The purpose of this paper is to focus on valuation practices applied by analysts to derive target price forecasts in Asian emerging markets. The key objective of this study is to…
Abstract
Purpose
The purpose of this paper is to focus on valuation practices applied by analysts to derive target price forecasts in Asian emerging markets. The key objective of this study is to understand valuation model preference of analysts and to compare the predictive utility of target price forecasts derived through heuristics-driven price-to-earnings (PE) model and theoretically sound discounted cash flow (DCF) model.
Design/methodology/approach
Each research report in the sample of 502 research reports has been studied in detail to understand the dominant valuation model (PE or DCF) applied by analyst to derive target price forecasts. These research reports have been issued on stocks trading in seven emerging markets including India, Malaysia, Indonesia, Taiwan, Philippines, Korea and Thailand during a six-year period starting 2008. Standard OLS and logit regression analysis has been performed to derive empirical findings.
Findings
The study finds that lower regulatory and reporting standards prevailing in emerging markets have no significant bearing on analyst choice of valuation model (PE or DCF). Time-series analysis suggests that emerging market analysts did not rely upon the usage of DCF model and preferred PE model during and immediately after the financial crisis of 2008. Multivariate regression results show weak evidence that PE model produces better results than DCF model after adjusting for the complexities associated with analyzing emerging market equities. The results imply that PE model, to some degree, is better equipped to capture market moods and sentiment in dynamic emerging markets rather than theoretically sound DCF model.
Originality/value
Most past studies on valuation model practices have focused on developed markets and this study provides a fresh perspective on analyst valuation model practices and performance in a new institutional setting of Asian emerging markets. The marginally better predictive utility of PE model as compared to DCF model is possibly a feature limited to Asian emerging markets.
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Keywords
PE and DCF are two popular valuation methodologies used by analysts to derive target price forecasts while performing equity research. Recent studies in developed markets show…
Abstract
Purpose
PE and DCF are two popular valuation methodologies used by analysts to derive target price forecasts while performing equity research. Recent studies in developed markets show that analysts using sophisticated models like DCF produce more accurate target price forecasts as compared to heuristics driven models like PE. This study investigates if analysts using DCF outperform analysts using PE in an emerging market institutional set up.
Design/methodology/approach
An in-depth analysis of 392 equity research reports is conducted to understand the dominant valuation model used by analysts to derive target price forecasts. Research reports with clear mention of valuation methodology (PE or DCF) to derive target price forecast are used for the purpose of performing this analysis. Multivariate OLS and logit regression analysis has been conducted to investigate if analysts using DCF outperform analysts using PE to derive target price forecasts.
Findings
The study finds that analysts using PE produce significantly better short-term results than analysts using DCF i.e. when target price accuracy is measured anytime during forecast horizon of 12 months. However, there is no significant difference in target price performance or target price forecast error of PE and DCF model when analyst performance is measured at the end of the forecast horizon.
Practical implications
In contrast to results from developed markets, this study does not find evidence of superior target price performance of DCF. On the contrary, results suggest that PE outperforms DCF on the short-term measure of target price accuracy. This study shows that PE model which captures market moods and sentiments effectively is more suitable in dynamic, emerging markets like India.
Originality/value
Past studies have explored the performance of PE and DCF in developed markets and this study provides fresh empirical evidence on target price accuracy of valuation model from an emerging market like India. The superior short-term target price performance of PE as compared to DCF may be relevant exclusively in emerging markets like India.
Basma Abd El-Rahiem, Ahmed Sedik, Ghada M. El Banby, Hani M. Ibrahem, Mohamed Amin, Oh-Young Song, Ashraf A. M. Khalaf and Fathi E. Abd El-Samie
The objective of this paper is to perform infrared (IR) face recognition efficiently with convolutional neural networks (CNNs). The proposed model in this paper has several…
Abstract
Purpose
The objective of this paper is to perform infrared (IR) face recognition efficiently with convolutional neural networks (CNNs). The proposed model in this paper has several advantages such as the automatic feature extraction using convolutional and pooling layers and the ability to distinguish between faces without visual details.
Design/methodology/approach
A model which comprises five convolutional layers in addition to five max-pooling layers is introduced for the recognition of IR faces.
Findings
The experimental results and analysis reveal high recognition rates of IR faces with the proposed model.
Originality/value
A designed CNN model is presented for IR face recognition. Both the feature extraction and classification tasks are incorporated into this model. The problems of low contrast and absence of details in IR images are overcome with the proposed model. The recognition accuracy reaches 100% in experiments on the Terravic Facial IR Database (TFIRDB).
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Lyndsay M.C. Hayhurst, Holly Thorpe and Megan Chawansky
Monica Nelson, Shannon Scovel and Holly Thorpe
At the 2020 Tokyo Olympics, Laurel Hubbard made history as the first openly transgender woman to compete in an individual sport. In the weeks leading up to and following her…
Abstract
At the 2020 Tokyo Olympics, Laurel Hubbard made history as the first openly transgender woman to compete in an individual sport. In the weeks leading up to and following her performance, hundreds of original news articles were written about her – few of which fully supported her participation. In this chapter, we detail our content analysis of written news media created in the weeks surrounding Hubbard's Olympic debut. Using Ahmed's (2000) theorization of the discursive creation of ‘strangers’, we relay how journalists' usage of imagery and narrative structures framed Hubbard as an ‘other’, separate from other elite athletes and undeserving of her status as an Olympian – serving to powerfully shape public perceptions of Hubbard's identity, humanity and her right to compete in the sport that she loves.
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Lyndsay M.C. Hayhurst, Holly Thorpe and Megan Chawansky
F.J. Farsana, V.R. Devi and K. Gopakumar
This paper introduces an audio encryption algorithm based on permutation of audio samples using discrete modified Henon map followed by substitution operation with keystream…
Abstract
This paper introduces an audio encryption algorithm based on permutation of audio samples using discrete modified Henon map followed by substitution operation with keystream generated from the modified Lorenz-Hyperchaotic system. In this work, the audio file is initially compressed by Fast Walsh Hadamard Transform (FWHT) for removing the residual intelligibility in the transform domain. The resulting file is then encrypted in two phases. In the first phase permutation operation is carried out using modified discrete Henon map to weaken the correlation between adjacent samples. In the second phase it utilizes modified-Lorenz hyperchaotic system for substitution operation to fill the silent periods within the speech conversation. Dynamic keystream generation mechanism is also introduced to enhance the correlation between plaintext and encrypted text. Various quality metrics analysis such as correlation, signal to noise ratio (SNR), differential attacks, spectral entropy, histogram analysis, keyspace and key sensitivity are carried out to evaluate the quality of the proposed algorithm. The simulation results and numerical analyses demonstrate that the proposed algorithm has excellent security performance and robust against various cryptographic attacks.
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Radha S., G. Josemin Bala and Nagabushanam P.
Energy is the major concern in wireless sensor networks (WSNs) for most of the applications. There exist many factors for higher energy consumption in WSNs. The purpose of this…
Abstract
Purpose
Energy is the major concern in wireless sensor networks (WSNs) for most of the applications. There exist many factors for higher energy consumption in WSNs. The purpose of this work is to increase the coverage area maintaining the minimum possible nodes or sensors.
Design/methodology/approach
This paper has proposed multilayer (ML) nodes deployment with distributed MAC (DS-MAC) in which nodes listen time is controlled based on communication of neighbors. Game theory optimization helps in addressing path loss constraints while selecting path toward base stations (BS).
Findings
The simulation is carried out using NS-2.35, and it shows better performance in ML DS-MAC compared to random topology in DS-MAC with same number of BS. The proposed method improves performance of network in terms of energy consumption, network lifetime and better throughput.
Research limitations/implications
Energy consumption is the major problem in WSNs and for which there exist many reasons, and many approaches are being proposed by researchers based on application in which WSN is used. Node mobility, topology, multitier and ML deployment and path loss constraints are some of the concerns in WSNs.
Practical implications
Game theory is used in different situations like countries whose army race, business firms that are competing, animals generally fighting for prey, political parties competing for vote, penalty kicks for the players in football and so on.
Social implications
WSNs find applications in surveillance, monitoring, inspections for wild life, sea life, underground pipes and so on.
Originality/value
Game theory optimization helps in addressing path loss constraints while selecting path toward BS.
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Keywords
The agricultural sector is a critical component of global economic development, and its significance has grown significantly in recent years. The risks associated with agriculture…
Abstract
Purpose
The agricultural sector is a critical component of global economic development, and its significance has grown significantly in recent years. The risks associated with agriculture and the behaviors of farmers in handling these risks are becoming increasingly important, given the sector’s increasing dependence worldwide. Various activities related to agriculture are vulnerable to multiple risks, which can have severe consequences for farmers’ livelihoods. The purpose of this systematic review is to present a comprehensive analysis of the sources of risk faced by farmers and their choices in adopting risk management strategies worldwide.
Design/methodology/approach
The Preferred Reporting Items for Systematic reviews and Meta-Analyses protocol was utilized to select relevant literature, and a total of 102 studies were analyzed. Through the use of Venn diagrams and graphical methods, the authors provide a transparent overview of the risks faced by farmers and the adoption of risk management strategies in developed and developing countries.
Findings
From the analysis, the authors found that, in terms of risk management strategies, diversification, reserve credit and accumulated assets are frequently used in developing countries, while developed countries tend to rely on future/forward contracts, crop insurance and hedging. Diversification is the most widely used risk management strategy across both developed and developing countries. Our study also highlights the different perceptions of weather-related risks among growers in developed and developing countries.
Practical implications
This systematic review provides valuable insights into the risks associated with agriculture and farmers' strategies in managing these risks, which could inform policy decisions and promote sustainable agricultural practices. For instance, understanding the individualistic nature of farmers' risk perception and the varying risk sources and management strategies depending on the locality and provide assistance to the farmers accordingly.
Originality/value
The paper explains how farmers behave during uncertainty in terms of risk perception and their decision to adopt risk management strategies in developed and developing countries.
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Bilal Alhayani and Abdallah Ali Abdallah
The manufacturing of intelligent and secure visual data transmission over the wireless sensor network is key requirement nowadays to many applications. The two-way transmission of…
Abstract
Purpose
The manufacturing of intelligent and secure visual data transmission over the wireless sensor network is key requirement nowadays to many applications. The two-way transmission of image under a wireless channel needed image must compatible along channel characteristics such as band width, energy-efficient, time consumption and security because the image adopts big space under the device of storage and need a long time that easily undergoes cipher attacks. Moreover, Quizzical the problem for the additional time under compression results that, the secondary process of the compression followed through the acquisition consumes more time.
Design/methodology/approach
Hence, for resolving these issues, compressive sensing (CS) has emerged, which compressed the image at the time of sensing emerges as a speedy manner that reduces the time consumption and saves bandwidth utilization but fails under secured transmission. Several kinds of research paved path to resolve the security problems under CS through providing security such as the secondary process.
Findings
Thus, concerning the above issues, this paper proposed the Corvus corone module two-way image transmission that provides energy efficiency along CS model, secured transmission through a matrix of security under CS such as inbuilt method, which was named as compressed secured matrix and faultless reconstruction along that of eminent random matrix counting under CS.
Originality/value
Experimental outputs shows intelligent module gives energy efficient, secured transmission along lower computational timing also decreased bit error rate.