3. REASERCH METHOD
3.2 DATA AND SAMPLE SELECTION
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3.2 DATA AND SAMPLE SELECTION
This study focuses on the Taiwan capital market and investigates the differences between news and annual financial reports. In order to examine research questions, this study not only collects financial news articles of selected companies but also annual financial statements as well. The detailed processes of data collection are as follows.
The firm list of listed companies of 2013 is taken from the website of Taiwan Stock Exchange (TSE), for an initial sample of 882 companies. Companies in the Finance and Insurance Sector are excluded because of different capital structures and industry characteristics. Annual financial reports and each released dates of listed companies of 2013 are taken from the website of Market Observation Post System (MOPS). The post-release dates of annual financial reports published during a 6-day working-day periods are collected, that is, [0, +5] working days, as the event day being the release day, suggesting that the week after each annual financial reports are released would have an impact on that company’s stock prices.
Most of the data sources used in this study are from Taiwan Economic Journal database (TEJ), as most of the information of public companies is included in the database. For each [0, +5] working days window, which depend on the publishing date for each company, this study collects a number of accounting and financial market variables. As dependent variables for our tests of Hypothesis 1 and Hypothesis 2, some measures of market returns around the date of the release date of the annual financial reports are required. To measure market returns, this study defines CAR as the cumulated abnormal return over the six-day working day window starting on the financial reports published date (0 working day to +5 working day). For each annual financial reports announcement dates, the regression coefficients estimated over the trading day window [−200, −21] relative to an earnings announcement day were used
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to compute abnormal returns during the [0, 5] window. Excluding 20 trading days before financial report announcements avoids the confounding of the estimated coefficient with annual financial report announcements. The sum of the abnormal returns during the [0, 5] event window is the dependent variable.
For control variables implemented for regression, this study collects variables likely associated with the market response, including variables meant to proxy for quantifiable information in the news articles other than language. This study measures the current quarter earnings surprise, SURP as the difference between annual actual earnings and the most recent consensus analyst earnings forecast made prior to the earnings announcement, scaled by stock price measured at the beginning of the year.
The analyst earnings forecasts are calculated as taking average of all forecasts of annual after-tax earnings for 2013, which ranging from 1 to 50 estimates per company. This study defines dummy variable BEAT to be 1 if announced earnings for the year of 2013 meet or exceeded analysts’ expectations (i.e., when SURP ≥ 0) and 0 otherwise.
This study constructs proxies for the concurrent disclosures made with earnings press releases found to be significant in prior research, which indicates that the presence of detailed financial statements, including the announcement of dividend increases and the reporting of nonrecurring earnings components relates to earnings (Hoskin et al.
1986; Francis et al. 2002b). Including the announcement of dividend increases as proxies for other quantifiable information in earnings press releases, this study believes that it is likely to be associated with market returns around the annual financial reporting announcement period. However, because of the adoption of IFRS since 2013, the reporting of nonrecurring earnings components are no longer required for disclosure.
Therefore, we do not include the reporting of nonrecurring earnings components as prior research does.
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In order to identify the presence of detailed financial statements, this study counts words and phrases in financial news articles. This study uses word lists of terms of accounts and wording used in the annual financial reports, such as “total liabilities” or
‘‘from financing activities”, related to the presence of a detailed balance sheet or a statement of cash flows, respectively. To control for dividend increases, compared to prior year, this study uses DIV_INC representing for a firm that dividend declared in 2014 greater than prior year. Then calculates the amount and defines DIV_INC to be 1 if the dividend change is positive. DIV_INC is 0 if the dividend change is less or equal to zero or there was no dividend announcement made in 20141. This variable definition is different to prior research (Davis et al. 2012). In the paper, they define DIV_INC as dividend declaration made during the three-day window surrounding the earnings press release date. This study adopts different meaning and calculation for that since all dividend declaration made didn’t match our six-day window, mostly would be announced later in 2014 but still thinks dividends can be a source of information to the stock market.
Finally, as additional measures of quantifiable information, this study collects book-to-market ratio (BM) as the book value of equity scaled by the market value of equity (both measured at the end of the cur-rent year). This study also collects current year sales (REV) and uses its natural logarithm (LOGREV). This study constructs a variable, FILELAG, equal to the number of days between the annual financial reports release date of each company and average companies to control for the potential for managers to choose when to release skeptically.
After deleting missing data, the numbers of remaining companies and news are 90
1 Though we discuss 2013 financial reports, related information should be announced before March 31, 2014. Therefore, we decide whether there is an increase in dividend by announcement made in 2014.
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and 212, respectively. As described below, the calculation and summary of the samples are summarized in Table3-1 and the industry breakdown is summarized in Table 3-2.
Table 3-1. Results of Selection of Samples
2013 listed companies 882
Companies with news 161
Delete companies without sufficient data 71
Total 90
Table 3-2. Industry Breakdown Two-digit
of SIC
Industry
Number of Firms
Percentage
09 Manufacture of Beverages 1 1.11
12 Manufacture of Wearing Apparel and Clothing Accessories
2 2.22
25 Manufacture of Fabricated Metal Products 1 1.11
08 Manufacture of Food Products 2 2.22
22 Manufacture of Plastics Products 1 1.11
29 Manufacture of Machinery and Equipment 4 4.44 38 Waste Collection, Treatment and Disposal
Activities; Materials Recovery
1 1.11
18 Manufacture of Chemical Material 7 7.78
20 Manufacture of Pharmaceuticals and Medicinal Chemical Products
1 1.11
21 Manufacture of Rubber Products 1 1.11
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Two-digit of SIC
Industry
Number of Firms
Percentage
23 Manufacture of Other Non-metallic Mineral Products
2 2.22
26 Manufacture of Electronic Parts and Components
27 30.00
27 Manufacture of Computers, Electronic and Optical Products
16 17.78
30 Manufacture of Motor Vehicles and Parts 1 1.11
41 Construction of Buildings 1 1.11
47-48 Retail Trade 7 7.78
50 Water Transportation 2 2.22
51 Air Transport 1 1.11
55 Accommodation 1 1.11
56 Food and Beverage Service Activities 1 1.11
61 Telecommunications 1 1.11
62 Computer Systems Design Services 1 1.11
64 Financial Intermediation 1 1.11
67 Real Estate Development Activities 6 6.67
45-46 Wholesale Trade 1 1.11
Total 90 100.00
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