Profit Forecasts Research Articles

What Can Analysts Learn from Artificial Intelligence about Fundamental Analysis?

We apply a machine learning algorithm to estimate Nissim and Penman’s (2001) structural framework that decomposes profitability into increasingly disaggregated profitability drivers. Our approach explicitly accommodates the non-linearities that precluded Nissim and Penman from estimating their framework. We find that out-of-sample profitability forecasts from our approach are generally more accurate than those of benchmark models. We use the profitability forecasts to estimate intrinsic values using the financial statement analysis design choices in Nissim and Penman’s framework and find that hypothetical investing strategies based on these value estimates generate risk-adjusted returns. Design choices that improve performance include increasingly granular disaggregation, a focus on core items, and long-horizon forecasts of operating performance. Perhaps surprisingly, we find only mixed evidence of benefits from incorporating historical financial statement information from beyond the current period.

Efficiency forecasting for municipal solid waste recycling in the context on sustainable development of economy

Ukraine’s further economic growth should be directed by Government Sustainable Development Strategy for harmonization of economy, environmental and social protection. One of the important modern problems is pollution by waste. The feasibility of introducing an eco-project for the municipal solid waste recycling is substantiated at the present research. The complex mathematical model of profit forecast is developed, which shows the tariffs influence on profitability of eco-project on construction of the plant for municipal solid waste recycling in Poltava region of Ukraine. The authors determine and analyse the dependences of the expected eco-project revenue from the change in tariffs for waste management services for each of the consumer categories. Two scenarios of economic development (inertial and innovative) are compared and resulted that the both scenarios have environmental and economic effect, so they are investment attractive. Emphasis is placed on the shortcomings and gaps of the existing tariff policy. The paper demonstrates lack of incentives for the development of business recycling under the existing tariff policy, so to establish a single tariff is proposed uniting the services cost for the removal, sorting, processing and disposal of the waste and also without dividing by consumer categories.

CONCEPTUAL ASPECTS OF THE ECOLOGICAL AND ECONOMIC MECHANISM OF AGRICULTURAL LANDING FOR FARMERS AND PERSONAL AGRICULTURAL GOVERNMENTS ON THE EXAMPLE OF RIVNE REGION

The sources of financing, such as the state budget, local budgets, own funds of enterprises, credits and loans, foreign investments and other sources of financing for investments in personal agriculture (OSG) are analyzed in the example of Rivne region. The coefficients of the correlation logarithmic dependence of enterprises’ profits on investments and fertilizers of farms and private peasant farms (OSG) are analyzed. A multifactor forecast model has been constructed, which is focused on the cost of complete replacement of mineral fertilizers with organic fertilizers (ths. UAH) by 2023. The resulting model is applied to the profit forecast for farms and farms by 2023 in the case of the transition to the organic farming model, as well as the partial replacement of mineral fertilizers by organic waste from livestock farms. odarstv. It has been found that when switching to an organic business model, businesses should raise their product prices by about three times in order to maintain their existing level of profitability. The transition of farms to organic production will lead to a significant increase in prices for vegetable products. However, the high demand for organic products available on the Ukrainian and world markets will make up for the difference in profits. The basic directions of the ecological and economic mechanism of agricultural land use for agricultural and personal peasant farms are offered, as well as directions for improving the status of agricultural land for agricultural and personal peasant farms in the context of corporatization of the ecological and economic mechanism of balanced use of agricultural land and agriculture.

Air pollution, affect, and forecasting bias: Evidence from Chinese financial analysts

We document a negative relation between air pollution during corporate site visits by investment analysts and subsequent earnings forecasts. After accounting for analyst, weather, and firm characteristics, an extreme worsening of air quality from “good/excellent” to “severely polluted” is associated with a more than 1 percentage point lower profit forecast, relative to realized profits. We explore heterogeneity in the pollution-forecast relation to understand better the underlying mechanism. Pollution only affects forecasts that are announced in the weeks immediately following a visit, indicating that mood likely plays a role, and the effect of pollution is less pronounced when analysts from different brokerages visit on the same date, suggesting a debiasing effect of multiple perspectives. Finally, there is suggestive evidence of adaptability to environmental circumstances – forecasts from analysts based in high pollution cities are relatively unaffected by site visit pollution.

Exploiting ergodicity in forecasts of corporate profitability

Theory suggests that competition tends to equalize profit rates through the process of capital reallocation, and numerous studies have confirmed that profit rates are indeed persistent and mean-reverting. Recent empirical evidence further shows that fluctuations in the profitability of surviving corporations are well approximated by a stationary Laplace distribution. Here we show that a parsimonious diffusion process of corporate profitability that accounts for all three features of the data achieves better out-of-sample forecasting performance across different time horizons than previously suggested time-series and cross-sectional models. As a consequence of replicating the empirical distribution of profit rates, the model prescribes a particular strength or speed for the mean-reversion of all returns, which leads to superior forecasts of individual time-series when we exploit information from the cross-sectional collection of firms. The new model should appeal to managers, analysts, investors, and other groups of corporate stakeholders who are interested in accurate forecasts of profitability. To the extent that mean-reversion in profitability is the source of predictable variation in earnings, our approach can also be used in forecasts of earnings and is thus useful for firm valuation.

Os efeitos dos intangíveis nas previsões dos analistas financeiros

Este estudo objetivou verificar a influência dos intangíveis sobre a acurácia e a dispersão das previsões de lucros feita pelos analistas financeiros. A execução deste estudo foi motivada ao observar que a literatura sugere que os intangíveis podem influenciar as previsões dos analistas. Contudo, os resultados verificados são divergentes, não havendo um consenso a respeito da direção dessa influência nos trabalhos à questão. Para atingir os objetivos de pesquisa, utilizou-se uma amostra de empresas americanas não financeiras com ações negociadas na Nasdaq, no período de 1995 a 2016, a partir do método OLS (Ordinary Least Squares ? Mínimos Quadrados Ordinários), conforme adotado pela maior parte da literatura internacional encontrada acerca do tema. A escolha dessa amostra se deu pela maior disponibilidade dos dados dos intangíveis e da cobertura dos analistas, pela comparabilidade com resultados existentes na literatura e pelo fato de a respectiva bolsa concentrar empresas com maior grau de intangibilidade, foco do trabalho. Desse modo, os principais resultados apontaram que os investimentos em P&D e ativos intangíveis reconhecidos são capazes de melhorar as previsões dos analistas. Contudo, o Goodwill mostrou-se negativamente relacionado com as previsões dos analistas ao reduzir a acurácia e aumentar a dispersão das previsões. Concluiu-se, então, a possibilidade em confirmar a existência de associação entre os intangíveis e as previsões dos analistas, além de ter fornecido indícios de que a direção dessa influência não pode ser generalizada a todos intangíveis, a depender do nível de incerteza e complexidade informacional do intangível estudado.

자산손상회계와 경영자 영업이익예측 간의 관련성

자산손상회계와 경영자 영업이익예측 간의 관련성

Research on the use of financial statement information for forecasting profitability

AbstractResearch on the use of financial statement information for forecasting profitability has two objectives: (i) to generate improved forecasts of profitability and accurate estimates of firm value; and (ii) to identify market inefficiencies with respect to financial statement information. For these areas of research, this article describes the evolution, provides examples and shares implications of the research. It also discusses opportunities for future research. The article highlights that financial statement analysis research has slowly evolved and has received limited attention from academics. The article argues that there are vast opportunities for impactful research on fundamental analysis and market inefficiencies.

Leading Indicators’ Applicability to Forecast Profitability of Commercial Bank: Case Study from Lithuania

Purpose of the article: Profitability is one of the most important ratios for performance measurement in any competitive commercial bank and key source to fund future working capital and investments needs. This leads to necessity to investigate topics related to profitability and applicability of factors, which would enable to capture latest trends in economy. In scientific literature, leading economic indicators (in addition to financial and lagging/coinciding economic indicators) are suggested as able to capture trends of economic development. However, there is still a discussion going on applicability of these indicators as well as on financial ratios and economic indicators. The problem is relevant from theoretical and practical point of view. Methodology/methods: Quantitative factors for forecasting commercial banks’ profitability were identified and tested employing methods of detailing, grouping and quantitative analysis (GMM estimator) in empirical research. Scientific aim: To identify applicability of leading economic indicators for bank’s profitability forecasting. Findings: Regression analysis of models using blend of bank, industry, economic ratios improves explanatory power in both dimensions – time (higher scores received for all forecasting horizons) and alternatives (different models that use different blends of determinants). Such improvement was found for all forecasting horizons (one, two and three-quarters) resulting improved explanatory power for one, two and three quarters in comparison to models without leading economic indicators. Conclusions: Leading economic indicators can help to better capture forwardd-looking signals, however, to avoid volatility in forecasts they should be employed with careful analysis of their methodologies and in combination with bank and industry specific, lagging and coinciding economic factors.

Decomposing the market, industry, and firm components of profitability: implications for forecasts of profitability

Academics and practitioners frequently highlight that overall market and industry performance is an important aspect of a firm’s profitability. However, few studies allow for the decomposition of a firm’s profitability into market, industry, and idiosyncratic components, and those that do often assume that the market and industry components are cross-sectional constants. In this study, we allow for variation in firm-specific sensitivities to market, industry, and idiosyncratic economic shocks, and then assess whether and when this decomposition results in improved forecasts of profitability. For the overall sample, we find significant improvements in terms of the magnitude of forecast errors and the frequency with which forecasts based on the decomposed values are superior versus forecasts using only total profitability. Across the sample as a whole, decomposing profitability in the forecasting process results in more accurate forecasts greater than two-thirds of the time (increasing to almost 80% within certain subsamples). Our results provide strong support for the role that firm-specific measures of market and industry profitability play in predicting a firm’s future performance, as well as highlighting settings where the decomposition provides the greatest benefit in terms of predicting future changes in profitability.

Life Cycle Models and Forecasting Growth and Profitability

ABSTRACTMean reversion in profitability and growth is a well-documented phenomenon; however, comparatively less is known about the level of analysis that best captures mean reversion. In this study, we find that analyzing firms by life cycle stage improves the out-of-sample accuracy of profitability and growth forecasts over analyzing firms pooled across the economy and analyzing firms by industry. The improved accuracy is robust to both short-term and long-term forecasts of profitability and growth. We also find that the improvement in accuracy of forecasts from life cycle analyses is greatest for firms in the introduction and decline stages and for firms with greater uncertainty. Finally, we examine market participants' use of life cycle information in forming expectations. We find inefficient use of life cycle information in analyst forecasts, but not in management forecasts. We also find that life cycle forecasts are associated with year-ahead abnormal stock returns.

Despite financial risks, region is looking at another banner year

Demand for chemicals is steady in China, Japanese chemical companies are upgrading their profit forecasts, and economic growth is accelerating in India. In sum: The outlook for the Asian chemical i...

Takeover Defenses in the United Kingdom

The present paper provides a framework of takeover defenses in the United Kingdom and analyzes the role of takeover defenses in the UK that has implemented the EU Takeover Directive in its jurisdiction. There is an analysis of UK hostile takeovers and takeover defenses regulation, along with the case law that formulated it. There is a presentation of takeover defenses involving frustrating actions, such as restructuring defenses, target repurchases, litigation, as well as defensive actions, including strategies such as the defense document strategy, lobbying, seeking alternative bids, profit forecasts. The analysis of takeover defenses in cases of hostile takeovers in the UK market aims to enhance the understanding of their application framework and to provide further insight on the way the structure of the economy influences takeover defenses and vice-versa. It, also, intends to provide feedback for the assessment of economic processes on potential restructuring and normalization in the UK as well as the EU, especially in the light of Brexit that will likely create extensive negotiations on future policy implementation both in the UK and EU.

Stock Returns and Profitability Forecasting by Quantile Regression

We show that quantile regression is better than ordinary-least-squares (OLS) regression in forecasting profitability for a range of profitability measures following the conventional setup of the accounting literature, including the mean absolute forecast error (MAFE) evaluation criterion. Moreover, we perform both a simulated-data and an archival-data analysis to examine how the forecasting performance of quantile regression against OLS changes with the shape of the profitability distribution. Considering the MAFE and mean squared forecast error (MSFE) criteria together, quantile regression is more accurate relative to OLS when the profitability to be forecast has a heavier-tailed distribution. In addition, the asymmetry of the profitability distribution has either a U-shape or an inverted-U-shape effect on the forecasting accuracy of quantile regression. An application of the distributional shape analysis framework to cash flows forecasting demonstrates the usefulness of the framework beyond profitability forecasting, providing additional empirical evidence on the positive effect of tail-heaviness and supporting the notion of an inverted-U-shape effect of asymmetry.

How is Investment Efficiency Related to Investment Transparency?

The relationship between investment efficiency and investment transparency is investigated using a sample of Australian listed company capital expenditure announcements between 2008 and 2014. We suggest two opposing hypotheses to explain why investment efficiency may influence the informativeness of investment disclosures, and present evidence that investment transparency is greater for firms that are over-investing and when sales growth is positive. This evidence is supported by the results from a simultaneous equation regression that considers endogeneity issues. Further evidence reveals that these firms achieve higher profitability and cash flow from operations surrounding the investment announcements, and that high sales growth firms maintain higher debt levels to sustain their investment. Hence the availability of liquid resources appears to support the aggressive investment practices of these firms, and their need for debt financing gives their managers incentives to disclose more financial information in order to ‘hype’ the stock and reduce the costs of financing. Considering possible reverse causality, the results show that investment transparency does not improve investment efficiency. Our interpretation is that managers’ forecasts of project profitability are unsubstantiated and hence in an over-investment situation are ineffective in reducing information asymmetries.

Use of statistical indicators of profit accounting for formation of a product portfolio

Article is related to perfection of product portfolio policy of the enterprise by formation of a product portfolio by means of using of statistics methods and mathematical criteria of the games theory. Such approach allows to decide many tasks of marketing at the enterprise, including to use results of marketing researches and demand and profit forecasting. As a result of the offered system of calculations of statistical indicators it is possible to receive a matrix of predicted risks and market growth for a concrete product portfolio, and also to estimate potential and market prospects of concrete commodity groups. It will form an optimal product portfolio for the specific market conditions.

German firms upbeat

The chief executives of Lanxess, Evonik Industries, and Covestro—three of Germany’s largest chemical firms—are in a sprightly mood after strong trading in the second quarter led them to raise their profit forecasts for 2016. Their improved outlook comes despite depressed chemical prices and turbulence in some markets. And it contrasts with that of BASF, Germany’s largest chemical maker. Lanxess has raised its forecast for 2016 pretax earnings to a range of $1.04 billion to $1.08 billion from its earlier prediction of $1.0 billion to $1.06 billion. The firm anticipates increased sales volumes, leaner costs, increased plant utilization, and a more profitable product mix achieved by restructuring of some businesses. Lanxess recorded a 13.8% drop in second-quarter net profits to $84 million on sales down 7.7% to $2.3 billion compared with the same period a year ago. For the first time, the firm’s results reflect the sale of 50% of its

Management earnings forecasts and IPO performance: evidence of a regime change

Companies undertaking initial public offerings (IPOs) in Greece were obliged to include next-year profit forecast in their prospectuses, until the regulation changed in 2001 to voluntary forecasting. Drawing evidence from IPOs issued in the period 1993–2015, this is the first study to investigate the effect of disclosure regime on management earnings forecasts and IPO long-term performance. The findings show mainly positive forecast errors (forecasts are lower than actual earnings) and higher long-term returns during the mandatory period, suggesting that the mandatory disclosure requirement causes issuers to systematically bias profit forecasts downwards as they opt for the safety of accounting conservatism. The mandatory disclosure requirement artificially improves IPO share performance. Overall, our results show that mandatory disclosure of earnings forecasts can impede capital market efficiency once it goes beyond historical financial information to involve compulsory projections of future performance.

Voluntary profit forecast disclosures, IPO pricing revisions and after-market earnings drift

Prospectus profit forecasts (PPF) constitute one of the most important discretionary disclosure items in an IPO. I examine such disclosures in the Hong Kong market, where both IPO activity and PPF disclosure rates are at high levels. The median forecast typically ‘underestimates’ future earnings by around 6%. More importantly, PPF disclosure exhibits a strong inverse association with pre-listing owners' retained equity levels (Hughes, 1986; and Li and McConomy, 2004). PPF disclosure is thus more likely in IPOs raising more capital and generating larger floats. I also demonstrate a strong link between PPF disclosure and post-IPO earnings drift.Ensuing forecast errors also bear strong connection with IPO coordinators' initial price determinations as well as with subsequent investor returns. This area usefully extends the related literature (Cheng and Firth, 2000; Chen, Firth and Krishnan, 2001; Jog and McConomy, 2003; Chong and Ho, 2007; and Gounopoulos, 2011), which stresses an association between forecast errors and initial investor returns but ignores the preceding price ‘determination’ process. It also suggests that forecast errors serve as a valuable ex-post proxy for the amount of ex-ante uncertainty surrounding issuer value (Beatty and Ritter, 1986; Falconieri, Murphy and Weaver, 2009). This study also demonstrates a connection between final offer price ‘determinations’ and the information content and “superiority” of PPFs (Brown, Richardson and Schwager, 1987). Finally, and in contrast to final offer price ‘determinations’, initial investor returns strongly anticipate post-IPO earnings drift.

The accuracy of management profit forecasts in IPO prospectuses

Purpose – The purpose of this paper is to measure the accuracy of management profit forecast in initial public offerings (IPO) prospectuses and investigate the determinants of any observed forecast error in Indonesia. Design/methodology/approach – A sample of 105 Indonesian IPO firms over a ten-year period, 1999-2008, is used in the present study. The accuracy of management profit forecasts, or forecast errors, in IPO prospectuses is calculated, following Lee et al. (2006), over the ten-year sample period. Then, a multivariate model, following the extant literature, is used to identify the determinants of any observed forecast error in Indonesia. Findings – A mean (median) forecast error of 19 percent (9 percent) is reported over the entire sample period. Multivariate analysis shows that, among the explanatory variables used in the present study, forecast horizon and management optimism seem to be the most significant determinants of forecast error in Indonesia. Research limitations/implications – The ordinary, specifically small, investors in Indonesia lack the sophistication needed to evaluate new issues while alternative independent sources of information or analysis on IPOs are virtually non-existent. Consequently, whether the forecasts made by the managers during IPOs are reliable or not is of particular importance in Indonesia. Originality/value – Indonesia is a significant emerging market in Asia. However, to date, no published work has examined the accuracy of management profit forecasts or forecast errors in this market. The present study attempts to fill this gap in the literature and is the first to capture the magnitude/degree of forecast accuracy or error and investigate the determinants of the documented forecast error in Indonesia using a sample of 105 IPO firms over the period 1999 through 2008.