Historical Earnings Research Articles

Forecasting Business Status of Organizations by Analyzing Historic Earnings Call Transcripts with the Aid of Text Refinement Framework

Objectives: The research work focuses on providing an effective framework for automated text refinement that aids in financial condition projections for the company based on prior transcripts of earnings calls. The proposed framework captures the ad hoc advancements of the organizations described in the earnings call as sentiments and computes a score based on the captured sentiments. The sentiment score is then used as prime parameter to predict the stock values of the organizations. Methods: The framework is equipped with sentiment analysis or opinion mining to identify and extract the subjective content using text mining and Natural Language Processing (NLP). The extracted sentiments help in yielding a sentiment score to aid in the process of stock projection. The research also illustrates how the sentiment score-based stock prediction enhances in projections of stock compared to existing ML frameworks like LSTM, Random Forest, ARIMA and Regression models. Findings: The proposed work has an accuracy score of 93%, precision 96% and recall 95% which is comparatively better than existing ML frameworks framed on LSTM, Random Forest, ARIMA and Regression models. Novelty: The research framework overcomes the influence of regular features and test data in stock prediction by using the computed sentiment prediction score from the extracted sentiment phase to aid in prediction stock values and determine the financial status of organizations. The existing frameworks project the stock price based on trained model from previous stock price repository, which tend to fail capturing ad hoc changes incurring in the organization such as change of management or any economic disaster which can poses a high impact on stock projections, the proposed research work captures these organizational changes from the earnings call transcripts as sentiments and build a score to yield the stock projection framework. Keywords: Natural Language Processing, Text Refinement, Loughran McDonald Sentiment Classifier, Term Frequency Inverse Document Frequency, Stock Price

Reconciling Competing Reporting Objectives Through Deferred Tax Accounts: Evidence on Private Italian Firms

This paper contributes to the growing literature on earnings management in private firms by focusing on deferred taxes. This accounting treatment requires sophisticated use of accruals that provides the chance to manage earnings and net assets without affecting the tax payable. We argue that in a setting with high book-tax conformity, the small room that allegedly exists to recognise deferred taxes remains a comfortable avenue to reach reporting objectives that a tax-minimisation strategy may preclude. We use a sample of private firms operating in a credit- and tax-driven environment such as Italy to test this expectation. Our results show that private firms use deferred taxes to extract multiple financial reporting benefits that may facilitate debt contracting: smoothing earnings over time, meeting/beating historical earnings, avoiding reporting accounting losses, and managing leverage. Tax loss carryforwards are the source of deferred tax assets where the exercise of discretion becomes more critical.

The Efficiency of Weekly Option Prices around Earnings Announcements

This study examines the efficiency of weekly option prices around firms’ earnings announcements. With most of the largest firms now having options that expire on a weekly basis, option traders can hedge or speculate on earnings news using options that expire very close to a firm’s earnings announcement date. For earnings announcements near an options expiration date, one can estimate a firm’s expected stock price move in response to its earnings news (i.e., its option implied earnings announcement move) as the price of its at-the-money straddle as a proportion of its stock price. This study tests whether differences between historical earnings announcement moves and option implied earnings announcement moves predict straddle returns. Through the analysis of portfolio returns and Fama–MacBeth regressions, this study finds that straddle returns are significantly higher (lower) when the historical earnings announcement move is high (low) relative to the option implied earnings announcement move. In contrast to prior research, this study does not find an association between straddle returns and historical volatility, historical earnings announcement volatility, implied volatility, or the difference between historical volatility and implied volatility. Overall, this study suggests that weekly straddle prices around earnings announcements are not optimally efficient.

The Relationship between Stock Prices and Silver Future Prices Based on VAR Model

Despite recent dramatic increases in the prices of coal, oil, natural gas, and other fossil energy futures, some of which have hit successive record highs, related stocks have seen substantial decreases. The price trend of commodities is typically driven by commodity futures, which serve as price discoverers. There is a relationship between futures and stocks in the market, meaning that when the price of the futures contract for a particular commodity rises, so will the price of the stock of the company that produces the commodity because investors anticipate rising earnings. But does the price of futures vary when the stock price does? Based on the findings of the VAR model and Granger causality test, this study concludes that the stock price, whether it be the current price or the historical earnings, does not significantly affect the futures price. Futures prices have a significant impact on future stock prices. This would facilitate investment decision-making.

Financial signaling mechanism in investor response to corporate donation disclosure: the moderating role of historical earnings trends

Purpose Corporate donation behavior sends two financial-related signals, i.e. sufficient cash flow and self-confidence in future earnings. This paper aims to investigate whether these financial-related signals released by corporate donation drive investors to make more optimistic forecasts about the firm’s future earnings per share (EPS) and whether this effect varies across different historical earnings trends. Design/methodology/approach This study is based on a controlled online experiment with 553 MBA students. Findings The results demonstrate that a financial signaling mechanism works, but it is moderated by historical earnings trends. When the earnings trend is always increasing, the more the number of financial signals received, the higher the investors’ EPS forecast; when the earnings trend is fluctuating (down then up or up then down), investors’ EPS forecast is higher when they receive financial signal(s) than when they do not, but no additive effect occurs from receiving one signal to two signals; when the earnings trend is always decreasing, investors’ EPS forecast is irrelevant to the number of financial signals received. Originality/value To the best of the authors’ knowledge, this study is the first to experimentally investigate a possible mechanism to explain investors’ positive response to corporate social responsibility (CSR) (specifically, corporate donation) disclosures – the financial signaling mechanism. This study also extends the research on the impact of financial information on investors’ use of nonfinancial information by investigating the moderating role of historical earnings trends on the financial signaling mechanism of the CSR effect.

Redefining Growth: Using Analyst Forecasts to Transcend the Value–Growth Dichotomy (Part 1)

Asset pricing literature typically labels stocks with high price multiples as growth and stocks with low price multiples as value. This definition is accompanied by the view that, over the long term, value outperforms growth and encourages investors to make a binary choice between the two styles. In this first of two articles, we seek to find an alternative definition of growth and, to this end, evaluate the efficacy of a range of metrics at predicting future earnings growth. We conclude that analysts’ forecasts have a stronger relationship with future earnings growth than price multiples do. In addition to this main observation, we find that profitability and historical earnings growth have a negative relationship with future earnings growth, thus challenging the notion that these metrics are useful for identifying growth stocks.

Historical Earnings, Accrual Accounting, and Future Cash Flows: A Malaysian Perspective

This study investigates the influence of historical earnings and historical accrual accounting on projecting future cash flows. The sample consisted of 159 construction, energy, and property development companies from the main capital market of Malaysia. The compiled data of these companies spanned from 2015 to 2019 and was collected from the financial statements of the companies, including operating cash flows and earnings. The profit or loss statement and cash flow statement were used for calculating historic accrual accounting. Earnings, cash flow, and accrual accounting models were used as the basis for the regression model construction. The accounting data demonstrated that the prediction performance of the models was improved by the three-year lag. The previous two-year earnings and accrual accounting had positive and significant predictive power for forecasting future cash flows. Moreover, the past one- and two-year cash flows from operations significantly predicted future cash flows. These results are important for a sound understanding among academics and practitioners of the crux of historical earnings, operating cash flow, and accrual accounting. The findings can assist corporate leaders and management executives in tracking the sustainability and financial growth of an organization.

ESG Risks and the Value Relevance of Current and Historical Earnings

AbstractWe investigate whether independent, third‐party assessments of firms’ Environmental, Social, and Governance (ESG) risk exposures provide forward‐looking information content to capital market participants by evaluating whether these ESG risks have a moderating effect on the ability of earnings and the book values of equity to predict investors’ expectations of the present value of future cash flows. We find that firms’ higher ESG risk exposure increases the association between current earnings and firm values, while decreasing the relevance of book values of equity (i.e., historical earnings). We find that this effect is strongest for firms with the highest levels of risk exposure and following large changes to ESG risk exposures. In additional analyses, we disaggregate ESG risk exposure and while we find that each component of ESG has predictive power consistent with the main findings, governance risks dominant the results in head to head specifications. Taken together, our findings suggest that governance risk exposures provide forward‐looking information content to investors when they evaluate the ability of current earnings to predict future cash flows. Our results are robust to several measures of ESG risk exposure, entropy balancing specifications, and exogenous shocks to ESG attention following global environmental and social justice initiatives.

Is the market surprised by the surprise?

This study examines how the market reacts to earnings surprises with different characteristics such as future earnings prospects and historical surprises embedded in the earnings announced. We also explore the effect of corporate governance on market reaction to earnings information disseminated through earnings announcements. The sample comprises of 1620 US firms for the period 2002–2016. Using a regression-based approach, the results reveal that the market reacts to earnings surprises, particularly, to their sign, magnitude, persistence, and the future earnings prospects. Moreover, these different characteristics of earnings surprises are more important for negative surprises than for positive surprises. Furthermore, we find evidence for the information transparency theory that earnings announcements are a relatively more important source of information for low-corporate-governance firms than for high-corporate-governance firms. Finally, historical earnings information is more relevant for low-corporate-governance firms, whereas prospective earnings information is more important for high-corporate-governance firms. This study contributes to the extant literature by revealing that the market does not only react to the magnitude/sign of the surprises but also to other additional characteristics of earnings surprises. The study also reveals that firm governance influences how the market reacts to earnings information announced. Consequently, managers should be mindful that strengthening corporate governance could improve investors’ confidence in earnings announced.

Equity Risk Premium in Pakistan: Comparative Estimates from Historical Returns, Dividend and Earnings Models

This paper compares the efficiencies of dividend and earnings growth models with a historical model in predicting the unconditional expected equity risk premium (ERP). Monthly data has been used from the period 2010 to 2018 from 2 sectors namely market (KSE100 Index), cement and banking. The research applies a two-step process. First, we estimate and compare the absolute expected ERP under three models: (a) dividend growth model (Gordon, 1959), (b) earnings growth model and (c) historical returns, to find out the most efficient model for forecast ERP. Next, the effectiveness of the model is tested using a panel regression analysis. ERPs have been calculated with two different mathematical approaches, a simple return and continuously compounding returns (log returns). The results show that the dividend growth model emerges as the most efficient model for 1. KSE100 Index’s, 2.commercial bank and 3. Cement sector for predicting ERP and hence, investors should follow dividend policy to value Pakistani companies.

Accessing the Equity Return Volatility Effect of East and South Asian Nations: The Econometrics Modelling Method

In financial management, the equity market performance is the critical element of equity market returns volatility wherever the shareholder’s resilience around the instability subsists. The data is collected from the authenticated secondary sources for the analysis. This paper shows that the 2008economicpredicament, as well as the effect above proceeding developing financial prudence of the globe, is found in the equity return instability connation of developing financial prudence (2004-2015). By the GARCH model, it can be examined that as the information from the U.S.A. stock market news has an essential consequences on the earnings of the S&P 500 stock market index, the indices of the east, as well as south Asian nations, has also influenced by the news of U.S.A. The GARCH model is estimated for the U.S.A. stock market news has a substantial effect or not on East and South Asian nation's daily share market returns. The outcomes show that market earnings in the equity market in east and south Asian nations are incredibly reliant on their historical earnings. It is found that Tokyo Topic (4.8929) is a highly volatile stock index among the East and South Asian stock returns, and the low volatile stock index is DSEX (0.0068). The news of the U.S.A. stock market has affected the equity market of India, Japan, China, and Korea, which are included in the East and South Asian stock market. In all the country’s share markets, found most significant variance in the equity income instability. This study is essential for the shareholders looking for the diversification in the portfolio, domestic institutional investors and foreign institutional investors

A Comparison of Equity Valuation Models: Empirical Evidence from a Sample of UK Companies

This paper aims to answer one main question: can the superior models in accounting field be superior in finance field? That is, can models that generate a better approximation to stock price also generate higher returns in the future? To answer this question, I conduct pricing errors analysis and time-series returns analysis. The most important finding is models that approximate stock price better tend to produce higher returns in the future; implying findings in accounting literature have practical implications to analysts and investors. The consistent rankings of models are observed throughout the research: forward earnings multiples perform the best, followed by fundamental valuation models and historical earnings multiples, and book value and sales multiples worst. However, multiples are ranked rather as a group in the UK. Interestingly, residual income models produce similar returns to forward earnings multiples, but the accuracy of their estimates varies depending on their terminal value assumptions.

Assessment of the Comparative Ability of Accounting Bases in Predicting Future Cash Flows: Evidence from Nigeria

Purpose of the article: This study examines the comparative abilities of accrual-based and cash-based accounting information to predict future operating cash flows with particular focus on quoted Nigerian non-financial companies. Secondary data were utilized for the study and were extracted from published annual statements and accounts of eighty (80) quoted firms in Nigeria between 2005–2015. Methodology/methods: Data collected were statistically analysed with the aid of the Ordinary Least Square (OLS) regression method, correlation analysis, variance inflation factor (VIF) tests for multicollinearity, and the Breusch-Pagan/Cook Weisberg test for heteroscedasticity. 5% level of the test of significance was employed to measure the degree of statistical relationship between stated variables. Scientific aim: This research is aimed at empirically ascertaining, by means of available statistics, the comparative predictive abilities of accrual-based and cash-based accounting information in forecasting future cash flows for quoted non-financial companies in the Nigerian stock exchange. Findings: It has been revealed in this study that historical earnings data prepared under the accrual-basis possessed superior predictive ability over operating cash flows data in forecasting future cash flows of quoted non-financial firms in Nigeria. Conclusions: Company management who are saddled with the responsibility of preparation and presentation of financial statements as part of their management responsibility should, as a matter of utmost priority, uphold integrity and transparency by adhering strictly to the provisions of accounting standards so as to enhance reliability and decision-usefulness of financial disclosures with a view to improving the predictive ability of accounting information.

Equity Risk Premium in India: Comparative Estimates from Historical Returns, Dividend and Earnings Models

The article compares efficiencies of dividend and earnings growth models with historical model in predicting the unconditional expected equity risk premium (ERP) in addition to analysing the impact of recession. The exercise is undertaken employing two different Indian capital market indices, NIFTY500 and SENSEX. The study period is 20 years (1997–2016) with pre- and post-recession periods as 2001–2008 and 2009–2016, respectively. The dividend growth model emerges as the most efficient model for predicting ERP while highlighting that Indian firms follow stable dividend policy. NIFTY500 index with a wider base proves to be a superior benchmark for market returns over SENSEX comprising 30 blue-chip firms.

Myth

There are several benefits to becoming an owner, including increased annual income and investment value. Understanding the financing landscape is important for veterinarians to understand in order to purchase the practice. Veterinary practices are typically valued as a multiple of historical earnings. To ensure maximal value of their business, sellers should be concerned with the profitably of their business for at least 3 years prior, and work with a business valuator to set the price of their practice. Industry specific third-party lenders have come to understand the veterinary landscape and the challenges inherent to our industry, such as the large student debt burden that recent graduates face. Fortunately, many cash-flow based loans allow for the transaction to still occur despite a collateral shortfall. The cash-flow analysis is at the core of the loan approval process to ensure that the new business owner will be able to pay the ordinary business expenses, pay the new proposed debt, pay themselves a sufficient salary to cover their personal obligations, and have some cushion left over. The strength of the veterinary profession and historically low default rates allow lenders to become comfortable lending to veterinarians to purchase practices.

How do sell-side analysts obtain price-earnings multiples to value firms?

Previous studies of analysts’ valuation methods show that sell-side analysts often rely on multiples-based relative valuation methods in deriving target price forecasts, predominantly earnings-based multiples. However, little is known about how analysts actually arrive at the earnings multiples that they apply in their valuations. Based on extant valuation theory, we analyse three benchmarks/reference points that analysts use to select these multiples using U.S. data. By mimicking analysts’ relative valuation processes, we show that analysts tend to assign earnings multiple premiums (discounts) to those firms expected to have growth premiums (higher risk levels) relative to comparable firms. We provide evidence that analysts use firms’ historical earnings multiples as benchmarks, and assign firms that are expected to have more (less) attractive fundamentals than they have had in the past earnings multiples that are at a premium (discount) relative to the average historical earnings multiples at which they traded. The forward price-earnings multiple for the broad U.S. market index signals the market’s expectations about the growth prospects of the U.S. economy and future economic conditions and we also find that changes in this multiple affect analysts’ choices of firm-specific earnings multiples.

How Investors Set Valuation Ratios Using a Micro-Founded Gordon Asset Pricing Model

A Micro-Founded Gordon Asset Pricing Model (MF-GAPM) is developed that allows calculation of the current E/P of an equity using reported data. In the original Gordon Model, the discounting is done assuming constant growth and a constant discount rate, with the simple result E/P = r - g where r is the so-called required yield and g is the growth expectation. The MF-GAPM applies the standard CRRA utility methodology to the real-world problem of investors maximizing their real returns, but in contrast to common practice in academic finance where the growth is subject to stochastic fluctuations, the MF-GAPM assumes constant growth like the original Gordon Model. It is shown that the E/P that maximizes the utility of the investors lifetime return then reduces to E/P = (γ-1)*µ where µ is the growth expectation and γ is the curvature of the investors CRRA utility function. This result can be viewed as a micro-founded Gordon Model with required yield equal r = γ*µ. An Empirical Model (Empirical Model) is developed to identify the data variables that investors use to set the MF-GAPM’s assumed parameters. The Empirical Model identifies two broad classes of variables whose variation about their own stationary means explain the variation of E/P about its mean: a sentiment variable S_N and a trailing earnings growth variable EG_N. The two data variables suggest there are two types of investors: rational investors who trade on observed earnings growth and irrational investors who trade on sentiment. Noting the natural associations, the first-order expansions of the functional relationships µ = µ(EG_N) and γ = γ(S_N) provide direct links between the data variables and the parameters of the MF-GAPM. The direct links allow price forecasts to be made using only expectations for the future values of the data variables themselves – expectations about expectations are not required. The feasibility of forecasting prices considering the Model’s StdError is discussed. The lack of randomness in the observed historical earnings growth record is discussed in an Academic Addendum as the rational for abandoning the i.i.d. lognormal growth assumption. With the inclusion of both rational and irrational agents, the MF-GAPM seeks to integrate the classical and behavioral approaches to finance.

Impact of Earnings Smoothness on Stock Prices, Stock Returns and Future Earnings Changes - the Polish Experience

Capital markets appreciate stability. It means that companies reporting smooth earnings patterns tend to be priced relatively high. However, the empirical issue is whether such valuation premiums for earnings smoothness are justified. We examine the relationships between past five-year earnings smoothness and relative stock prices of companies listed on the Warsaw Stock Exchange. The empirical investigation confirmed that on the Polish market the smooth historical earnings are rewarded with valuation premiums and the erratic earnings are penalized with valuation discounts. However, stocks with smooth past earnings tend to bring sub-par future stock returns while stocks with relatively erratic earnings seem to generate above-average returns. Furthermore, the scope of past earnings smoothness does not show any discernible relationships to realized investment risk measures. Finally, companies with smooth earnings tend to report "negative earnings surprises" and relatively slow earnings growth rates in the following year. All in all, our research suggests that there is not any empirically observable justification for the valuation premiums observed in the case of stocks with smooth past earnings because such smoothness translate neither into relatively low future investment risks nor relatively fast future earnings growth.

Adding Value to Value: Is There a Value Premium Among Large Stocks?

According to Fama and French's (2012) price-to-book sorts, there is no global value premium among large stocks. Two simple departures from their methodology restore such premium: sorting stocks based on price-to-earnings rather than price-to-book ratios, and using global rather than regional value breakpoints. The resulting global value premium among large stocks, measured as the return spread between top 30% and bottom 30% stocks, increases from 17 (t-stat=1.09) to 64 (t-stat=2.61) basis points per month. Using price-to-earnings computed from earnings estimates rather than historical earnings further sharpens the value effect among large stocks. Not confined to small stocks, the value premium remains a key topic in Finance. Because valuation ratios are not interchangeable, researchers should look beyond price-to-book when studying, or controlling for, the value effect.

Investigating The Impact Of Historical Costing On Real Earnings Management: An Empirical Study

The current study examines the relationship between Historical Cost Accounting (HCA) and real earnings management. Accounting literature argues that HCA provides a chance for manipulation. HCA creates large unrealized capital gains/losses that are recognized in income statements only when managers decide to sell such assets. This may induce managers to manipulate earnings. Moreover, managers are able to decide which assets to sell and during which period. Therefore, managers can exploit HCA in real earnings management by interfering in the structuring of asset sale transactions. The current study aims to contribute to the ongoing debate over dropping HCA and replacing it with Fair Value Accounting (FVA). Using a sample of the 71 most actively traded non-financial firms listed on the Egyptian Stock Exchange during 20042010, multiple regression analysis is employed to test two main hypotheses: the income-smoothing hypothesis and the debt/equity hypothesis. The results provide evidence that managers in the Egyptian business environment exploit HCA in real earnings management to some extent. Managers with negative earnings changes tend to use HCA to smooth earnings, while managers with earnings changes do not. Moreover, there is no evidence for managers use of HCA to avoid violating debt contract terms based on accounting numbers.