dc.contributor.advisor | 劉文卿 | zh_TW |
dc.contributor.author (Authors) | 楊昇達 | zh_TW |
dc.contributor.author (Authors) | Yang, Sheng Ta | en_US |
dc.creator (作者) | 楊昇達 | zh_TW |
dc.creator (作者) | Yang, Sheng Ta | en_US |
dc.date (日期) | 2005 | en_US |
dc.date.accessioned | 18-Sep-2009 14:38:05 (UTC+8) | - |
dc.date.available | 18-Sep-2009 14:38:05 (UTC+8) | - |
dc.date.issued (上傳時間) | 18-Sep-2009 14:38:05 (UTC+8) | - |
dc.identifier (Other Identifiers) | G0933560341 | en_US |
dc.identifier.uri (URI) | https://nccur.lib.nccu.edu.tw/handle/140.119/35284 | - |
dc.description (描述) | 碩士 | zh_TW |
dc.description (描述) | 國立政治大學 | zh_TW |
dc.description (描述) | 資訊管理研究所 | zh_TW |
dc.description (描述) | 93356034 | zh_TW |
dc.description (描述) | 94 | zh_TW |
dc.description.abstract (摘要) | 近年來,投資理財的重要性與日俱增;但是,一般投資大眾往往無法掌握市場運作產生的資料、資訊;一方面是因為市場上流動的資訊過多,投資大眾很難有效篩選有幫助的資訊。另一方面則是因為投資人無法了解資料的涵義;因此,聽從某些專家的意見進行投資,可能是沒有時間與信心自行研究的一般投資大眾最終選擇。但是這些市場上所謂的專家們數量眾多,提出的意見可信度究竟有多少;一般投資大眾應該採信那些專家的意見,以降低投資的風險與獲利。本研究將結合內容分析法(Content analysis)與分析網路程序法(Analytic Network Process),以專家提出的意見可信度來評估專家們的價值。預期提供投資人一個參考的依據,選擇價值較高的專家提出之意見進行研究,相信比起直接取用所有的專家意見進行分析,風險與成本會更為降低。 | zh_TW |
dc.description.abstract (摘要) | Recent years, there is more and more importance in investing and managing finances. Because too many information and the investors do not understand what these data really mean, the investors do not have ability to help themselves investing and earning profit. For the investors without time or confidence, it may be the final choice that according to some opinions comes from some professors to invest. However, there are so many professors, which one’s opinion is more reliably and believable? As a general investor, will apply which opinions help us reduce risk and make profit? In this research we combine content analysis and analytic network process to evaluate the professors in the financial market by how much believable in their opinions. We expect that this will support the investor a reference materials. Comparing with analyzing all opinions in the market directly, the risk and cost will be lower if applying the opinions comes from some valuable professors. | en_US |
dc.description.tableofcontents | 摘要 IAbstract II謝辭 III目錄 IV表目錄 VI圖目錄 VII一、序論 11.1 研究背景與現況 11.2 研究目的 21.3 研究架構 2二、文獻探討 32.1 內容分析法 32.1.1 內容分析法的發展 32.1.2 內容分析法的定義 42.1.3 內容分析法的種類 62.2 分析網路程序法 72.2.1 分析網路程序法的簡介 72.2.2 分析網路程序法的流程 82.2.3 分析網路程序法與分析層級程序法之比較 11三、研究方法 133.1 研究模型 133.2 研究流程 143.3 類目定義 153.4 分析專家意見 163.5 建構網路化結構 183.6 計算估計值 223.7 比較估計值與實際值之差異 233.8 評估專家之價值 24四、實證研究 254.1 實證流程 254.2 詞彙分類 26表4-1 詞彙分類結果 264.3 內容分析 274.4 網路化結構與各因子之權重 354.5 計算估計值與相關係數 384.6 評估專家價值 40五、結論與未來發展方向 425.1 結論 425.2 研究限制 425.3 未來發展方向 43參考文獻 44表目錄表3-1 ANP評估尺度表 20表3-2 隨機指標(RI)對照表 21表4-1 詞彙分類結果 26表4-2建弘電子基金的經理人月報分析結果節錄 27表4-3 倍立高科技基金的經理人月報分析結果節錄 29表4-4 建弘電子基金的經理人月報分析結果節錄 32表4-5 倍立高科技基金的經理人月報分析結果節錄 33表4-6 建弘電子基金之各集群與因子給分結果 34表4-7 建弘電子基金94年4月至12月各因子權重計算結果 37表4.8 倍立高科技基金94年4月至10月各因子權重計算結果 38表4-9 國內股市加權指數與電子指數紀錄 39表4-10 94年4月至10月基金成長度實際值與估計值 39表4-11 相關係數計算 40表4-12 夏普比率與資訊比率比較 41圖目錄圖2-1 ANP網路結構 8圖2-2 超級矩陣 9圖2-3 網路化結構範例 10圖3-1 本研究模型 13圖3-2 本研究流程圖 14圖3-3 類目定義模型 15圖3-4 理財商品關聯模型 16圖3-5 影響理財商品指標之各構面網路化結構 18圖3-6 應用分析網路程序法決定影響權重流程圖 19圖4-1 使用Super Decisions Software設定集群畫面 35圖4-2 使用Super Decisions Software設定因子畫面 36圖4-3 用Super Decisions Software建立網路化結構之結果 36圖4-4 用Super Decisions Software依據因子的給分進行成偶比較 37 | zh_TW |
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dc.language.iso | en_US | - |
dc.source.uri (資料來源) | http://thesis.lib.nccu.edu.tw/record/#G0933560341 | en_US |
dc.subject (關鍵詞) | 專家 | zh_TW |
dc.subject (關鍵詞) | 專家意見 | zh_TW |
dc.subject (關鍵詞) | 內容分析法 | zh_TW |
dc.subject (關鍵詞) | 分析網路程序法 | zh_TW |
dc.subject (關鍵詞) | 專家價值 | zh_TW |
dc.title (題名) | 應用專家意見評估金融市場上專家價值之研究 | zh_TW |
dc.type (資料類型) | thesis | en |
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