Financial statement analysis and the prediction of stock returns

Ou, Jane A.; Penman, Stephen H.

doi:10.1016/0165-4101(89)90017-7

Cited by 780 publications

(493 citation statements)

References 16 publications

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“…Hence, the market share price or value eventually digresses towards the calculated intrinsic share value (Nilsson, 2003;Ou & Penman, 1989). Ou & Penman (1989) opined that the intrinsic share values calculated identifies values that the market share prices do not contain. This is why Nilsson (2003) classified this view as the fundamental analysis view of value relevance.…”

Section: Concept Of Value Relevancementioning

confidence: 99%

Value relevance of financial statements and share price: a study of listed banks in Nigeria

Uwuigbe

Jafaru

Igbinoba

et al. 2016

Banks and Bank Systems

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This paper examined the effects of value relevance of financial statements on firms share price in Nigeria. In achieving the objectives of this research, the fact book from the Nigerian Stock Exchange Market and the audited financial statement of listed banks spanning the period 2010-2014 were used. Also, a total of 15 listed banks in the Nigerian stock exchange market were selected and analyzed for the study using the purposive sampling method. However, in analyzing the research hypotheses, the study adopted the use of both descriptive statistics and the use of Fixed Effects Panel data method of data analysis technique. Findings from the study showed that a significant positive relationship existed between earnings per share (EPS) and Last day share price (LDSP). The study recommends the need for banks in the country to improve on the quality of earnings reported, since it has a stronger ability to explaining share prices of firm.

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Section: Concept Of Value Relevancementioning

confidence: 99%

Value relevance of financial statements and share price: a study of listed banks in Nigeria

Uwuigbe

Jafaru

Igbinoba

et al. 2016

Banks and Bank Systems

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“…Sletten et al find that earnings informativeness is higher in bad-news periods than in good-new periods [12]. Alam et al were able to show that disaggregated earnings data were better able to predict next period's earnings in the banking industry [13].Ou et al were the first researchers to focus on the usefulness of accounting information to predict the direction of movement of earnings relative to trend adjusted current earnings [10,14]. The study is important because it evaluates whether accounting information can consequently be used as the basis for profitable investment strategy.…”

mentioning

confidence: 99%

“…While earlier research has only been able to show relatively low informativeness of earnings later studies were able to show the incremental information content of specific components of the financial statements [4][5][6][7]. For example, Finger et al show that earnings provide information for future earnings and cash flows, and predict sign changes in the earnings per share using forecasting models developed from various income statement and balance sheet components [8][9][10]14]. Shroff et al assess the predictive ability of a "composite" model, which forecasts as a function of current earnings and current security prices, against three univariate benchmarks: a random walk model, a random walk with drift model, and a first order autoregressive/moving average (ARIMA) model [11].…”

mentioning

confidence: 99%

“…Ou et al were the first researchers to focus on the usefulness of accounting information to predict the direction of movement of earnings relative to trend adjusted current earnings [10,14]. The study is important because it evaluates whether accounting information can consequently be used as the basis for profitable investment strategy.…”

mentioning

confidence: 99%

“…XBRL allows the expression of semantic meaning commonly required in business reporting. One use of XBRL is to define and exchange financial information, such as a financial statement [10,14].The SEC has created the XBRL US GAAP Financial Reporting Taxonomy. This taxonomy is a collection of accounting data concepts and rules that enables companies to present their financial reports electronically.…”

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confidence: 99%

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The Prediction of Earnings Movements Using Accounting Data: Using XBRL

Baranes¹,

Palas²

2017

Int J Account Res

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These studies highlight the necessity to develop a tool to better predict future earnings and help develop various investment strategies.Many research papers have concentrated on the importance of earnings announcements and forecasts in the determination of investment decisions. While earlier research has only been able to show relatively low informativeness of earnings later studies were able to show the incremental information content of specific components of the financial statements [4][5][6][7]. For example, Finger et al. show that earnings provide information for future earnings and cash flows, and predict sign changes in the earnings per share using forecasting models developed from various income statement and balance sheet components [8][9][10]14]. Shroff et al. assess the predictive ability of a "composite" model, which forecasts as a function of current earnings and current security prices, against three univariate benchmarks: a random walk model, a random walk with drift model, and a first order autoregressive/moving average (ARIMA) model [11]. The findings indicate that the composite model obtains significantly lower forecast errors relative to the benchmark models. Sletten et al. find that earnings informativeness is higher in bad-news periods than in good-new periods [12]. Alam et al. were able to show that disaggregated earnings data were better able to predict next period's earnings in the banking industry [13].Ou et al. were the first researchers to focus on the usefulness of accounting information to predict the direction of movement of earnings relative to trend adjusted current earnings [10,14]. The study is important because it evaluates whether accounting information can consequently be used as the basis for profitable investment strategy. Given investors' reliance on earnings this could be a valuable tool for a profitable investment strategy. The authors found that financial statement analysis can provide a measure that is an indicator of future earnings which in turn is used as a successful investment strategy. However, the evidence from subsequent studies has been mixed [15][16][17][18][19].One objective of this study is to repeat the original Ou et al. study over a more recent time period and provide a viable tool for investment decisions. However, the main objective is to examine the methodology using, not the original COMPUSAT database, but the XBRL database. XBRL (extensible Business Reporting Language) is a freely available and global standard for exchanging business information. XBRL allows the expression of semantic meaning commonly required in business reporting. One use of XBRL is to define and exchange financial information, such as a financial statement [10,14].The SEC has created the XBRL US GAAP Financial Reporting Taxonomy. This taxonomy is a collection of accounting data concepts and rules that enables companies to present their financial reports electronically. The SEC's deployment was launched in 2008 in phases, and all public US GAAP companies were required to file the...

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The Prediction of Earnings Using Financial Statement Information: Empirical Evidence With Logit Models and Artificial Neural Networks

Charitou

Charalambous

1996

Int. J. Intell. Syst. Acc. Fin. Mgmt.

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In the past three decades, earnings have been one of the most researched variables in accounting. Empirical research provided substantial evidence on its usefulness in the capital markets but evidence in predicting earnings has been limited, yielding inconclusive results. The purpose of this study is to validate and extend prior research in predicting earnings by examining aggregate and industry‐specific data. A sample of 10,509 firm‐year observations included in the Compustat database for the period 1982–91 is used in the study. The stepwise logistic regression results of the present study indicated that nine earnings and non‐earnings variables can be used to predict earnings. These predictor variables are not identical to those reported in prior studies. These results are also extended to the manufacturing industry. Two new variables are identified to be significant in this industry. Moreover, an Artificial Neural Network (ANN) approach is employed to complement the logistic regression results. The ANN model's performance is at least as high as the logistic regression model's predictive ability.

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Financial statement analysis and the prediction of stock returns

Cited by 780 publications

References 16 publications

Value relevance of financial statements and share price: a study of listed banks in Nigeria

Value relevance of financial statements and share price: a study of listed banks in Nigeria

The Prediction of Earnings Movements Using Accounting Data: Using XBRL

The Prediction of Earnings Using Financial Statement Information: Empirical Evidence With Logit Models and Artificial Neural Networks

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