Corporate Valuation: Looking Beyond the Forecast Period Through New “Fuzzy Lenses”

Taliento, Marco

doi:10.1109/tem.2019.2904955

Cited by 5 publications

(4 citation statements)

References 75 publications

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“…The results obtained based on this method allow for a more accurate assessment and proposal of a plan for the development of the electric system of the Republic of Tajikistan. It should be noted that the effectiveness of this method today remains one of the most effective methods that is confirmed by numerous scientific publications in recent years [24][25][26][27][28][29][30][31]. It should also be noted that due to the simplicity of this method, it is often used in combination with artificial intelligence and machine learning methods [7,8,12,14].…”

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confidence: 74%

Forecasting of Electricity Consumption by Household Consumers Using Fuzzy Logic Based on the Development Plan of the Power System of the Republic of Tajikistan

et al. 2023

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Seasonal fluctuations in electricity consumption, and uneven loading of supply lines reduce not only the energy efficiency of networks, but also contribute to a decrease in the service life of elements of power supply systems. To solve the problem of forecasting power consumption, it is proposed to use the theory of fuzzy sets to assess the effective development of the energy system of the Republic of Tajikistan. According to the statistical data of power consumption for the previous period, a fuzzy logic model with membership functions is proposed, which makes it possible to evaluate consumer satisfaction using the criteria unsatisfactory, satisfactory, conditionally satisfactory, and satisfactory, as well as the efficiency of the consumption mode of compliance using the criteria high, medium, and low, allowing the evaluation of the efficiency plan for the development of the energy system of the Republic of Tajikistan. To obtain and set more accurate data on electricity consumption, calculations were made for the winter period of the year. Based on the proposed calculation model of fuzzy logic, a quantitative component of electricity consumption, the corresponding satisfaction of the consumer, and the efficiency of the regime for nine cities of the Republic of Tajikistan were proposed in the form of diagrams of seasonal electricity consumption. The obtained seasonal power consumption makes it possible to improve the accuracy of estimating power consumption, thereby equalizing the balance of consumption and generation.

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confidence: 74%

Forecasting of Electricity Consumption by Household Consumers Using Fuzzy Logic Based on the Development Plan of the Power System of the Republic of Tajikistan

et al. 2023

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“…The generalized approach used by Berliner and Buehlmann (1993) is shown in Table 1. A recent example of the same model can be found in the case of corporate valuation which explores the scenarios beyond the forecasting period (Taliento, 2019). Source: Berliner & Buehlmann (1993) In addition to the triangular and trapezoidal fuzzy logic system, another technique called the Mamdani fuzzy logic system, which expands the use of a stochastic fuzzy input variable system, was studied.…”

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confidence: 99%

Fuzzy Cash Flow Analysis of Fluctuations in Interest Rates at the State Bank of Pakistan using Present Worth Criterion

Gohar

2024

IJAHP

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A systematic approach is required to analyze present worth by incorporating annual interest rate fluctuations. This is a key factor in attracting local and foreign investors and maintaining a level of economic advancement. This study primarily focuses on the domain of the State Bank of Pakistan (SBP) and contributes towards achieving three major objectives. The first objective includes modeling interest rate values as triangular fuzzy numbers, and using the Analytic Hierarchy Process (AHP), a Multi-criteria Decision-Making technique (MCDM). Second, the triangular fuzzy interest rates are forecasted over a future timespan. Subsequently, the last objective includes the use of the Present Worth Analysis (PWA) to calculate the final net present value. The results demonstrate a trend in interest rates with net present values of specific future years. This research is a good initiative for the SBP and helpful for both foreign and local investors. The study is novel in that it involves the merging of qualitative and quantitative data. Furthermore, the combination of the forecasting technique, the AHP, fuzzy set theory, and present worth criteria renders a unique approach to formulating present worth. There is no previous research of this magnitude that has been conducted on this topic in a developing country such as Pakistan. This study delves into the annual interest rate fluctuations, providing valuable insights for present worth calculations.

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“…Likewise, Hašková [24] dealt with predicting the profitability of investments in supported renewable energy sourcesbiogas stations; the given fuzzy model provided information about the level of investment security in terms of its resistance to possible loss. This was due, among other things, to the fact that the fuzzy approach expands the range of the sensitivity analysis performed by the evaluator when valuing projects and companies and enables decision makers to have more relevant information available for processes or predictions [25]. The connection between fuzzy predictive methods and sustainability was documented by Lo et al [26].…”

Section: Related Workmentioning

confidence: 99%

A Fuzzy Multi-Criteria Evaluation System for Share Price Prediction: A Tesla Case Study

2023

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The article presents the predictive capabilities of a fuzzy multi-criteria evaluation system that operates on the basis of a non-fuzzy neural approach, but also one that is capable of implementing a learning paradigm and working with vague concepts. Within this context, the necessary elements of fuzzy logic are identified and the algebraic formulation of the fuzzy system is presented. It is with the help of the aforementioned that the task of predicting the short-term trend and price of the Tesla share is solved. The functioning of a fuzzy system and fuzzy neural network in the field of time series value prediction is discussed. The authors are inclined to the opinion that, despite the fact that a fuzzy neural network reacts in terms of applicability and effectiveness when solving prediction problems in relation to input data with a faster output than a fuzzy system, and is more “user friendly”, a sufficiently knowledgeable and experienced solver/expert could, by using a fuzzy system, achieve a higher speed of convergence in the learning process than a fuzzy neural network using the minimum range of input data carrying the necessary information. A fuzzy system could therefore be a possible alternative to a fuzzy neural network from the point of view of prediction.

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Corporate Valuation: Looking Beyond the Forecast Period Through New “Fuzzy Lenses”

Cited by 5 publications

References 75 publications

Forecasting of Electricity Consumption by Household Consumers Using Fuzzy Logic Based on the Development Plan of the Power System of the Republic of Tajikistan

Forecasting of Electricity Consumption by Household Consumers Using Fuzzy Logic Based on the Development Plan of the Power System of the Republic of Tajikistan

Fuzzy Cash Flow Analysis of Fluctuations in Interest Rates at the State Bank of Pakistan using Present Worth Criterion

A Fuzzy Multi-Criteria Evaluation System for Share Price Prediction: A Tesla Case Study

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