Abstract
Practitioners have long criticized risk-factor disclosures in the 10-K as generic and boilerplate. In response, regulators emphasize the importance of being specific. By using a computing algorithm, this paper establishes a new measure (Specificity) to quantify the level of specificity of firms’ qualitative risk-factor disclosures. We first examine determinants of variations in Specificity, and document that firms with high proprietary costs provide less specific risk-factor disclosures. More importantly, we find that, controlling for numerous determinants, the market reaction to the 10-K filing is positively and significantly associated with Specificity. In addition, our results suggest that analysts are better able to assess fundamental risk when firms’ risk-factor disclosures are more specific. Together, these findings suggest that more specific risk-factor disclosures benefit users of financial statements.
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Notes
By “specificity” we mean that a higher level of detail is provided conditional on the firm deciding to disclose a particular risk. In other words, given the disclosed risk factors (we control for the proxies for content used in extant research), the construct we are interested in captures the variation in the specificity of the disclosure.
Inferences are unaffected if we do not scale by the total number of words.
For completeness, accounting academics had sought risk-related information in financial reports even before explicit risk disclosure was required by regulatory authorities. For example, Beaver et al. (1970) were the first to study the relation between beta and financial-statement risk measures. They document that market-based beta is positively correlated with a firm’s leverage and earnings variability and negatively correlated with a firm’s dividend payout ratio (see also Hamada 1972; Lev 1974).
The MD&A also includes discussion about risks but is not explicitly focused on risk. Other accounting rules related to risk disclosures include SFAS No. 140, which requires firms with securitized financial assets to disclose information about key assumptions made in determining fair values of retained interests, and SFAS No. 133, which encourages firms to disclose quantitative information about market risks of derivative instruments and hedging activities.
To be precise, FRR 48 is about market risk (e.g., interest rate risk, foreign currency exchange rate risk, and commodity price risk) inherent in market risk sensitive instruments. In contrast, Item 1A requires the discussion of “the most significant factors that make the company speculative or risky.” (Regulation SK, Item 305(c), SEC 2005).
Dechow and You (2015) also provide evidence that is at least indirectly relevant. They predict and find that analysts’ target-price implied returns are a function of the expected dividend distribution, analysts’ private information, and errors with respect to forecasting cash flows and discount rates.
Jørgensen and Kirschenheiter (2003) analytically examine how risk disclosures can affect stock returns in a multi-firm setting.
In addition to these economics-based arguments, supporting arguments also exist in the psychology literature. In particular, according to Construal-Level Theory (e.g., Trope and Liberman 2010), concrete or specific information has greater impact on the judgments of events or objects that are psychologically close to the individuals, whereas abstract or general information has greater impact on the judgments of events or objects that are psychologically distant. To the extent that investors (analysts) and a particular firm they are investing in (covering) can be regarded as psychologically close, risk information that is more specific will have a greater impact on investors’ and analysts’ decisions. In other words, given a certain amount of risk disclosed, a higher level of specificity leads to a greater portion of risk information being processed, enhancing investors’ and analysts’ risk understanding.
The implicit assumption here is that firms can only choose to disclose or to withhold specificity in risk-factor disclosures. They cannot provide misleading or false content. This assumption appears in many analytical works (e.g., Dye 1985; Shin 1994; Kumar et al. 2013). As a practical matter, we control for numerous determinants of variations in risk disclosure when testing for the economic consequences of variations in these disclosures.
Similar to our hypothesis for investors’ market reactions, additional support can also be found from construal-level theory. The firms covered by analysts can be viewed as psychologically close to the analysts because analysts cannot issue any reports without extensive research. Analysts refer to those covered firms as firms in “my/our” coverage (social); analysts are more “confident” about the performance of those firms (hypothetical); analysts’ predictions are based on most “current” data and relevant for “near future” (temporal).
However, alternative arguments exist to support the idea that analysts’ reliability in assessing fundamental risk is not affected by the level of specificity in risk-factor disclosures. To the extent that analysts do not pay attention to risk-factor disclosure by either unintentionally neglecting or intentionally ignoring such information, as is shown in anecdotal evidence, Specificity should not affect analysts’ risk assessments. As an example, consider the argument that “risk-factors are looked upon as boilerplate. The irony of it is that risk-factors are almost meant not to be read, or relied upon” (Reuters 2005).
The term “Named Entity” was developed in Message-Understanding Conferences (MUC) in 1995, and has been widely used in Information Extraction (IE), Question Answering (QA), and other Natural-Language Processing (NLP) applications. Researchers note the importance of recognizing information units such as names and numeric expressions, thus extracting these entities is recognized as one of the important sub-tasks of Information Extraction. NER systems can now identify more sophisticated categories, such as “Odyssey” as a book title, “Windows” as a product name, and “Empire State Building” as a geographical and political entity, and so on.
We use Stanford NER tool13 version 3.2.0 to identify entities in seven categories including Time, Location, Organization, Person, Money, Percent, and Date. Finkel et al. (2005) explain the basic idea of the Stanford NER tool. The theory underneath Stanford NER tool is Conditional Random Field (CRF), first introduced by Lafferty et al. (2001). In our setting, we feed all Item 1A text into the CRF classifier to obtain extracted entities along with the categories they belong to.
A securities class action filed on September 3, 2015, against Wayfair for its failure to identify its specific competitor, Overstock, when discussing competition risk in the risk-factor section, provides further external validation of the idea of counting specific entity names to measure the specificity level of risk-factor disclosures. The class-action lawsuit suggests that investors regard specific competitor names as material information, and this provides us external validation from the investors’ perspective. (The details of the case can be found at the Stanford securities class action database.)
Our approach is consistent with Brown and Tucker (2011), who use unsigned market reactions to examine the usefulness of updated MD&A disclosures.
Note that we do not use the same controls for the market-reaction and analyst tests, as we follow prior literature when choosing control variables. However, no inferences are impacted if we impose a constant set of controls for both analyses.
Using the Fama–French 48 industry classification does not change our inferences.
No inferences are affected if we instead cluster by firm or by firm and year.
Risk-factor disclosure was mandated from December 2005. For completeness, we also download 10-Ks filed in EDGAR in 2005, but few of those files contain risk-factor disclosure sections.
We use a different method from Campbell et al. (2014) to extract Item 1A from 10-K reports. However, the size of our extracted sample is comparable to theirs.
For the smaller sample with available scenario analyses from Morgan Stanley analysts, untabulated statistics show that the sample covers a variety of industries.
In contrast, for the market reaction tests we are able to utilize the full sample of firms.
This data-collection process shows that analyst coverage is not significantly related to Specificity, and that analyst coverage is not concentrated in the high Specificity group but rather distributes slightly toward the bottom group.
The mean of HighSpecificity is not equal to 0.50 because we manually match Morgan Stanley analysts’ reports with the top and bottom quintiles extracted from all sample risk-factor disclosures. A greater number of firms in the bottom quintile are matched, which leads to the mean of HighSpecificity being smaller than 0.5. As a robustness check, we reclassify the sample into two groups based on Specificity. We define HighSpecificity as an indicator variable which equals one when Specificity is above the sample median and zero otherwise. Conclusions are unaltered with this approach.
In untabulated analyses we consider institutional ownership and the Herfindahl Index as additional determinants of Specificity. Including these variables does not increase the explanatory power of the model (and reduces the sample size by 11 %). More importantly, their inclusion does not affect any inferences for our market-reaction and risk-assessment analyses.
No inferences are affected if we exclude any of the control variables.
In terms of economic significance, if Specificity is increased by one standard deviation (and other variables are held unchanged), the market reaction increases by 8 basis points. This effect is similar to that of Specificity-10K and Amount, greater than that of Fog and RiskWords, and smaller than that of TotalLength.
The earnings announcement precedes the 10-K filing date, and we control for any earnings-announcement effect (|CAR EA−1,1 |) following prior literature.
Because year 2006 is the first year after risk-factor disclosures are required, the effects that year could either be weaker due to the transition period’s weaker regulatory enforcement or stronger due to more attention being paid to the new section of information. Excluding year 2006 from the full sample does not affect any conclusions. Further, the negative coefficient for NumItems likely relates to its correlation (0.5) with Segments. If we exclude Segments, the estimated coefficient on NumItems is positive and our other inferences do not change.
It is important to note that even if the Specificity score does not change from one risk disclosure to the next, this does not imply that there is no new information provided in the risk disclosures. Specifically, the risk disclosures could contain completely new information while the specificity level remains the same; thus our setting is different from the typical disclosure setting in the accounting literature. Nevertheless, as an untabulated sensitivity analysis we implement a changes specification in which we use the first difference of both the dependent and all the independent variables. The estimated coefficients on the change in Specificity are positive and statistically significant for both returns and volume, providing further support to our primary analyses.
If the [−60, −11] window includes earnings announcements, the trading volume data in three-day windows around the announcements are excluded in calculation.
An increase in Specificity of one standard deviation is associated with an increase in abnormal trading volume of 2 %. This is similar to the effect for Amount and TotalLength and greater than the effect for Specificity-10K, Fog, and RiskWords.
In untabulated analysis, we alternatively use the number of shares outstanding at the most recent fiscal quarter end as scalar. For Specificity, the estimated coefficient continues to be positive and significant at the 0.05 level. In another untabulated test we reestimate Specificity without removing filler words. Using this measure, both the abnormal returns and volume effects are significant at the 0.05 level.
As explained, in this study we are interested in the textual feature of Item IA and whether greater specificity of disclosure induces greater market reaction. However, to compare with prior research by Campbell et al. (2014) and Kravet and Muslu (2013), we reestimate using signed returns as the dependent variable. Specifically, we test whether the effect documented by Campbell et al. (2014) is amplified for high-Specificity firms. In untabulated analyses we find that this is indeed the case (i.e., the interaction term is negative with a t-value of 1.96).
We partition based on whether the sample firms have non-zero R&D costs or not (zero R&D is also the median for the sample). Whereas the difference in coefficient estimates across partitions is significant for the volume test it is insignificant for the returns test.
There are many opportunities to apply Specificity in accounting research. As but two examples, segment reporting and major customer identification seem fertile grounds in which to employ this new measure.
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Acknowledgments
We have benefited from discussions with Chang Liu regarding the Named Entity Recognition technique. We would also like to thank Yimin Cheng, Mahfuz Chy, Han Wu, Ke Wang (discussant), two anonymous reviewers, and seminar participants at the Rotman School of Management, Hong Kong Polytechnic University, Tsinghua University, University of Lausanne, VU Amsterdam, 2014 Temple University Conference, 2014 Peking University Summer Accounting Camp, 2014 Canadian Academic Accounting Association Meeting, and 2014 American Accounting Association Meeting for valuable comments. Hope gratefully acknowledges the financial support of the Deloitte Professorship.
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Appendices
Appendix 1: Examples of risk-factor disclosure with high and low Specificity
Example with high Specificity: risk-factor disclosures from Williams Controls (December 2007)
ITEM 1A. RISK FACTORS
An investment in our common stock involves a high degree of risk. You should carefully consider the risks discussed below and the other information in this report on Form 10-K before deciding whether to invest in our common stock.
Risks related to our business:
A significant portion of our sales are derived from a limited number of customers, and results of operations could be adversely affected and stockholder value harmed if we lose any of these customers.
A significant portion of our revenues historically have been derived from a limited number of customers. For the years ended September 30, 2007, 2006 and 2005, The Volvo Group accounted for 17, 16 and 18 %, Paccar, Inc. accounted for 14, 17 and 17 %, Freightliner, LLC accounted for 13, 17 and 18 %, Navistar International Corporation accounted for 6, 8 and 7 % and Caterpillar, Inc. accounted for 6, 5 and 5 %, of net sales from continuing operations, respectively. The loss of any significant customer would adversely affect our revenues and stockholder value.
Demand for equipment on which our products are installed may decrease, which could adversely affect our revenues and stockholder value.
We sell our products primarily to manufacturers of heavy trucks, transit busses and off-road equipment. If demand for our customers’ vehicles or equipment decreases, demand for our products would decrease as well. This decrease in demand would adversely impact our revenues and stockholder value.
Our products could be recalled, which could increase our costs and decrease our revenues.
Our vehicle component products must comply with the National Traffic and Motor Vehicle Safety Act of 1966, as amended, and regulations promulgated thereunder, which are administered by the National Highway Traffic Safety Administration (“NHTSA”). If NHTSA finds that we are not in compliance with its standards or regulations, it may, among other things, require that we recall products found not to be in compliance, and repair or replace such products. Such a recall could increase our costs and adversely impact our reputation in our industry, both of which would adversely affect our revenues, profit margins, results of operations and stockholder value. We experienced such a recall with respect to certain of our products in fiscal 2001.
We purchase raw materials and component parts from suppliers and changes in the relationships with such suppliers, as well as increases in the costs of such raw materials and/or component parts, would adversely affect our ability to produce and market our products, which would adversely affect our profit margins, results from operations and stockholder value.
We purchase raw materials and component parts from suppliers to be used in the manufacturing of our products. If a supplier is unable or unwilling to provide us with such raw materials and/or component parts, we may be unable to produce certain products, which could result in a decrease in revenue and adversely impact our reputation in our industry. Also, if prices of such raw materials and/or component parts increase and we are not able to pass on such increase to our customers, our profit margins would decrease. The occurrence of either of these would adversely affect our results from operations and stockholder value.
Our products could be subject to product liability claims by customers and/or consumers, which would adversely affect our profit margins, results from operations and stockholder value.
A significant portion of our products are used on heavy trucks and transit busses. If our products are not properly designed or built and/or personal injuries are sustained as a result of our equipment, we could be subject to claims for damages based on theories of product liability and other legal theories. We maintain liability insurance for these risks; however, the costs and resources to defend such claims could be substantial, and if such claims are successful, we could be responsible for paying some or all of the damages. Also, our reputation could be adversely affected, regardless of whether such claims are successful. Any of these results would adversely affect our profit margins, results from operations and stockholder value. We are currently named as a co-defendant in a product liability case that seeks class action. Refer to ITEM 3—LEGAL PROCEEDINGS.
Work stoppages or other changes in the relationships with our employees could make it difficult for us to produce and effectively market our products, which would adversely affect our profit margins, results from operations and stockholder value.
If we experience significant work stoppages, as we did in fiscal 2003, we likely would have difficulty manufacturing our products. Also, our labor costs could increase and we may not be able to pass such increase on to our customers. The occurrence of either of the foregoing would adversely affect profit margins, results from operations and stockholder value.
Our defined benefit pension plans are under-funded and, therefore, we may be required to increase our contributions to the plans, which would adversely affect our cash flows.
We maintain two defined benefit pension plans among the retirement plans we sponsor. No new employees are being admitted to participate in these two plans. Participants in these two plans are entitled to a fixed formula benefit upon retirement. Although we make regular contributions to these two plans in accordance with minimum ERISA funding requirements, investment earnings may be less than expected, and we may be required to increase contributions to the under-funded plan(s), which would adversely affect our cash flows.
Risks related to environmental laws:
The soil and groundwater at our Portland, Oregon facility contains certain contaminants that may require us to incur substantial expense to investigate and remediate, which would adversely affect our profit margins, results from operations and stockholder value.
The soil and groundwater at our Portland, Oregon facility contain certain contaminants. Some of this contamination has migrated offsite to neighboring properties and potentially to other properties. We have retained an environmental consulting firm to investigate the extent of the contamination and to determine what, if any, remediation will be required and the associated costs. During the third quarter of fiscal 2004, we entered the Oregon Department of Environmental Quality’s voluntary clean-up program and during fiscal 2004 we established a liability of $950 for this matter. At September 30, 2007, we recorded an additional liability of $546 and as of September 30, 2007, this liability totaled $1046. Our overall costs could exceed this liability, which could adversely affect our profit margins, results from operations and stockholder value.
We are required to comply with federal and state environmental laws, which could become increasingly expensive and could result in substantial liability if we do not comply.
We produce small quantities of hazardous waste in our operations and are subject to federal and state air, water and land pollution control laws and regulations. Compliance with such laws and regulations could become increasingly costly and the failure to comply could result in substantial liability. Either of these results could increase expenses, thereby adversely affecting our profit margins and stockholder value.
Risks related to foreign operations:
Fluctuations in the value of currencies could adversely affect our international sales, which would result in reduced revenues and stockholder value.
We sell products in Canada, Belgium, Sweden, Mexico, South America, the Pacific Rim nations, Australia, China and certain European nations, purchase components from suppliers in China and Europe, have a manufacturing and sales operation in China, and a sales and technical center in Germany. For the years ended September 30, 2007, 2006 and 2005, foreign sales were approximately 41, 36, and 35 % of net sales, respectively. Although currently virtually all of our sales and purchases are made in U.S. dollars, we anticipate that over time more of our purchases of component parts and sales of our products will be denominated in foreign currencies. We do not presently engage in any hedging of foreign currency risk. In the future, our operations in the foreign markets will likely become subject to fluctuations in currency values between the U.S. dollar and the currency of the foreign markets. Our results from operations and stockholder value could be adversely affected if currency of any of the foreign markets increases in value relative to the U.S. dollar.
Complying with the laws applicable to foreign markets may become more difficult and expensive in the future, which could adversely affect our results from operations and stockholder value.
Our operations in foreign markets are subject to the laws of such markets. Compliance with these laws may become more difficult and costly in the future. In addition, these laws may change and such change may require us to change our operations. Any of these results could adversely affect our results from operations and stockholder value by increasing expenses and reducing revenues, thereby reducing profits.
Political and economic instability in the foreign markets may make doing business there more difficult and costly, which could adversely affect our results from operations and stockholder value.
Economic and political instability may increase in the future in foreign markets. Such instability may make it more difficult to do business in those countries, may make it more expensive to do so and could disrupt supplies of components into our Portland or Suzhou facilities. If our operations were nationalized by the government of China, this could cause us to write off the value of our operations in such foreign markets and eliminate revenues generated by such operations. Any of these results could result in onetime charges or increased expenses as well as lower revenues, which would adversely affect our results of operations and harm stockholder value.
Risks Related to our Capital Structure:
The market price of our stock has been and may continue to be volatile, which could result in losses for stockholders.
Our common stock is currently listed on the NASDAQ Capital Market and is thinly traded. Prior to October 9, 2006 our stock was traded on the OTC Bulletin Board. Volatility of thinly traded stocks is typically higher than the volatility of more liquid stocks with higher trading volumes. The market price of our common stock has been and, in the future, could be subject to significant fluctuations as a result of the foregoing, as well as variations in our operating results, announcements of technological innovations or new products by us or our competitors, announcements of new strategic relationships by us or our competitors, general conditions in our industries or market conditions unrelated to our business and operating results. Any of these results could adversely impact stockholder value.
Example with low Specificity: risk-factor disclosures from Tennant Company (March 2010)
We may encounter additional financial difficulties if the United States or other global economies continue to experience a significant long-term economic downturn, decreasing the demand for our products.
To the extent that the U.S. and other global economies experience a continued significant long-term economic downturn, our revenues could decline to the point that we may have to take additional cost saving measures to reduce our fixed costs to a level that is in line with a lower level of sales in order to stay in business long-term in a depressed economic environment. Our product sales are sensitive to declines in capital spending by our customers. Decreased demand for our products could result in decreased revenues, profitability and cash flows and may impair our ability to maintain our operations and fund our obligations to others.
We may not be able to effectively manage organizational changes which could negatively impact our operating results or financial condition.
We are continuing to integrate acquired companies into our business and adjust to reduced staffing levels as a result of our workforce reduction. This consolidation and reallocation of resources is part of our ongoing efforts to optimize our cost structure in the current economy. Our operating results may be negatively impacted if we are unable to manage these organizational changes either by failing to incorporate new employees from acquired businesses or failing to assimilate the work of the positions that are eliminated as part of our actions to reduce headcount. In addition, if we do not effectively manage the transition of our reduced headcount, we may not fully realize the anticipated savings of these actions or they may negatively impact our ability to serve our customers or meet our strategic objectives.
We may not be able to effectively optimize the allocation of Company resources to our strategic objectives, which could adversely affect our operating results.
The decline in the global economy has constrained resources that are available to allocate among strategic business objectives. If we are not able to appropriately prioritize our objectives, we risk allocating our resources to projects that do not accomplish our strategic objectives most effectively, which could result in increased costs and could adversely impact our operating results.
We are subject to competitive risks associated with developing innovative products and technologies, which generally cost more than our competitors’ products.
Our products are sold in competitive markets throughout the world. Competition is based on product features and design, brand recognition, reliability, durability, technology, breadth of product offerings, price, customer relationships, and after-sale service. Although we believe that the performance and price characteristics of our products will provide competitive solutions for our customers’ needs, because of our dedication to innovation and continued investments in research and development, our products generally cost more than our competitor’s products. We believe that customers will pay for the innovation and quality in our products; however, in the current economic environment, it may be difficult for us to compete with lower cost products offered by our competitors and there can be no assurance that our customers will continue to choose our products over products offered by our competitors. If our products, markets and services are not competitive, we may experience a decline in sales, pricing, and market share, which adversely impacts revenues, margin, and the success of our operations.
We may not be able to adequately acquire, retain and protect our proprietary intellectual property rights which could put us at a competitive disadvantage.
We rely on trade secret, copyright, trademark and patent laws and contractual protections to protect our proprietary technology and other proprietary rights. Our competitors may attempt to copy our products or gain access to our trade secrets. Our efforts to secure patent protection on our inventions may be unsuccessful. Notwithstanding the precautions we take to protect our intellectual property rights, it is possible that third parties may illegally copy or otherwise obtain and use our proprietary technology without our consent. Any litigation concerning infringement could result in substantial cost to us and diversions of our resources, either of which could adversely affect our business. In some cases, there may be no effective legal recourse against duplication of products or services by competitors. Intellectual property rights in foreign jurisdictions may be limited or unavailable. Patents of third parties also have an important bearing on our ability to offer some of our products and services. Our competitors may obtain patents related to the types of products and services we offer or plan to offer. Any infringement by us on intellectual property rights of others could result in litigation and adversely affect our ability to continue to provide, or could increase the cost of providing, our products and services.
We may encounter difficulties as we invest in changes to our processes and computer systems that are foundational to our ability to maintain and manage our systems data.
We rely on our computer systems to effectively manage our business, serve our customers and report financial data. Our current systems are adequate for our current business operations; however, we are in the process of standardizing our processes and the way we utilize our computer systems with the objective that we will improve our ability to effectively maintain and manage our systems data so that as our business grows, our processes will be able to more efficiently handle this growth. There are inherent risks in changing processes and systems data and if we are not successful in our attempts to improve our data and system processes, we may experience higher costs or an interruption in our business which could adversely impact our ability to serve our customers and our operating results.
We may be unable to conduct business if we experience a significant business interruption in our computer systems, manufacturing plants or distribution facilities for a significant period of time.
We rely on our computer systems, manufacturing plants and distribution facilities to efficiently operate our business. If we experience an interruption in the functionality in any of these items for a significant period of time, we may not have adequate business continuity planning contingencies in place to allow us to continue our normal business operations on a long-term basis. Significant long-term interruption in our business could cause a decline in sales, an increase in expenses and could adversely impact our operating results.
We are subject to product liability claims and product quality issues that could adversely affect our operating results or financial condition.
Our business exposes us to potential product liability risks that are inherent in the design, manufacturing and distribution of our products. If products are used incorrectly by our customers, injury may result leading to product liability claims against us. Some of our products or product improvements may have defects or risks that we have not yet identified that may give rise to product quality issues, liability and warranty claims. If product liability claims are brought against us for damages that are in excess of our insurance coverage or for uninsured liabilities and it is determined we are liable, our business could be adversely impacted. Any losses we suffer from any liability claims, and the effect that any product liability litigation may have upon the reputation and marketability of our products, may have a negative impact on our business and operating results. We could experience a material design or manufacturing failure in our products, a quality system failure, other safety issues, or heightened regulatory scrutiny that could warrant a recall of some of our products. Any unforeseen product quality problems could result in loss of market share, reduced sales, and higher warranty expense.
We may encounter difficulties obtaining raw materials or component parts needed to manufacture our products and the prices of these materials are subject to fluctuation.
Raw materials and commodity-based components. As a manufacturer, our sales and profitability are dependent upon availability and cost of raw materials, which are subject to price fluctuations, and the ability to control or pass on an increase in costs of raw materials to our customers. We purchase raw materials, such as steel, rubber, lead and petroleum-based resins and components containing these commodities for use in our manufacturing operations. The availability of these raw materials is subject to market forces beyond our control. Under normal circumstances, these materials are generally available on the open market from a variety of sources. From time to time, however, the prices and availability of these raw materials and components fluctuate due to global market demands, which could impair our ability to procure necessary materials, or increase the cost of such materials. Inflationary and other increases in the costs of these raw materials and components have occurred in the past and may recur from time to time, and our financial performance depends in part on our ability to incorporate changes in costs into the selling prices for our products. Freight costs associated with shipping and receiving product and sales and service vehicle fuel costs are impacted by fluctuations in the cost of oil and gas. We do not use derivative commodity instruments to manage our exposure to changes in commodity prices such as steel, oil, gas and lead. Any fluctuations in the supply or prices for any of these commodities could have a material adverse effect on our profit margins and financial condition.
Single-source supply. We depend on many suppliers for the necessary parts to manufacture our products. However, there are some components that are purchased from a single supplier due to price, quality, technology or other business constraints. These components cannot be quickly or inexpensively re-sourced to another supplier. If we are unable to purchase on acceptable terms or experience significant delays or quality issues in the delivery of these necessary parts or components from a particular vendor and we need to locate a new supplier for these parts and components, shipments for products impacted could be delayed, which could have a material adverse effect on our business, financial condition and results of operations.
We are subject to a number of regulatory and legal risks associated with doing business in the United States and international markets.
Our business and our products are subject to a wide range of international, federal, state and local laws, rules and regulations, including, but not limited to, data privacy laws, anti-trust regulations, employment laws, product labeling and regulatory requirements, and the Foreign Corrupt Practices Act and similar anti-bribery regulations. Many of these requirements are challenging to comply with as there are frequent changes and many inconsistencies across the various jurisdictions. Any violation of these laws or regulations could lead to significant fines and/or penalties could limit our ability to conduct business in those jurisdictions and could cause us to incur additional operating and compliance costs.
We are subject to risks associated with changes in foreign currency exchange rates.
We are exposed to market risks from changes in foreign currency exchange rates. As a result of our increasing international presence, we have experienced an increase in transactions and balances denominated in currencies other than the U.S. dollar. There is a direct financial impact of foreign currency exchange when translating profits from local currencies to U.S. dollars. Our primary exposure is to transactions denominated in the Euro, British pound, Australian and Canadian dollar, Japanese yen, Chinese yuan and Brazilian real. Any significant change in the value of the currencies of the countries in which we do business against the U.S. dollar could affect our ability to sell products competitively and control our cost structure. Because a substantial portion of our products are manufactured in the United States, a stronger U.S. dollar generally has a negative impact on results from operations outside the United States while a weaker dollar generally has a positive effect. Unfavorable changes in exchange rates between the U.S. dollar and these currencies impact the cost of our products sold internationally and could significantly reduce our reported sales and earnings. We periodically enter into contracts, principally forward exchange contracts, to protect the value of certain of our foreign currency-denominated assets and liabilities. The gains and losses on these contracts generally approximate changes in the value of the related assets and liabilities. However, all foreign currency exposures cannot be fully hedged, and there can be no assurances that our future results of operations will not be adversely affected by currency fluctuation.
Appendix 2: Validity test instructions
Assignment—Evaluation of the specificity level of risk disclosures
Name ____________________________
You are randomly assigned the risk disclosures from the financial statements of FIVE different companies. You are asked to evaluate the level of specificity of these risk disclosures. The definition of specific risk disclosure is provided below:
A piece of risk disclosure is defined as specific if it contains information that cannot be applied to other firms. In other words, information is considered to be more specific when the disclosure contains more detailed information specifically about the disclosing firm.
Please rate each sample firm into one of the following five levels:
Very specific: | 5 |
Specific: | 4 |
Specific to not very specific: | 3 |
Not very specific: | 2 |
Not specific at all: | 1 |
The following examples with constructed hypothetical sentences are for illustration.
Google’s main business in United States Google Search, accounting 30 % of the profit, is facing fierce competition from Microsoft’s Bing | (5) |
Google’s main business in United States Google Search is facing fierce competition from Microsoft’s Bing | (4) |
Google’s main business in United States is facing fierce competition from Microsoft | (3) |
The firm’s main business in United States is facing fierce competition from other firms | (2) |
The firm’s main business is facing fierce competition globally from other firms | (1) |
Appendix 3: Variable definitions
Dependent variables | |
|Unanticipated-return| | \(\frac{{Price_{it + 365} -\, Price_{it} }}{{Price_{it} }} - \frac{{Base_{it} - \,Price_{it} }}{{Price_{it} }}\) The absolute value of the difference between the 1-year ahead realized raw return and the Base. Base is the forecast for the 1-year ahead stock price in the first analyst report with scenario analysis issued by Morgan Stanley after the firm files 10-K report for year t |
|CAR 10k−1,1 | | The absolute value of the difference between the 3-day stock return starting one trading day before the 10-K release and ending one trading day after and the expected return estimated using the Fama–French three-factor model |
ABVOL 10-K−1,1 | Average daily trading volume in 3-day window around 10-K file date in excess of the mean daily trading volume in the [−60, −11] trading day window (scaled by the [−60, −11] period volume), excluding the trading volume data in 3-day window around earnings announcements. Day 0 is defined as the 10-K file date |
Independent variables | |
Specificity | The number of specific words identified by the Stanford NER program in Item 1A in the 10-K report divided by the number of total words in Item 1A after stop-words removed. The list of stop words is from Python natural language processing package |
Specificity 10K | The number of specific words identified by the Stanford NER program in the 10-K report divided by the number of total words in 10-K report after stop-words removed. The list of stop words is from Python natural language processing package |
Amount | The log of the number of one plus the risk-related words in Item 1A. The risk-related words are identified using dictionaries developed in Campbell et al. (2014) |
RiskWords | The log of one plus the total number of word “risk” and its derivative words defined in Li (2006) in 10-Ks |
Fog | Fog index downloaded from Feng Li’s website |
TotalLength | The log of the number of all words in the 10-K file |
Spread | \(\frac{{Bull_{it}\, -\, Bear_{it} }}{{Base_{it} }}\) Bull and Bear are the bull-case and bear-case forecasts for the 1-year ahead stock price contained in the first analyst report with scenario analysis issued by Morgan Stanley after the firm files 10-K report for year t |
HighSpecificity | An indicator variable that equals one if Specificity for firm i is in the top quintile among all sample firms in 2010, zero if Specificity is in the bottom quintile |
BtM | The ratio of book value of equity to market value of equity |
ReturnVolatility | The standard deviation of daily stock returns in year t − 1 |
EarningsVolatility | The standard deviation of quarterly earnings in the past 20 quarters scaled by the absolute value of the mean of quarterly earnings in the past 20 quarters |
NegEarnings | An indicator variable that equals one if the sum of the past four quarterly earnings is negative, and zero otherwise |
ΔEarnings | The difference between net income in year t and net income in year t – 1 |
Accrual | The absolute value of accruals calculated using the cash flows statement deflated by average total assets |
PastLoss | An indicator variable that equals one if the firm has one or more loss years over the previous 5 years, zero otherwise |
Litigation | An indicator variable that equals one for firms in SIC codes 2833–2836, 3570–3577, 3600–3674, 5200–5961, 7370–7374, and 8731–8734, zero otherwise |
|CAR EA−1,1 | | The same calculation as |CAR 10k−1,1 | with event date as the annual earnings announcement date |
FileDate | An indicator variable that equals one when the 10-K filing date is at least 90 days after the year end, zero otherwise |
NumItems | The number of non-missing items on COMPUSTAT in a fiscal year |
Size | The natural logarithm of the market value of equity |
Leverage | The ratio of long-term debt to total assets |
Segments | The natural logarithm of one plus the number of segments |
HighInstitution | An indicator variable that equals one if the firm’s institutional ownership is above the median institutional ownership of all firms in the same year |
ProprietaryCost | R&D intensity, calculated as the R&D expense divided by total asset at the beginning of the fiscal year. Missing data is replaced by zero |
Num8K | The number of 8-K files in the 1-year period before the 10-K filings |
ForecastError | The difference of the mean EPS forecast with the announced EPS standardized by the stock price at the beginning of the fiscal year. Missing data is replace by zero |
ForecastMissing | An indicator that equals one if Forecast Error is missing and zero otherwise |
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Hope, OK., Hu, D. & Lu, H. The benefits of specific risk-factor disclosures. Rev Account Stud 21, 1005–1045 (2016). https://doi.org/10.1007/s11142-016-9371-1
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DOI: https://doi.org/10.1007/s11142-016-9371-1
Keywords
- Risk-factor disclosure
- Specificity
- Market reactions
- Trading volume
- Analyst risk assessments
- Scenario analysis