，CCI指數在因果檢定上領先CRB指數與CRB農產品指數；除了美國的GDP之外，CCI指數也領先各項總體經濟指標，但不論是CRB現貨指數或CRB農產品指數，對總經物價指標的領先-落後關係都不明顯，表示在CCI指數為較佳的預測指標。由衝擊反應分析的結果顯示，除了有共整合關係的變數間相互影響為長期性之外，受影響的物價指標僅在短期內會受到原物料價格變動的影響：總體物價指標面對原物料價格波動的反應約3期之後反應便逐漸消失，顯示原物料價格與總體物價指數之間的短期失衡期間並不長。 / This paper investigates the relationship between the commodity indexes and macroeconomic price indexes. Due to the sharp increase of food price in recent years, we add CRB index (Commodity Research Bureau), CCI index (Continuous Commodity Index), and CRB foodstuffs index in the research to see the magnitude of commodity price indexes to macroeconomic price indexes. This paper selects United State, Taiwan and China as samples and manages to find out the relationship of commodity indexes and macroeconomic price indexes by applying monthly data from October 2001 to March 2011. Macroeconomic price indexes are PPI (Producer Price Index), CPI( Consumer Price Index) and plus GDP Index. This paper tries to get the answer by applying Johansen Cointegration Test, Vector Autoregression Model(VAR), Vector Error Correction Model (VECM), Granger causality test and Impulse Response Analysis. The result does not show obvious long-term relationship between commodity price indexes and macroeconomic price indexes; and Granger causality test exhibits that CCI index takes the lead in the change of time. But we do not get consistent result between CRB index, CRB foodstuffs index and macroeconomic price indexes in Granger causality test which means commodity spot indexes do not necessarily lead in the change of time. This result implies that CCI index a better indicator in forecasting. According to Impulse Response Analysis, macroeconomic price indexes are influenced by commodity index only in a short period of time and this result tells us that the disequilibrium between commodity indexes and macroeconomic price indexes will not last long.

本篇探討在2010年4月16日滬深300股指期貨正式上市到2012年9月18日止的連續近月每日收盤日資料，進行區域內金融期貨市場連動關係的研究，試圖發現兩岸三地之股價指數期貨市場在亞太地區的金融主導地位，以作為國內外投資者在區域內的投資決策參考。 實證結果顯示，從共整合及向量誤差修正模型檢定發現，兩岸三地股指期貨具有長期均衡及短期的互動關係，因此可以視此三地為單一區域市場。在Granger因果檢定上，台股指數期貨雖無法預測恆生指數期貨，但仍明顯領先滬深300股指期貨且程度大於恆生指數期貨，或可推測兩岸因ECFA的簽訂使實體經濟的關聯性更為緊密，至於恆生指數期貨大多以金融、地產股為其主要成分，與大陸主要以實體經濟為主的金融市場，其Granger預測滬深300股指期貨的能力因此相對較弱。另由衝擊反應檢定得知恆生指數期貨為一獨立的市場，不受台灣及大陸指數期貨市場衝擊的影響；滬深300指數期貨因大陸金融市場逐漸開放，也會受到香港及台灣金融期貨市場之衝擊而產生影響；至於台股指數期貨則在兩岸三地，最易受到其他市場影響。最後由預測變異數分解檢定發現，台股指數期貨及滬深300股指期貨的波動皆易受到恆生股價指數期貨變異的影響，而恆生指數期貨在兩岸三地間之解釋能力最強，於兩岸三地間具金融主導地位。至於台股指數期貨對大陸金融期貨的影響也有突出的表現，因此若政府有心推展亞太金融中心之營運，勢必得加強區域間整合的力度，提出有利吸引外資之最政策，以增加台灣股市於國際間之競爭力。 / This study conducts analysis of regional linkage between financial futures market by examining consecutive daily closing information from April 16, 2010 (the official list date of CSI 300 index futures) to September 18, 2012. This study tries to find the financial dominance of these index futures market in the Asia Pacific region and hopefully it may be used as an investment decision reference for domestic and foreign investors. The empirical results show that from the total integration and vector error correction model tests and three places all indicate long-run equilibrium stock index futures and short-term interaction. Therefore, these three places can be viewed as a single regional market. In the Granger causality test on the TAIEX futures and Hang Seng Index futures, in spite of TAIEX futures can’t predict Hang Seng Index futures, it is significantly ahead of the CSI 300 index futures. TAIEX futures on the CSI 300 index futures even more impact than the Hang Seng Index Futures. It can explain that the ECFA has been signed and results show closely-related economy. Since the Hang Seng Index futures are mainly from financial and real estate stocks while the mainland-based financial market is mainly from the real economy, Granger predicts ability of CSI 300 index futures is relatively weak. Another test on the impulse response shows that (1) Hang Seng Index Futures is an independent market and is not affected by shocks from Taiwan and the mainland index futures markets, (2) CSI 300 index futures is affected by shocks from Hong Kong and Taiwan because of the gradually open financial markets, and (3) TAIEX futures can be seen as a potential Taiwanese dish economy because it is most vulnerable to other market influences among the three places. To sum up, the forecast variance decomposition tests show that TAIEX futures and the CSI 300 stock index futures are vulnerable to fluctuations in the Hang Seng index futures. In order words, the Hang Seng Index futures have the strongest explanatory power among the three places and shows financial dominance. The TAIEX futures also show its significant impact on the mainland China financial futures index. If the Government decides to promote the operation of the Asia-Pacific financial center and to increase competitiveness of Taiwan stock market, it will inevitably have to strengthen inter-regional integration efforts and make the most favorable policies to attract foreign investment.

本文的主要研究目的，在於將文化因素（即龍年與虎年效果）納入生育行為的考量，以重新審視台灣生育率與婦女教育程度之間的Granger因果關係。利用台灣1952年至1994年資料進行實證的Cheng and Nwachukwu（1997）及Cheng（1999），其結論指出台灣教育程度與生育率之Granger因果關係並不顯著。本文將以該文章之實證模型為基礎，並加入代表龍年效應與虎年效應的虛擬變數以建立本文模型。 首先根據Cheng（1999）的資料與變數，利用台灣1952年至2005年之年資料，建立一個包含粗出生率、教育程度大專以上的比例、女性勞動參與率、與實質經濟成長率等四個內生變數，以及代表龍虎年效應的兩個虛擬變數之VAR模型。並以Toda and Yamamoto（1995）提出的Granger因果關係檢定，檢定台灣教育程度與生育率之間的因果關係。隨後，為增進估計的有效性，本文利用台灣地區1978年至2005年的季資料，共112個樣本進行實證研究。變數定義方面，將粗出生率替換為一般生育率，教育程度大專以上的比例替換為育齡婦女大專以上的比例。並根據上述建立之VAR模型，進行Granger因果關係檢定。 經由本文的實證研究發現，將龍年效果與虎年效果納入考量後，台灣婦女教育程度的提昇會Granger影響生育率的下降。亦即台灣婦女教育程度日益提升，是解釋生育率下降的重要因素，此結果與Cheng（1999）所提出的結果並不一致。此外，龍年與虎年對台灣的生育率分別有顯著正向與負向的影響。 / This paper tries to revisit the null hypothesis of Granger no-causality between female education and fertility rate in Taiwan, by considering the culture factors captured by Dragon and Tiger Years which might influences the fertility behavior. In addition, this study compares the primary finding with the result proposed by Cheng and Nwachukwu (1997) and Cheng (1999) which are that female education does not affect fertility rate in Taiwan. According to Cheng (1999), official time series yearly data from 1952 to 2005 provided by Taiwan government are used first, and quarterly data from 1978 to 2005 are required to improve the efficiency. This study models a 4-Variables VAR and applies Granger no-causality test proposed by Toda and Yamamoto (1995). The primary finding of this study is that there is a negative causality from female education to fertility rate in Taiwan, which is inconsistent with conclusions in Cheng (1999). In addition, culture factors do play a very important role in fertility behavior in Taiwan.

Στην παρούσα εργασία μελετούμε τη σχέση μεταξύ χρηματιστηριακών αποδόσεων και δείκτη εμπιστοσύνης στις 27 χώρες-μέλη της ΕΕ για τα έτη 1985-2006. Βρήκαμε ότι για το μεγαλύτερο μέρος των χωρών της ΕΕ εμφανίζεται θετική συσχέτιση μεταξύ αποδόσεων και δείκτη εμπιστοσύνης του καταναλωτή στον βραχυχρόνιο ορίζοντα. Οι μεταβολές και στους δύο δείκτες τείνουν να κινούνται παράλληλα στην ίδια περίοδο, με εξαίρεση την πλειοψηφία των νεοεισελθέντων χωρών. Στον μακροπρόθεσμο ορίζοντα, βρήκαμε ότι για τις περισσότερες χώρες ο συντελεστής γίνεται σχεδόν μηδενικός. Για το μεγαλύτερο μέρος των χωρών της ΕΕ υφίσταται σχέση αιτιότητας μεταξύ των μεταβλητών, με τις αποδόσεις να προκαλούν κατά Granger τον δείκτη εμπιστοσύνης του καταναλωτή και τον δείκτη οικονομικής εμπιστοσύνης, αλλά το αντίστροφο δεν ισχύει. Αμφίδρομη σχέση αιτιότητας μεταξύ αποδόσεων και εμπιστοσύνης των καταναλωτών παρατηρείται μόνο για την Γαλλία οριακά, ενώ για την ΕΕ βρήκαμε οτι υπάρχει αμφίδρομη σχέση αιτιότητας μεταξύ αποδόσεων και δείκτη οικονομικής εμπιστoσύνης. / This paper studies the relationship between stock market developments and confidence index for the 27 EU countries - members over the years 1985-2006. We found that for the majority of the EU countries exists positive correlation between the stock market index and the confidence indicators (consumer confidence indicator and economic sentiment indicator) in the short horizon. The changes between these indexes tempt to move in the same direction contemporaneously and in the short horizon (of 1 month), with the new EU members to be an exception. The correlation becomes almost zero in the long horizon. For the most of the EU countries there is causality between the variables. Stock returns in general Granger-cause the Consumer Confidence Index and the Economic Sentiment Indicator, but not vice versa. We found also that there is feedback causality relationship between stock returns and confidence for France and the EU as a whole.

Η παρούσα διπλωματική εργασία ερευνά την σχέση μεταξύ των συναλλαγών των μετοχικών αμοιβαίων κεφαλαίων και των χρηματιστηριακών αποδόσεων για την περίπτωση του Ελληνικού Χρηματιστηρίου για την χρονική περίοδο 1994-2002. Με την χρησιμοποίηση ποικίλων οικονομετρικών μεθόδων γίνεται έλεγχος για την ύπαρξη σχέσης συνολοκλήρωσης καθώς και κάποιας βραχυχρόνιας σχέσης μεταξύ αυτών των δύο παραγόντων, ενώ γίνεται προσπάθεια εντοπισμού κάποιας σχέσης αιτιότητας μεταξύ αυτών με βάση τον έλεγχο αιτιότητας του Granger. / This diplomatic thesis investigates the relationship between the trading of mutual funds and stock returns in the case of the Greek Stock Exchange Market, for the period 1994 - 2002. A variety of econometric methods was used to check the existence of a cointegration relationship and a kind of a short-run relationship between these two factors. Finally an attempt was made to identify causal relationships between them using the Granger causality test.

金融商品的價格變動是投資人用以判斷獲利與否的重要工具，因為價格變動不易精確預測，所以常利用其他變數輔助預測價格變動，其中以交易量最常被投資人用來分析價格變動。本文是利用台灣首檔指數型股票基金「台灣50指數股票型基金，簡稱TTT」，分析基金的價格變動與交易量之間的關係。 由於TTT具有「實物申購╱買回」機制，當TTT發生折溢價現象時，投資者會利用此機制進行策略性的投資。因此，「實物申購╱買回」機制使用，會對TTT交易量產生影響，並且使得基金淨值與價格更為貼進。所以本文也將分析TTT折溢價與交易量之間的關係。 本研究利用Granger因果關係理論檢測變數之間的因果關係，實證結果發現，TTT的交易量與價格變動呈現雙向因果關係，且折溢價對於交易量具有單向因果關係，即折溢價可以解釋和預測交易量變動，並且折溢價偏離的現象在半天之內會消失。因此，歸論「實物申購╱買回」機制能有效發揮其作用。 / This study examines intraday patterns of the Taiwan Top 50 Tracker Fund (TTT), with special emphasis on the causal relationship between trading volume and return, and the causal relationship between trading volume and deviation ratio. We find strong intraday seasonality, namely the W-shaped trading pattern which appeared to be caused by the so-called lunch-break effect. After accounting for this apparent seasonality, and by employing the Granger causality test, we find that there is a causal bi-direction relationship between trading volume and absolute return. However, there only exists a uni-directional causal relationship from the deviation ratio to trading volume, but not vice versa. Also, the deviation is disappeared within half day.

In this work, we study and extend algorithms for Sparse Regression and Causal Inference problems. Both the problems are fundamental in the area of Data Science. The goal of regression problem is to nd out the \best" relationship between an output variable and input variables, given samples of the input and output values. We consider sparse regression under a high-dimensional linear model with strongly correlated variables, situations which cannot be handled well using many existing model selection algorithms. We study the performance of the popular feature selection algorithms such as LASSO, Elastic Net, BoLasso, Clustered Lasso as well as Projected Gradient Descent algorithms under this setting in terms of their running time, stability and consistency in recovering the true support. We also propose a new feature selection algorithm, BoPGD, which cluster the features rst based on their sample correlation and do subsequent sparse estimation using a bootstrapped variant of the projected gradient descent method with projection on the non-convex L0 ball. We attempt to characterize the efficiency and consistency of our algorithm by performing a host of experiments on both synthetic and real world datasets. Discovering causal relationships, beyond mere correlation, is widely recognized as a fundamental problem. The Causal Inference problems use observations to infer the underlying causal structure of the data generating process. The input to these problems is either a multivariate time series or i.i.d sequences and the output is a Feature Causal Graph where the nodes correspond to the variables and edges capture the direction of causality. For high dimensional datasets, determining the causal relationships becomes a challenging task because of the curse of dimensionality. Graphical modeling of temporal data based on the concept of \Granger Causality" has gained much attention in this context. The blend of Granger methods along with model selection techniques, such as LASSO, enables efficient discovery of a \sparse" sub-set of causal variables in high dimensional settings. However, these temporal causal methods use an input parameter, L, the maximum time lag. This parameter is the maximum gap in time between the occurrence of the output phenomenon and the causal input stimulus. How-ever, in many situations of interest, the maximum time lag is not known, and indeed, finding the range of causal e ects is an important problem. In this work, we propose and evaluate a data-driven and computationally efficient method for Granger causality inference in the Vector Auto Regressive (VAR) model without foreknowledge of the maximum time lag. We present two algorithms Lasso Granger++ and Group Lasso Granger++ which not only constructs the hypothesis feature causal graph, but also simultaneously estimates a value of maxlag (L) for each variable by balancing the trade-o between \goodness of t" and \model complexity".

Trade liberalization in Kenya started in the early 1980s with the structural adjustment programmes, and continued under the multilateral framework of the WTO. During the same period, the incidence of poverty and level of inequality also worsened. The government’s focus on trade negotiations has been to ensure that there is policy space for the daily running of the economy even though welfare impacts are also important. Non-state actors have argued that trade liberalization has negatively affected the poor; particularly the farmers, since they cannot compete with the developed countries whose farmers enjoy significant government support through subsidies, making their products much cheaper in the world market. Government officials, on the other hand, contend that trade liberalization is good as it brings in competition and transfer of technology which is good for an economy. It is important to examine how trade liberalization has affected household’s welfare in Kenya, given that this kind of analysis has not been conducted in Kenya. This study is unique because it does not assume the existence of a trade liberalization– poverty relationship, unlike most studies. It uses a multi-method approach to first test the hypothesis that there is no statistically significant relationship between trade liberalization and poverty, it further tests for multiplier effects of trade liberalization on poverty determinants. Trade Liberalization and poverty is found to have a stochastic relationship, furthermore investments and capital stock were found to significantly affect poverty determinants in the stochastic model. Due to unavailability of household welfare measure data in time series, a CGE model was used to establish the dynamics of trade liberalization on poverty at a point in time using the 2003 Social Accounting Matrix Data for Kenya. Overall, trade liberalization accompanied by FDI had the greatest impact on household welfare. Trade liberalization had a positive impact on household welfare since household incomes and consumption increased. Micro simulations results, based on changes in consumption, also showed that poverty incidence reduced for all households, even though the urban households experienced higher decreases. The study found that there was little difference in protecting sensitive products and not protecting them; secondly, trade liberalization accompanied by foreign direct investment had greater impact on improving the household welfare. Consumption and incomes increased, resulting in overall poverty reduction. The welfare of urban households was much higher than rural households in terms of income and consumption increases. However, income inequality was much higher in urban than rural areas. / Economics / D. Litt. et Phil. (Economics)

Exponential smoothing algorithms are very attractive for the practical world such as in industry. When considering bivariate exponential smoothing methods, in addition to the properties of univariate methods, additional properties give insight to relationships between the two components of a process, and also to the overall structure of the model. It is important to study these properties, but even with the merits the bivariate exponential smoothing algorithms have, exponential smoothing algorithms are nonstatistical/nonstochastic and to study the properties within exponential smoothing may be worthless. As an alternative approach, the (bivariate) ARIMA and the structural models which are classes of statistical models, are shown to generalize the exponential smoothing algorithms. We study these properties within these classes as they will have implications on exponential smoothing algorithms. Forecast properties are studied using the state space model and the Kalman filter. Comparison of ARIMA and structural model completes the study. / Mathematical Sciences / M. Sc. (Statistics)

This study provides evidence of the relationship between bank-granted credit and business cycles in South Africa. The study is conducted in three phases, namely qualitative research (Phase I), quantitative research (Phase II) and econometric analysis (Phase III). A sequential (connected data) mixed methodology (Phase I and II) is used to collect and analyze primary data from market participants. The qualitative research (Phase I) involves structured interviews with influential or well informed people on the subject matter. Phase I of the study is used to understand the key determinants of bank credit in South Africa and to appreciate how each of the credit aggregates behaves during alternate business cycles. Qualitative survey results suggest key determinants of commercial bank credit in South Africa as economic growth, collateral value, bank competition, money supply, deposit liabilities, capital requirements, bank lending rates and inflation. The qualitative results are used to formulate questions of the structured survey questionnaire (Quantitative research- Phase II). The ANOVA and Pearman’s product correlation analysis techniques are used to assess relationship between variables. The quantitative results show that there is direct and positive relationship between bank lending behavior and credit aggregates namely economic growth, collateral value, bank competition and money supply. On the other hand, the results show that there is a negative relationship between credit growth and bank capital and lending rates. Overall, the quantitative findings show that bank lending in South Africa is procyclical. The survey results indicate that the case for demand-following hypothesis is stronger than supply-leading hypothesis in South Africa. The econometric methodology is used to augment results of the survey study. Phase III of the study re-examines econometric relationship between bank lending and business cycles. The study employs cointegration and vector error correction model (VECM) techniques in order to test for existence of long-run relationship between the selected variables. Granger causality test technique is applied to the variables of interest to test for direction of causation between variables. The study uses quarterly data for the period of 1980:Q1 to 2013:Q4. Business cycles are determined and measured by Gross Domestic Product at market prices while bank-granted credit is proxied by credit extension to the private sector. The econometric test results show that there is a significant long-run relationship between economic growth and bank credit extension. The Granger causality test provides evidence of unidirectional causal relationship with direction from economic growth to credit extension for South Africa. The study results indicate that the case for demand-following hypothesis is stronger than supply-leading hypothesis in South Africa. Economic growth spurs credit market development in South Africa. Overall, the results show that there is a stable long-run relationship between macroeconomic business cycles and real credit growth in South Africa. The results show that economic growth significantly causes and stimulates bank credit. The study, therefore, recommends that South Africa needs to give policy priority to promotion and development of the real sector of the economy to propel and accelerate credit extension. Economic growth is considered as the significant policy variable to stimulate credit extension. The findings therefore hold important implications for both theory and policy. / Business Management / D.B.L.