Expected Shortfall (ES) is the average return on a risky asset conditional on the return being below some quantile of its distribution, namely its Value-at-Risk (VaR). The Basel III Accord, which ...will be implemented in the years leading up to 2019, places new attention on ES, but unlike VaR, there is little existing work on modeling ES. We use recent results from statistical decision theory to overcome the problem of “elicitability” for ES by jointly modeling ES and VaR, and propose new dynamic models for these risk measures. We provide estimation and inference methods for the proposed models, and confirm via simulation studies that the methods have good finite-sample properties. We apply these models to daily returns on four international equity indices, and find the proposed new ES–VaR models outperform forecasts based on GARCH or rolling window models.
Analytical technologies that structure and process data hold great promise for organizations but also may pose fundamental challenges for how knowledge workers accomplish tasks. Knowledge workers are ...generally considered experts who develop deep understanding of their tools, but recent observations suggest that in some situations, they may black box their analytical technologies, meaning they trust their tools without understanding how they work. I conducted a two-year inductive ethnographic study of the use of analytical technologies across four groups in an investment bank and found two distinct paths that these groups used to validate financial analyses through what I call “validating practices”: actions that confirm whether a produced analysis is trustworthy. Surprisingly, engaging in these practices does not necessarily equate to understanding the calculations performed by the technologies. In one path, validating practices are partitioned across junior and senior roles: junior bankers engage in assembling tasks and use the analytical tools to perform analysis, while only senior bankers interpret the analysis. In the other path, junior and senior members engage in co-construction: junior bankers do both assembling and interpreting tasks, and senior bankers engage in interpreting and provide feedback on junior bankers’ reasoning and choices. Both junior and senior bankers in the partitioning groups routinely black boxed the algorithms embedded in their technologies, taking them for granted without understanding them. By contrast, bankers in the co-construction groups were conscious of the algorithms and understood their potential impact. I found that black boxing influenced the knowledge outputs of these bankers and constrained the development of junior members’ expertise, with consequences for their career trajectories.
We develop a bid-ask spread estimator from daily high and low prices. Daily high (low) prices are almost always buy (sell) trades. Hence, the high-low ratio reflects both the stock's variance and its ...bid-ask spread. Although the variance component of the high-low ratio is proportional to the return interval, the spread component is not. This allows us to derive a spread estimator as a function of high-low ratios over 1-day and 2-day intervals. The estimator is easy to calculate, can be applied in a variety of research areas, and generally outperforms other low-frequency estimators.
Lahjie AM, Lepong A, Simarangkir BDAS, Kristiningrum R, Ruslim Y. 2018. Financial analysis of dipterocarp log production and rubber production in the forest and land rehabilitation program of Sekolaq ...Muliaq, West Kutai District, Indonesia. Biodiversitas 19: 757-766. The Dayak community of East Kalimantan in the last decade has begun to develop production systems that integrate forest timber tree species into plantation commodity enterprises. They have become aware that the natural forest species of their surroundings such as Meranti (Shorea sp.) and Kapur (Dryobalanops aromatica) are often easier to exploit economically, and represent potentially cheaper investments, than are introduced plantation crops such as rubber (Hevea brasiliensis). This is because the price of rubber latex has decreased over the years and has ceased to give a financial return commensurate with the investment required to develop rubber as a monocrop. The research described in this paper aimed to evaluate the viability of a dipterocarp forest/rubber plantation system cultivated by people in the West Kutai District of East Kalimantan. The viability of the system was evaluated by (i) measuring its production of dipterocarp logs and natural rubber; (ii) determining the diameter distribution of its dipterocarp trees and (iii) assessing the financial feasibility of the dipterocarp/rubber system using the theories of increment production and basal area applied to the determination of Pay Back Period, Net Present Value (NPV), Net Benefit Cost (B/C) ratio and Internal Rate of Return (IRR). The research areas on which the evaluation was performed consisted of (1) a mixed population of Shorea spp. (Meranti) and rubber (Hevea brasiliensis) and (2) a mixed population of Dryobalanops aromatica (Kapur) and rubber. The growth analysis of Shorea spp. combined with rubber as well as D. aromatica combined with rubber at the planting distance of 5m x 5m showed that the maximum cycle was reached at the age of 40 years. Whereas the rubber trees in monoculture cultivation reached their maximum cycle at the age of 17 years. The optimum increment of MAI and CAI of Shorea spp. combined with rubber reached 3.61 m3 ha-1 year-1 and 3.62 m3 ha-1 year-1 respectively. The maximum increment of MAI and CAI of Dryobalanops aromatica combined with rubber reached 3.09 m3 ha-1 year-1 and 3 m3 ha-1 year-1 respectively.
This paper aims to develop an innovative neural network approach to achieve better stock market predictions. Data were obtained from the live stock market for real-time and off-line analysis and ...results of visualizations and analytics to demonstrate Internet of Multimedia of Things for stock analysis. To study the influence of market characteristics on stock prices, traditional neural network algorithms may incorrectly predict the stock market, since the initial weight of the random selection problem can be easily prone to incorrect predictions. Based on the development of word vector in deep learning, we demonstrate the concept of “stock vector.” The input is no longer a single index or single stock index, but multi-stock high-dimensional historical data. We propose the deep long short-term memory neural network (LSTM) with embedded layer and the long short-term memory neural network with automatic encoder to predict the stock market. In these two models, we use the embedded layer and the automatic encoder, respectively, to vectorize the data, in a bid to forecast the stock via long short-term memory neural network. The experimental results show that the deep LSTM with embedded layer is better. Specifically, the accuracy of two models is 57.2 and 56.9%, respectively, for the Shanghai A-shares composite index. Furthermore, they are 52.4 and 52.5%, respectively, for individual stocks. We demonstrate research contributions in IMMT for neural network-based financial analysis.
ABSTRACT
We use a large pictorial sample of Chinese financial analysts to test the association between facial width‐to‐height ratio (fWHR) and performance in men. Financial analysts offer an ideal ...setting for our investigation because we can objectively track individual analysts’ behaviors and performance. We find that high‐fWHR analysts are more likely to conduct corporate site visits and they exhibit better performance. The positive fWHR–performance association survives a battery of robustness checks and the association is more pronounced for analysts with lower status, for firms with higher uncertainty, and for analysts facing more intense competition. Our results suggest that the dominant trait predicted by fWHR is achievement drive.
This research aims to determine the costs, receipts, business advantages, and business feasibility of food Small Medium Enterprise (SMEs). The primary method used in this study is analytical ...descriptive with survey techniques. This research involved food SMEs entrepreneurs in Sukoharjo Regency with several 50 respondents. The sampling method uses a simple random sampling method. Data is obtained by interview and observation methods. The analytical techniques used are profit analysis, R/C ratio, liquidity analysis, solvency, business rentability, and risk analysis. The results showed that the RoA value was 12.102% so that the Food SMEs in Sukoharjo Regency showed possible outcomes to be developed. SMEs' solvency value represents a figure of 0.016%, based on creditors funding the business of 0.016% of the total assets held.
The sustainable development of the global economy and society calls for the practice of the environmental, social and governance (ESG) principle. The ESG principle has been developed for 17 years ...following its formal proposal in 2004. Countries around the world continue to promote the coordinated development of the environment, society, and governance in accordance with the ESG principle. In order to review and summarize ESG research, this study takes the literature related to ESG research as the research object and presents the cooperation status, hot spots, and trends of ESG research with the help of the literature analysis tool CiteSpace. On the basis of quantitative analysis results, this study presents an examination and comprehensive summary of progress in the research into ESG combined with a systematic literature review. This includes the theoretical basis of ESG research, the interaction between the dimensions of ESG, the impact of ESG on the economic consequences, the risk prevention role of ESG, and ESG measurement. Based on the systematic summary of research progress, this paper further refines the characteristics of ESG research, reveals the shortcomings of ESG research, and propose a focus for ESG research in the future in order to provide a reference for academic research and the practice of ESG.
Abstract
The swift development and transformation of emerging technologies such as augmented reality, robotics, biometrics and 3D printing place varying degree of pressure to the electronic industry ...to play a trailblazing role in making the world a smarter place of living. The concept of smart city increases the demand for the upgrades and sophistication of electronic components. Shorter product life cycles of personal and commercial electronic products also keep the electronic companies in a never-ending loop for huge investments in materials, equipment and expertise. Electronic companies in Malaysia are still facing financial stress in their operations. Therefore, this paper aims to optimize the financial management of listed electronic companies, namely D&O, GTRONIC, UNISEM and VITROX with asset, liability, equity, earning, profit and optimum management item as the objectives using goal programming model. The benchmarks of all the goals are obtained by comparing the maximum and minimum values of the optimal values of these companies. The results of this study show that the goal programming model is able to generate the optimal solution for each company. Besides liability and earnings, all the goals have been attained by these companies upon analysis using goal programming. Possible refinement values particularly for liabilities for all the companies have been generated from this model to provide insights for these companies to benchmark for risk alleviation and strategic decision making.
•Application of the even tree method for an evaluation of the financial performance of power plants.•A method for granular assessment of the operation and maintenance costs of power plants and ...related financial consequences.•Improved estimation of the recoverable amount of power plants by assessing value-in-use.
Reliability and risk analyses in engineering have seldom been linked to financial analyses despite the significant role that risk assessment plays in the field of finance. Cash flow analyses for power plants typically do not account for contingent and successive events. Hence, the related financial assessments rarely incorporate a quantification of the adverse effects resulting from the combination of subsequent failures that could lead to extreme outcomes. The proposed approach aims to address this gap by employing the event tree method.
The novel contribution lies in introducing an event tree-based method that enables a granular evaluation of the financial performance of power plants and can serve as a foundation for the development of a variety of sensitivity and optimization analyses. The method enhances the accuracy of financial performance estimates by specifically targeting the assessment of operation and maintenance costs. The results show the importance of an improved assessment of the expenses related to equipment failures, which are approximately one-third of the revenue and add up to around 380,000 EUR for the lifespan of а photovoltaic plant with an installed capacity of 1 MW.
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