| dc.contributor.advisor | 張清福 | zh_TW |
| dc.contributor.advisor | Chang,Chingfu | en_US |
| dc.contributor.author (作者) | 魏向璟 | zh_TW |
| dc.contributor.author (作者) | Wei,Hsiang-Chin | en_US |
| dc.creator (作者) | 魏向璟 | zh_TW |
| dc.creator (作者) | Wei,Hsiang-Chin | en_US |
| dc.date (日期) | 2005 | en_US |
| dc.date.accessioned | 11-九月-2009 17:24:19 (UTC+8) | - |
| dc.date.available | 11-九月-2009 17:24:19 (UTC+8) | - |
| dc.date.issued (上傳時間) | 11-九月-2009 17:24:19 (UTC+8) | - |
| dc.identifier (其他 識別碼) | G0093353040 | en_US |
| dc.identifier.uri (URI) | https://nccur.lib.nccu.edu.tw/handle/140.119/30181 | - |
| dc.description (描述) | 碩士 | zh_TW |
| dc.description (描述) | 國立政治大學 | zh_TW |
| dc.description (描述) | 會計研究所 | zh_TW |
| dc.description (描述) | 93353040 | zh_TW |
| dc.description (描述) | 94 | zh_TW |
| dc.description.abstract (摘要) | 基於SEC之要求，越來越多美國金融機構於其財務報表附註中揭露金融交易資產之風險值；然而計算風險值涉及到許多假設，於是導致過去部分文獻對於風險值資訊揭露之可靠性產生質疑。本研究以風險值之揭露對於報表使用者之資訊價值作為研究課題；為求與附註揭露之風險值資訊比較，本研究以公司帳列之金融交易資產(Trading Assets)、金融交易收入(Trading Revenue)為基礎，利用蒙地卡羅模擬法模擬帳列金融交易資產於次期可能產生之最大潛在損失，並且透過OLS regression及panel data model探討： (1)風險值及金融交易資產潛在可能損失是否可以預測次期金融交易收入波動 (2)風險值與金融交易資產潛在可能損失資訊之提供是否影響次期股票交易量 (3)風險值與金融交易資產潛在可能損失資訊是否可以有效預測次期股價報酬 率變異。 實證結果顯示，風險值之揭露與金融交易資產潛在可能損失之資訊對於預計次期金融交易收入之波動與股價報酬率變異均呈現顯著正相關；易言之，上述兩種資訊之揭露均提供增額之資訊價值。惟另方面，風險值之揭露與金融交易資產潛在可能損失之資訊卻與次期股票交易量呈正相關，也就是說上述兩種資訊的揭露反而會造成投資人降低長期投資持有的意願。 | zh_TW |
| dc.description.abstract (摘要) | Financial institutions in the United States are required by the Securities and Exchange Commission to disclose their Value at Risk (VaR) in the footnotes of the financial statements. Over the years, VaR has been used by institutional investors, industry consultants, and regulators as one of the key measures of market risk. However, there are a number of approaches to calculating VaR and some of them may involve various statistical models and assumptions. Due to the fact that different models and assumptions may be used, the VaR numbers produced by different institutions are difficult to compare with one another. The usefulness of these numbers is therefore decreased. This thesis examines the usefulness of disclosures of VaR information. In order to compare with VaR disclosures, the implied potential maximum losses of trading assets are simulated by using Monte Carlo simulation. We then employ the OLS regression and the panel data models to investigate the following research questions: (1)whether VaR and implied potential maximum losses of trading assets disclosed by financial institutions are instrumental in predicting the variability of trading revenue for the next quarter; (2)whether VaR and implied potential maximum losses of trading assets disclosed by financial institutions affect investors` investing decision; (3)how useful are VaR and implied potential maximum losses of trading assets in predicting the volatility of daily stock return next quarter. The empirical results indicate that VaR and implied potential maximum losses of trading assets are significantly related to the variability of trading revenue and the volatility of daily stock returns next quarter. This evidence suggests that both types of disclosures provide incremental information on predicting the variability of trading revenue and investment risk in the future. Nevertheless, we also find that both VaR disclosures and implied potential maximum losses of trading assets are positively associated with future average stock trading volume, implying that investors tend to trade stock more frequently when the market risk information is disclosed. | en_US |
| dc.description.tableofcontents | Contents I. INTRODUCTION 1 1. Motivation 1 2. Purposes of the Thesis 3 3. Research Questions 3 4. Layout of the Thesis 5 II. LITERATURE REVIEW 6 1. What Market Risk is? 6 2. An Overview of FRR No.48 6 3. Market Risk Research 8 III. RESEARCH DESIGN 11 1. VaR as a Market Risk Measure 11 2. Simulating the Path with One Random Variable 12 3. Hypothesis 16 4. Research Models and Data Source 18 IV. RESEARCH RESULTS 23 1. Variables Description 23 2. The Empirical Results 27 V. CONCLUSIONS 44 1. The Aims of the Research 44 2. The Contributions of the Research 45 3. Conclusions and Implications 46 4. Limitations and the Avenues for Further Research 47 References 49 Contents Table 1: Variables and their Descriptions 26 Table 2: Description Statistics 29 Table 3: Estimation of regression of banks’ future trading revenue on disclosed quarterly VaR in the financial statements 32 Table 4: Estimation of regression of banks’ future trading revenue on calculated quarterly VaR in the financial statements 33 Table 5: Estimation of regression of average stock trading volume next quarter on disclosed quarterly VaR 35 Table 6: Estimation of regression of average stock trading volume next quarter on calculated quarterly VaR 37 Table 7: Estimation of regression of volatility of daily stock returns in the subsequent quarter on disclosed quarterly VaR 39 Table 8: Estimation of regression of volatility of daily stock returns in the subsequent quarter on calculated quarterly VaR 41 | zh_TW |
| dc.language.iso | en_US | - |
| dc.source.uri (資料來源) | http://thesis.lib.nccu.edu.tw/record/#G0093353040 | en_US |
| dc.subject (關鍵詞) | 市場風險 | zh_TW |
| dc.subject (關鍵詞) | 風險值 | zh_TW |
| dc.subject (關鍵詞) | 蒙地卡羅模擬法 | zh_TW |
| dc.subject (關鍵詞) | 幾何布朗運動 | zh_TW |
| dc.subject (關鍵詞) | Market risk | en_US |
| dc.subject (關鍵詞) | Value at Risk (VaR) | en_US |
| dc.subject (關鍵詞) | Monte Carlo simulation | en_US |
| dc.subject (關鍵詞) | Geometric Brownian Motion | en_US |
| dc.title (題名) | 會計揭露對於市場風險之資訊內涵 | zh_TW |
| dc.title (題名) | How informative are accounting disclosures about market risk? | en_US |
| dc.type (資料類型) | thesis | en |
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