quality of accounting information and stock price adjustment

In this study, we examined the relationship between the quality of accounting information with a delay of stock price adjustment based on a new approach. Due to the theoretical literature, the stock price adjustment was measured by Hou and Moskowitz (2005) model. Independent variables measured in three groups include, Earnings quality indicator variables, misrepresented financial statements indicator variables and accounting variables driving risk. Hypothesis research was tested with data over the period 1380 to 1390. The sample covers 93 listed companies Tehran Stock Exchange and 1023 firm-year observations. This research present evidence that poor accounting quality is associated with delayed price adjustment to information. So that, the poor accruals quality can lead to a 3% increase delay

The Effect of Cash Distributions to Shareholders on Operational and Free Cash Flow Predictability

This paper examines the effectiveness of cash distributions to shareholders on operational and free cash flow predictability. The Wilcoxon rank sum test has been used to compare the prediction errors and data from 123 firms listed in Tehran Stock Exchange (TSE) for the period from 2002 to 2011 has been examined. Results show that operational and free cash flow prediction errors are different among firms with least and most net cash distributions to shareholders, and also with least and most size. Also, results indicate that, after controlling firm size effect, net cash distributions to shareholders have effect on operational cash flow prediction error, however, after controlling firm size effect, net cash distributions to shareholders have no effect on free cash flow prediction error. Actually this study suggests that net cash distribution to shareholders is a sign of future condition of operational cash flow

Relationship of endometrial thickness detected by transvaginal sonography with the results of endometrial biopsy & hysteroscopic directed biopsy in post menopausal bleeding

Background: Post-menopausal hemorrhage is one of the most common complains in gynecologic clinics. More than 60% of these cases have abnormal findings in diagnostic work ups. There is contraversy about the best diagnostic method for evaluating post-menopausal hemorrhage. The aim of this study was to evaluate the results of Trans-Vaginal Ultrasonography and compare its result to ones derived from direct endometrial biopsy and Hysteroscopy findings.Methods: In a cross-sectional study, menopausal women who attended the outpatient clinic of Arash Hospital, Tehran University of medical Sciences, from April 2005 to March 2006 with the complain of hemorrhage were evaluated. In all of these patients, after getting informed consent, Trans-Vaginal Ultrasonography, Dilatation and Curettage and Hysteroscopy were performed.Results: The total number of 90 women was recruited to the study with the age range of 41-80 years. The mean age of participants was 53.84 ± 6 years and 4.3 ± 5.1 years had passed from their menopause. The mean thickness of endometrium, measured by Trans Vaginal ultrasonography was 6.25 ± 3.7 millimeter. In the biopsy derived specimens, the most finding pathological presentation was atrophy (48.9%) and the Proliferative endometrium had the second prevalence (36.7%). Atrophy (44.4%) and Proliferative endometrium (33.3%) were the most prevalent finding in Hysteroscopy. There was a significant difference in endometrial thickness between groups of different pathological findings. A significant difference in endometrial thickness was also seen between groups with different Hysteroscopic finding. By grouping the data according to endometrial thickness, it became evident that endometrial thickness can predict the outcome of endometrial biopsy and Hysteroscopic finding efficiently. We used ROC curves to find the best grouping threshold for endometrial thickness to achieve the best sensitivity and specificity.Conclusion: Measuring the endometrial thickness by Trans-Vaginal Ultrasonography is an appropriate non-invasive test for screening post-menopausal hemorrhage.&nbsp

Non-linear height-diameter models for oriental beech (Fagus orientalis Lipsky) in the Hyrcanian forests, Iran

The relationship between tree height and diameter is an important element in growth and yield models, in carbon budget and timber volume models, and in the description of stand dynamics. Six non-linear growth functions (i.e. Chapman-Richards, Schnute, Lundqvist/Korf, Weibull, Modified Logistic and Exponential) were fitted to tree height-diameter data of oriental beech in the Hyrcanian mixed hardwood forests of Iran. The predictive performance of these models was in the first place assessed by means of different model evaluation criteria such as adjusted R squared (adj R2), root mean square error (RMSE), Akaike information criterion (AIC), mean difference (MD), mean absolute difference (MAD) and mean square (MS) error criteria. Although each of the six models accounted for approximately 75% of total variation in height, a large difference in asymptotic estimates was observed. Apart from this, the predictive performance of the models was also evaluated by means of cross-validation and by splitting the data into 5-cm diameter classes. Plotting the MD in relation to these diameter at breast height (DBH) classes showed for all growth functions, except for the Modified Logistic function, similar mean prediction errors for small- and medium-sized trees. Large-sized trees, however, showed a higher mean prediction error. The Modified Logistic function showed the worst performance due to a large model bias. The Exponential and Lundqvist/Korf models were discarded due to their showing biologically illogical behavior and unreasonable estimates for the asymptotic coefficient, respectively. Considering all the above-mentioned criteria, the Chapman-Richards, Weibull, and Schnute functions provided the most satisfactory height predictions. However, we would recommend the Chapman-Richards function for further analysis because of its higher predictive performance.status: publishe

B A S E Non-linear height-diameter models for oriental beech (Fagus orientalis Lipsky) in the Hyrcanian forests, Iran

The relationship between tree height and diameter is an important element in growth and yield models, in carbon budget and timber volume models, and in the description of stand dynamics. Six non-linear growth functions (i.e. Chapman-Richards, Schnute, Lundqvist/Korf, Weibull, Modified Logistic and Exponential) were fitted to tree height-diameter data of oriental beech in the Hyrcanian mixed hardwood forests of Iran. The predictive performance of these models was in the first place assessed by means of different model evaluation criteria such as adjusted R squared (adj R 2 ), root mean square error (RMSE), Akaike information criterion (AIC), mean difference (MD), mean absolute difference (MAD) and mean square (MS) error criteria. Although each of the six models accounted for approximately 75% of total variation in height, a large difference in asymptotic estimates was observed. Apart from this, the predictive performance of the models was also evaluated by means of cross-validation and by splitting the data into 5-cm diameter classes. Plotting the MD in relation to these diameter at breast height (DBH) classes showed for all growth functions, except for the Modified Logistic function, similar mean prediction errors for small-and medium-sized trees. Large-sized trees, however, showed a higher mean prediction error. The Modified Logistic function showed the worst performance due to a large model bias. The Exponential and Lundqvist/Korf models were discarded due to their showing biologically illogical behavior and unreasonable estimates for the asymptotic coefficient, respectively. Considering all the above-mentioned criteria, the Chapman-Richards, Weibull, and Schnute functions provided the most satisfactory height predictions. However, we would recommend the Chapman-Richards function for further analysis because of its higher predictive performance. Keywords. Forest trees, Fagus orientalis, simulation models, growth, Iran. Modèles non linéaires de diamètre de hauteur pour le hêtre oriental (Fagus orientalis Lipsky) dans les forêts Hyrcaniennes en Iran. La relation entre la hauteur des arbres et le diamètre est un élément important pour les modèles de croissance, de rendement, du budget de carbone et de volume du bois, et pour la description de la dynamique des peuplements. Six fonctions de croissance non linéaires (Chapman-Richards, Schnute, Lundqvist/Korf, Weibull, fonctions logistiques et exponentielles modifiées) ont été ajustées aux données de diamètre de hauteur des arbres de hêtre oriental dans les forêts mélangées hyrcaniennes d'Iran. La performance prévue des modèles a été évaluée à l'aide du R² ajusté (adj R²), de l'erreur quadratique moyenne (RMSE), du critère d'information d'Akaike (AIC), de la différence moyenne (MD), de la différence absolue moyenne (MAD) et de l'erreur quadratique moyenne (MS). Les résultats ont montré que chacun de ces six modèles représente environ 75 % de la variation totale de hauteur, mais produit différentes estimations asymptotiques. La performance prévue a également été évaluée à l'aide des validations croisées et par séparation des données en classes de 5 cm de diamètre à hauteur de poitrine (DBH) afin de calculer le MD pour chaque classe. Les visualisations de MD pour toutes les classes DBH ont montré que les six fonctions de croissance, sauf la logistique modifiée, produisent des erreurs de prédiction moyennes similaires pour les arbres de tailles petites et moyennes. Cependant, pour les arbres de grande taille, l'erreur de prédiction moyenne est plus élevée. La fonction de logistique modifiée est la moins performante, en raison d'un large biais. Les modèles exponentiels et de Lundqvist/Korf ont été rejetés en raison, respectivement, de leur comportement biologique illogique et des estimations déraisonnables pour les coefficients asymptotiques. En envisageant tous les critères mentionnés ci-dessus, les fonctions Chapman-Richards, Weibull et Schnute fournissent les prédictions de hauteur les plus satisfaisantes, mais la fonction de Chapman-Richards pourrait être recommandée pour une analyse plus approfondie en raison de sa meilleure performance