A neural approach to the value investing tool F-Score

Gimeno, Ruth; Lobán, Lidia; Vicente, Luis

doi:10.1016/j.frl.2019.101367

Cited by 7 publications

(4 citation statements)

References 13 publications

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“…Disisi lain, seminal penelitian Piotroski (2000) yang merumuskan f-score (i.e., simple accounting-based fundamental analysis) mampu mengidentifikasi saham yang memiliki potensi value premium. Selain banyak dimanfaatkan sebagai screening saham pada perusahaan sekuritas dan platform investasi, f-score juga banyak dirujuk oleh penelitian terkini terutama dimanfaatkan sebagai fundamental value untuk mengestimasi prospek entitas bisnis maupun sebagai indikator value investing (Chaudhari & Ghorpade, 2020;Festa et al, 2021;Gimeno et al, 2020;Jun et al, 2021;Pätäri et al, 2021;Rossi et al, 2020).…”

Section: Pendahuluanunclassified

Relevansi Nilai Informasi Akuntansi Di Indonesia Berdasar Simple Accounting-Based Fundamental Analysis

Murti

Widyastuti

2023

JAA

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Decreasing the value relevance of accounting information issues cannot be separated from complexity of accounting standards and their implementation. This phenomenon is our motivation to examine whether the valuation model on the prospects of companies that prioritize the parsimony principle by using accounting information also indicates a decrease in the relevance of accounting information in Indonesia. We examined the f-score indicator which is referred to as a simple accounting-based fundamental analysis. This study observed all financial statements of issuers in Indonesia from 2006 to 2019 and their share prices in the secondary market during year t+1.We used multiple regression to estimate the value of r-square in each year of observation. This study could not find any indication of a decrease in the value relevance of accounting information during the observation period based on the r-square which is estimated by the f-score indicator. This finding can be a part of an empirical study that is not only related to value relevance, but also to the topic of accounting information readability.

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Section: Pendahuluanunclassified

Relevansi Nilai Informasi Akuntansi Di Indonesia Berdasar Simple Accounting-Based Fundamental Analysis

Murti

Widyastuti

2023

JAA

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“…Trfm uses 6 out of 9 financial indicators used by Piotroski, but with a reverse scoring regarding two of them (Nast, 2017). NF-Score is a neural model built using all 9 fundamental signals developed in F-Score (Gimeno et al, 2019). There is also a great similarity between F-Score and FS-Score -the differences between these models concerned free cash flow instead of operating cash flows and the difference between the number of own shares repurchased and shares issued instead of taking into account only the number of shares issued (Gray, 2015).…”

Section: F-score Modificationsmentioning

confidence: 99%

Building of F-Score-Like Models on the Example of the Polish Stock Market

Pilch

2023

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Theoretical background: Value investing is one of the most popular investing approaches. In their frame, there could be a high B/M investing strategy identified. F-Score, developed by Piotroski, is a scoring model applied to the sample of high B/M entities. Its purpose is to select companies with strong financial foundations and buy their shares for the investment portfolio to generate positive market-adjusted returns in the following periods. The effectiveness of this model was mostly empirically confirmed, especially regarding developed markets. Purpose of the article: The main aim of the paper was to build F-Score-like models based on the data from the Polish stock market. The main hypothesis concerned the higher effectiveness of such models than F-Score, as the specificity of a given market should result in a better fit to the data. Research methods: Building of the models based on the discriminant analysis and formation of the investment portfolios based on the indications of these models as well as F-Score. Finally, backtesting of the portfolios built to assess their effectiveness. The sample covered most of the Polish-listed companies. The period taken into account was 2012–2022. Main findings: Models built (X-Score and Y-Score) were less efficient than F-Score. Moreover, they led to generating negative rates of return (both raw and market-adjusted). On the other hand, using of F-Score for the analyzed period seems to be purposeful due to the 1.35% mean annual market-adjusted return generated. Apart from the scoring models analyzed, the research partially confirmed the advisability of using a high B/M investing strategy. Generally, the results obtained are in line with the findings of most of other authors –regarding the F-Score effectiveness. However, an approach based on Mohanram’s idea – using the differences between absolute values of a given variable and median from the sample – proved to be inadequate in the Polish stock market.

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“…For the next stage, the following indicators are included: LEVER, LIQUID and EQ_OFFER. The last part includes the operational efficiency scores: MARGIN and TURN (Gimeno et al 2019).…”

Section: Implementing Controls and Training Is Costlymentioning

confidence: 99%

A Statistical Model of Fraud Risk in Financial Statements. Case for Romania Companies

Sabău

Mare

Safta

2021

Risks

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Tax avoidance is one of the most frequent reasons for which companies tend to resort to creative accounting techniques. The purpose of the study is to identify which of the eight-variables from the Beneish influences the most or least the outcome of the final score, as a percent, by developing a statistical model. The sample was selected from the Bucharest Stock Exchange and consists of 66 companies traded on the main market, for the years 2015–2019. The results show that from the total of the eight variables, GMI (Gross Margin Index), AQI (Asset Quality Index), DEPI (Depreciation Index) and TATA (Total Accruals to Total Assets) are significantly influencing the probability to commit fraud. The developed model is validated with only 10% of the non-fraud companies being mistakenly considered as fraud based on our model and vice versa.

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A neural approach to the value investing tool F-Score

Cited by 7 publications

References 13 publications

Relevansi Nilai Informasi Akuntansi Di Indonesia Berdasar Simple Accounting-Based Fundamental Analysis

Relevansi Nilai Informasi Akuntansi Di Indonesia Berdasar Simple Accounting-Based Fundamental Analysis

Building of F-Score-Like Models on the Example of the Polish Stock Market

A Statistical Model of Fraud Risk in Financial Statements. Case for Romania Companies

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