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  • 學位論文

台灣總體經濟變數與店頭指數相關性之研究

The Relationships between Macroeconomic Factors and OTC Indices

指導教授 : 楊浩二
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摘要


我國證券市場自民國五十一年成立迄今,已有四十年餘的歷史,國內股票市場可分為集中市場及店頭市場,而不論在集中市場或店頭市場,影響股票市場的因素很多,大致可分為非系統性因素及系統性因素。非系統性因素是指某一公司獨有而隨機變動的因素,系統性因素則是指政治、總體經濟、社會、環保、文化等因素,其中僅總體經濟因素有客觀之數據資料可供分析。既然總體經濟因素是影響股票市場的重要因素,當然,也是本研究的研究重點與主要變數。 本文以多元迴歸模式,利用SPSS統計軟體作為分析工具,探討總體經濟變數中那些變數對店頭市場整體股價指數、金融類股股價指數及證券類股股價指數存在具有顯著之相關性,同時找出最佳的多元迴歸模式。藉由實證研究與分析,得到下列結論。 一、總體經濟變數與店頭市場整體股價指數關係 (1)以相關分析法得知15個總體經濟變數中CPI消費者物價指數、WPI躉售物價指數、M1a年增率、M1b年增率、M2年增率、綜合判斷分數、同時指標、領先指標、出口年增率、進口年增率、外銷訂單年增率及工業生產年增率與店頭市場整體股價指數具有正相關,其中與綜合判斷分數相關係數為0.812,為高度正相關。而失業率、外匯存底及台灣銀行基本放款利率具有負相關,其中與失業率相關係數為-0.702,為高度負相關。主要原因失業率高顯示總體經濟景氣不佳,不利股市發展;基本放款利率越高,顯示企業資金成本越高,獲利越少,每股盈餘越低,本益比越低,股價指數自然越低。 (2)在逐步迴歸法下,進入以顯著水準α=0.01為標準,以逐步迴歸法來篩選變數,自15個總體經濟變數中選入6個自變數,分別為M2年增率(X5)、綜合判斷分數(X6)、同時指標(X7)、領先指標(X8)、外銷訂單年增率(X11)及失業率(X13),調整後判定係數(Ra2)為0.804,F檢定值為40.225,α=0.01,達顯著性,表示迴歸模型的解釋力相當高,是具有統計意義的。 二、總體經濟變數與金融類股價指數關係 (1)以相關分析法得知15個總體經濟變數中CPI消費者物價指數、WPI躉售物價指數、M1a年增率、M1b年增率、M2年增率、綜合判斷分數、領先指標及工業生產年增率等8個自變數與金融類股價指數呈正相關,有3個自變數與金融類股價指數呈負相關,分別是失業率(X13)、外匯存底(X14)及台灣銀行基本放款利率(X15),主要原因為失業率高及基本放款利率越高,均會對企業獲利造成不利影響,而金融機構獲利主要來源為對企業的放款,企業獲利不佳則會導致金融機構逾放比過高,進而影響金融機構的獲利,因此,失業率及基本放款利率與金融類股價指數呈負相關。 (2)在逐步迴歸法下,進入以顯著水準α=0.01為標準,以逐步迴歸法來篩選變數,自15個總體經濟變數中選入3個自變數,分別為綜合指標(X6)、外銷訂單年增率(X11)及同時指標(X7),調整後判定係數(Ra2)為0.593,F檢定值為13.523,α=0.01,達顯著性,表示迴歸效果具有統計意義。 三、總體經濟變數與證券類股價指數關係 (1)以相關分析法得知15個總體經濟變數中CPI消費者物價指數、WPI躉售物價指數、M1a年增率、M1b年增率、綜合判斷分數、同時指標、領先指標、進口年增率、工業生產年增率及外匯存底等10個自變數與證券類股價指數呈正相關,僅有失業率(X13)1個自變數與證券類股價指數呈負相關,主要原因為失業率越高,表示總體經濟景氣不佳,導致投資人收入減少,降低投資人投資股市意願,而證券公司以收取投資人的手續費為主要收入來源,失業率高,投資人收入減少,證券公司獲利自然縮水,因此,失業率與證券類股價呈負相關。 (2)在逐步迴歸法下,進入以顯著水準α=0.01為標準,以逐步迴歸法來篩選變數,自15個總體經濟變數中選入4個自變數,分別為外匯存底(X14)、躉售物價指數(X2)、M1b年增率(X4)及消費者物價指數(X1),整後判定係數(Ra2)為0.895,F檢定值為44.728,α=0.01,均達顯著,表示迴歸效果具有統計意義。

並列摘要


Taiwan’s security market has been established since 1962, and now it can be classified into the TSE market and the OTC market. In TSE or OTC market, there are many factors influencing the overall stock market’s performance, and those factors are either systematic or non-systematic. Nonsystematic factors are the variables that are mainly caused by one or more companies’ business strategy or behavior whereas systematic factors are mostly attributed to overall market environments, such as politics, social, macroeconomics, and cultures. Among those systematic variables, only macroeconomic may have objective information or data to be relied upon for the prospective analysis given its statistical confirmations. Hence, macroeconomic factors are the main focus in this research, and their impacts on Taiwan’s stock market are also the focal point of the research. This paper used multiple regression models with the aid of SPSS statistical software in supporting the investigation of what macroeconomic variables can impact the Taiwan OTC market, financial stock price index, security stock price index, and their correlation with those variables. And through the above analysis, the research will cover the most representative multi-variable regression model. From the empirical research and analysis in this research, following conclusions have been achieved. iii 1. The Relationship Between Macroeconomic Variables and OTC Overall Stock Price Index (1). Among 15 macroeconomic variables, Consumer Price Index (CPI), Wholesale Price Index (WPI), M1a annual growth rate, M1b annual growth rate, M2 annual growth rate, composition index, coincident indicators, leading indicators, export annual growth rate, import annual growth rate, annual growth rate of export order and industrial production annual growth rate have positive relationship with OTC overall stock price index. Among these variables, composition index has the highest positive correlation of 0.812. Independent variables such as unemployment rate, foreign reserves and Taiwan Bank prime rate have negative relationship with dependent variable OTC overall stock price index. Among these, unemployment rate has highest negative relationship of -0.702.The main reason is duet to high unemployment indicate macroeconomic prosperity is in depress, which is not good for stock market development. Higher the prim rate means higher the financing capital for enterprise, less profit return, each share dividend is less, lower the benefit, spontaneously the stock price index is also lower. (2). Under stepwise regression method, introduce level of significance α=0.01 as standard and choose 6 independent variables, which are M2 annual growth rate(Y5), composition index (Y6), coincident indicators(Y7), leadings indicators(Y8), annual growth rate of export order(Y11)and unemployment rate(Y13). Adjusted determination coefficient (Ra2) is 0.804,F test value is 40.225,α=0.01, which are all significant. It means that the regression model can explain the result and the F test value is statistically significant. 2. The Relationship Between Macroeconomic Variables and Financial Stock Price Index (1). Among 15 macroeconomic variables,Consumer Price Index (CPI), Wholesale Price Index (WPI), M1a annual growth rate, M1b annual growth rate, M2 annual growth rate, composition index, leadings indicators and industrial production annual growth rate, there are 8 independent variables have positive relationship with financial stock price index, and 3 of them are having negative relationship with financial stock price index, which are unemployment rate, foreign reserves and Taiwan Bank prim rate. The main reason is because high unemployment rate and prim rate are having negative influence towards enterprise benefits;moreover, the main profit resources of financial institution are from enterprise loan, and bad profit return, which will lead to exceed loans being release and so affect the profitability of financial institution. Thus, unemployment rate and prim rate are having negative relationship toward financial price index. (2). Under stepwise regression method, introduce level of significance α=0.01 as standard and choose 3 independent variables out of 15 macroeconomic variables, which are composition index (X6),annual growth rate of export order(X11)and coincident indicators(X7). The adjusted determination coefficient(Ra2)is 0.593, F test value is 13.523,and α=0.01, which are all significances, and it means regression effect has statistical meaning. The regression model is 3. The Relationship Between Macroeconomic Variables and Security Stock Price Index (1). Among 15 macroeconomic variables, Consumer Price Index (CPI), Wholesale Price Index (WPI), M1a annual growth rate, M1b annual growth rate, composition index, coincident indicators, leadings indicators, import annual growth rate, industrial production annual growth rate, foreign reserves, there are 10 independent variables have positive relationship with security price index, and only 1 independent variable has negative relationship with it, which is unemployment. The main reason is the higher the unemployment means the macroeconomic prosperity is in depress, which lead reduce in investor’s income, and then decrease their willingness to invest in stock market;moreover, the commission fee is the main income sources of security company. High unemployment rate means less income, and then profits for security companies has reduce, thus unemployment rate has negative with security price index. (2). Under stepwise regression method, introduce level of significance α=0.01 as standard and choose 4 independent variables out of 15 macroeconomic variables, which are foreign reserves (X14), Wholesale Price index(X2), M1b annual growth rate(X4)and Consumer Price Index(X1). The adjusted determination coefficient(Ra2) is 0.895, F test value is 44.728,and α=0.01;they are all significances, and it means regression effect has statistic meaning. The regression model is

並列關鍵字

Macroeconomic Factors OTC Indices

參考文獻


Yi-Mao, Chen,(陳溢茂) Yen-Shi,(施燕) Li-Lin Zen,(鄭麗玲) “ Causality relationship of Stock price, interest rate and savings in bank 0 implementation of VAR model”, Global Investor, Volume 14, 2nd edition, 1992, 48-59.
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Chun-Ying, Chang,(張峻穎) “Empirical research of interaction between macroeconomic variances and stock index” National Taiwan University of Science and Technology Department of Management postgraduate thesis, 2000.
Fu-Yong, Chu,(朱博湧) Shou-Shan Wu,(吳壽山) “First exploration on macroeconomic model of risk return under change of Taiwan financial environment”, Monthly Science Development, Volume 19, 1st edition, 1991, 16-24.
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