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数 据 与 实 证 研 究. 高 宁 博 士 国 泰安 金融教育集团 常 务 副 总裁 西安交通大 学 教授 香港浸 会 大 学 商 学 院 Honorary Associate 香港浸 会 大 学 公司管制 与 金融政策研究中心 Research Fellow. http://www.gtafe.com. 什么是实证研究？ 以事实、实际情况和收集到的数据为对象，通过分析、计算、实验、研究，解释和预测会计金融实务，回答 “ 实际是什么 ” 的问题 。. ◎ 实证研究要求客观、准确、理性的描述现实 ◎ 实证研究以解释现实为目的，认为存在就是事实
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数 据 与 实 证 研 究 高宁博 士 国泰安金融教育集团常务副总裁 西安交通大学教授 香港浸会大学商学院 Honorary Associate 香港浸会大学公司管制与金融政策研究中心Research Fellow http://www.gtafe.com
什么是实证研究？ • 以事实、实际情况和收集到的数据为对象，通过分析、计算、实验、研究，解释和预测会计金融实务，回答 “实际是什么”的问题。
◎ 实证研究要求客观、准确、理性的描述现实 ◎ 实证研究以解释现实为目的，认为存在就是事实 ◎ 实证研究采用客观中立的立场 ◎ 目前，在国际上，实证研究方法广泛的应用在经济、金融、会计等社会学科的研究中
实 证 研 究 的 发 展 与 趋 势
----实证经济学 1953 弗里德曼《实证经济学方法论》 发 展 历 程 ----实证会计学 1968 Ball，R.J., P.Brown 《An Empirical Evaluation of Accounting Income Numbers》《Journal of Accounting Research》 1986 Watts， Zimmerman《实证会计理论》 20世纪80年代《Accounting Review》上实证性研究的论文占半数以上，有的年份还高达81％。现在实证研究已成为会计，金融研究的主流。 趋 势 由于金融市场每天都产生海量的数据，这些数据又是从真实的交易 过程中产生的, 这一特性使实证研究成为现代金融研究的主流话语” ――Ross
推动实证研究 发展的因素 （William Beaver)
推动实证研究发展的因素（William Beaver) 1 财务和经济学的发展 2 证券市场在经济中的地位 政府对证券市场的积极监管，不断推出新的课题 3 4 机构投资者占股权比重的增大 5 • 计算机技术和数据库的发展 6 学术刊物受重视程度的增强
实 证 的 要 素 • 数据：反映客观状况的数字材料。 • 模型：刻画客观现象的数学形式。 • 假设：对所研究问题的结果或状态的 一种预期。 • 检验：利用数据，使用统计学知识对假设的统计显著性作出判断。 • 推理：基于知识和经验对假设检验结果进行推理。 • 结论：利用假设检验的结果，通过合情的逻辑推理得出的结论，观点。
实 证 研 究 方 法 步 骤 确立研究课题 寻找相关理论 提出命题假设 设计研究方案 搜集事实数据 分析数据检验命题 得出研究结论
CSMAR 实 证 论 文 举 例
题 目 Information Content and Timing of Earnings Announcements 作 者 陈工孟 高 宁 郑子云（香港理工大学） Journal of Business Finance and Accounting,January 2005, Vol 32, Iss. 1- 2, Pg. 65－95 发表刊物 摘 要 文章研究了中国上市公司盈余公告时间选择对股票交易量和未预期收益的影响。研究发现，与较晚月份公告盈余的公司相比，较早月份进行年度盈余公告的公司具有较强的股票交易量反应。文章认为愿意早些公告盈余的公司往往拥有利好的信息，并且这些较早的盈余公告含有更大的信息量,带来较大的交易量增幅和未预期收益；较晚公告盈余的公司则往往拥有利差的信息，而且更容易被市场预期,因而带来的交易量增幅和未预期收益也较小。
以1995年至2002年间发行A股或同时发行A，B股，在时间区间内发表年度盈余公告的上市公司为研究样本。样本容量为3802。
CSMAR 总 体 样 本 容 量
文 献 回 顾 和 假 设
为什么选交易量而不是价格 • Bamber, Barron and Stober (1997) suggest that trading volume is related to the magnitude of the disagreement among investors about a firm’s earnings. • Kim and Verrecchia (1991a) argue that price changes reflect the average • change in the aggregate market’s average beliefs, while trading volume • isthe sum of all individual investors’ trades, which also depends on the • prevailing information asymmetry level before disclosure. They suggest • that although all investors have equal access to public pre-disclosure • information, they acquire private pre-disclosure information with • different degrees of precision.
为什么选交易量而不是价格 • Atiase and Bamber (1994) and Kross et al. (1994)suggest that trading volume is an increasing function of the degree of divergent pre-disclosure expectations。 • Bamber and Cheon (1995) argue that the reason for different reactions is that price reactions reflect the average belief revision, while trading volume arises when individual investors make differential belief revisions.
更 进 一 步 的 分 析 • Kim and Verrecchia (1994) suggest that there may be more information asymmetry at the time of an announcement than in a non-announcement period. This is because earnings announcements provide information that allows certain traders to make judgements about a firm’s performance that are superior to the judgements of other traders. • Lobo and Tung (1997) find that the trading volume around quarterly earnings announcements is related to the level of pre-disclosure information asymmetry. For firms with a high level of pre-disclosure information asymmetry, the trading volume is low prior to and after the announcement, but high during the announcement.
更 进 一 步 的 分 析 • Bamber(1986) employs the divergence of earnings forecasts from analysts’ forecasts as a proxy for information asymmetry. She finds that the higher the information asymmetry, the greater the abnormal volume reaction. In this study, we first use unexpected earnings as a control variable for information asymmetry. • Earlier announcements should generate a greater surprise in the market because it is more difficult to predict earlier announcements than later announcements. Chambers and Penman (1984) argue that longer reporting lags provide the opportunity for more of the report’s information to be supplied by other sources, either through search activity by investors, through other voluntary disclosures by firms, or through predictions that are supplied in the earnings releases of earlier reporting firms. • Haw et al. (1999) study the Chinese stock market and find that firms with good news publicize their annual reports earlier than those with bad news, and loss-making firms are the last to release their annual reports. They define the reporting lag as the number of days from the fiscal year-end to the report announcement date.
更 进 一 步 的 分 析 • Earlier announcements should generate a greater surprise in the market because it is • more difficult to predict earlier announcements than later announcements. Chambers and Penman (1984) argue that longer reporting lags provide the opportunity for more of the report’s information to be supplied by other sources, either through search activity by • investors, through other voluntary disclosures by firms, or through predictions that are • supplied in the earnings releases of earlier reporting firms. • Haw et al. (1999) study the Chinese stock market and find that firms with good news • publicize their annual reports earlier than those with bad news, and loss-making firms • are the last to release their annual reports. They define the reporting lag as the number of days from the fiscal year-end to the report announcement date.
时 间 窗 口 的 确 定 1. First, normally due to potential insider trading and information leakage, it is possible that the market reaction starts long before the actual announcements. Consequently, we employ [-20, 2] and [-20, -3] to capture the possible pre- event reaction. 2. Second, in the relatively efficient market, announcement effects should not exist in the long event window. Therefore, we use four short symmetrical event windows to capture announcement effects. They are [-1, +1], [-2, +2], [-5, +5], and [-7, +7]. [-20, 2] [-20, -3] [-1, +1] [-2, +2] [-5, +5] [-7, +7] 共6个
比 较 期 间（beta 期 间） 250 trading days from day –280 to day –31. A time gap between the end of the estimation window and the beginning of the event window (i.e. from day –30 to day –21) is employed to avoid using unusual price or volume data (due to information leaka-ge) for model estimation.
三个不同的时间变量(TEA)定义 • To focus our analysis on the number of tradable days, we define the reporting lag as • the number of working days from the fiscal year-end to the annual release date. • 1. a continuous variable, Announcement Timing Index (ATI), to proxy the reporting lag, which is defined as ATI = n/N, where n is the nth working day from January 1 on which the earnings announcement is made. N is the total number of working days in the period from January 1 to April 30 in the event year.
三个不同的时间变量(TEA)定义 2. the unexpected ATI (UATI), a proxy for the unexpected reporting lag, is defined as the difference between the actual and expected ATI (the expected ATI of the current year should be the same as the ATI of the previous year), UATI = ATIt – ATIt-1. 3. The final TEA is a dummy variable, called MAD, with a value of 1 for March and April announcements and 0 otherwise.
简 单 的 假 设 Null Hypothesis: Firms with earlier and later earnings announcements should receive similar abnormal market reaction. Alternative Hypothesis: Firms with earlier earnings announcements should receive a higher abnormal maket reaction.
主 要 模 型 异常交易量的决定因素多变量回归模型 CATV (CAR) = 0 + 1UEA (UERW, UEGM)+ 2SIZE + 3POWN + 4TEA (UATI, ATI, MAD)+ 5EXCH + iYEARi-5 + jINDj-12 + 18FOR CATV 累积异常交易量 CAR 累积异常收益率 UEA SIZE 人民币计价的总资产的自然 未预期盈余的绝对值 POWN TEA 盈余公告时间 流通股所占百分比 EXCH 交易所哑变量 YEAR 公告年的哑元变量 IND 行业哑变量 FOR 外资股的哑变量
Abnormal Trading Volume around Earnings Announcement by bi-monthly sample
Abnormal Trading Volume around Earnings Announcement by bi-monthly sample
◎Most of the ATVs for all monthly samples are significant, which indicates that the announcements do provide information to the market. ◎ The magnitudes of the ATVs and CATVs for the January and February sample are much greater than those for the March and April sample.
Panel A: Between the Lowest 40% of the ATI Sample and Highest40% of the ATI Sample Lowest 40% of ATISample Highest 40% of ATISample Difference in Mean CATV CATV3 0.0253 0.0141 0.0112cd CATV5 0.0337 0.0182 0.0155cd CATV11 0.0478 0.0229 0.0249cd CATV15 0.0545 0.0258 0.0287ab CATV18 0.0265 0.0298 -0.0033 CATV23 0.0602 0.0479 0.0123
Panel B: Between the Positive UATI Sample and Negative UATI Sample Positive UATI Sample Negative UATI Sample Difference in Mean CATV 0.0106 0.0290 -0.0184cd 0.0132 0.0413 -0.0281cd 0.0160 0.0631 -0.0471cd 0.0166 0.0755 -0.0589cd 0.0110 0.0407 -0.0297a 0.0242 0.0820 -0.0578cd CATV3 CATV5 CATV11 CATV15 CATV18 CATV23
The lowest 40% of ATI samples demonstrates a significantly greater volume reaction than those of the highest 40% of ATI samples. • The negative UATI samples demonstrate a significantly greater volume reaction than those of the positive UATI samples. earlier announcements provide more information content to the market than later announcements do.
The earlier the announcement by one company relative to other companies, • and the earlier the announcement of the company relative to its time of • disclosure of the previous year, the greater the abnormal trading volume. • Greater unexpected earnings (UERW), smaller firm size (SIZE), and • Shanghai stocks (EXCH) also lead to greater volume reactions.
