PERBANDINGAN TINGKAT KEAKURATAN MODEL LABA PERMANEN, LABA TRANSITORI DAN LABA AGREGAT DALAM MEMPREDIKSI LABA MASA DEPAN (Studi Empiris pada Perusahaan Manufaktur yang Terdaftar di Bursa Efek Jakarta)

2008 ◽  
Author(s):  
Matthew Jeffalino ◽  
Yunilma Yunilma
Keyword(s):  
Time Series ◽  
Sensitivity Analysis ◽  
Cash Flow ◽  
Financial Statements ◽  
Exponential Smoothing ◽  
Future Earnings ◽  
Aggregate Earnings ◽  
Reported Earnings ◽  
Core Activity ◽  
Naive Model

Earnings represent information which very paid attention by users of financial statements. Some research was examined the ability of earnings to forecast future earnings which only focused to aggregate earnings. Some literature mention that reported earnings number contain permanent and transitory earnings component which can be used to forecast future earnings and future cash flow. Permanent earnings is earnings related to core activity of the firms which always happened each every period. while transitory earnings are earnings do not relate with core activity of the firms and is not expected to happened in next period. This research empirically examines the level of accuracy model with permanent, transitory, and aggregate earnings component to forecast future earnings of the firms. This research also use naive model as benchmark compared with permanent, transitory, and aggregate earnings to forecast future earnings. By using 60 observations by time-series from 2000-2006. the result of research indicate that model with permanent earnings component more accurate compared model with transitory, aggregate earnings component, and naive model to forecast future earnings. This research also use exponential smoothing model as benchmark in sensitivity analysis. The result demonstrate that model with permanent earnings component more accurate compared model with transitory, aggregate earnings component, naive model, and exponential smoothing model to forecast future earnings.

scholarly journals Perbandingan Keakuratan Model Laba Permanen, Transitori Dan Agregat Dalam Memprediksi Laba Masa Depan

2017 ◽  
Vol 9 (1) ◽  
pp. 48-58
Author(s):  
Galuh Artika Febriyanti
Keyword(s):  
Cash Flow ◽  
Financial Statements ◽  
Future Earnings ◽  
Future Cash Flow ◽  
Aggregate Earnings ◽  
Reported Earnings ◽  
Core Activity

Earnings represent information which very paid attention by users of financial statements. Some research was examined the ability of earnings to forecast future earnings which only focused to aggregate earnings. Some literature mention that  reported earnings number contain permanent and transitory earnings component  which can be used to forecast future earnings and future cash flow. Permanent earnings is earnings related to core activity of the firms which always happened each every period, while transitory earnings are earnings do not relate with core activity of the firms and is not expected to happened in next period. This research empirically examines the level of accuracy model with permanent, transitory, and aggregate earnings component to forecast future earnings of the firms

scholarly journals Earnings Predictability of Quoted Firms in Nigeria

2020 ◽  
Vol 2 (1) ◽  
pp. 23-32
Author(s):  
Taiwo Azeez Olaniyi ◽  
Segun Abogun ◽  
Mudathir Olanrewaju Salam
Keyword(s):  
Secondary Data ◽  
Financial Statements ◽  
Method Of Moment ◽  
Future Earnings ◽  
Earnings Information ◽  
Dynamic Panel Regression ◽  
Earnings Predictability ◽  
Reported Earnings ◽  
Generalized Method Of Moment ◽  
The Impact

The inability of investors to predict future earnings of firms exposes them to further risk such that potential investors may be scared away while existing ones may be prompted to withdraw their investment. Thus, it becomes imperative to evaluate the earnings predictability of Nigerian quoted firms with a view to establish the ability or inability of earnings to predict itself. Also, the study examined the impact of volatility on earnings predictability of Nigerian quoted firms. The total number of seventy three (73) quoted Nigerian firms constitutes the population of this study and the entire 73 firms were studied. The causal relationship research design was adopted. The secondary data used were collected from the financial statements of the quoted firms for the period 1996 to 2015. The system generalized method of moment (GMM) was used to estimate the dynamic panel regression models of the study. The study found that earnings of firms are predictable. The study also found that volatility has adverse effect on earnings predictability. It was therefore recommended more interest/investment in Nigerian firms since earnings information is available and is predictable while managements of firms should reduce instability in reported earnings.  

Pengaruh Jumlah Dewan Komisaris, Leverage, Profitabilitas, Intensitas Modal, Cash Flow, Dan Ukuran Perusahaan Terhadap Konservatisme (Studi Empiris Pada Perusahaan Manufaktur Yang Terdaftar Di Bursa Efek Indonesia Tahun 2012-2017)

2019 ◽  
Vol 8 (1) ◽  
pp. 17-24
Author(s):  
Siti Suharni ◽  
Arini Wildaniyati ◽  
Dea Andreana
Keyword(s):  
Cash Flow ◽  
Sampling Method ◽  
Stock Exchange ◽  
Secondary Data ◽  
Capital Intensity ◽  
Financial Statements ◽  
Descriptive Statistics ◽  
Company Size ◽  
Manufacturing Companies ◽  
Financial Reports

This study is aimed at examining the effects of the Number of Board of Commissioners, Leverage, Profitability, Capital Intensity, Cash Flow, and Company Size toward Conservatism in the manufacturing companies listed on the Indonesian Stock Exchange (IDX). The population used in this study is the yearly financial statements on firm of manufacturing listed at BEI period 2012-2017, using purposive sampling method. The type of data used is secondary data obtained from yerly financial reports published and downloaded through the official BEI website. Data analyzed with Descriptive statistics, test of classic assumption and exmination of hypothesis with multiple linier regression method. The result of hypothesis research shows variable Profitability and Cash Flow have a significant effect on the ability of Conservatism, while the Number of Board of Commissioners, Leverage, Capital Intensity, and Company Size has no effect on the ability of Conservatism.

scholarly journals Sensitivity Analysis of Sentinel-1 Backscatter to Oil Palm Plantations at Pluriannual Scale: A Case Study in Gabon, Africa

2021 ◽  
Vol 13 (11) ◽  
pp. 2075
Author(s):  
J. David Ballester-Berman ◽  
Maria Rastoll-Gimenez
Keyword(s):  
Time Series ◽  
Sensitivity Analysis ◽  
Oil Palm ◽  
Time Interval ◽  
Potential Candidate ◽  
Initial Growth ◽  
Natural Forests ◽  
Wet Season ◽  
Radar Signatures ◽  
The Times

The present paper focuses on a sensitivity analysis of Sentinel-1 backscattering signatures from oil palm canopies cultivated in Gabon, Africa. We employed one Sentinel-1 image per year during the 2015–2021 period creating two separated time series for both the wet and dry seasons. The first images were almost simultaneously acquired to the initial growth stage of oil palm plants. The VH and VV backscattering signatures were analysed in terms of their corresponding statistics for each date and compared to the ones corresponding to tropical forests. The times series for the wet season showed that, in a time interval of 2–3 years after oil palm plantation, the VV/VH ratio in oil palm parcels increases above the one for forests. Backscattering and VV/VH ratio time series for the dry season exhibit similar patterns as for the wet season but with a more stable behaviour. The separability of oil palm and forest classes was also quantitatively addressed by means of the Jeffries–Matusita distance, which seems to point to the C-band VV/VH ratio as a potential candidate for discrimination between oil palms and natural forests, although further analysis must still be carried out. In addition, issues related to the effect of the number of samples in this particular scenario were also analysed. Overall, the outcomes presented here can contribute to the understanding of the radar signatures from this scenario and to potentially improve the accuracy of mapping techniques for this type of ecosystems by using remote sensing. Nevertheless, further research is still to be done as no classification method was performed due to the lack of the required geocoded reference map. In particular, a statistical assessment of the radar signatures should be carried out to statistically characterise the observed trends.

The predicted load balancing algorithm based on the dynamic exponential smoothing

Open Physics ◽  
2020 ◽  
Vol 18 (1) ◽  
pp. 439-447
Author(s):  
Lijie Yan ◽  
Xudong Liu
Keyword(s):  
Time Series ◽  
Load Balancing ◽  
Exponential Smoothing ◽  
Load Prediction ◽  
The Common ◽  
Load Balancing Algorithm ◽  
Balancing Efficiency

AbstractTo a large extent, the load balancing algorithm affects the clustering performance of the computer. This paper illustrated the common load balancing algorithms and elaborated on the advantages and drawbacks of such algorithms. In addition, this paper provides a kind of balancing algorithm generated on the basis of the load prediction. Due to the dynamic exponential smoothing model, such an algorithm helps obtain the corresponding smoothing coefficient with the server node load time series of current phrase and allows researchers to make prediction with the load value at the next moment of this node. Subsequently, the dispatcher makes the scheduling with the serve request of users according to the load predicted value. OPNET Internet simulated software is applied to the test, and we may conclude from the results that the application of such an algorithm acquires a higher load balancing efficiency and better load balancing effect.

Special Items: A Descriptive Analysis

2011 ◽  
Vol 25 (3) ◽  
pp. 511-536 ◽  
Author(s):  
Peter M. Johnson ◽  
Thomas J. Lopez ◽  
Juan Manuel Sanchez
Keyword(s):  
Firm Value ◽  
Temporal Frequency ◽  
Descriptive Analysis ◽  
Financial Statements ◽  
Comprehensive Analysis ◽  
The Other ◽  
Future Earnings ◽  
Special Items ◽  
Increasing Function ◽  
Frequency Magnitude

SYNOPSIS We provide a comprehensive analysis of special items and the characteristics of the firms that recognize them. Our analysis reveals that the temporal frequency, magnitude, and persistence of special items has increased significantly in the last 30 years, and that such increases are primarily driven by negative special items. More recently, however, our evidence is consistent with both a decline in frequency and magnitude of negative special items. On the other hand, we find that the frequency of reporting of positive special items, which remained relatively constant through 2002, has increased in more recent years. We also find strong evidence that subsequent special item reporting is an increasing function of the frequency of “prior” special item reporting. Using a random subsample of firms reporting special items, we document that 22 percent of the amounts reported in Compustat do not reconcile with the amounts reported on the firms' actual financial statements. Our comprehensive analysis should be of interest to regulators, academics, and managers interested in the implications of special items on firm-related consequences such as future earnings and firm value. Our examination can also serve as a catalyst for researchers interested in extending this important area of inquiry.

PERAMALAN TINGKAT PENGANGGURAN DI INDONESIA MENGGUNAKAN METODE TIME SERIES DENGAN MODEL ARIMA DAN HOLT-WINTERS

2021 ◽  
Vol 26 (1) ◽  
pp. 13-28
Author(s):  
Agus Sulaiman ◽  
Asep Juarna
Keyword(s):  
Time Series ◽  
Mean Square Error ◽  
Moving Average ◽  
Exponential Smoothing ◽  
Mean Square ◽  
Autoregressive Integrated Moving Average ◽  
Model Time Series

Beberapa penyebab terjadinya pengangguran di Indonesia ialah, tingkat urbanisasi, tingkat industrialisasi, proporsi angkatan kerja SLTA dan upah minimum provinsi. Faktor-faktor tersebut turut serta mempengaruhi persentase data terkait tingkat pengangguran menjadi sedikit fluktuatif. Berdasarkan pergerakan persentase data tersebut, diperlukan sebuah prediksi untuk mengetahui persentase tingkat pengangguran di masa depan dengan menggunakan konsep peramalan. Pada penelitian ini, peneliti melakukan analisis peramalan time series menggunakan metode Box-Jenkins dengan model Autoregressive Integrated Moving Average (ARIMA) dan metode Exponential Smoothing dengan model Holt-Winters. Pada penelitian ini, peramalan dilakukan dengan menggunakan dataset tingkat pengangguran dari tahun 2005 hingga 2019 per 6 bulan antara Februari hingga Agustus. Peneliti akan melihat evaluasi Range Mean Square Error (RMSE) dan Mean Square Error (MSE) terkecil dari setiap model time series. Berdasarkan hasil penelitian, ARIMA(0,1,12) menjadi model yang terbaik untuk metode Box-Jenkins sedangkan Holt-Winters dengan alpha(mean) = 0.3 dan beta(trend) = 0.4 menjadi yang terbaik pada metode Exponential Smoothing. Pemilihan model terbaik dilanjutkan dengan perbandingan nilai akurasi RMSE dan MSE. Pada model ARIMA(0,1,12) nilai RMSE = 1.01 dan MSE = 1.0201, sedangkan model Holt-Winters menghasilkan nilai RMSE = 0.45 dan MSE = 0.2025. Berdasarkan data tersebut terpilih model Holt-Winters sebagai model terbaik untuk peramalan data tingkat pengangguran di Indonesia.

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