Journal articles: 'Financial forecasts'

1

Arora, Vivek. "Monetary policy transparency and financial market forecasts in South Africa." Journal of Economic and Financial Sciences 2, no. 1 (April 30, 2008): 31–56. http://dx.doi.org/10.4102/jef.v2i1.358.

Full text

Abstract:

The transparency of monetary policy in South Africa has increased substantially since the end of the 1990s. But little empirical work has been done to examine the economic benefits of the increased transparency. This paper shows that, in recent years, South African private sector forecasters have become better able to forecast interest rates, are less surprised by reserve bank policy announcements, and are less diverse in the cross-sectional variety of their interest rate forecasts. In addition, there is some evidence that the accuracy of inflation forecasts has increased. The improvements in interest rate and inflation forecasts have exceeded those in real output forecasts, suggesting that increases in monetary policy transparency are likely to have played a role.

APA, Harvard, Vancouver, ISO, and other styles

2

Keung, Edmund C. "Do Supplementary Sales Forecasts Increase the Credibility of Financial Analysts’ Earnings Forecasts?" Accounting Review 85, no. 6 (November 1, 2010): 2047–74. http://dx.doi.org/10.2308/accr.2010.85.6.2047.

Full text

Abstract:

ABSTRACT: This study examines whether the market reacts more strongly to earnings forecast revisions when financial analysts supplement their earnings forecasts with sales forecasts. I find that earnings forecast revisions supplemented with sales forecast revisions have a greater impact on security prices than do stand-alone earnings forecast revisions, controlling for the incremental information content in sales forecasts. Supplemented earnings forecasts are more accurate ex post, controlling for other individual analyst characteristics. Results are robust to controlling for earnings persistence and time effects. Taken as a whole, financial analysts are more likely to supplement their earnings forecasts with sales forecasts when they have better information. Supplementary sales forecasts appear to lend credibility to earnings forecasts because financial analysts provide sales forecasts when they are more informed.

APA, Harvard, Vancouver, ISO, and other styles

3

Keskek, Sami, and Senyo Y. Tse. "Does Forecast Bias Affect Financial Analysts’ Market Influence?" Journal of Accounting, Auditing & Finance 33, no. 4 (September 1, 2016): 601–23. http://dx.doi.org/10.1177/0148558x16665965.

Full text

Abstract:

Prior studies find that analysts tend to bias their forecasts upward in poor information environments and downward in rich information environments, consistent with attempts to curry favor with management. We find that investors anticipate this behavior by reducing their response to upward forecasts in poor information environments and downward forecasts in rich information environments. Using Hugon and Muslu’s measure of analyst conservatism as an ex ante indicator of individual analysts’ forecast bias tendencies, we show that the stronger return response they find to conservative analysts’ forecast revisions is restricted to poor information environments, where optimistic analyst bias is prevalent. Our results suggest that analysts pay a price in market influence when their forecasts reinforce analysts’ typical forecast bias for the firm’s information environment. Conversely, analysts whose forecasts conflict with the typical bias for the firm are rewarded with larger than average return responses.

APA, Harvard, Vancouver, ISO, and other styles

4

Park, Hyung Ju, and Joong-Seok Cho. "Earnings Transparency and Financial Analysts’ Target Price Forecasts." International Journal of Financial Research 11, no. 4 (June 28, 2020): 1. http://dx.doi.org/10.5430/ijfr.v11n4p1.

Full text

Abstract:

This paper examines the effect of earnings transparency on analysts’ target price forecast properties. The issuance of target price forecasts by financial analysts is a very recent event and target price forecasts are regarded as the most summarized and explicit estimate of the postulated future value of the firm.The sample consists of financial analysts’ forecasts of annual target price issued for firms listed on U.S. stock exchanges from 2001 to 2017. We measure each firm’s earnings transparency as the contemporaneous co-movement between firm’s earnings and change in earnings and stock returns, consisting in industry-specific and -neutral components in earnings-returns relation.Our results show that target price forecasts for more transparent earnings are less biased and more tend to attain the actual stock prices. These results demonstrate that earnings transparency is positively related with analysts’ target price forecasts. Our empirical results corroborate that more transparent accounting information help the market participants in forming more accurate and attainable forecasts. Our study extends the body of research studying the relation between analysts’ forecast properties and the usefulness of accounting information by investigation target price forecasts.

APA, Harvard, Vancouver, ISO, and other styles

5

Frischmann, Peter, K. C. Lin, and Dilin Wang. "Analyst reaction to non-articulation between the balance sheet and the statement of cash flows." Journal of Applied Accounting Research 21, no. 1 (November 19, 2019): 163–84. http://dx.doi.org/10.1108/jaar-02-2019-0036.

Full text

Abstract:

Purpose The purpose of this paper is to investigate the effect of non-articulation on analyst earnings forecast quality. The authors look for evidence on the relationship between non-articulation and analyst earnings forecast properties: forecast inaccuracy, forecast dispersion and forecast bias. Design/methodology/approach The empirical tests are primarily based analyst earnings and cash flow forecasts covered by Institutional Broker Estimate System and financial statement information obtained from Compustat North America database. Findings The authors hypothesize and find that non-articulation is positively related to analyst forecast dispersion, forecast accuracy and forecast bias for one-year ahead of earnings. The effects of non-articulation on analyst earnings forecast inaccuracy and bias are neutralized when the analyst issues a cash flow forecast and when such forecast provides accurate information regarding the forecasted firm’s operating cash flow. On the other hand, cash flow forecast issuance alone does not mitigate the negative influence of non-articulation. Research limitations/implications The sample selection procedure limits the generalizability of the findings. Practical implications The findings confirm CFA Institute and prior research asserting that non-articulation deteriorates the quality of earnings forecasts by financial statement users (more specifically, the financial analysts). The authors add to the literature by documenting that accurate cash flow forecasts help analysts mitigate the negative influence of non-articulation on earnings forecast quality. Originality/value It remains an empirical question whether non-articulation between the balance sheet and the statement of cash flows has an effect on financial statement users’ ability to assimilate financial information. The paper highlights the detrimental effect of non-articulation by documenting the relationship between the non-articulation and the quality of earnings expectation.

APA, Harvard, Vancouver, ISO, and other styles

6

Fedyk, Tatiana. "Refining financial analysts’ forecasts by predicting earnings forecast errors." International Journal of Accounting & Information Management 25, no. 2 (May 2, 2017): 256–72. http://dx.doi.org/10.1108/ijaim-06-2016-0065.

Full text

Abstract:

Purpose The purpose of this paper is to examine the way serial correlation in quarterly earnings forecast errors varies with firm and analyst attributes such as the firm’s industry and the analyst’s experience and brokerage house affiliation. Prior research on financial analysts’ quarterly earnings forecasts has documented serial correlation in forecast errors. Design/methodology/approach Finding that serial correlation in forecast errors is significant and seemingly independent of firm and analyst attributes, the consensus forecast errors are modeled as an autoregressive process. The model of forecast errors that best fits the data is AR(1), and the obtained autoregressive coefficients are used to predict consensus forecast errors. Findings Modeling the consensus forecast errors as an autoregressive process, the present study predicts future consensus forecast errors and proposes a series of refinements to the consensus. Originality/value These refinements were not presented in prior literature and can be useful to financial analysts and investors.

APA, Harvard, Vancouver, ISO, and other styles

7

Ugurlu, Umut, Oktay Tas, Aycan Kaya, and Ilkay Oksuz. "The Financial Effect of the Electricity Price Forecasts’ Inaccuracy on a Hydro-Based Generation Company." Energies 11, no. 8 (August 11, 2018): 2093. http://dx.doi.org/10.3390/en11082093.

Full text

Abstract:

Electricity price forecasting has a paramount effect on generation companies (GenCos) due to the scheduling of the electricity generation scheme according to electricity price forecasts. Inaccurate electricity price forecasts could cause important loss of profits to the suppliers. In this paper, the financial effect of inaccurate electricity price forecasts on a hydro-based GenCo is examined. Electricity price forecasts of five individual and four hybrid forecast models and the ex-post actual prices are used to schedule the hydro-based GenCo using Mixed Integer Linear Programming (MILP). The financial effect measures of profit loss, Economic Loss Index (ELI) and Price Forecast Disadvantage Index (PFDI), as well as Mean Absolute Error (MAE) of the models are used for comparison of the data from 24 weeks of the year. According to the results, a hybrid model, 50% Artificial Neural Network (ANN)–50% Long Short Term Memory (LSTM), has the best performance in terms of financial effect. Furthermore, the forecast performance evaluation methods, such as Mean Absolute Error (MAE), are not necessarily coherent with inaccurate electricity price forecasts’ financial effect measures.

APA, Harvard, Vancouver, ISO, and other styles

8

Thiagarajah, K., and A. Thavaneswaran. "Fuzzy random‐coefficient volatility models with financial applications." Journal of Risk Finance 7, no. 5 (October 1, 2006): 503–24. http://dx.doi.org/10.1108/15265940610712669.

Full text

Abstract:

PurposeThe purpose of this research is to introduce a class of FRC (fuzzy random coefficient) volatility models and to study their moment properties. Fuzzy option values and the superiority of fuzzy forecasts over minimum mean‐square forecasts are also discussed in some detail.Design/methodology/approachFuzzy components are assumed to be triangular fuzzy numbers. Buckley's data‐driven method is used to determine the spread of the triangular fuzzy numbers by using standard errors of the estimated parameters.FindingsThe fuzzy kurtosis of various volatility models is obtained in terms of fuzzy coefficients. Fuzzy option values and fuzzy forecasts are illustrated with examples. Fuzzy forecast intervals are narrower than the corresponding MMSE forecast intervals.Originality/valueThis paper will be of value to econometricians and to anyone with an interest in financial volatility models.

APA, Harvard, Vancouver, ISO, and other styles

9

Ghysels, Eric, Alberto Plazzi, Rossen Valkanov, Antonio Rubia, and Asad Dossani. "Direct Versus Iterated Multiperiod Volatility Forecasts." Annual Review of Financial Economics 11, no. 1 (December 26, 2019): 173–95. http://dx.doi.org/10.1146/annurev-financial-110217-022808.

Full text

Abstract:

Multiperiod-ahead forecasts of returns’ variance are used in most areas of applied finance where long-horizon measures of risk are necessary. Yet, the major focus in the variance forecasting literature has been on one-period-ahead forecasts. In this review, we compare several approaches of producing multiperiod-ahead forecasts within the generalized autoregressive conditional heteroscedastic (GARCH) and realized volatility (RV) families—iterated, direct, and scaled short-horizon forecasts. We also consider the newer class of mixed data sampling (MIDAS) methods. We carry the comparison on 30 assets, comprising equity, Treasury, currency, and commodity indices. While the underlying data are available at high frequency (5 minutes), we are interested in forecasting variances 5, 10, 22, 44, and 66 days ahead. The empirical analysis, which is performed in sample and out of sample with data from 2005 to 2018, yields the following results: Iterated GARCH dominates the direct GARCH approach, and the direct RV is preferred to the iterated RV. This dichotomy of results emphasizes the need foran approach that uses the richness of high-frequency data and, at the same time, produces a direct forecast of the variance at the desired horizon, without iterating. The MIDAS is such an approach, and unsurprisingly, it yields the most precise forecasts of variance both in and out of sample. More broadly, our study dispels the notion that volatility is not forecastable at long horizons and offers an approach that delivers accurate out-of-sample predictions.

APA, Harvard, Vancouver, ISO, and other styles

10

Bordalo, Pedro, Nicola Gennaioli, Yueran Ma, and Andrei Shleifer. "Overreaction in Macroeconomic Expectations." American Economic Review 110, no. 9 (September 1, 2020): 2748–82. http://dx.doi.org/10.1257/aer.20181219.

Full text

Abstract:

We study the rationality of individual and consensus forecasts of macroeconomic and financial variables using the methodology of Coibion and Gorodnichenko (2015), who examine predictability of forecast errors from forecast revisions. We find that individual forecasters typically overreact to news, while consensus forecasts under-react relative to full-information rational expectations. We reconcile these findings within a diagnostic expectations version of a dispersed information learning model. Structural estimation indicates that departures from Bayesian updating in the form of diagnostic overreaction capture important variation in forecast biases across different series, yielding a belief distortion parameter similar to estimates obtained in other settings. (JEL C53, D83, D84, E13, E17, E27, E47)

APA, Harvard, Vancouver, ISO, and other styles

11

Lo, Kin, and Serena Shuo Wu. "The Impact of Seasonal Affective Disorder on Financial Analysts." Accounting Review 93, no. 4 (October 1, 2017): 309–33. http://dx.doi.org/10.2308/accr-51953.

Full text

Abstract:

ABSTRACT We examine the impact of Seasonal Affective Disorder (SAD) on financial analysts. We hypothesize and find that analysts are more pessimistic, less precise, and more asymmetric in their boldness in the fall, as indicated by their forecasts of quarterly earnings. The effects are apparent in all forecast horizons analyzed and robust across multiple specifications. Importantly, pessimism in fall forecast revisions shows analyst-specific persistence, providing a strong indication that the effect is a result of SAD rather than other coincident factors. We also find evidence of a reversal in pessimism in the spring. Additional analyses show that analyst forecasts exhibit less seasonality than equity returns, and that the presence of analyst forecasts in the fall is associated with attenuation in the seasonal pattern in stock returns. Overall, the evidence suggests that SAD affects both financial analysts and equity investors, but the effect on the latter is stronger. JEL Classifications: G11; G12; G14; G41; M41. Data Availability: Data are available from public sources cited in the text.

APA, Harvard, Vancouver, ISO, and other styles

12

Harris, Richard D. F., and Pengguo Wang. "Model-based earnings forecasts vs. financial analysts' earnings forecasts." British Accounting Review 51, no. 4 (June 2019): 424–37. http://dx.doi.org/10.1016/j.bar.2018.10.002.

Full text

APA, Harvard, Vancouver, ISO, and other styles

13

Campbell, Sean D., and Steven A. Sharpe. "Anchoring Bias in Consensus Forecasts and Its Effect on Market Prices." Journal of Financial and Quantitative Analysis 44, no. 2 (April 2009): 369–90. http://dx.doi.org/10.1017/s0022109009090127.

Full text

Abstract:

AbstractPrevious empirical studies on the “rationality” of economic and financial forecasts generally test for generic properties such as bias or autocorrelated errors but provide only limited insight into the behavior behind inefficient forecasts. This paper tests for a specific form of forecast bias. In particular, we examine whether expert consensus forecasts of monthly economic releases are systematically biased toward the value of previous months’ releases. Such a bias would be consistent with the anchoring and adjustment heuristic described by Tversky and Kahneman (1974) or could arise from professional forecasters’ strategic incentives. We find broad-based and significant evidence for this form of bias, which in some cases results in sizable predictable forecast errors. To investigate whether market participants’ expectations are influenced by this bias, we examine interest rate reactions to economic news. We find that bond yields react only to the residual, or unpredictable, component of the forecast error and not to the component induced by anchoring, suggesting that expectations of market participants anticipate this bias embedded in expert forecasts.

APA, Harvard, Vancouver, ISO, and other styles

14

Jaditz, Ted, Leigh A. Riddick, and Chera L. Sayers. "MULTIVARIATE NONLINEAR FORECASTING Using Financial Information to Forecast the Real Sector." Macroeconomic Dynamics 2, no. 3 (September 1998): 369–82. http://dx.doi.org/10.1017/s1365100598008049.

Full text

Abstract:

Previous work shows that financial series contain important information on the current state of the economy and expectations for the future. Further, numerous papers find links between the financial sectors and the real sectors of the economy. We add to those findings by exploring whether financial variables help to forecast the growth rate of industrial production. We evaluate linear and nonlinear forecasting methods using out-of-sample forecasting performance. We compare autoregressive models, error-correcting models, and multivariate nearest-neighbor regression models, and we explore the use of optimally combined forecasts. We find that no single forecasting technique appears to outperform any other method, and the evidence for persistent nonlinear patterns is weak. However, although nonparametric methods do not offer significant improvements in forecast accuracy by themselves, more accurate forecasts are obtained when the nonlinear forecasts are optimally combined. Our results indicate that financial information can statistically improve the forecasts of the real sector in these combined models, but the magnitude of the improvement in root-mean-squared error is small.

APA, Harvard, Vancouver, ISO, and other styles

15

Fulton, Chad, and Kirstin Hubrich. "Forecasting US Inflation in Real Time." Finance and Economics Discussion Series 2021, no. 014 (March 4, 2021): 1–32. http://dx.doi.org/10.17016/feds.2021.014.

Full text

Abstract:

We perform a real-time forecasting exercise for US inflation, investigating whether and how additional information--additional macroeconomic variables, expert judgment, or forecast combination--can improve forecast accuracy and robustness. In our analysis we consider the pre-pandemic period including the Global Financial Crisis and the following expansion--the longest on record--featuring unemployment that fell to a rate not seen for nearly sixty years. Distinguishing features of our study include the use of published Federal Reserve Board staff forecasts contained in Tealbooks and a focus on forecasting performance before, during, and after the Global Financial Crisis, with relevance also for the current crisis and beyond. We find that while simple models remain hard to beat, the additional information that we consider can improve forecasts, especially in the post-crisis period. Our results show that (1) forecast combination approaches improve forecast accuracy over simpler models and robustify against bad forecasts, a particularly relevant feature in the current environment; (2) aggregating forecasts of inflation components can improve performance compared to forecasting the aggregate directly; (3) judgmental forecasts, which likely incorporate larger and more timely datasets, provide improved forecasts at short horizons.

APA, Harvard, Vancouver, ISO, and other styles

16

Chen, Sophia, and Romain Ranciere. "Financial Information and Macroeconomic Forecasts." IMF Working Papers 16, no. 251 (2016): 1. http://dx.doi.org/10.5089/9781475563177.001.

Full text

APA, Harvard, Vancouver, ISO, and other styles

17

Chen, Sophia, and Romain Ranciere. "Financial information and macroeconomic forecasts." International Journal of Forecasting 35, no. 3 (July 2019): 1160–74. http://dx.doi.org/10.1016/j.ijforecast.2019.03.005.

Full text

APA, Harvard, Vancouver, ISO, and other styles

18

Rogers, Jonathan L., and Phillip C. Stocken. "Credibility of Management Forecasts." Accounting Review 80, no. 4 (October 1, 2005): 1233–60. http://dx.doi.org/10.2308/accr.2005.80.4.1233.

Full text

Abstract:

We examine how the market's ability to assess the truthfulness of management earnings forecasts affects how managers bias their forecasts, and we evaluate whether the market's response to management forecasts is consistent with it identifying predictable forecast bias. We find managers' willingness to misrepresent their forwardlooking information as a function of their incentives varies with the market's ability to detect misrepresentation. We examine incentives induced by the litigation environment, insider trading activities, firm financial distress, and industry concentration. With regard to the stock price response to forecasts, we find the market varies its response with the predictable bias in the forecast. The efficiency of the market's response, however, varies with the forecast news.

APA, Harvard, Vancouver, ISO, and other styles

19

Oh, Hyun Min, and Ho young Shin. "A Study on the Relationship between Analysts’ Cash Flow Forecasts Issuance and Accounting Information: Evidence from Korea." Sustainability 11, no. 12 (June 20, 2019): 3399. http://dx.doi.org/10.3390/su11123399.

Full text

Abstract:

This study analyzes the relationship between the future cash flow forecast information provided by financial analysts and accounting information. We examine whether the joint issuance of financial analyst earnings forecasts and cash flow forecasts from 2011 to 2015 contributes to the information usefulness of Korean listed firms. The empirical results of this study are as follows. First, the issuance of analysts’ cash flow forecasts and earnings forecast accuracy were significant positive values. Cash flow forecast accuracy and earnings forecast accuracy were significant positive values. Second, the issuance of analysts’ cash flow forecasts and buy–sell bid spread are significant negative values. These results show that the information asymmetry between the manager and the investor can be reduced based on the rich information environment. This study suggests that cash flow forecasting information of financial analysts provides important evidence for capital market participants because it provides evidence that capital market participants’ information can be used as useful information for economic decision-making. These results show the sustainability of a firm from the viewpoint of a financial analyst who acts as an intermediary and external supervisor in the capital market. In addition, the analysts’ cash flow forecasting information is expected to reduce the information asymmetry between the company and the investor, thereby increasing the transparency and sustainability of the firm.

APA, Harvard, Vancouver, ISO, and other styles

20

Hernandez, Michael Kevin, Caroline Howard, Richard Livingood, and Cynthia Calongne. "Applications of Decision Tree Analytics on Semi-Structured North Atlantic Tropical Cyclone Forecasts." International Journal of Sociotechnology and Knowledge Development 11, no. 2 (April 2019): 31–53. http://dx.doi.org/10.4018/ijskd.2019040103.

Full text

Abstract:

This interdisciplinary quantitative study examines how a text mining technique that is widely used to understand financial market forecasts could also help in understanding North Atlantic Tropical Cyclone (TC) forecasts. TCs are a destructive circulation of thunderstorms over a surface low-pressure center. The C4.5 decision tree algorithm has been used successfully to aid in the understanding of financial market forecasts with accuracy rates greater than 55%. This study has examined the use of the C4.5 decision tree algorithm on a 15-year period of the National Hurricane Centers five-day TC forecasts to see if the algorithm could provide a statistically significant value to improving the overall TC forecast accuracy. Improvements in the overall TC forecast accuracy can aid in providing those impacted by a TC adequate early, relevant, and lifesaving TC watches and warnings. This study has helped identify key weather pattern components that have significant information gain, which can help both researchers and practitioners prioritize projects that could help improve TC forecasts.

APA, Harvard, Vancouver, ISO, and other styles

21

Barron, Orie E., Charles R. Enis, and Hong Qu. "Do Financial Professionals Process Information Better as a Group Than Non-Professionals?" Journal of Risk and Financial Management 14, no. 5 (May 20, 2021): 230. http://dx.doi.org/10.3390/jrfm14050230.

Full text

Abstract:

In this study, we study information processing by financial professionals benchmarked with non-professionals and how correlation among individual forecasts explains the group level forecast performance. In an experiment in which participants make price forecasts based on common financial information, we find that individual professionals are no better than individual non-professionals in forecasting, but professionals’ mean forecasts are superior. Our analysis suggests that financial professionals’ individual errors are less correlated as they process information from more diverse perspectives. This leads to superior mean forecasts because the uncorrelated individual errors cancel each other out in the aggregate. In contrast, non-professionals are similar in using salient information such as earnings or cash flow. As a result, their individual errors are highly correlated. Instead of cancelling each other out, the individual errors are enlarged in the aggregated mean forecasts. We are the first to show the difference in the comparisons of professionals and non-professionals at the group level versus at the individual level. Our paper contributes to the literature by documenting the evidence of diversity in information processing by financial professionals.

APA, Harvard, Vancouver, ISO, and other styles

22

Umezawa, Toshihiro, and Ujo Goto. "Corporate ownership structure and management earnings forecast." Corporate Ownership and Control 4, no. 3 (2007): 247–50. http://dx.doi.org/10.22495/cocv4i3c2p2.

Full text

Abstract:

The purpose of this paper is to examine how the structure of corporate ownership impacts the accuracy of management earning forecasts in Japan. An evaluation of the financial reporting reform from 2000 is also presented. As a result, corporate ownership structure variables, such as managerial ownership, financial institution ownership, foreign investment ownership and corporation ownership, are negatively associated with the accuracy of management earnings forecast. We find that corporate ownership structure makes the manager announce more accurate management earnings forecasts. In addition, the reform of financial reporting system in 2000 has an influence on the quality of financial disclosures

APA, Harvard, Vancouver, ISO, and other styles

23

Hodder, Leslie, Patrick E. Hopkins, and David A. Wood. "The Effects of Financial Statement and Informational Complexity on Analysts’ Cash Flow Forecasts." Accounting Review 83, no. 4 (July 1, 2008): 915–56. http://dx.doi.org/10.2308/accr.2008.83.4.915.

Full text

Abstract:

ABSTRACT: We characterize the operating-activities section of the indirect-approach statement of cash flows as backward because it presents reconciling adjustments in a way that is opposite from the intuitively appealing, future-oriented, Conceptual Framework definitions of assets, liabilities, and the accruals process. We propose that the reversed-accruals orientation required in the currently mandated indirect-approach statement of cash flows is unnecessarily complex, causing information-processing problems that result in increased cash flow forecast error and dispersion. We also predict that the mixed pattern (i.e., +/−, −/+) of operating cash flows and operating accruals reported by most companies impedes investors’ ability to learn the time-series properties of cash flows and accruals. We conduct a carefully controlled experiment and find that (1) cash flow forecasts have lower forecast error and dispersion when the indirect-approach statement of cash flows starts with operating cash flows and adds changes in accruals to arrive at net income and (2) cash flow forecasts have lower forecast error and dispersion when the cash flows and accruals are of the same sign (i.e., +/+, −/−); with the sign-based difference attenuated in the forward-oriented statement of cash flows. We also conduct a quasi-experiment to test our mixed-sign versus same-sign hypotheses using archival samples of publicly available I/B/E/S and Value Line cash flow forecasts. We find that the passively observed samples of cash flow forecasts exhibit a similar pattern of mixed-sign versus same-sign forecast error as documented in our experiment.

APA, Harvard, Vancouver, ISO, and other styles

24

Salamouris, Ioannis S., and Yaz Gulnur Muradoglu. "Estimating analyst's forecast accuracy using behavioural measures (Herding) in the United Kingdom." Managerial Finance 36, no. 3 (February 23, 2010): 234–56. http://dx.doi.org/10.1108/03074351011019564.

Full text

Abstract:

PurposeThe purpose of this paper is to identify herding behaviour on financial markets and measure the herding behaviour impact on the accuracy of analysts' earnings forecasts.Design/methodology/approachTwo alternative measures of herding behaviour, on analysts' earnings forecasts are proposed. The first measure identifies herding as the tendency of analysts to forecast near the consensus. The second measure identifies herding as the tendency of analysts to follow the most accurate forecaster. This paper employs the method of The Generalised Method of Moments in order to relax any possible biases.FindingsIn both measures employed, a positive and significant relation is found between the accuracy of analysts' earnings forecasts and herding behaviour. According to the first measure analysts exhibit herding behaviour by forecasting close to the consensus estimates. According the second herding measure, it is found that analysts tend to herd towards the best forecaster at the time. Finally, it is concluded that the accuracy of analysts' forecasts increases as herding increases.Research limitations/implicationsThe present study triggers concerns for further research in the modelling of analysts' forecasting behaviour.Originality/valueThis paper proposes that a measure based on human biases is the best way to estimate and predict the analysts' earnings forecast future accuracy.

APA, Harvard, Vancouver, ISO, and other styles

25

Haw, In-Mu, Kooyul Jung, and William Ruland. "The Accuracy of Financial Analysts' Forecasts after Mergers." Journal of Accounting, Auditing & Finance 9, no. 3 (July 1994): 465–83. http://dx.doi.org/10.1177/0148558x9400900306.

Full text

Abstract:

This paper examines forecasts developed by financial analysts before and after mergers. The study finds that forecast accuracy decreases sharply after mergers. These accuracy reductions tend to be more pronounced when financial leverage changes, when the merger does not provide earnings or industry diversification, when the purchase method of accounting is used to record the transaction, when capital intensity changes, and when the size of the target corporation is large compared to the size of the acquiring corporation. The data also show that reductions in forecast accuracy after mergers tend to be temporary. Accuracy returns to approximately the premerger level within four years after the merger. The study also finds that overprediction bias increases sharply in the year immediately following the merger. This increase in over-prediction bias, however, is also temporary. Overprediction bias returns to approximately the premerger level within the four-year postmerger study period.

APA, Harvard, Vancouver, ISO, and other styles

26

Ratha, Dilip, and Sanket Mohapatra. "Forecasting migrant remittances during the global financial crisis." MIGRATION LETTERS 7, no. 2 (January 28, 2014): 203–13. http://dx.doi.org/10.33182/ml.v7i2.193.

Full text

Abstract:

The financial crisis has highlighted the need for forecasts of remittance flows in many developing countries where these flows have proved to be a lifeline to the poor people and the economy. This note describes a simple methodology for forecasting country-level remittance flows in a manner consistent with the medium-term outlook for the global economy. Remittances are assumed to depend on bilateral migration stocks and income levels in the host country and the origin country. Changes in remittance costs, shifts in remittance channels, global exchange rate movements and unpredictable immigration controls in the migrant-destination countries pose risks to the forecasts. Much remains to be done to improve the forecast methodology, data on bilateral flows, and high-frequency monitoring of migration and remittance flows.

APA, Harvard, Vancouver, ISO, and other styles

27

Babikir, Ali, and Henry Mwambi. "Forecasting financial variables using artificial neural networks - dynamic factor model." Journal of Economic and Financial Sciences 10, no. 1 (June 6, 2017): 94–106. http://dx.doi.org/10.4102/jef.v10i1.7.

Full text

Abstract:

In this paper we introduce a new model that uses the dynamic factor model (DFM) framework combined with artificial neural network (ANN) analysis, which accommodates a large cross-section of financial and macroeconomic time series for forecasting. In our new ANN-DF model we use the factor model to extract factors from ANNs in sample forecasts for each single series of the dataset, which contains 228 monthly series. These factors are then used as explanatory variables in order to produce more accurate forecasts. We apply this new model to forecast three South African variables, namely, Rate on three-month trade financing, Lending rate and Short-term interest rate in the period 1992:1 to 2011:12. The model comparison results, based on the root mean square errors of three, six and twelve months ahead out-of-sample forecasts over the period 2007:1 to 2011:12 indicate that, in all of the cases, the ANN-DFM and the DFM statistically outperform the autoregressive (AR) models. In the majority of cases the ANN-DFM outperforms the DFM. The results indicate the usefulness of the factors in forecasting performance. The RMSE results are confirmed by the test of equality of forecast accuracy proposed by Diebold-Mariano.

APA, Harvard, Vancouver, ISO, and other styles

28

Khaustova, V. Ye, N. V. Demchenko, V. G. Kovalchuk, and M. V. Volkova. "GLOBAL FINANCIAL SYSTEM: RISKS AND FORECASTS." Financial and credit activity: problems of theory and practice 1, no. 24 (March 30, 2018): 368–73. http://dx.doi.org/10.18371/fcaptp.v1i24.128474.

Full text

APA, Harvard, Vancouver, ISO, and other styles

29

Gauci, Bernard, and Thomas Baumgartner. "Inaccurate Financial Forecasts and Societal Complexity." Human Systems Management 8, no. 2 (1989): 145–54. http://dx.doi.org/10.3233/hsm-1989-8209.

Full text

APA, Harvard, Vancouver, ISO, and other styles

30

Du, Ning, David V. Budescu, Marjorie K. Shelly, and Thomas C. Omer. "The appeal of vague financial forecasts." Organizational Behavior and Human Decision Processes 114, no. 2 (March 2011): 179–89. http://dx.doi.org/10.1016/j.obhdp.2010.10.005.

Full text

APA, Harvard, Vancouver, ISO, and other styles

31

Christodoulakis, George A. "Generalised Rational Bias in Financial Forecasts." Annals of Finance 2, no. 4 (May 4, 2006): 397–405. http://dx.doi.org/10.1007/s10436-006-0043-1.

Full text

APA, Harvard, Vancouver, ISO, and other styles

32

Strawser, Jerry R. "An Investigation of the Effect of Accountant Involvement with Forecasts on the Decisions and Perceptions of Commercial Lenders." Journal of Accounting, Auditing & Finance 9, no. 3 (July 1994): 533–57. http://dx.doi.org/10.1177/0148558x9400900312.

Full text

Abstract:

Guidance for the traditional attest function recently has been expanded to provide directions to independent accountants performing engagements on forecasted financial statements (“Financial Forecasts and Projections,” AICPA [1992, AT 200]). Although the use of forecasted financial information in lending decisions has been extensively examined in previous research, the extent to which engagements identified by “Financial Forecasts and Projections” actually affect users' decisions and perceptions has not been determined. This study examines whether decisions and perceptions of commercial lenders are influenced by the level of accountant involvement (no involvement, a compilation engagement, or an examination engagement) with a hypothetical loan candidate's forecasted financial statements. The results of this study indicate that bankers consider the extent of accountant involvement with forecasted financial statements in their lending decisions. In addition, a significant interaction between the level of accountant involvement with historical financial statements and forecasted financial statements indicates that this effect is more pronounced when the accountant also audits the loan candidate's historical financial statements. However, bankers' perceptions of the responsibilities assumed and assurances provided by the accountant in these engagements differ from statements in accountants' reports. These inconsistencies suggest the need for the AICPA to modify current accountants' reports to communicate more clearly the nature of these engagements and to provide further education to users.

APA, Harvard, Vancouver, ISO, and other styles

33

Chlebus, Marcin. "EWS-GARCH: New Regime Switching Approach to Forecast Value-at-Risk." Central European Economic Journal 3, no. 50 (December 18, 2018): 01–25. http://dx.doi.org/10.1515/ceej-2017-0014.

Full text

Abstract:

Abstract In the study, the two-step EWS-GARCH models to forecast Value-at-Risk is presented. The EWS-GARCH allows different distributions of returns or Value-at-Risk forecasting models to be used in Value-at-Risk forecasting depending on a forecasted state of the financial time series. In the study EWS-GARCH with GARCH(1,1) and GARCH(1,1), with the amendment to the empirical distribution of random errors as a Value-at-Risk model in a state of tranquillity and empirical tail, exponential or Pareto distributions used to forecast Value-at-Risk in a state of turbulence were considered. The evaluation of Value-at-Risk forecasts was based on the Value-at-Risk forecasts and the analysis of loss functions. Obtained results indicate that EWS-GARCH models may improve the quality of Value-at-Risk forecasts generated using the benchmark models. However, the choice of best assumptions for the EWS-GARCH model should depend on the goals of the Value-at-Risk forecasting model. The final selection may depend on an expected level of adequacy, conservatism and costs of the model.

APA, Harvard, Vancouver, ISO, and other styles

34

Liu, Xiaohui Gloria, and Ramachandran Natarajan. "The Effect of Financial Analysts' Strategic Behavior on Analysts' Forecast Dispersion." Accounting Review 87, no. 6 (June 1, 2012): 2123–49. http://dx.doi.org/10.2308/accr-50212.

Full text

Abstract:

ABSTRACT Financial analysts' forecast dispersion has been used in a variety of contexts in accounting and finance studies. In this study, we provide large sample evidence on the cross-sectional determinants of forecast dispersion and examine to what extent analysts' strategic behavior biases the observed dispersion from the dispersion of unmanaged forecasts. We propose a method to estimate the dispersion bias for each sample observation. We find that observed dispersion, on average, understates dispersion of unmanaged forecasts by 53.4 percent and this downward bias varies considerably across firms. We further discuss the implications of the significant cross-sectional variation in the bias in observed dispersion for studies that rely on dispersion to estimate constructs such as consensus and information quality as well as those that use dispersion directly in research design. Data Availability: The data are publicly available for the sources indicated.

APA, Harvard, Vancouver, ISO, and other styles

35

Heo, Kyongsun, and Seoyoung Doo. "Segment Reporting Level And Analyst Forecast Accuracy." Journal of Applied Business Research (JABR) 34, no. 3 (May 7, 2018): 471–86. http://dx.doi.org/10.19030/jabr.v34i3.10170.

Full text

Abstract:

In a setting where the primary financial statements have been converted from individual financial statements to consolidated financial statements in Korea, we examine the effect of segment information disclosed by the firm on analysts’ consolidated-base earnings forecast accuracy. Since Korean firms have prepared the primary financial statements on a non-consolidated basis in the pre-IFRS regime, the adoption of International Financial Reporting Standards (IFRS) leads to a great deal of difficulties and complexities in making accurate consolidated forecasts for users of financial statements, even for financial analysts who are sophisticated users of financial statements. In this situation, we conjecture that the amount of details and types of information in segment disclosure will influence analysts’ forecast accuracy. Consistent with the prediction, we find that financial analysts are able to make more accurate earnings projections when firms provide more disaggregated accounting figures by each segment. Moreover, we find that analysts can make forecasts more accurately when firms disclose more persistent earnings component (i.e., segment operating income). Furthermore, we find that the effect of the segment disclosure levels on analysts’ forecast accuracy is more pronounced for firms with multi-segments. Our results indicate that disaggregated segment information is a useful source for financial analysts to have better understanding about complete picture of firms’ consolidated earnings and improve their forecasting performance.

APA, Harvard, Vancouver, ISO, and other styles

36

Kothari, S. P., Eric So, and Rodrigo Verdi. "Analysts’ Forecasts and Asset Pricing: A Survey." Annual Review of Financial Economics 8, no. 1 (October 23, 2016): 197–219. http://dx.doi.org/10.1146/annurev-financial-121415-032930.

Full text

APA, Harvard, Vancouver, ISO, and other styles

37

Zheng, Xinyuan. "Financial Time Series Analysis by Using MATLAB." Asian Business Research 4, no. 3 (October 8, 2019): 48. http://dx.doi.org/10.20849/abr.v4i3.687.

Full text

Abstract:

This report contains two parts. For part A, performing a Principle Components Analysis (PCA) and analyzing the drivers. Then, carrying out factor analyses and comparing them. For part B, employing 5 different quantitative models to forecast and generate moving origin horizon one forecasts of both return and volatility. Then, figuring out the optimal weights for the portfolio and assigning the optimal portfolio. Finally, comparing the returns and risk measure from all portfolio and models.

APA, Harvard, Vancouver, ISO, and other styles

38

Turki, Hela, Senda Wali, and Younes Boujelbene. "The effect of the level of indebtedness on the earnings information content stemming from the mandatory IFRS adoption." International Journal of Accounting and Economics Studies 4, no. 1 (January 18, 2016): 12. http://dx.doi.org/10.14419/ijaes.v4i1.5585.

Full text

Abstract:

<p>This paper examines the impact of IFRS / IAS (International Financial Reporting Standards / International Accounting Standards) mandatory adoption on the earning's information content apprehended by the level of information asymmetry and whether this impact differs from one company to another with regard to its level of indebtedness. The information asymmetry is measured by the properties of financial analysts’ forecasts (error and dispersion).This study is conducted over 11 years from 2002 to 2012 by taking as a sample all the companies that belong to the CAC all tradable indexes. The results show a significant effect of these international's standards on financial analysts' forecasts, which stress informational content improvement. In addition, high level of indebtedness associated with IFRS adoption reduces forecast dispersion. By contrast, low level of indebtedness associated with IFRS adoption reduces forecast error.</p>

APA, Harvard, Vancouver, ISO, and other styles

39

Sukhanova, E. I., S. Y. Shirnaeva, and E. G. Repina. "Binary Choice Models-based Assessment of Company’s Financial Sustainability." SHS Web of Conferences 62 (2019): 13002. http://dx.doi.org/10.1051/shsconf/20196213002.

Full text

Abstract:

Assessment of financial sustainability is a key instrument that every company should use to successfully operate in the contemporary marketplace. In this paper profit was chosen as one of the sustainability indices and binary choice model logistics regression model (logit model) was built for that index. The research data for this study is drawn from accounting statements of a textile industry business in Samara city. A combination of econometric approaches was used in the data analysis. Binary choice models were adopted in this research. Then those models were estimated for validity. Also scenario forecasts methodology was employed in this study. Several logit models with a set of explanatory variables were constructed. After the comparison of those models the preferred one was determined. Based on that model a scenario for profits was forecasted including both the worst-case and the best-case ones. The average-case scenario forecast was also made.

APA, Harvard, Vancouver, ISO, and other styles

40

Hunton, James E., Ruth Ann McEwen, and Benson Wier. "The Reaction of Financial Analysts to Enterprise Resource Planning (ERP) Implementation Plans (Retracted)." Journal of Information Systems 16, no. 1 (March 1, 2002): 31–40. http://dx.doi.org/10.2308/jis.2002.16.1.31.

Full text

Abstract:

This study investigates the extent to which investors believe that enterprise resource planning (ERP) systems enhance firm value by examining changes in financial analysts' earnings predictions before and after they receive an announcement that a firm plans to implement an ERP system. A total of 63 analysts participated in a two (firm size: small and large) by two (firm health: unhealthy and healthy) randomized between-subjects design. The ERP announcement represented a within-subjects manipulation. The analysts' overall reaction to ERP implementation plans was positive, as mean post-announcement earnings forecasts were significantly higher than mean pre-announcement forecasts. Additionally, as expected, mean earnings forecast revisions in the small/healthy and large/unhealthy firm conditions were significantly greater than mean forecast revisions in the small/unhealthy firm condition. Experimental results from the current study support archival findings reported by Hayes et al. (2001), who explored the same research questions, among others, by examining cumulative abnormal returns surrounding ERP announcements. Triangulation studies of this nature using multimethods (e.g., behavioral vs. archival) and complementary criterion variables (e.g., earnings forecasts vs. cumulative abnormal returns) are important to social scientists, as they provide insight into the reliability, consistency, and validity (both internal and ecological) of proposed theoretical relationships (Boyd et al. 1993; Flick 1992; Libby et al. 2002).

APA, Harvard, Vancouver, ISO, and other styles

41

Ahmed, Kamran, Muhammad Nurul Houqe, John Hillier, and Steven Crockett. "Properties of analysts’ consensus cash flow forecasts for Australian firms." Accounting Research Journal 33, no. 1 (January 2, 2020): 128–47. http://dx.doi.org/10.1108/arj-11-2017-0197.

Full text

Abstract:

Purpose The purpose of this paper is to determine the properties of analysts’ cash flows from operations (CFO) forecast generated for Australian listed firms as a productive activity, within the wider processes of financial disclosure in Australia. Design/methodology/approach Two categories of criteria are adopted: first, basic predictive statistical performance relative to a benchmark model and earnings forecasts; and second, relevance for equity pricing, as indicated by the market reaction to cash flow or forecast error reactions. The final sample comprised 2,138 observations between 2001 and 2016 and several regression models are estimated to determine the relative performance and market reaction. Findings Analysts’ consensus cash flow forecasts demonstrate poor predictive performance relative to earnings forecasts. Cash flow forecasts are typically naïve extensions of earnings forecasts. Furthermore, cash flow forecasts appear to be of minimal use for equity market participants in complementing earnings forecasts’ role in informing firms’ equity pricing. Practical implications While analysts’ earnings forecasts are useful for making predictions, the role of analysts’ cash flow forecasts in capital market functional efficiency appears quite limited. Originality/value This study is one of few that examines comparative usefulness of analysts’ earnings and cash flow forecasts and their predictive power using the Australian setting. Additionally, it enriches the sparse international literature on such forecasts.

APA, Harvard, Vancouver, ISO, and other styles

42

Miller, Jeffrey S., and Lisa M. Sedor. "Do Stock Prices Influence Analysts' Earnings Forecasts?" Behavioral Research in Accounting 26, no. 1 (September 1, 2013): 85–108. http://dx.doi.org/10.2308/bria-50626.

Full text

Abstract:

ABSTRACT This study uses an experiment with professional financial analysts to examine whether stock prices influence analysts' earnings forecasts. The findings indicate that analysts' revised forecasts made in response to a management earnings forecast differ depending on the level of uncertainty communicated by management's guidance and the stock price reaction to it. Lower (higher) stock price leads to lower (higher) analysts' forecasts when uncertainty about future earnings is high, but not when uncertainty about future earnings is low. Overall, the evidence suggests that the documented association between prior security returns and analysts' earnings forecasts is due, at least in part, to the influence of stock price on analysts' earnings forecasts. Data Availability: Contact the authors.

APA, Harvard, Vancouver, ISO, and other styles

43

Pasha, G. R., Tahira Qasim, and Muhammad Aslam. "Estimating and Forecasting Volatility of Financial Time Series in Pakistan with GARCH-type Models." LAHORE JOURNAL OF ECONOMICS 12, no. 2 (July 1, 2007): 115–49. http://dx.doi.org/10.35536/lje.2007.v12.i2.a6.

Full text

Abstract:

In this paper we compare the performance of different GARCH models such as GARCH, EGARCH, GJR and APARCH models, to characterize and forecast financial time series volatility in Pakistan. The comparison is carried out by comparing symmetric and asymmetric GARCH models with normal and fat-tailed distributions for the innovations, over short and long forecast horizons. The forecasts are evaluated according to a set of statistical loss functions. Daily data on the Karachi Stock Exchange (KSE) 100 index are analyzed. The empirical results demonstrate that the use of asymmetry in the GARCH models and the assumption of fat-tail distributions for the innovations improve the volatility forecasts. Overall, EGARCH fits the best while the GJR model, with both normal and non-normal innovations, seems to provide superior forecasting ability over short and long horizons.

APA, Harvard, Vancouver, ISO, and other styles

44

Wu, Yi (Ava), and Mark Wilson. "Audit Quality and Analyst Forecast Accuracy: The Impact of Forecast Horizon and Other Modeling Choices." AUDITING: A Journal of Practice & Theory 35, no. 2 (July 1, 2015): 167–85. http://dx.doi.org/10.2308/ajpt-51216.

Full text

Abstract:

SUMMARY The accuracy and other properties of analyst earnings forecasts represent potentially useful proxies for the impact of audit quality on client financial reports. Extant research in the auditing literature, however, is characterized by diametrically opposite predictions and inconsistent findings regarding the relationship between audit quality and analyst forecast accuracy. We argue that a potential reason for the inconsistency in the literature reflects these studies' focus on end-of-year forecast accuracy, which is subject to competing effects of audit quality. High-quality auditors may simultaneously improve forecast accuracy through their impact on the decision usefulness of clients' prior period reports, and reduce forecast accuracy by constraining client attempts to manage earnings in the direction of the consensus forecast. We argue and present evidence in support of the conjecture that analysts' beginning-of-year forecasts are a superior metric for identifying the impact of audit quality on the properties of analyst forecasts because the decision usefulness effect of audit quality should be dominant with respect to those forecasts. Data Availability: Data are available from sources identified in the article.

APA, Harvard, Vancouver, ISO, and other styles

45

Nam, Hye-Jeong. "K-IFRS Adoption and Financial Analyst’s Forecasts." korean management review 44, no. 3 (June 30, 2015): 933. http://dx.doi.org/10.17287/kmr.2015.44.3.933.

Full text

APA, Harvard, Vancouver, ISO, and other styles

46

Glover, Jonathan C., Yuji Ijiri, Carolyn B. Levine, and Pierre Jinghong Liang. "Separating Facts from Forecasts in Financial Statements." Accounting Horizons 19, no. 4 (December 1, 2005): 267–82. http://dx.doi.org/10.2308/acch.2005.19.4.267.

Full text

APA, Harvard, Vancouver, ISO, and other styles

47

Pan, Shanshan, Michael Lacina, and Haeyoung Shin. "Income Classification Shifting and Financial Analysts’ Forecasts." Review of Pacific Basin Financial Markets and Policies 22, no. 02 (June 2019): 1950010. http://dx.doi.org/10.1142/s0219091519500103.

Full text

Abstract:

Income classification shifting involves misclassifying core expenses into non-core items to boost core earnings. Managers engage in classification shifting because they believe they can manage the perceptions of investors and financial analysts. We examine analysts’ earnings forecasts to determine whether analysts can identify classification shifting ex post and how they respond to shifted income statement components. Analysts play a role as information intermediaries between firms and investors. We find that analysts respond less to increased core earnings from classification shifting. However, analysts fail to gauge the full impact of classification shifting, leading to more optimistically biased and less accurate forecasts.

APA, Harvard, Vancouver, ISO, and other styles

48

Sharpe, William F. "Post-Retirement Financial Strategies: Forecasts and Valuation." European Financial Management 18, no. 3 (March 13, 2012): 324–51. http://dx.doi.org/10.1111/j.1468-036x.2011.00639.x.

Full text

APA, Harvard, Vancouver, ISO, and other styles

49

Das, Somnath. "Financial analysts’ earnings forecasts for loss firms." Managerial Finance 24, no. 6 (June 1998): 39–50. http://dx.doi.org/10.1108/03074359810765570.

Full text

APA, Harvard, Vancouver, ISO, and other styles

50

Copleston, Peter V., Graham Scorthorne, and Jean Whittaker. "Preparing Financial Forecasts and Planning for Profit." Management Research News 13, no. 3/4 (March 1990): 21–32. http://dx.doi.org/10.1108/eb028070.

Full text

APA, Harvard, Vancouver, ISO, and other styles

Journal articles on the topic 'Financial forecasts'

Create a spot-on reference in APA, MLA, Chicago, Harvard, and other styles