Search results for: automated stock investment system

Authors: Manish Jain, Dinesh Gopalani

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Growing dependency of mankind on software technology increases the need for thorough testing of the software applications and automated testing techniques that support testing activities. We have outlined our testing strategy for performing various types of automated testing of Java applications using AspectJ which has become the de-facto standard for Aspect Oriented Programming (AOP). Likewise JUnit, a unit testing framework is the most popular Java testing tool. In this paper, we have evaluated our proposed AOP approach for automated testing and JUnit on various parameters. First we have provided the similarity between the two approaches and then we have done a detailed comparison of the two testing techniques on factors like lines of testing code, learning curve, testing of private members etc. We established that our AOP testing approach using AspectJ has got several advantages and is thus particularly more effective than JUnit.

Keywords: aspect oriented programming, AspectJ, aspects, JU-nit, software testing

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Authors: Miang Hong Ngerng, Noor Diyana Jasme, May Jin Theong

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Volatile market environment is inevitable. Fund managers are struggling to choose the right strategy to survive and overcome uncertainties and adverse market movement. Therefore, finding certainty in the mist of uncertainty future is one of the key performance objectives for fund managers. Current available theoretical results are not practical due to strong reliance on the investment assumption made. This paper is to identify the component that can be forecasted in Ex-ante setting which is the realistic situation facing a fund manager in the actual execution of asset allocation in portfolio management. Partial lease square method was used to generate an index with 10 years accounting data from 191 companies listed in KLSE. The result shows that the index reflects the inner nature of the business and up to 30% of the stock return can be explained by the index.

Keywords: active portfolio management, asset allocation ex-ante investment, asset class, partial lease square

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Authors: Pieter C. M. Cornelis

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European theme parks invest approximately 10 percent of their yearly turnover into new rides and park improvements. Without these investments these parks assume not to be a very competitive and appealing daytrip for their target audiences. However, the impact of investments in attracting new visitors is not well-known and seems to differ dramatically between parks. This paper presents a case study from the Netherlands in which a small amusement park applied a suggested, not yet proven, investment method. The results of the investment are discussed in (a) the form of return on investment and (b) the success of the predictions with regard to this investment. Suggestions for future research are presented.

Keywords: entertainment industry, innovation, investments, theme parks

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Authors: Zane Turner, Kevin Labille, Susan Gauch

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Sentiment analysis is a broad and expanding field that aims to extract and classify opinions from textual data. Lexicon-based approaches are based on the use of a sentiment lexicon, i.e., a list of words each mapped to a sentiment score, to rate the sentiment of a text chunk. Our work focuses on predicting stock price change using a sentiment lexicon built from financial conference call logs. We present a method to generate a sentiment lexicon based upon an existing probabilistic approach. By using a domain-specific lexicon, we outperform traditional techniques and demonstrate that domain-specific sentiment lexicons provide higher accuracy than generic sentiment lexicons when predicting stock price change.

Keywords: computational finance, sentiment analysis, sentiment lexicon, stock movement prediction

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Authors: Zane Turner, Kevin Labille, Susan Gauch

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Sentiment analysis is a broad and expanding field that aims to extract and classify opinions from textual data. Lexicon-based approaches are based on the use of a sentiment lexicon, i.e., a list of words each mapped to a sentiment score, to rate the sentiment of a text chunk. Our work focuses on predicting stock price change using a sentiment lexicon built from financial conference call logs. We introduce a method to generate a sentiment lexicon based upon an existing probabilistic approach. By using a domain-specific lexicon, we outperform traditional techniques and demonstrate that domain-specific sentiment lexicons provide higher accuracy than generic sentiment lexicons when predicting stock price change.

Keywords: computational finance, sentiment analysis, sentiment lexicon, stock movement prediction

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Authors: Yosra Mefteh Rekik

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A computational agent-based model of financial markets stresses interactions and dynamics among a very diverse set of traders. The growing body of research in this area relies heavily on computational tools which by-pass the restrictions of an analytical method. The main goal of this research is to understand how the stock market operates and behaves how to invest in the stock market and to study traders’ behavior within the context of the artificial stock markets populated by heterogeneous agents. All agents are characterized by adaptive learning behavior represented by the Artificial Neuron Networks. By using agent-based simulations on artificial market, we show that the existence of heterogeneous agents can explain the price dynamics in the financial market. We investigate the relation between market diversity and market efficiency. Our empirical findings demonstrate that greater market heterogeneity play key roles in market efficiency.

Keywords: agent-based modeling, artificial stock market, heterogeneous expectations, financial stylized facts, computational finance

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Authors: Yih-Wenn Laih

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In recent times, the dependence and co-movement among international financial markets have become stronger than in the past, as evidenced by commentaries in the news media and the financial sections of newspapers. Studying the co-movement between returns in financial markets is an important issue for portfolio management and risk management. The realization of co-movement helps investors to identify the opportunities for international portfolio management in terms of asset allocation and pricing. Since the election of the new Prime Minister, Shinzo Abe, in November 2012, the yen has weakened against the US dollar from the 80 to the 120 level. The policies, known as “Abenomics,” are to encourage private investment through a more aggressive mix of monetary and fiscal policy. Given the close economic relations and competitions among Asia markets, it is interesting to discover the co-movement relations, affected by the depreciation of yen, between stock market of Japan and 5 major Asia stock markets, including China, Hong Kong, Korea, Singapore, and Taiwan. Specifically, we devote ourselves to measure the co-movement of stock markets between Japan and each one of the 5 Asia stock markets in terms of rank correlation coefficients. To compute the coefficients, return series of each stock market is first fitted by a skewed-t GARCH (generalized autoregressive conditional heteroscedasticity) model. Secondly, to measure the dependence structure between matched stock markets, we employ the symmetrized Joe-Clayton (SJC) copula to calculate the probability density function of paired skewed-t distributions. The joint probability density function is then utilized as the scoring scheme to optimize the sequence alignment by dynamic programming method. Finally, we compute the rank correlation coefficients (Kendall's  and Spearman's ) between matched stock markets based on their aligned sequences. We collect empirical data of 6 stock indexes from Taiwan Economic Journal. The data is sampled at a daily frequency covering the period from January 1, 2013 to July 31, 2015. The empirical distributions of returns indicate fatter tails than the normal distribution. Therefore, the skewed-t distribution and SJC copula are appropriate for characterizing the data. According to the computed Kendall’s τ, Korea has the strongest co-movement relation with Japan, followed by Taiwan, China, and Singapore; the weakest is Hong Kong. On the other hand, the Spearman’s ρ reveals that the strength of co-movement between markets with Japan in decreasing order are Korea, China, Taiwan, Singapore, and Hong Kong. We explore the effects of “Abenomics” on Asia stock markets by measuring the co-movement relation between Japan and five major Asia stock markets in terms of rank correlation coefficients. The matched markets are aligned by a hybrid method consisting of GARCH, copula and sequence alignment. Empirical experiments indicate that Korea has the strongest co-movement relation with Japan. The strength of China and Taiwan are better than Singapore. The Hong Kong market has the weakest co-movement relation with Japan.

Keywords: co-movement, depreciation of Yen, rank correlation, stock market

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Authors: Golamhassan Ghahramani Aghdam, Pedram Bavili Tabrizi

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The aim of this research is to investigate the relationship between accounting information and the value of the companies accepted in Tehran Exchange Market. The dependent variable in this research is the value of a company that is measured by price coefficients, and the independent variables are balance sheet information, profit and loss information, cash flow state information, and profit quality characteristics. The profit quality characteristic index is to be related and to be on-time. This research is an application research, and the research population includes all companies that are active in Tehran exchange market. The number of 194 companies was selected by the systematic method as the statistics sample in the period of 2018-2019. The multi-variable linear regression model was used for the hypotheses test. The results show that there is no relationship between accounting information and companies’ value (stock value) that can be due to the lack of efficiency of the investment market and the inability to use the accounting information by investment market activists.

Keywords: accounting information, company value, profit quality characteristics, price coefficient

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Authors: Rawan A. Abdelrazeq, Ahmed M. Khalafallah, Nabil A. Kartam

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Selection of competent contractors for construction projects is usually accomplished through competitive bidding or negotiated contracting in which the contract bid price is the basic criterion for selection. The evaluation of contractor’s safety performance is still not a typical criterion in the selection process, despite the existence of various safety prequalification procedures. There is a critical need for practical and automated systems that enable owners and decision makers to evaluate contractor safety performance, among other important contractor selection criteria. These systems should ultimately favor safety-conscious contractors to be selected by the virtue of their past good safety records and current safety programs. This paper presents an exploratory sequential mixed-methods approach to develop a framework for an automated decision support system that evaluates contractor safety performance based on a multitude of indicators and metrics that have been identified through a comprehensive review of construction safety research, and a survey distributed to domain experts. The framework is developed in three phases: (1) determining the indicators that depict contractor current and past safety performance; (2) soliciting input from construction safety experts regarding the identified indicators, their metrics, and relative significance; and (3) designing a decision support system using relational database models to integrate the identified indicators and metrics into a system that assesses and rates the safety performance of contractors. The proposed automated system is expected to hold several advantages including: (1) reducing the likelihood of selecting contractors with poor safety records; (2) enhancing the odds of completing the project safely; and (3) encouraging contractors to exert more efforts to improve their safety performance and practices in order to increase their bid winning opportunities which can lead to significant safety improvements in the construction industry. This should prove useful to decision makers and researchers, alike, and should help improve the safety record of the construction industry.

Keywords: construction safety, contractor selection, decision support system, relational database

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Authors: Hannes Koester

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Driven by difficult market conditions and increasing regulations, many banks are making the strategic decision to restructure their portfolio by divesting several business segments. Using a unique dataset of 727 portfolio restructuring announcements by 161 international listed banks over the period 1999 to 2015, we investigate the impact of restructuring measurements on the stock performance as well as on the banks’ profitability and risk. Employing the event study methodology, we detect positive stock market reactions on the announcement of restructuring measurements. These positive stock market reactions indicate that shareholders reward banks’ specialization activities. However, the results of the system GMM regressions show a negative relation between restructuring measurements and banks’ return on assets and a positive relation towards the individual and systemic risk of banks. These empirical results indicate that there is no guarantee that portfolio restructurings will result in a more profitable and less risky institution.

Keywords: bank performance, bank risk, divestiture, restructuring, systemic risk

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Authors: Charawee Butbumrung

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The purpose of this study is to evaluate the monetary worthiness of investment and the usefulness of risk estimation as a tool employed by a production section of an electronic factory. This study employed the case study of accidents occurring in production areas. Data is collected from interviews with six production of safety coordinators and collect the information from the relevant section. The study will present the ratio of benefits compared with the operation costs for investment. The result showed that it is worthwhile for investment with the safety measures. In addition, the organizations must be able to analyze the causes of accidents about the benefits of investing in protective working process. They also need to quickly provide the manual for the staff to learn how to protect themselves from accidents and how to use all of the safety equipment.

Keywords: cost and benefit, enterprises in Thailand, investment in safety and health, risk estimation

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Authors: Min-Ming Wen

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Applying the U.S. lodging and tourism industry as a research sample, we examine the relation between the corporate governance structure and managerial risk-taking behavior. In light of the global financial crisis, the importance of effective governance structures is essential in protecting claimholder interests. We propose a governance structure consisting of shareholder governance measured by anti-takeover provisions to examine whether the governance structure has a significant impact on managerial risk-taking behaviors in terms of the investment policy. We will use capital expenditure and R&D investment to measure managerial risk-taking and the firm’s investment policy. In addition, we will examine whether the effects of governance on investment policy differ significantly between speculative and investment-grade firms.

Keywords: corporate governance, risk-taking, firm value, lodging industry

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Authors: Gurmail Singh

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Effective supply chain is the main priority of every organization which is the outcome of strategic corporate investments with deliberate management action. Value-driven supply chain is defined through development, procurement and by configuring the appropriate resources, metrics and processes. However, responsiveness of the supply chain can be improved by proper coordination. So the Bullwhip effect (BWE) and Net stock amplification (NSAmp) values were anticipated and used for the control of inventory in organizations by both discrete wavelet transform-Artificial neural network (DWT-ANN) and Adaptive Network-based fuzzy inference system (ANFIS). This work presents a comparative methodology of forecasting for the customers demand which is non linear in nature for a multilevel supply chain structure using hybrid techniques such as Artificial intelligence techniques including Artificial neural networks (ANN) and Adaptive Network-based fuzzy inference system (ANFIS) and Discrete wavelet theory (DWT). The productiveness of these forecasting models are shown by computing the data from real world problems for Bullwhip effect and Net stock amplification. The results showed that these parameters were comparatively less in case of discrete wavelet transform-Artificial neural network (DWT-ANN) model and using Adaptive network-based fuzzy inference system (ANFIS).

Keywords: bullwhip effect, hybrid techniques, net stock amplification, supply chain flexibility

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Authors: Sofia Stoica

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In this paper, we use historical data to predict the stock price of a tech company. To this end, we use a dataset consisting of the stock prices in the past five years of ten major tech companies – Adobe, Amazon, Apple, Facebook, Google, Microsoft, Netflix, Oracle, Salesforce, and Tesla. We experimented with a variety of models– a linear regressor model, K nearest Neighbors (KNN), a sequential neural network – and algorithms - Multiplicative Weight Update, and AdaBoost. We found that the sequential neural network performed the best, with a testing error of 0.18%. Interestingly, the linear model performed the second best with a testing error of 0.73%. These results show that using historical data is enough to obtain high accuracies, and a simple algorithm like linear regression has a performance similar to more sophisticated models while taking less time and resources to implement.

Keywords: finance, machine learning, opening price, stock market

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Authors: Y. P. Wang, J. K. Chen, C. H. Lee, G. H. Huang, M. C. Wang, S. W. Chen, Y. T. Kuan, H. C. Lin, C. Y. Huang, W. H. Liang, W. C. Lin, H. C. Yu

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The hi-tech industries in the Science Park at southern Taiwan were heavily damaged by a strong earthquake early 2016. The financial loss in this event was attributed primarily to the automated stocker system handling fully processed products, and recovery of the automated stocker system from the aftermath proved to contribute major lead time. Therefore, development of effective means for protection of stockers against earthquakes has become the highest priority for risk minimization and business continuity. This study proposes to mitigate the seismic response of the stockers by introducing viscous fluid dampers in between the ceiling and the top of the stockers. The stocker is expected to vibrate less violently with a passive control force on top. Linear damper is considered in this application with an optimal damping coefficient determined from a preliminary parametric study. The damper is small in size in comparison with those adopted for building or bridge applications. Component test of the dampers has been carried out to make sure they meet the design requirement. Shake table tests have been further conducted to verify the proposed scheme under realistic earthquake conditions. Encouraging results have been achieved by effectively reducing the seismic responses of up to 60% and preventing the FOUPs from falling off the shelves that would otherwise be the case if left unprotected. Effectiveness of adopting a viscous fluid damper for seismic control of the stocker on top against the ceiling has been confirmed. This technique has been adopted by Macronix International Co., LTD for seismic retrofit of existing stockers. Demonstrative projects on the application of the proposed technique are planned underway for other companies in the display industry as well.

Keywords: hi-tech industries, seismic protection, automated stocker system, viscous fluid damper

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Authors: Miriam Sosa, Edgar Ortiz, Alejandra Cabello

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This paper examines the volatility changes and leverage effects of the MILA stock markets and their changes since the 2007 global financial crisis. This group integrates the stock markets from Chile, Colombia, Mexico and Peru. Volatility changes and leverage effects are tested with a symmetric GARCH (1,1) and asymmetric TARCH (1,1) models with a dummy variable in the variance equation. Daily closing prices of the stock indexes of Chile (IPSA), Colombia (COLCAP), Mexico (IPC) and Peru (IGBVL) are examined for the period 2003:01 to 2015:02. The evidence confirms the presence of an overall increase in asymmetric market volatility in the Peruvian share market since the 2007 crisis.

Keywords: financial crisis, Latin American Integrated Market, TARCH, GARCH

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Authors: Xiaoyun Zhao, Rami Darwish, Anna Pernestål

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Automated vehicles (AVs) have the potential to enhance road capacity, improving road safety and traffic efficiency. Research and development on AVs have been going on for many years. However, when the complicated traffic rules and real situations interacted, AVs fail to make decisions on contradicting situations, and are not able to have control in all conditions due to highly dynamic driving scenarios. This limits AVs’ usage and restricts the full potential benefits that they can bring. Furthermore, regulations, infrastructure development, and public acceptance cannot keep up at the same pace as technology breakthroughs. Facing these challenges, this paper proposes automated vehicle traffic control tower (AVTCT) acting as a safe, efficient and integrated solution for AV control. It introduces a concept of AVTCT for control, management, decision-making, communication and interaction with various aspects in transportation. With the prototype demonstrations and simulations, AVTCT has the potential to overcome the control challenges with AVs and can facilitate AV reaching their full potential. Possible functionalities, benefits as well as challenges of AVTCT are discussed, which set the foundation for the conceptual model, simulation and real application of AVTCT.

Keywords: automated vehicle, connectivity and automation, intelligent transport system, traffic control, traffic safety

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Authors: Taha Benarbia

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The advent of automated and connected vehicles has revolutionized the transportation industry, presenting new opportunities for enhancing the efficiency, safety, and sustainability of our transportation networks. This paper explores the integration of automated and connected vehicles into a smart transportation framework, leveraging the power of deep learning techniques to optimize the overall network performance. The first aspect addressed in this paper is the deployment of automated vehicles (AVs) within the transportation system. AVs offer numerous advantages, such as reduced congestion, improved fuel efficiency, and increased safety through advanced sensing and decisionmaking capabilities. The paper delves into the technical aspects of AVs, including their perception, planning, and control systems, highlighting the role of deep learning algorithms in enabling intelligent and reliable AV operations. Furthermore, the paper investigates the potential of connected vehicles (CVs) in creating a seamless communication network between vehicles, infrastructure, and traffic management systems. By harnessing real-time data exchange, CVs enable proactive traffic management, adaptive signal control, and effective route planning. Deep learning techniques play a pivotal role in extracting meaningful insights from the vast amount of data generated by CVs, empowering transportation authorities to make informed decisions for optimizing network performance. The integration of deep learning with automated and connected vehicles paves the way for advanced transportation network optimization. Deep learning algorithms can analyze complex transportation data, including traffic patterns, demand forecasting, and dynamic congestion scenarios, to optimize routing, reduce travel times, and enhance overall system efficiency. The paper presents case studies and simulations demonstrating the effectiveness of deep learning-based approaches in achieving significant improvements in network performance metrics

Keywords: automated vehicles, connected vehicles, deep learning, smart transportation network

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Authors: Ugbajah Maryjane

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The study examined the production of grass cutter and the constraints in Anambra state, Nigeria. Specifically, it described socio-economic characteristics of the respondents, determinants of net farm income and constraints to grass cutter production. Multistage and random sampling methods were used to select 50 respondents for this study. Primary data were collected by means of structured questionnaire. Non-parametric and parametric statistical tools including frequency percentage mean ranking counts, cost and returns and returns and multiple regression were deployed for data analysis. Majority 84% produce on small scale, 64 % had formal education 68% had 3-4 years of farming experience hence small scaled production were common. The income (returns) on investment was used as index of profitability, gross margin (#5,972,280), net farm income (#5,327,055.2) net return on investment (2.5) and return on investment 3.1. Net farm income was significantly influence by stock size and years of farming experience. Grass cutter farmers production problem would be ameliorated by the expression of extension education awareness campaigns to discourage unhealthy practices such as indiscriminant bush burning, use of toxic chemicals as baits, and provision of credits to the farmers.

Keywords: socio-economic factors, profitability, awareness, toxic chemicals, credits

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Authors: Michelo Obrey

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Traditionally, mutual funds have long been esteemed as stand-alone entities in the U.S. However, the prevalence of the fund families’ affiliation to financial conglomerates is eroding this striking feature. Mutual fund families' affiliation with financial conglomerates can potentially be an important source of superior performance or cost to the affiliated mutual fund investors. On the one hand, financial conglomerates affiliation offers the mutual funds access to abundant resources, better research quality, private material information, and business connections within the financial group. On the other hand, conflict of interest is bound to arise between the financial conglomerate relationship and fund management. Using a sample of U.S. domestic equity mutual funds from 1994 to 2017, this paper examines whether fund family affiliation to an investment bank help the affiliated mutual funds deliver superior performance through private material information advantage possessed by the investment banks or it costs affiliated mutual fund shareholders due to the conflict of interest. Robust to alternative risk adjustments and cross-section regression methodologies, this paper finds that the investment bank-affiliated mutual funds significantly outperform those of the mutual funds that are not affiliated with an investment bank. Interestingly the paper finds that the outperformance is confined to holding return, a return measure that captures the investment talent that is uninfluenced by transaction costs, fees, and other expenses. Further analysis shows that the investment bank-affiliated mutual funds specialize in hard-to-value stocks, which are not more likely to be held by unaffiliated funds. Consistent with the information advantage hypothesis, the paper finds that affiliated funds holding covered stocks outperform affiliated funds without covered stocks lending no support to the hypothesis that affiliated mutual funds attract superior stock-picking talent. Overall, the paper findings are consistent with the idea that investment banks maximize fee income by monopolistically exploiting their private information, thus strategically transferring performance to their affiliated mutual funds. This paper contributes to the extant literature on the agency problem in mutual fund families. It adds to this stream of research by showing that the agency problem is not only prevalent in fund families but also in financial organizations such as investment banks that have affiliated mutual fund families. The results show evidence of exploitation of synergies such as private material information sharing that benefit mutual fund investors due to affiliation with a financial conglomerate. However, this research has a normative dimension, allowing such incestuous behavior of insider trading and exploitation of superior information not only negatively affect the unaffiliated fund investors but also led to an unfair and unleveled playing field in the financial market.

Keywords: mutual fund performance, conflicts of interest, informational advantage, investment bank

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Authors: M. H. Shwehdi, S. Raja Mohammad

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Recently energy savings have become more pronounced as a result of the world financial crises as well the unstable oil prices. Certainly all entities needs to adapt Energy Conservation and Management Strategies due to high monthly consumption of their spread locations and advancements of its telecom systems. These system improvements necessitate the establishment of more exchange centers as well provide energy savings. This paper investigates the impact of HVAC System Characteristics, Operational Strategies, the impact of Envelope Thermal Characteristics, and energy conservation measures. These are classified under three types of measures i.e. Zero-Investment; Low-Investment and High-Investment Energy Conservation Measures. The study shows that the Energy Conservation Measures (ECMs) pertaining to the HVAC system characteristics and operation represent the highest potential for energy reduction, attention should be given to window thermal and solar radiation characteristics when large window areas are used. The type of glazing system needs to be carefully considered in the early design phase of future buildings. Paper will present the thermal optimization of different size centers in the two hot-dry and hot-humid Saudi Arabian city of Al Khobar, East province.

Keywords: energy conservation, optimization, thermal design, intermittent operation, exchange centers, hot-humid climate, Saudi Arabia

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Authors: Mo-Se Lee, Cheol-Hwi Ahn, Kee-Young Kwahk, Hyunchul Ahn

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Over the past decade, deep learning has been in spotlight among various machine learning algorithms. In particular, CNN (Convolutional Neural Network), which is known as effective solution for recognizing and classifying images, has been popularly applied to classification and prediction problems in various fields. In this study, we try to apply CNN to stock market prediction, one of the most challenging tasks in the machine learning research. In specific, we propose to apply CNN as the binary classifier that predicts stock market direction (up or down) by using a graph as its input. That is, our proposal is to build a machine learning algorithm that mimics a person who looks at the graph and predicts whether the trend will go up or down. Our proposed model consists of four steps. In the first step, it divides the dataset into 5 days, 10 days, 15 days, and 20 days. And then, it creates graphs for each interval in step 2. In the next step, CNN classifiers are trained using the graphs generated in the previous step. In step 4, it optimizes the hyper parameters of the trained model by using the validation dataset. To validate our model, we will apply it to the prediction of KOSPI200 for 1,986 days in eight years (from 2009 to 2016). The experimental dataset will include 14 technical indicators such as CCI, Momentum, ROC and daily closing price of KOSPI200 of Korean stock market.

Keywords: convolutional neural network, deep learning, Korean stock market, stock market prediction

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Authors: Qiang Bu

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This paper compares the explanatory power of sentiment level and sentiment shock. The preliminary test results show that sentiment shock plays a more significant role in explaining stocks returns, including the raw return and abnormal return. We also find that sentiment shock beta has a higher statistical significance than sentiment beta. These finding sheds new light on the relationship between investor sentiment and stock returns.

Keywords: sentiment level, sentiment shock, explanatory power, abnormal stock return, beta

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Authors: Jacob Livingston Slosser, Naja Holten Moller, Thomas Troels Hildebrandt, Henrik Palmer Olsen

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In this paper, we propose a model for human-AI interaction in public administration that involves legal decision-making. Inspired by Alan Turing’s test for machine intelligence, we propose a way of institutionalizing a continuous working relationship between man and machine that aims at ensuring both good legal quality and higher efficiency in decision-making processes in public administration. We also suggest that our model enhances the legitimacy of using AI in public legal decision-making. We suggest that case loads in public administration could be divided between a manual and an automated decision track. The automated decision track will be an algorithmic recommender system trained on former cases. To avoid unwanted feedback loops and biases, part of the case load will be dealt with by both a human case worker and the automated recommender system. In those cases an experienced human case worker will have the role of an evaluator, choosing between the two decisions. This model will ensure that the algorithmic recommender system is not compromising the quality of the legal decision making in the institution. It also enhances the legitimacy of using algorithmic decision support because it provides justification for its use by being seen as superior to human decisions when the algorithmic recommendations are preferred by experienced case workers. The paper outlines in some detail the process through which such a model could be implemented. It also addresses the important issue that legal decision making is subject to legislative and judicial changes and that legal interpretation is context sensitive. Both of these issues requires continuous supervision and adjustments to algorithmic recommender systems when used for legal decision making purposes.

Keywords: administrative law, algorithmic decision-making, decision support, public law

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Authors: Syed Jawad Hussain Shahzad, Muhammad Zakaria, Mobeen Ur Rehman, Saniya Khaild

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This study examines the co-movement between the Pakistan, Indian, S&P 500 and Nikkei 225 stock markets using weekly data from 1998 to 2013. The time-frequency relationship between the selected stock markets is conducted by using measures of continuous wavelet power spectrum, cross-wavelet transform and cross (squared) wavelet coherency. The empirical evidence suggests strong dependence between Pakistan and Indian stock markets. The co-movement of Pakistani index with U.S and Japanese, the developed markets, varies over time and frequency where the long-run relationship is dominant. The results of cross wavelet and wavelet coherence analysis indicate moderate covariance and correlation between stock indexes and the markets are in phase (i.e. cyclical in nature) over varying durations. Pakistan stock market was lagging during the entire period in relation to Indian stock market, corresponding to the 8~32 and then 64~256 weeks scale. Similar findings are evident for S&P 500 and Nikkei 225 indexes, however, the relationship occurs during the later period of study. All three wavelet indicators suggest strong evidence of higher co-movement during 2008-09 global financial crises. The empirical analysis reveals a strong evidence that the portfolio diversification benefits vary across frequencies and time. This analysis is unique and have several practical implications for regional and international investors while assigning the optimal weightage of different assets in portfolio formulation.

Keywords: co-movement, Pakistan stock exchange, S&P 500, Nikkei 225, wavelet analysis

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Authors: Agata Ferreira

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Rapidly increasing debates and initiatives in the area of Corporate Social Responsibility (“CSR”) have reached the world of international investment law. CSR standards that focus on the operations of multinational companies are increasingly relevant in the context of international investment policy making. In the past, the connection between CSR standards and legal framework for foreign direct investment has been largely non-existent. Recently, however, there is a growing trend of a more balance approach to rights and obligations as between investors and states under investment treaties. CSR principles join other social and environmental measures slowly being included in the investment treaties to enhance their sustainable development dimension. Issues of CSR are present on negotiation tables of new mega regional investment treaties like TTIP for example. To date, only a very few bilateral investment treaties and a handful of other international treaties with investment provisions include CSR clauses. In addition, the existing provisions tend to be of a soft type, where parties merely acknowledge importance of good corporate governance and CSR for sustainable development or generally affirm their aim to encourage enterprises to observe internationally recognised guidelines and principles of CSR. The relevant provisions often leave it up to the states to encourage enterprises operating within their territories to voluntarily incorporate CSR principles. The interaction between general non-binding CSR standards, domestic laws and policies and provisions of international investment treaties have not been tested by investment tribunals yet. The role of investment treaties in raising awareness and promoting CSR is still in its infancy. The use of CSR standards in the international investment protection regime for promotion of CSR standards, and as a tool for disciplining investors into complying with such standards, pose a number of questions and is met with resistance from investors` lobbies. Integration of these two areas, CSR and international investment law, both consisting of multilayered, diverse and often overlapping instruments is by no means an easy task. Whether international investment world is ready to embrace CSR standards or shrug them off is a matter of uncertain future. The subject however has been raised, first introductions have been made and the time will show whether the relationship between legal framework of international investment and CSR will flourish or remain dormant.

Keywords: corporate social responsibility, foreign direct investment, investment treaties, sustainable development

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Authors: Mas Pertiwi I. G. AG Istri, Sri Kristinayanti Wayan, Oka Aryawan I. Gede Made

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Ability of government to meet the needs of infrastructure investment constrained by the size of the budget commitments for other sectors. Another barrier is the complexity of the process of land acquisition. Public Private Partnership can help bridge the investment gap by including the amount of funding from the private sector, shifted the responsibility of financing, construction of the asset, and the operation and post-project design and care to them. In principle, a construction project implementation always requires the investor as a party to provide resources in the form of funding which it must be contained in a successor agreement in the form of a contract. In general, construction contracts consist of contracts which passed in Indonesia and contract International. One source of funding used in the implementation of construction projects comes from funding that comes from the collaboration between the government and the private sector, for example with the system: BLT (Build Lease Transfer), BOT (Build Operate Transfer), BTO (Build Transfer Operate) and BOO (Build Operate Own). And form of payment under a construction contract can be distinguished several ways: monthly payment, payments based on progress and payment after completed projects (Turn Key). One of the tools used to analyze the feasibility of the investment is to use financial models. The financial model describes the relationship between different variables and assumptions used. From a financial model will be known how the cash flow structure of the project, which includes revenues, expenses, liabilities to creditors and the payment of taxes to the government. Net cash flow generated from the project will be used as a basis for analyzing the feasibility of investment source of project financing Public Private Partnership could come from equity or debt. The proportion of funding according to its source is a comparison of a number of investment funds originating from each source of financing for a total investment cost during the construction period by selected the contract system and several alternative financing percentage ratio determined according to sources will generate cash flow structure that is different. Of the various possibilities for the structure of the cash flow generated will be analyzed by software is to test T Paired to compared the contract system used by various alternatives comparison of financing to determine the effect of the contract system and the comparison of such financing for the feasibility of investment toll road construction project for the economic life of 20 (twenty) years. In this use case studies of toll road contruction project Bali Mandara. And in this analysis only covered two systems contracts, namely Build Operate Transfer and Turn Key. Based on the results obtained by analysis of the variable investment feasibility of the NPV, BCR and IRR between the contract system Build Operate Transfer and contract system Turn Key on the interest rate of 9%, 12% and 15%.

Keywords: contract system, financing, internal rate of return, net present value

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Authors: İlhami Karahanoglu, Oguz Ceylan

Abstract:

As its well-known definitions; systemic risk refers to whole economic system down-turn movement even collapse together in very severe cases. In fact, it points out the contagion effects of the defaults. Such a risk is can be depicted with the famous Chinese game of falling domino stones. During and after the Bear & Sterns and Lehman Brothers cases, it was well understood that there is a very strong effect of systemic risk in financial services sector. In this study, we concentrate on the existence of systemic risk in Turkish Banking Sector based upon the Halkbank Case during the end month of 2013; there was a political turmoil in Turkey in which the close relatives of the upper politicians were involved in illegal trading activities. In that operation, the CEO of Halkbank was also arrested and in investigation, Halkbank was considered as part of such illegal actions. That operation had an impact on Halkbanks stock value. The Halkbank stock value during that time interval decreased remarkably, the distributional profile of stock return changed and became more volatile as well as more skewed. In this study, the daily returns of 5 leading banks in Turkish banking sector were used to obtain 48 return distributions (for each month, 90-days-back stock value returns are used) of 5 banks for the period 12/2011-12/2013 (pre operation period) and 12/2013-12/2015 (post operation period). When those distributions are compared with timely manner, interestingly; the distribution of the 5 other leading banks in Turkey, public or private, had also distribution profiles which was different from the past 2011-2013 period just like Halkbank. Those 5 big banks, whose stock values are monitored with sub index in Istanbul stock exchange (BIST) as BN10, had more skewed distribution just following the Halkbank stock return movement during the post operation period, with lover mean value and as well higher volatility. In addition, the correlation between the stock value return distributions of the leading banks after Halkbank case, where the returns are more skewed to the left, increased (which is measured in monthly base before and after the operation). The dependence between those banks was stronger under the case where the stock values were falling compared with the normal market condition. Such distributional effect of stock returns between the leading banks in Turkey, which is valid for down sub-market (financial/banking sector) condition, can be evaluated as an evidence for the existence of contagious effect and systemic risk.

Keywords: financial risk, systemic risk, banking sector, return distribution, dependency structure

Procedia PDF Downloads 264

Authors: Ernest Nweke

Abstract:

Mongolia has made giant strides in the development of its auditing and accounting system from Soviet-style to a market-oriented system. High levels of domestic and foreign investment desired by the Mongolian government require that better and improved quality of corporate information and disclosure consistent with international standards be made available to investors. However, the Mongolian Certified Public Accountants (CPA) profession is still developing, and the quality of services provided by accounting firms in most cases do not comply with International Financial Reporting Standards (IFRS) framework approved by the government for use in financial reporting. Against this backdrop, Accounting and audit reforms, liberalization and deregulation, establishment of an efficient and effective professional monitoring and supervision regime are policy necessities. These will further enhance the Mongolian business environment, eliminate incompetence in the system, make the economy more attractive to investors and ultimately lift reporting standards and bring about improved accounting, auditing and disclosure practices among Mongolian firms. This paper examines the fundamental issues in the accounting and auditing environment in Mongolia and investigates the relationship between selected characteristics of Mongolian Stock Exchange (MSE) listed firms (profitability, leverage, firm size, firm auditor size, firm listing age, board size and proportion of independent directors) and voluntary accounting disclosures in their annual reports and accounts. The selected sample of firms for the research purpose consists of the top 20 indexes of the MSE, representing over 95% of the market capitalization. An empirical analysis of the hypothesized relationship was carried out using multiple regression in EViews analytical software. Research results lend credence to the fact that only a few of the company attributes positively impact voluntary accounting disclosures in Mongolian Stock Exchange-listed firms. The research is motivated by the absence of empirical evidence on the correlation between the quality of voluntary accounting disclosures made by listed companies in Mongolia and company characteristics and the findings thereof significantly useful to both firms and regulatory authorities. The concluding part of the paper precisely consists of useful research-based recommendations for listed firms and regulatory agencies on measures to put in place in order to enhance the quality of corporate financial reporting and disclosures in Mongolia.

Keywords: accounting, auditing, corporate disclosure, listed firms

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Authors: C. F. Popoola, K. Akinsanya, S. B. Babarinde, D. A. Farinde

Abstract:

This study investigated published financial statement as correlate of investment decision among commercial bank stakeholders in Nigeria. A correlation research design was used in the study. 180 users of published financial statement were purposively sampled from Lagos and Ibadan. Data generated were analyzed using Pearson correlation and regression. The findings of the study revealed that, balance sheet is negatively related with investment decision (r=-.483; p < .01) while income statement (r= .249; p < .001), notes on the account (r= .230; p < .001), cash flow statement (r= .202; p < .001), value added statement (r= .328; p < .001) and five-year financial summary (r= .191 ;p < .01) are positively related with investment decision. Findings also revealed that components of published financial statement significantly predicted good investment decision (R2= .983; F(5,175)=284.5; p < .05) for commercial bank stakeholders. Therefore, it was suggested that Nigeria banks and professional bodies should instigate programs that will increase the knowledge of stakeholders on published financial statement.

Keywords: commercial banks, financial statement, income statement, investment decision, stakeholders

Procedia PDF Downloads 433