Updated Value Research Articles

The Magnetically Induced Radial Velocity Variation of Gliese 341 and an Upper Limit to the Mass of Its Transiting Earth-sized Planet

Abstract The Transiting Exoplanet Survey Satellite (TESS) mission identified a potential 0.88R ⊕ planet with a period of 7.577 days, orbiting the nearby M1V star GJ 341 (TOI 741.01). This system has already been observed by the James Webb Space Telescope (JWST) to search for presence of an atmosphere on this planet. Here, we present an in-depth analysis of the GJ 341 system using all available public data. We provide improved parameters for the host star, an updated value of the planet radius, and support the planetary nature of the object (now GJ 341 b). We use 57 HARPS radial velocities to model the magnetic cycle and activity of the host star, and constrain the mass of GJ 341 b to upper limits of 4.0 M ⊕ (3σ) and 2.9 M ⊕ (1σ). We also rule out the presence of additional companions with M sin i > 15.1 M ⊕, and P < 1750 days, and the presence of contaminating background objects during the TESS and JWST observations. These results provide key information to aid the interpretation of the recent JWST atmospheric observations and other future observations of this planet.

Valuing the Societal Impact of Medicines and Other Health Technologies: A User Guide to Current Best Practices.

This study argues that value assessment conducted from a societal perspective should rely on the Generalized Cost-Effectiveness Analysis (GCEA) framework proposed herein. Recently developed value assessment inventories- such as the Second Panel on Cost-Effectiveness's "impact inventory" and International Society of Pharmacoeconomics Outcomes Research (ISPOR) "value flower"- aimed to more comprehensively capture the benefits and costs of new health technologies from a societal perspective. Nevertheless, application of broader value elements in practice has been limited in part because quantifying these elements can be complex, but also because there have been numerous methodological advances since these value inventories have been released (e.g. generalized and risk-adjusted cost effectiveness). To facilitate estimation of treatment value from a societal perspective, this paper provides an updated value inventory- called the GCEA value flower- and a user guide for implementing GCEAfor health economics researchers and practitioners. GCEA considers 15 broader value elements across four categories: (i)uncertainty, (ii) dynamics, (iii)beneficiary, and (iv) additional value components. The uncertainty category incorporates patient risk preferences into value assessment. The dynamics category petals account for the evolution of real-world treatment value (e.g. option value) and includes drug pricing trends (e.g. future genericization). The beneficiary category accounts for the fact health technologies can benefit others (e.g. caregivers) and also that society may care to whom health benefits accrue (e.g. equity). Finally, GCEA incorporates additional broader sources of value (e.g. community spillovers, productivity losses). This GCEA user guide aims to facilitate both the estimation of each of these value elements and the incorporation of these values into health technology assessment when conducted from a societal perspective.

Constraining planetary albedo of JWST targets in the TESS bandpass, using TESS, HST, and Spitzer eclipse depth observations

ABSTRACT Albedo is one of the important characteristics of hot Jupiter exoplanets. However, albedo constraints have been obtained for very few exoplanets. In this work, we present the Transiting Exoplanet Survey Satellite (TESS) phase curve observations of WASP-18b, WASP-19b, WASP-121b, WASP-43b, WASP-17b, and WASP-77b, all targets for atmospheric characterization and constrain their occultation depth as well as geometric albedo (A$_{\rm g}$). We use a grid of self-consistent model atmospheres to constrain the metallicity, C/O ratio, and heat re-distribution for these six targets by fitting to their HST and/or Spitzer observations and also compute the thermal contribution to total occultation depth in the TESS bandpass. We report the first value of TESS occultation depth for WASP-17b ($151_{-66}^{+83}$ ppm) and updated value for WASP-77Ab ($94_{-62}^{+53}$ ppm). We find self-consistent models constrain high values of thermal contribution to total occultation compared to Planck models. We find very low A$_{\rm g}$ values for WASP-18b (<0.089), WASP-19b (<0.022), WASP-121b ($0.0^{+0.055}_{-0.104}$), WASP-77Ab ($0.017^{+0.126}_{-0.147}$) and significantly higher value for WASP-43b ($0.109^{+0.086}_{-0.088}$), and WASP-17b ($0.401^{+0.526}_{-0.307}$). We find WASP-17b lies in the ideal spot of low gravity and low equilibrium temperature, conducive for cloud formation, leading to high A$_{\rm g}$. With the best-fitting models, we constrain low heat re-distribution for all planets, with WASP-18b having the least. We also constrain sub-solar metallicity for all planets except WASP-17b and WASP-19b. We find a highly sub-solar C/O ratio for WASP-77Ab and WASP-43b, solar for WASP-18b, and super-solar for WASP-121b. The best-fitting P–T profiles show thermal inversion for WASP-18b and WASP-121b and none for WASP-77b and WASP-43b, which is in agreement with previous works.

State-Level Childhood Lead Poisoning Prevention Policies and Practices in the United States: 2022-2023.

The purpose of this analysis is to better understand laws and practices guiding prevention activities in childhood lead poisoning prevention programs funded by the Centers for Disease Control and Prevention (CDC). In 2022, CDC surveyed 62 funded programs using the Awardee Lead Profile Assessment. Information was collected about childhood lead poisoning-related laws and guidance, surveillance and prevention strategies, and program services including at what blood lead levels (BLLs) various activities are performed. Separately, CDC reviewed state health department websites to obtain information on which states implemented CDC's updated blood lead reference value. Awardee Lead Profile Assessment results are only reported for 47 states, the District of Columbia, and Puerto Rico. Almost all programs (96%) have laws requiring reporting of BLLs, and 51% require BLLs be reported electronically to jurisdictional health departments. Most programs (80%) prioritize areas and populations that are high risk for lead poisoning prevention activities. Approximately half of the programs (51%) have a lead elimination plan or goal. Thirty-nine percent of the programs have already implemented policies, laws, or regulations to achieve lead elimination, and 74% are in the Northeast and Midwest regions of the country. As of March 2023, 71% of the programs have implemented CDC's updated blood lead reference value, and most (65%) did so via guidance for health care providers and laboratories for what BLL should initiate case management and other services for lead-exposed children. Almost all programs have mandatory BLL reporting laws, and about two-thirds of the programs updated their BLLs that trigger public health action.

Modeling electrical impedance in brain tissue with diffusion tensor imaging for functional neurosurgery applications

Objective.Decades ago, neurosurgeons used electrical impedance measurements in the brain for coarse intraoperative tissue differentiation. Over time, these techniques were largely replaced by more refined imaging and electrophysiological localization. Today, advanced methods of diffusion tensor imaging (DTI) and finite element method (FEM) modeling may permit non-invasive, high-resolution intracerebral impedance prediction. However, expectations for tissue-impedance relationships and experimentally verified parameters for impedance modeling in human brains are lacking. This study seeks to address this need.Approach.We used FEM to simulate high-resolution single- and dual-electrode impedance measurements along linear electrode trajectories through (1) canonical gray and white matter tissue models, and (2) selected anatomic structures within whole-brain patient DTI-based models. We then compared intraoperative impedance measurements taken at known locations along deep brain stimulation (DBS) surgical trajectories with model predictions to evaluate model accuracy and refine model parameters.Main results.In DTI-FEM models, single- and dual-electrode configurations performed similarly. While only dual-electrode configurations were sensitive to white matter fiber orientation, other influences on impedance, such as white matter density, enabled single-electrode impedance measurements to display significant spatial variation even within purely white matter structures. We compared 308 intraoperative single-electrode impedance measurements in five DBS patients to DTI-FEM predictions at one-to-one corresponding locations. After calibration of model coefficients to these data, predicted impedances reliably estimated intraoperative measurements in all patients (R=0.784±0.116,n=5). Through this study, we derived an updated value for the slope coefficient of the DTI conductance model published by Tuchet al,k=0.0649 S⋅smm-3 (originalk=0.844), for use specifically in humans at physiological frequencies.Significance.This is the first study to compare impedance estimates from imaging-based models of human brain tissue to experimental measurements at the same locationsin vivo. Accurate, non-invasive, imaging-based impedance prediction has numerous applications in functional neurosurgery, including tissue mapping, intraoperative electrode localization, and DBS.

On the use of dioxane as reference for determination of the hydrodynamic radius by NMR spectroscopy

Measuring the compaction of a protein or complex is key to our understanding of the interactions within and between biomolecules. Experimentally, protein compaction is often probed either by estimating the radius of gyration (Rg) obtained from small-angle x-ray scattering (SAXS) experiments or the hydrodynamic radius (Rh) obtained, for example, by pulsed field gradient NMR (PFG NMR) spectroscopy. PFG NMR experiments generally report on the translational diffusion coefficient, which in turn can be used to estimate Rh using an internal standard to account for sample viscosity and uncertainty about the gradient strength. 1,4-Dioxane is one such commonly used internal standard, and the reference value of Rh is therefore important. We have revisited the basis for the commonly used reference value for the Rh of dioxane (2.12 Å) that is used to convert measured diffusion coefficients into a hydrodynamic radius. We followed the same approach that was used to establish the current reference value by measuring SAXS and PFG NMR data for a set of seven different proteins and using these as standards. Our analysis shows that the current Rh reference value for dioxane Rh is underestimated, and we instead suggest a new value of 2.27 ± 0.04 Å. Using this updated reference value results in a ∼7% increase in Rh values for proteins whose hydrodynamic radii have been measured by PFG NMR. These results are particularly important when the absolute value of Rh is of interest such as when determining or validating ensemble descriptions of intrinsically disordered proteins.

The impact of demographic change on value set validity and obsolescence.

To investigate the contribution of demographic trends in countries' age and gender composition to value set validity and obsolescence. Time-trade off (TTO) valuation data from 3 EQ-5D-3L value sets of 20 years or older from the United Kingdom, Japan, and the United States were re-analyzed using Bayesian heteroskedastic Tobit models with sex and age group-specific scale parameters. Original value sets were obtained by weighting the original preference structures with the countries' original demographic composition at the time of the data collection. Updated value sets were created using the original preference structure weighted using the countries' most recent demographic composition. The differences between the original and updated value sets were monitored and compared based on 95% credible intervals. The gender and age composition of the investigated countries changed in all 3 countries over time. The modelled health state preferences also depended on the respondents' gender and age. However, the overall impact of this demographic change on the investigated value sets was negligeable in all 3 countries and this finding was robust to accounting for the impact of ethnicity trends in the United States. Value sets may become redundant and obsolete for various reasons, but demographic change was not identified as a contributing factor.

Evaluation of GNSS-TEC Data-Driven IRI-2016 Model for Electron Density

The ionosphere is one of the important error sources that affect the communication of radio signals. The international reference ionosphere (IRI) model is a commonly used model to describe ionospheric parameters. The driving parameter IG12 of the IRI-2016 model was optimally updated based on GNSS-TEC data from 2015 and 2019. The electron density profiles and NmF2 calculated by the IRI-2016 model (upda-IRI-2016) driven by the updated IG12 value (IG-up) were evaluated for their accuracy using ionosonde observations and COSMIC inversion data. The experiments show that both the electron density profiles and NmF2 calculated by upda-IRI-2016 driven by IG-up show significant optimization effects, compared to the IRI-2016 model driven by IG12. For electron density, the precision improvement (PI) for both MAE and RMSE at the Beijing station exceed 31.2% in January 2015 and 16.0% in January 2019. While the PI of MAE and RMSE at the Wuhan station, which is located at a lower latitude, both exceed 32.5% in January 2015, both exceed 42.1% in January 2019, which is significantly higher than that of the Beijing station. In 2015, the PI of MAE and RMSE compared with COSMIC are both higher than 20%. For NmF2, the PI is greater for low solar activity years and low latitude stations, with the Wuhan station showing a PI of more than 11.7% in January 2019 compared to January 2015. The PI compared to COSMIC was higher than 17.2% in 2015.

Prediction of nonresectability using the updated Predictive Index value model assessed by imaging and surgery in tubo-ovarian cancer: a prospective multicenter ISAAC study

BackgroundA laparoscopy-based scoring system was developed by Fagotti et al (Fagotti or Predictive Index Value (PIV)score) based on the intraoperative presence or absence of carcinomatosis on predefined sites. Later, the authors updated the PIV score calculated only in the absence of one or both absolute criteria of non-resectability (mesenteric retraction and miliary carcinomatosis of the small bowel) (updated PIV model). ObjectiveThe aim was to demonstrate the non-inferiority of ultrasound to other imaging methods (contrast enhanced computed tomography (CT) and whole-body diffusion-weighted (WB DWI)/MRI) in predicting non-resectable tumor (defined as residual disease>1 cm) using the updated PIV model in patients with tubo-ovarian cancer. The agreement between imaging and intraoperative findings as a reference was also calculated. Study designThis was a European prospective multicenter observational study. We included patients with suspected tubo-ovarian carcinoma who underwent preoperative staging and prediction of non-resectability at ultrasound, CT, WB-DWI/MRI and surgical exploration. The predictors of non-resectability were suspicious mesenteric retraction and/or miliary carcinomatosis of the small bowel or if absent, a PIV>8 (updated PIV model). The PIV score ranges from 0 to 12 according to the presence of disease in six predefined intra-abdominal sites (great omentum, liver surface, lesser omentum/stomach/spleen, parietal peritoneum, diaphragms, bowel serosa/mesentery). The reference standard was surgical outcome, in terms of residual disease>1 cm, assessed by laparoscopy and/or laparotomy. The area under the receiver operating characteristic curve (AUC) to assess the performance of the methods in predicting non-resectability was reported. Concordance between index tests at detection of disease at six predefined sites and intraoperative exploration as reference standard was also calculated using Cohen’s kappa. ResultsThe study was between 2018 and 2022 in five European gynecological oncology centers. Data from 242 patients having both mandatory index tests (ultrasound and CT) were analyzed. 145/242 (59.9%) patients had no macroscopic residual tumor after surgery (R0) (5/145 laparoscopy and 140/145 laparotomy) and 17/242 (7.0%) had residual tumor ≤1cm (R1) (laparotomy). In 80/242 patients (33.1%), the residual tumor was >1 cm (R2), 30 of them underwent laparotomy and maximum surgery was carried out and 50/80 underwent laparoscopy and cytoreduction was not feasible in all of them.After excluding 18/242 (7.4%) patients operated on but not eligible for extensive surgery, the predictive performance of three imaging methods was analyzed in 167 women. The AUCs of all methods in discriminating between resectable and non-resectable tumor was 0.80 for ultrasound, 0.76 for CT, 0.71 for WB-DWI/MRI and 0.90 for surgical exploration. Ultrasound had the highest agreement (Cohen’s kappa ranging from 0.59 to 0.79) compared to CT and WB-DWI/MRI to assess all parameters included in the updated PIV model. ConclusionsUltrasound showed non-inferiority to CT and to WB-DWI/MRI in discriminating between resectable and non-resectable tumor using the updated PIV model. Ultrasound had the best agreement between imaging and intraoperative findings in the assessment of parameters included in the updated PIV model. Ultrasound is an acceptable method to assess abdominal disease and predict non-resectability in patients with tubo-ovarian cancer in the hands of specially trained ultrasound examiners.

The battle of factors

This study delves into the battle of factors in Canadian capital markets, employing spanning tests to evaluate 17 factors from ten multifactor models for 1991–2022. While the value factor (HML) proves redundant, its monthly updated counterpart excels. The size factor (SMB) is not improved by discounting mispriced stocks but gains potency after controlling for profitability and investment. Q-based and mispricing factors subsume the momentum factor (UMD). No single asset-pricing model emerges dominant, except in three instances. A six-factor model including market, size, monthly updated value, ROE, expected growth, and PEAD factors proves effective for asset pricing in Canadian markets.

The q2 moments in inclusive semileptonic B decays

We compute the first moments of the q2 distribution in inclusive semileptonic B decays as functions of the lower cut on q2, confirming a number of results given in the literature and adding the Oαs2β0\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$ O\\left({\\alpha}_s^2{\\beta}_0\\right) $$\\end{document} BLM contributions. We then include the q2-moments recently measured by Belle and Belle II in a global fit to the moments. The new data are compatible with the other measurements and slightly decrease the uncertainty on the nonperturbative parameters and on |Vcb|. Our updated value is |Vcb| = (41.97 ± 0.48) × 10−3.

Response to Comment on the Updated ACOEM Guidance Statement-Role and Value of the Corporate Medical Director.

Response to Comment on the Updated ACOEM Guidance Statement-Role and Value of the Corporate Medical Director.

The New Stage of State Real Estate Cadastre Valuation (in the Russian Federation)

Accurate real estate market data is crucial for decision-making by governments, businesses, and individuals. Without it, costs rise and development of investment and tax policies suffers. In Russia, the state real estate cadastre valuation is the main data source, but its credibility wanes due to errors and delayed updates. This article reviews the 20-year evolution of this system through four stages. The aim of this study is to analyse the problems and shortcomings in conducting cadastre valuation and property assessment in the Russian Federation, and to propose recommendations for improving this system. In the process of research, normative documents that served as an information base for achieving the set goal were analysed, and a comparative analysis of property tax assessment systems and tax policies of various countries was conducted. Based on the conducted analysis, the author proposes recommendations to enhance tax policy and real estate cadastre valuation in Russia. The recommendations involve adjustments, updated tax value criteria, considering diverse property value factors, separating cadastre valuation from mass appraisal, and accommodating variations in tax base calculation. Implementing these recommendations can contribute to addressing issues in cadastre valuation and create a fairer, more effective taxation system for land and property.

Day Level Forecasting for COVID-19 Pandemic Spread in SAARC Countries

The COVID-19 is declared a global epidemic by the World Health Organization (WHO). Till now there is no effective medicine and vaccine is not available to treat COVID-19 and the genetic mutation capability of COVID-19 is very aggressive. Day-level knowledge of COVID-19 spread distribution is essential to measure the nature of the virus. The aim of this paper is two folds. Firstly, we compare the forecasting performance of three models namely Simple Exponential Smoothing (SES), Moving Average (MA) and Weighted Moving Average (WMA) for South Asian Association for Regional Cooperation (SAARC) countries. Secondly, the best forecasting model is used to predict the day level number of infected case for SAARC countries. In this study we consider the daily infected case from March 08, 2020 to May 18, 2020. The empirical analysis showed that the SES model give beter forcasting performance for all of the SAARC countries based on graphical comparison as well as Mean Absolute Percentage Eorror (MAPE), Mean Absolute Deviation (MAD), Mean Square Error (MSE). The one month aheah forecast result of infected case for Bangladesh, India, Pakistan, Bhutan, Nepal, Maldives and Afghanistan will be 71702, 246726, 90926, 26, 1339, 1490, 2152 and 17934 respectively. Besides these we also shows the growth rate of the infected case based on Exponential and logarithmic scale. Having access to skilful daily updated forecast value of infected case could help better informed decision on how to manage the spread of COVID-19. International Journal of Statistical Sciences, Vol. 23(2), November, 2023, pp 129-142

The unusual 3D distribution of NaCl around the asymptotic giant branch star IK Tau

Context. Sodium chloride (NaCl) is a diatomic molecule with a large dipole moment, which allows for its detection even at relatively low abundances. It has been detected towards several evolved stars, including the asymptotic giant branch (AGB) star IK Tau, around which it is distributed in several clumps that lie off-centre from the star. Aims. We aim to study the 3D distribution of NaCl around the AGB star IK Tau and determine the abundance of NaCl relative to H2 for each of the clumps. Methods. First, a new value for the maximum expansion velocity was determined. The observed ALMA channel maps were then de-projected to create a 3D model of the distribution of NaCl. This model was then used as input for the radiative transfer modelling code Magritte. We determined the NaCl abundances of each of the clumps by comparing the observations with the results of the Magritte simulations. Results. We derive an updated value for the maximum expansion velocity of IK Tau: υexp = 28.4 ± 1.7 km s−1. A spiral-like shape can be discerned in our 3D distribution model of NaCl. This spiral lies more or less in the plane of the sky, with the distribution flatter in the line-of-sight direction than in the plane of the sky. We find clump abundances of between 9 × 10−9 and 5 × 10−8 relative to H2; the relative abundance is typically lower for clumps closer to the star. Conclusions. This is the first time de-projection has been used to understand the 3D environment of molecular emission around an AGB star and to calculate the fractional abundance of NaCl in clumps surrounding the star.

Determining the ratio of the jet to the unbeamed luminosities for γ-ray blazars

ABSTRACT The spectacular observational phenomena lying in blazars can be well explained and described by the relativistic beaming effect that the emission in the jet is highly boosted along the line of sight to observers. Aiming to reveal the intrinsic emission core dominance in γ-ray loud blazars, we collect a large sample including 226 blazars with available superluminal motion data and radio core-dominance parameters at 5 GHz, and calculate a crucial parameter, R⊥, defined as the ratio of the luminosity in the jet to the unbeamed luminosity when the viewing angle comes up to 90°. R⊥ is a better parameter than the well-known core-dominance parameter, R, to reveal more intrinsic physical properties behind the prominent observational characteristics within blazars. We primarily ascertain the updated median value of R⊥ = 0.032 at 5 GHz, illustrating around 97 per cent of the total radio emission are dominated by the jets in γ-ray loud blazars. We also make further discussion on the physical difference in BL Lacertae objects and flat-spectrum radio quasars.

Graph Convolutional Network Design for Node Classification Accuracy Improvement

Graph convolutional networks (GCNs) provide an advantage in node classification tasks for graph-related data structures. In this paper, we propose a GCN model for enhancing the performance of node classification tasks. We design a GCN layer by updating the aggregation function using an updated value of the weight coefficient. The adjacency matrix of the input graph and the identity matrix are used to calculate the aggregation function. To validate the proposed model, we performed extensive experimental studies with seven publicly available datasets. The proposed GCN layer achieves comparable results with the state-of-the-art methods. With one single layer, the proposed approach can achieve superior results.

A Social Edge-Based IoT Framework Using Reputation-Based Clustering for Enhancing Competitiveness

The introduction of the IoT technology and its pervasive penetration in our daily life implies that IoT smart objects can often participate in social events, and in this case their paradigm of interaction is commonly denoted as social IoT (SIoT). To make reliable transactions into a SIoT scenario, in this article, we introduce a multi-agent SIoT architecture, which integrates a reputation system based on a clustering of the SOs. In our framework, when a SO looks for a resource and detects a reliable partner having that resource, then the two SOs can interact to make a transaction, and at the end of the transaction each of them provides a feedback about the partner to the local reputation system of the edge server, to update the SOs’ reputation scores. Moreover, each edge server sends these reputation scores to the cloud, which updates the associated reputation values of the SOs, deriving from experiences coming from all the edge domains. This architecture provides a given object, moving from an edge domain to another one, with the possibility to have an updated value of its reputation, represented by the value stored in the cloud. We have validated our approach by a campaign of simulations, whose results seem particularly promising.

Comparison of Red Blood Corpuscle Indices versus Hemoglobin High-Performance Liquid Chromatography as a Screen for Hemoglobinopathies in Pregnant Women

Introduction: Beta-thalassemia plagues India and thalassemia screening of pregnant women is crucial. Hemoglobin (Hb) high-performance liquid chromatography (HPLC) (Hb-HPLC) is the gold standard, however in distant places it is rarely an option. While data on the use of red blood cell (RBC) indices to screen pregnant women for thalassemia trait is still developing, a sensitive and specific RBC index is needed to test for beta thalassemia. In service situations, these affordable indices may be useful without HPLC. Objective: We aimed to determine the role of red blood corpuscle indices as a screening tool to differentiate between iron deficiency anemia (IDA) and hemoglobinopathies in pregnant women and to find out the most sensitive and the most specific index. Methods: With ethical approval, 500 patients were evaluated from February 2020 to August 2021. Complete blood Counts and peripheral blood smears were performed. Participants with microcytic hypochromic anemia were included. On these patients, the RBC indices (i) Shine and Lal, (ii) Mentzer’s index, (iii) red cell distribution width index, and (iv) Srivastava were calculated. Ferritin, iron, and total iron-binding capacity levels were also tested. Hb-HPLC was utilized as the gold standard. The Mann–Whitney U-test was used to compare continuous variables between groups. Sensitivity, specificity, positive predictive value, negative predictive value, and diagnostic accuracy were calculated for various metrics. A P < 0.05 was statistically significant. Results: Hb-HPLC showed 29 (5.8%) heterozygous beta thalassemia and 471 (94.2%) IDA. Based on the updated cutoff value (4.727), Srivastava Index was the best screening tool. Conclusion: RBC indices can distinguish IDA from beta thalassemia in pregnant women and are valuable screening tools in service settings.

Empirical Analysis of Unlisted Companies' Valuation Using Discounted Cash Flow Methods

Objective – This paper aims to examine the theoretical and practical aspects of the widely used discounted cash flow (DCF) valuation method. Methodology – The proposed method is probably the most widely used approach in the valuation of unlisted companies. It involves estimating the future cash flows that the company is expected to generate and discounting them to their present value using a discount rate. The study was conducted on Spanish olive oil companies between 2005 and 2020. Findings – Our results show that there are two values for valuing companies: static and dynamic values. Both values are calculated based on the sum of the updated cash value plus the remaining value. The static value provides only one value, while the dynamic value provides a range of values, resulting in a more accurate understanding of a company's value and a better comprehension of the risks associated with that value. Therefore, the company is considered a cash flow generator, and the value of the company is found by calculating the present value of these flows using an appropriate discount rate. Novelty – Despite this method being a powerful tool for evaluating companies, even in complex situations, the DCF method is subject to a significant assumption bias, and even slight changes in the underlying assumptions of the analysis can greatly alter the evaluation results. Type of Paper: Empirical JEL Classification: G12, G31, M21 Keywords: Cash flow; Unlisted companies; Valuation methods; Discounted Cash flow Reference to this paper should be made as follows: DRISSI, R. (2023). Empirical Analysis of Unlisted Companies' Valuation Using Discounted Cash Flow Methods, J. Fin. Bank. Review, 8(1), 73 – 84. https://doi.org/10.35609/jfbr.2023.8.1(4)