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運用文字探勘及財務資料探討中國市場營運概況文字敘述及財務表現之一致性 / Using Text Mining and Financial Data to Explore for Consistency between Narrative Disclosure and Financial Performance in China Market

本研究透過文字探勘對中國大陸2011年上市公司的MD&A進行分析,並搭配財務資訊相互比對,分析中國大陸上市公司所揭露的MD&A是否誇大,再透過實證研究分析造成中國大陸上市公司MD&A揭露誇大與否的原因。本研究樣本為2011年中國大陸所有上市公司所揭露的MD&A及相關財務資訊,MD&A非量化資訊係運用Stanford Word Segmenter斷詞資料庫、正負向詞典、TFIDF、K-means等技術進行群集分析,並結合財務資訊的K-Means群集分析,分析出中國大陸2011年上市公司MD&A揭露是否誇大;再代入公司規模、管理階層對風險的偏好程度、獲利能力、償債能力等變數,分析影響公司MD&A揭露誇大與否的因素。研究結果顯示,公司規模、管理階層對風險的偏好程度與公司MD&A資訊揭露傾向於不誇大呈顯著負相關,而公司獲利能力、公司償債能力與公司MD&A資訊揭露傾向於不誇大呈顯著正相關。本研究希望提供投資人另一種分析MD&A的方式,並建議投資人運用上市公司所揭露的MD&A資訊時,需額外考慮公司MD&A揭露有無誇大的情勢,並作適度的調整,以降低投資風險,擬定正確的投資決策。 / This study presented a way to analyze MD&A on listed companies in 2011 in China via text mining, crossing comparison with its fiscal information, validating whether disclosed MD&A on the China listed companies is overstated and its possible factors by empirical study. The research sample is the disclosed MD&A and related financial information on China listed companies in 2011. Qualitative narrative MD&A utilizes Stanford Word Segmenter, NTUSD, TFIDF and K-means performing cluster analysis, combining K-means cluster analysis of financial information, figuring out disclosed MD&A of China listed companies in 2011 exaggerated. By the variables of company scale, the Management of risk preference, profit, liquidity analyzes the effect factor of whether disclosed MD&A exaggerated or not. According to the research, the disclosed MD&A tending not to exaggerate is significantly and negatively related to company scale and the management of risk preference. Profitability and liquidity are significantly and positively relationship to disclosed MD&A tending not to exaggerate. The research is providing another way of reading MD&A with investors, suggesting investors need to take whether disclosed MD&A is overstated into consideration, and adjusting in appropriate in reducing the investment risk when making Investment decisions.

Identiferoai:union.ndltd.org:CHENGCHI/G0100353054
Creators鄭凱文
Publisher國立政治大學
Source SetsNational Chengchi University Libraries
Language中文
Detected LanguageEnglish
Typetext
RightsCopyright © nccu library on behalf of the copyright holders

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