Search results for: abnormal stock return

Authors: Raymond Yudhi Purba, Levy Olivia Nur, Radial Anwar

Abstract:

This research presents the design and measurement of a skew planar wheel antenna that is used to visualize the first person view perspective of unmanned aerial vehicles. The antenna has been designed using CST Studio Suite 2019 to have voltage standing wave ratio (VSWR) ≤ 2, return loss ≤ -10 dB, bandwidth ≥ 100 MHz to covering outdoor access point band from 5.725 to 5.825 GHz, omnidirectional radiation pattern, and elliptical polarization. Dimensions of skew planar wheel antenna have been modified using parameter sweep technique to provide good performances. The simulation results provide VSWR 1.231, return loss -19.693 dB, bandwidth 828.8 MHz, gain 3.292 dB, and axial ratio 9.229 dB. Meanwhile, the measurement results provide VSWR 1.237, return loss -19.476 dB, bandwidth 790.5 MHz, gain 3.2034 dB, and axial ratio 4.12 dB.

Keywords: skew planar wheel, cloverleaf, first-person view, unmanned aerial vehicle, parameter sweep

Procedia PDF Downloads 182

Authors: Guillaume Craveur

Abstract:

This study shows the opportunity to use numerical tools dedicated to Fire Safety Engineering for the Rolling Stock. Indeed, some lawful requirements can now be demonstrated by using numerical tools. The first part of this study presents the use of modelling evacuation tool to satisfy the criteria of evacuation time for the rolling stock. The buildingEXODUS software is used to model and simulate the evacuation of rolling stock. Firstly, in order to demonstrate the reliability of this tool to calculate the complete evacuation time, a comparative study was achieved between a real test and simulations done with buildingEXODUS. Multiple simulations are performed to capture the stochastic variations in egress times. Then, a new study is done to calculate the complete evacuation time of a train with the same geometry but with a different interior architecture. The second part of this study shows some applications of Computational Fluid Dynamics. This work presents the approach of a multi scales validation of numerical simulations of standardized tests with Fire Dynamics Simulations software developed by the National Institute of Standards and Technology (NIST). This work highlights in first the cone calorimeter test, described in the standard ISO 5660, in order to characterize the fire reaction of materials. The aim of this process is to readjust measurement results from the cone calorimeter test in order to create a data set usable at the seat scale. In the second step, the modelisation concerns the fire seat test described in the standard EN 45545-2. The data set obtained thanks to the validation of the cone calorimeter test was set up in the fire seat test. To conclude with the third step, after controlled the data obtained for the seat from the cone calorimeter test, a larger scale simulation with a real part of train is achieved.

Keywords: fire safety engineering, numerical tools, rolling stock, multi-scales validation

Procedia PDF Downloads 273

Authors: Ousmane Sarr

Abstract:

The Senegalese coasts have high productivity of fishery resources due to the frequency of intense up-welling system that occurs along its coast, caused by the maritime trade winds making its waters nutrients rich. Fishing plays a primordial role in Senegal's socioeconomic plans and food security. However, a global diagnosis of the Senegalese maritime fishing sector has highlighted the challenges this sector encounters. Among these concerns, some significant stocks, a priority target for artisanal fishing, need further assessment. If no efforts are made in this direction, most stock will be overexploited or even in decline. It is in this context that this research was initiated. This investigation aimed to apply a multi-modal approach (LBB, Catch-only-based CMSY model and its most recent version (CMSY++); JABBA, and JABBA-Select) to assess the stock of Atlantic bonito, Sarda sarda (Bloch, 1793) in the Senegalese Exclusive Economic Zone (SEEZ). Available catch, effort, and size data from Atlantic bonito over 15 years (2004-2018) were used to calculate the nominal and standardized CPUE, size-frequency distribution, and length at retentions (50 % and 95 % selectivity) of the species. These relevant results were employed as input parameters for stock assessment models mentioned above to define the stock status of this species in this region of the Atlantic Ocean. The LBB model indicated an Atlantic bonito healthy stock status with B/BMSY values ranging from 1.3 to 1.6 and B/B0 values varying from 0.47 to 0.61 of the main scenarios performed (BON_AFG_CL, BON_GN_Length, and BON_PS_Length). The results estimated by LBB are consistent with those obtained by CMSY. The CMSY model results demonstrate that the SEEZ Atlantic bonito stock is in a sound condition in the final year of the main scenarios analyzed (BON, BON-bt, BON-GN-bt, and BON-PS-bt) with sustainable relative stock biomass (B2018/BMSY = 1.13 to 1.3) and fishing pressure levels (F2018/FMSY= 0.52 to 1.43). The B/BMSY and F/FMSY results for the JABBA model ranged between 2.01 to 2.14 and 0.47 to 0.33, respectively. In contrast, The estimated B/BMSY and F/FMSY for JABBA-Select ranged from 1.91 to 1.92 and 0.52 to 0.54. The Kobe plots results of the base case scenarios ranged from 75% to 89% probability in the green area, indicating sustainable fishing pressure and an Atlantic bonito healthy stock size capable of producing high yields close to the MSY. Based on the stock assessment results, this study highlighted scientific advice for temporary management measures. This study suggests an improvement of the selectivity parameters of longlines and purse seines and a temporary prohibition of the use of sleeping nets in the fishery for the Atlantic bonito stock in the SEEZ based on the results of the length-base models. Although these actions are temporary, they can be essential to reduce or avoid intense pressure on the Atlantic bonito stock in the SEEZ. However, it is necessary to establish harvest control rules to provide coherent and solid scientific information that leads to appropriate decision-making for rational and sustainable exploitation of Atlantic bonito in the SEEZ and the Eastern Atlantic Ocean.

Keywords: multi-model approach, stock assessment, atlantic bonito, healthy stock, sustainable, SEEZ, temporary management measures

Procedia PDF Downloads 35

Authors: S. Yessengabulov, A. Uyzbayeva

Abstract:

Residential buildings fund of Kazakhstan was built in the Soviet time about 35-60 years ago without considering energy efficiency measures. Currently, most of these buildings are in a rundown condition and fail to meet the minimum of hygienic, sanitary and comfortable living requirements. The paper aims to examine the reports of recent building energy survey activities in the country and provide a possible solution for retrofitting existing housing stock built before 1989 which could be applicable for building envelope in cold climate. Methodology also includes two-dimensional modeling of possible practical solutions and further recommendations.

Keywords: energy audit, energy efficient buildings in Kazakhstan, retrofit, two-dimensional conduction heat transfer analysis

Procedia PDF Downloads 217

Authors: Zeynep Şahin, Züleyha Yılmaz, Fikret Çankaya

Abstract:

In today's business world, in which it is difficult to survive, the economic life of products, services or knowledge is considerably reduced. Competitors produce similar products or extra-featured ones instantly. In this environment, the contribution of companies to the social and economic environment is a preferred criterion by consumers alongside products or services. Therefore, consumers need to obtain more detailed information about companies. Besides, this drastic change in the market encourages companies to become sustainable. Sustainable business means the company puts consumed products back. Corporate sustainability, corresponds to sustainability at the level of the company, and gives equal importance to company growth and profitability together with environmental and social issues. The BIST Sustainability Index started to be calculated by the Istanbul Stock Exchange (BIST) in 2014 to evaluate the sustainability performance of companies in Turkey. The main objective of this study is to present the importance of sustainability reports in Turkey. To this aim, the performances of 15 companies in the BIST Sustainability Index were compared the periods before and after entering the index. On the other hand, sustainability reporting practices should be encouraged to increase studies on this issue. In this context, to remain on the agenda of the issue is a further objective of this study. To achieve these objectives, the financial data of the companies in the period before and after entering to the BIST Sustainability Index were analyzed using t-test in Statistical Package for the Social Sciences (SPSS) package. The results of the study showed that no significant difference between the performances of the companies in terms of the net profit margin, the return on assets and equity capital in these periods could be found. Therefore, it can be said that insufficient importance is given to sustainability issues in Turkey. The reasons for this situation might be considered as a lack of awareness due to the recent introduction and calculation of the index. It is expected that the awareness of firms and investors about sustainability will increase, and that they will demonstrate the necessary importance to this issue over time.

Keywords: sustainability reporting, sustainability index, firm performance, BIST sustainability index

Procedia PDF Downloads 246

Authors: Mohammad Karimi Moridani, Mohammad Abdi Zadeh, Zahra Shahiazar Mazraeh

Abstract:

In recent years, the use of intelligent systems in biomedical engineering has increased dramatically, especially in the diagnosis of various diseases. Also, due to the relatively simple recording of the electrocardiogram signal (ECG), this signal is a good tool to show the function of the heart and diseases associated with it. The aim of this paper is to design an intelligent system for automatically detecting a normal electrocardiogram signal from abnormal one. Using this diagnostic system, it is possible to identify a person's heart condition in a very short time and with high accuracy. The data used in this article are from the Physionet database, available in 2016 for use by researchers to provide the best method for detecting normal signals from abnormalities. Data is of both genders and the data recording time varies between several seconds to several minutes. All data is also labeled normal or abnormal. Due to the low positional accuracy and ECG signal time limit and the similarity of the signal in some diseases with the normal signal, the heart rate variability (HRV) signal was used. Measuring and analyzing the heart rate variability with time to evaluate the activity of the heart and differentiating different types of heart failure from one another is of interest to the experts. In the preprocessing stage, after noise cancelation by the adaptive Kalman filter and extracting the R wave by the Pan and Tampkinz algorithm, R-R intervals were extracted and the HRV signal was generated. In the process of processing this paper, a new idea was presented that, in addition to using the statistical characteristics of the signal to create a return map and extraction of nonlinear characteristics of the HRV signal due to the nonlinear nature of the signal. Finally, the artificial neural networks widely used in the field of ECG signal processing as well as distinctive features were used to classify the normal signals from abnormal ones. To evaluate the efficiency of proposed classifiers in this paper, the area under curve ROC was used. The results of the simulation in the MATLAB environment showed that the AUC of the MLP and SVM neural network was 0.893 and 0.947, respectively. As well as, the results of the proposed algorithm in this paper indicated that the more use of nonlinear characteristics in normal signal classification of the patient showed better performance. Today, research is aimed at quantitatively analyzing the linear and non-linear or descriptive and random nature of the heart rate variability signal, because it has been shown that the amount of these properties can be used to indicate the health status of the individual's heart. The study of nonlinear behavior and dynamics of the heart's neural control system in the short and long-term provides new information on how the cardiovascular system functions, and has led to the development of research in this field. Given that the ECG signal contains important information and is one of the common tools used by physicians to diagnose heart disease, but due to the limited accuracy of time and the fact that some information about this signal is hidden from the viewpoint of physicians, the design of the intelligent system proposed in this paper can help physicians with greater speed and accuracy in the diagnosis of normal and patient individuals and can be used as a complementary system in the treatment centers.

Keywords: neart rate variability, signal processing, linear and non-linear features, classification methods, ROC Curve

Procedia PDF Downloads 221

Authors: Javad Izadi, Sahar Majioud

Abstract:

This study presents an approach of assessing the choice of performance measures of companies in the United Kingdom after the application of IFRS in 2005. The aim of this study is to investigate the effects of IFRS on the choice of performance evaluation methods for UK companies. We analyse through an econometric model the relationship of the dependent variable, the firm’s performance, which is a nominal variable with the independent ones. Independent variables are split into two main groups: the first one is the group of accounting-based measures: Earning per share, return on assets and return on equities. The second one is the group of market-based measures: market value of property plant and equipment, research and development, sales growth, market to book value, leverage, segment and size of companies. Concerning the regression used, it is a multinomial logistic regression performed on a sample of 130 UK listed companies. Our finding shows after IFRS adoption, and companies give more importance to some variables such as return on equities and sales growth to assess their performance, whereas the return on assets and market to book value ratio does not have as much importance as before IFRS in evaluating the performance of companies. Also, there are some variables that have no impact on the performance measures anymore, such as earning per share. This article finding is empirically important for business in subjects related to IFRS and companies’ performance measurement.

Keywords: performance’s Measure, nominal variable, econometric model, evaluation methods

Procedia PDF Downloads 116

Authors: Taylan Kabbani, Ekrem Duman

Abstract:

The design of adaptive systems that take advantage of financial markets while reducing the risk can bring more stagnant wealth into the global market. However, most efforts made to generate successful deals in trading financial assets rely on Supervised Learning (SL), which suffered from various limitations. Deep Reinforcement Learning (DRL) offers to solve these drawbacks of SL approaches by combining the financial assets price "prediction" step and the "allocation" step of the portfolio in one unified process to produce fully autonomous systems capable of interacting with its environment to make optimal decisions through trial and error. In this paper, a continuous action space approach is adopted to give the trading agent the ability to gradually adjust the portfolio's positions with each time step (dynamically re-allocate investments), resulting in better agent-environment interaction and faster convergence of the learning process. In addition, the approach supports the managing of a portfolio with several assets instead of a single one. This work represents a novel DRL model to generate profitable trades in the stock market, effectively overcoming the limitations of supervised learning approaches. We formulate the trading problem, or what is referred to as The Agent Environment as Partially observed Markov Decision Process (POMDP) model, considering the constraints imposed by the stock market, such as liquidity and transaction costs. More specifically, we design an environment that simulates the real-world trading process by augmenting the state representation with ten different technical indicators and sentiment analysis of news articles for each stock. We then solve the formulated POMDP problem using the Twin Delayed Deep Deterministic Policy Gradient (TD3) algorithm, which can learn policies in high-dimensional and continuous action spaces like those typically found in the stock market environment. From the point of view of stock market forecasting and the intelligent decision-making mechanism, this paper demonstrates the superiority of deep reinforcement learning in financial markets over other types of machine learning such as supervised learning and proves its credibility and advantages of strategic decision-making.

Keywords: the stock market, deep reinforcement learning, MDP, twin delayed deep deterministic policy gradient, sentiment analysis, technical indicators, autonomous agent

Procedia PDF Downloads 148

Authors: Giulia Dal Maso

Abstract:

Within the contemporary financial capitalist configuration, the interplay of Chinese statecraft and financialization has shaped a new ‘ecology of financial expertise.’ This indicates the emergence of a new financial technocratic governance; that is increasingly changing the Chinese economy, reducing the state’s administrative and fiscal functions and increasing state assets in accordance with a new shareholder logic. In this shift, the creation of the stock market by the state was conceived not only as a new redistributor of wealth but as a ‘clearing house’ for social discontent resulting from work casualization, wage repression and a lack of social welfare. Since its inception in the wake of Deng Xiaoping’s reforms, the Chinese state has used the stock market as a means of securing social legitimation by providing a prearranged space where the disaggregated and vulnerable subjects left behind by the dismantlement of the collective work units of the Maoist period (danwei) can congregate. However, fieldwork which included both participant observation as well as interviews with investors in brokerage rooms in Shanghai (where one of only two mainland Chinese stock exchanges is situated) reveals that both new formal and informal financial experts—namely the haigui (Chinese returnees with a financial degree abroad) and sanhu (individual Chinese scattered players), are equally dissatisfied with their investing activities. They express discontent with the state, which they hold responsible for the summer 2015 financial crisis and for the financial turmoil that jeopardizes China’s financial and political project. What the investors want is a state that will guarantee the continuation of the current gupiaore ‘stock fever’. This paper holds that, by embracing financialization, the state is undermining the contract at the base of its legitimacy.

Keywords: Chinese state, Deng Xiaoping, financial capitalism, individual investors

Procedia PDF Downloads 415

Authors: Byomakesh Debata, Jitendra Mahakud

Abstract:

The recent financial crisis has been characterized by massive monetary policy interventions by the Central bank, and it has amplified the importance of liquidity for the stability of the stock market. This paper empirically elucidates the actual impact of monetary policy interventions on stock market liquidity covering all National Stock Exchange (NSE) Stocks, which have been traded continuously from 2002 to 2015. The present study employs a multivariate VAR model along with VAR-granger causality test, impulse response functions, block exogeneity test, and variance decomposition to analyze the direction as well as the magnitude of the relationship between monetary policy and market liquidity. Our analysis posits a unidirectional relationship between monetary policy (call money rate, base money growth rate) and aggregate market liquidity (traded value, turnover ratio, Amihud illiquidity ratio, turnover price impact, high-low spread). The impulse response function analysis clearly depicts the influence of monetary policy on stock liquidity for every unit innovation in monetary policy variables. Our results suggest that an expansionary monetary policy increases aggregate stock market liquidity and the reverse is documented during the tightening of monetary policy. To ascertain whether our findings are consistent across all periods, we divided the period of study as pre-crisis (2002 to 2007) and post-crisis period (2007-2015) and ran the same set of models. Interestingly, all liquidity variables are highly significant in the post-crisis period. However, the pre-crisis period has witnessed a moderate predictability of monetary policy. To check the robustness of our results we ran the same set of VAR models with different monetary policy variables and found the similar results. Unlike previous studies, we found most of the liquidity variables are significant throughout the sample period. This reveals the predictability of monetary policy on aggregate market liquidity. This study contributes to the existing body of literature by documenting a strong predictability of monetary policy on stock liquidity in an emerging economy with an order driven market making system like India. Most of the previous studies have been carried out in developing economies with quote driven or hybrid market making system and their results are ambiguous across different periods. From an eclectic sense, this study may be considered as a baseline study to further find out the macroeconomic determinants of liquidity of stocks at individual as well as aggregate level.

Keywords: market liquidity, monetary policy, order driven market, VAR, vector autoregressive model

Procedia PDF Downloads 345

Authors: Zoltan Horvath, Dora Nagy

Abstract:

In this research, it was examined whether individual COVID variants cause differences in the lactate curve of cyclists. After all, the virus variants attacked different organs in our body during the infections. During our tests, we used a traditional lactate step test, the results of which were compared with the values before the infection. In the tests, it has been proven that different virus variants show unique lactate curves. In this way, based on the lactate curve, it is possible to identify which variant caused the disease. Thanks to this, it has been shorten the return time, because we can apply the best return protocol after infection to the competitors.

Keywords: COVID-Sars19, lactate, virus mutation, lactate profile

Procedia PDF Downloads 37

Authors: Vish Putcha, Chandrasekhar Putcha, Siva Hari

Abstract:

In the current digital era of free trading and pandemic-driven remote work culture, markets worldwide gained momentum for retail investors to trade from anywhere easily. The number of retail traders rose to 24% of the market from 15% at the pre-pandemic level. Most of them are young retail traders with high-risk tolerance compared to the previous generation of retail traders. This trend boosted the growth of subscription-based market predictors and market data vendors. Young traders are betting on these predictors, assuming one of them is correct. However, 90% of retail traders are on the losing end. This paper presents multiple indicators and attempts to derive behavioral patterns from the underlying stocks. The two major indicators that traders and investors follow are technical and fundamental. The famous investor, Warren Buffett, adheres to the “Value Investing” method that is based on a stock’s fundamental Analysis. In this paper, we present multiple indicators from various methods to understand the behavior patterns of stocks. For this research, we picked five stocks with a market capitalization of more than $200M, listed on the exchange for more than 20 years, and from different industry sectors. To study the behavioral pattern over time for these five stocks, a total of 8 indicators are chosen from fundamental, technical, and financial indicators, such as Price to Earning (P/E), Price to Book Value (P/B), Debt to Equity (D/E), Beta, Volatility, Relative Strength Index (RSI), Moving Averages and Dividend yields, followed by detailed mathematical Analysis. This is an interdisciplinary paper between various disciplines of Engineering, Accounting, and Finance. The research takes a new approach to identify clear indicators affecting stocks. Statistical Analysis of the data will be performed in terms of the probabilistic distribution, then follow and then determine the probability of the stock price going over a specific target value. The Chi-square test will be used to determine the validity of the assumed distribution. Preliminary results indicate that this approach is working well. When the complete results are presented in the final paper, they will be beneficial to the community.

Keywords: stock pattern, stock market analysis, stock predictions, trading, investing, fundamental analysis, technical analysis, quantitative trading, financial analysis, behavioral analysis

Procedia PDF Downloads 54

Authors: Monica Santi, Evita Puspitasari

Abstract:

International Financial Reporting Standard (IFRS) has developed the principle based accounting standard. Based on this, IASB then eliminated the conservatism concept within accounting framework. Conservatism concept represents a prudent reaction to uncertainty to try to ensure that uncertainties and risk inherent in business situations are adequately considered. The conservatism concept has two ingredients: conditional conservatism or ex-post (news depending prudence) and unconditional conservatism or ex-ante (news-independent prudence). IFRS in substance disregards the unconditional conservatism because the unconditional conservatism can cause the understatement assets or overstated liabilities, and eventually the financial statement would be irrelevance since the information does not represent the real fact. Therefore, the IASB eliminate the conservatism concept. However, it does not decrease the practice of unconditional conservatism in the financial statement reporting. Therefore, we expected the earnings quality would be affected because of this situation, even though the IFRS implementation was expected to increase the earnings quality. The objective of this study was to provide empirical findings about the unconditional conservatism and the earnings quality before and after the IFRS adoption. The earnings per accrual measure were used as the proxy for the unconditional conservatism. If the earnings per accrual were negative (positive), it meant the company was classified as the conservative (not conservative). The earnings quality was defined as the ability of the earnings in reflecting the future earnings by considering the earnings persistence and stability. We used the earnings response coefficient (ERC) as the proxy for the earnings quality. ERC measured the extant of a security’s abnormal market return in response to the unexpected component of reporting earning of the firm issuing that security. The higher ERC indicated the higher earnings quality. The manufacturing companies listed in the Indonesian Stock Exchange (IDX) were used as the sample companies, and the 2009-2010 period was used to represent the condition before the IFRS adoption, and 2011-2013 was used to represent the condition after the IFRS adoption. Data was analyzed using the Mann-Whitney test and regression analysis. We used the firm size as the control variable with the consideration the firm size would affect the earnings quality of the company. This study had proved that the unconditional conservatism had not changed, either before and after the IFRS adoption period. However, we found the different findings for the earnings quality. The earnings quality had decreased after the IFRS adoption period. This empirical results implied that the earnings quality before the IFRS adoption was higher. This study also had found that the unconditional conservatism positively influenced the earnings quality insignificantly. The findings implied that the implementation of the IFRS had not decreased the unconditional conservatism practice and has not altered the earnings quality of the manufacturing company. Further, we found that the unconditional conservatism did not affect the earnings quality. Eventhough the empirical result shows that the unconditional conservatism gave positive influence to the earnings quality, but the influence was not significant. Thus, we concluded that the implementation of the IFRS did not increase the earnings quality.

Keywords: earnings quality, earnings response coefficient, IFRS Adoption, unconditional conservatism

Procedia PDF Downloads 236

Authors: Talal Alsulaiman, Khaldoun Khashanah

Abstract:

In this paper, we provided a literature survey on the artificial stock problem (ASM). The paper began by exploring the complexity of the stock market and the needs for ASM. ASM aims to investigate the link between individual behaviors (micro level) and financial market dynamics (macro level). The variety of patterns at the macro level is a function of the AFM complexity. The financial market system is a complex system where the relationship between the micro and macro level cannot be captured analytically. Computational approaches, such as simulation, are expected to comprehend this connection. Agent-based simulation is a simulation technique commonly used to build AFMs. The paper proceeds by discussing the components of the ASM. We consider the roles of behavioral finance (BF) alongside the traditionally risk-averse assumption in the construction of agent's attributes. Also, the influence of social networks in the developing of agents’ interactions is addressed. Network topologies such as a small world, distance-based, and scale-free networks may be utilized to outline economic collaborations. In addition, the primary methods for developing agents learning and adaptive abilities have been summarized. These incorporated approach such as Genetic Algorithm, Genetic Programming, Artificial neural network and Reinforcement Learning. In addition, the most common statistical properties (the stylized facts) of stock that are used for calibration and validation of ASM are discussed. Besides, we have reviewed the major related previous studies and categorize the utilized approaches as a part of these studies. Finally, research directions and potential research questions are argued. The research directions of ASM may focus on the macro level by analyzing the market dynamic or on the micro level by investigating the wealth distributions of the agents.

Keywords: artificial stock markets, market dynamics, bounded rationality, agent based simulation, learning, interaction, social networks

Procedia PDF Downloads 323

Authors: Rodrigo Arnaldo Scarpel

Abstract:

Trend following is a widely accepted investment strategy that adopts a rule-based trading mechanism that rather than striving to predict market direction or on information gathering to decide when to buy and when to sell a stock. Thus, in trend following one must respond to market’s movements that has recently happen and what is currently happening, rather than on what will happen. Optimally, in trend following strategy, is to catch a bull market at its early stage, ride the trend, and liquidate the position at the first evidence of the subsequent bear market. For applying the trend following strategy one needs to find the trend and identify trade signals. In order to avoid false signals, i.e., identify fluctuations of short, mid and long terms and to separate noise from real changes in the trend, most academic works rely on moving averages and other technical analysis indicators, such as the moving average convergence divergence (MACD) and the relative strength index (RSI) to uncover intelligible stock trading rules following trend following strategy philosophy. Recently, some works has applied machine learning techniques for trade rules discovery. In those works, the process of rule construction is based on evolutionary learning which aims to adapt the rules to the current environment and searches for the global optimum rules in the search space. In this work, instead of focusing on the usage of machine learning techniques for creating trading rules, a time series trend classification employing a semi-supervised approach was used to early identify both the beginning and the end of upward and downward trends. Such classification model can be employed to identify trade signals and the decision-making procedure is that if an up-trend (down-trend) is identified, a buy (sell) signal is generated. Semi-supervised learning is used for model training when only part of the data is labeled and Semi-supervised classification aims to train a classifier from both the labeled and unlabeled data, such that it is better than the supervised classifier trained only on the labeled data. For illustrating the proposed approach, it was employed daily trade information, including the open, high, low and closing values and volume from January 1, 2000 to December 31, 2022, of the São Paulo Exchange Composite index (IBOVESPA). Through this time period it was visually identified consistent changes in price, upwards or downwards, for assigning labels and leaving the rest of the days (when there is not a consistent change in price) unlabeled. For training the classification model, a pseudo-label semi-supervised learning strategy was used employing different technical analysis indicators. In this learning strategy, the core is to use unlabeled data to generate a pseudo-label for supervised training. For evaluating the achieved results, it was considered the annualized return and excess return, the Sortino and the Sharpe indicators. Through the evaluated time period, the obtained results were very consistent and can be considered promising for generating the intended trading signals.

Keywords: evolutionary learning, semi-supervised classification, time series data, trading signals generation

Procedia PDF Downloads 49

Authors: Vilma Deltuvaitė

Abstract:

Comparisons of financial development across countries are central to answering many of the questions on factors leading to economic development. For this reason this study analyzes the implications of financial system’s development on country’s economic development. The aim of the article: to analyze the impact of financial system’s development on economic development. The following research methods were used: systemic, logical and comparative analysis of scientific literature, analysis of statistical data, time series model (Autoregressive Distributed Lag (ARDL) Model). The empirical results suggest about positive short and long term effect of stock market development on GDP per capita.

Keywords: banking sector, economic development, financial system’s development, stock market, private bond market

Procedia PDF Downloads 348

Authors: Dezie L. Warganegara, Dewi Tamara

Abstract:

The objectives of this study are to investigate the existence of the sticky cost behaviour of firms listed in the Indonesia Stock Exchange (IDX) and to find an evidence on the effects of sticky operating expenses (SG&A expenses) on profitability of firms. For the first objective, this study found that the sticky cost behaviour does exist. For the second objective, this study finds that the stickier the operating expenses the less future profitability of the firms. This study concludes that sticky cost affects negatively to the performance and, therefore, firms should include flexibility in designing the cost structure of their firms.

Keywords: sticky costs, Indonesia Stock Exchange (IDX), profitability, operating expenses, SG&A

Procedia PDF Downloads 283

Authors: Libena Cernohorska

Abstract:

The goal of this paper is to specify factors influencing the profitability of selected banks. Next, a model will be created to help establish variables that have a demonstrable influence on the development of the selected banks' profitability ratios. Czech banks and their international parent companies were selected for analyzing profitability. Banks categorized as large banks (according to the Czech National Bank's system, which ranks banks according to balance sheet total) were selected to represent the Czech banks. Two ratios, the return on assets ratio (ROA) and the return on equity ratio (ROE) are used to assess bank profitability. Six endogenous and four external indicators were selected from among other factors that influence bank profitability. The data analyzed were for the years 2001 – 2013. First, correlation analysis, which was supposed to eliminate correlated values, was conducted. A large number of correlated values were established on the basis of this analysis. The strongly correlated values were omitted. Despite this, the subsequent regression analysis of profitability for the individual banks that were selected did not confirm that the selected variables influenced their profitability. The studied factors' influence on bank profitability was demonstrated only for Československá Obchodní Banka and Société Générale using regression analysis. For Československá Obchodní Banka, it was demonstrated that inflation level and the amount of the central bank's interest rate influenced the return on assets ratio and that capital adequacy and market concentration influenced the return on equity ratio for Société Générale.

Keywords: banks, profitability, regression analysis, ROA, ROE

Procedia PDF Downloads 223

Authors: Autcha Araveeporn

Abstract:

This paper presents a study about a nonparametric regression model consisting of a smoothing spline method and a penalized spline regression method. We also compare the techniques used for estimation and prediction of nonparametric regression model. We tried both methods with crude oil prices in dollars per barrel and the Stock Exchange of Thailand (SET) index. According to the results, it is concluded that smoothing spline method performs better than that of penalized spline regression method.

Keywords: nonparametric regression model, penalized spline regression method, smoothing spline method, Stock Exchange of Thailand (SET)

Procedia PDF Downloads 394

Authors: H. C. Chinwenyi, H. D. Ibrahim, F. A. Ahmed

Abstract:

In modern financial mathematics, valuing derivatives such as options is often a tedious task. This is simply because their fair and correct prices in the future are often probabilistic. This paper examines three different Stochastic Differential Equation (SDE) models in finance; the Constant Elasticity of Variance (CEV) model, the Balck-Karasinski model, and the Heston model. The various Martingales option price valuation formulas for these three models were obtained using the replicating portfolio method. Also, the numerical solution of the derived Martingales options price valuation equations for the SDEs models was carried out using the Monte Carlo method which was implemented using MATLAB. Furthermore, results from the numerical examples using published data from the Nigeria Stock Exchange (NSE), all share index data show the effect of increase in the underlying asset value (stock price) on the value of the European Put Option for these models. From the results obtained, we see that an increase in the stock price yields a decrease in the value of the European put option price. Hence, this guides the option holder in making a quality decision by not exercising his right on the option.

Keywords: equivalent martingale measure, European put option, girsanov theorem, martingales, monte carlo method, option price valuation formula

Procedia PDF Downloads 106

Authors: Emma M. Iglesias

Abstract:

We have analyzed extreme movements of the main stocks traded in the Eurozone in the 2000-2012 period. Our results can help future very-risk-averse investors to choose their portfolios in the Eurozone for risk management purposes. We find two main results. First, we can clearly classify firms by economic sector according to their different estimated VaR values in five of the seven countries we analyze. In special, we find sectors in general where companies have very high (telecommunications and banking) and very low (petroleum, utilities, energy and consumption) estimated VaR values. Second, we only find differences according to the geographical situation of where the stocks are traded in two countries: (1) all firms in the Irish stock market (the only financially rescued country we analyze) have very high estimated VaR values in all sectors; while (2) in Spain all firms have very low estimated VaR values including in the banking and the telecommunications sectors. All our results are supported when we study also the expected shortfall of the firms.

Keywords: risk management, firms, pareto tail thickness parameter, GARCH-type models, value-at-risk, extreme value theory, heavy tails, stock indexes, eurozone

Procedia PDF Downloads 335

Authors: Godfrey Katende, Lillian Nakimera

Abstract:

The process of caregiving may cause emotional distress in form of anxiety and depression among family carers of cancer patients. Little is known about the prevalence anxiety and depression among family carers of cancer patients in Uganda. This cross-sectional study aimed to determine the prevalence of anxiety and depression among family carers of cancer patients and related factors associated with abnormal levels of anxiety and depression. A total of 119 family carers from Uganda Cancer Institute (UCI) were assessed by the Hospital Anxiety and Depression Scale (HADS) standardized questionnaire. The prevalence of anxiety and depression among family carers was high (45% and 26 % respectively); (2) abnormal levels of anxiety (ALA) and depression (ALD) was significantly associated with being a relative carer. Incorporating evidence based psychological therapies targeting family carers into usual care of cancer patients is imperative.

Keywords: anxiety, cancer, carer, cross-sectional design, depression, Uganda

Procedia PDF Downloads 348

Authors: Shuai Yang, Bin Li, Sixing Chen

Abstract:

Engaging and co-creating value with buyers (i.e., the buying organizations) have rapidly become a rising trend for sellers (i.e., the selling organizations) within Business-to-Business (B2B) environments, through which buyers can interact more with sellers and be better informed about products. One important way to achieve this is through engaging with buyers on social media, termed as brand engagement on social media, which provides a platform for sellers to interact with customers. This study addresses the research gap by answering the following questions: (1) Are B2B firms’ brand engagement on social media related to their firm value? (2) To what extent do analyst stock recommendations channel B2B firms’ brand engagement on social media’s possible impact on firm value? To answer the research questions, this study collected data merged from multiple sources. The results show that there is a positive association between seller-initiated engagement and B2B sellers’ firm value. Besides, analyst stock recommendations mediate the positive relationships between seller-initiated engagement and firm value. However, this study reveals buyer-initiated engagement has a counterintuitive and negative relationship with firm value, which shows a dark side of buyer-initiated engagement on social media for B2B sellers.

Keywords: brand engagement, B2B firms, firm value, social media, stock recommendations

Procedia PDF Downloads 282

Authors: Mohammad Rahim Rahnama, Amir Ali Kharazmi, Safiye Rokni

Abstract:

The tourism industry will be the most important unlimited, sustainable source of income after the oil and automotive industries by 2020 and not only countries, but cities are striving to apprehend its various facets. In line with this objective, the present descriptive-analytical study, through survey and using a questionnaire, seeks to evaluate the probability of tourists’ return and their recommendation to their countrymen to travel to Mashhad, Iran. The population under study is a sample of 384 foreign tourists who, in 2016, arrived at Mashhad, the second metropolis in Iran and its biggest religious city. The Kaplan-Meier estimator was used to analyze the data. Twenty-six percent of the tourists are female and 74% are male. On average, each tourist has had 3.02 trips abroad and 2.1 trips to Mashhad. Tourists from 14 different countries have arrived at Mashhad. Kuwait (15.9%), Armenia (15.6%), and Iraq (10.9%) were the countries where most tourists originated. Seventy-six percent of the tourists traveled with family and 90% of the tourists arrived at Mashhad via airplane. Major purposes of tourists’ trip include pilgrimage (27.9%), treatment (22.1%) followed by pilgrimage and treatment combined (35.4%). Major issues for tourists, in the order of priority, include quality of goods and services (30.2%), shopping (18%), and inhabitants’ treatment of foreigners (15.9%). Main tourist attractions, in addition to the Holy Shrine of Imam Reza, include Torqabeh and Shandiz (Torqabeh 40.9% and Shandiz 29.9%), Neyshabour (18.2%) followed by Kalat, 4.4%. The average willingness to return among tourists is 3.13, which is higher than the mean 3, indicating satisfaction with the stay in Mashhad. Similarly, the average for tourists’ recommending to their countrymen to visit Mashhad is 3.42, which is also an indicator of tourists’ satisfaction with their presence in Mashhad. According to the findings of the Kaplan-Meier estimator, an increase in the number of tourists’ trips to Mashhad, and an increase in the number of tourists’ foreign trips, reduces the probability of recommending a trip to Mashhad by tourists. Similarly, willingness to return is higher among those who stayed at a relatives’ home compared with other patterns of residence (hotels, self-catering accommodation, and pilgrim houses). Therefore, addressing the issues raised by tourists is essential for their return and their recommendation to others to travel to Mashhad.

Keywords: international tourist, probability of return, satisfaction, Mashhad

Procedia PDF Downloads 134

Authors: Matěj Kuc

Abstract:

This paper compares different types of profitability measures of cooperative banks from two developed regions: the European Union and the United States of America together with Canada. We created balanced dataset of more than 200 cooperative banks covering 2011-2016 period. We made series of tests and run Random Effects estimation on panel data. We found that American and Canadian cooperatives are more profitable in terms of return on assets (ROA) and return on equity (ROE). There is no significant difference in net interest margin (NIM). Our results show that the North American cooperative banks accommodated better to the current market environment.

Keywords: cooperative banking, panel data, profitability measures, random effects

Procedia PDF Downloads 91

Authors: Katarzyna Olejko

Abstract:

The need to redefine the goals and adapt the operational activities carried out in accordance with the concept of sustainable management to these goals results in the increasing importance of information on the company's activities perceived from the perspective of the effectiveness and efficiency of environmental goals implementation. The narrow scope of reporting data on a company's impact on the environment is not adequate to meet the information needs of modern investors. Reporting obligations are therefore imposed on companies in order to increase the effectiveness of corporate governance and to improve the process of assessing the achievement of environmental goals. The non-financial reporting obligations introduced in Polish legislation increased the scope of reported information. However, the lack of detailed guidelines on the method of reporting resulted in a large diversification of the scope of non-financial information, making it impossible to compare the data presented by companies. The source of information regarding the level of the implementation of standards in Environmental, social and corporate governance (ESG) is the report on compliance with best practices published by the Warsaw Stock Exchange. The document Best Practices of Warsaw Stock Exchange (WSE) Listed Companies (2021), amended by the WSE in 2021, includes the rules applicable to this area (ESG). The aim of this article is to present the level of compliance with good practices in the area of ESG by selected companies listed on the Warsaw Stock Exchange The research carried out as part of this study, which was based on information from reports on the compliance with good practices of companies listed on the Warsaw Stock Exchange that was made available in the good practice scanner, have revealed that good practices in the ESG area are implemented by companies to a limited extent. The level of their application in comparison with other rules is definitely lower. The lack of experience and clear guidelines on ESG reporting may cause some confusion, which is why conscious investors and reporting companies themselves are pinning their hopes on the Corporate Sustainability Reporting Directive (CSRD) adopted by European Parliament.

Keywords: reporting, ESG, corporate governance, best practices

Procedia PDF Downloads 46

Authors: Tomasz L. Nawrocki, Danuta Szwajca

Abstract:

The growing importance of reputation in building enterprise value and achieving long-term competitive advantage creates the need for its measurement and evaluation for the management purposes (effective reputation and its risk management). The paper presents practical application of self-developed corporate reputation assessment model from the viewpoint of stock market investors. The model has a pioneer character and example analysis performed for selected industry is a form of specific test for this tool. In the proposed solution, three aspects - informational, financial and development, as well as social ones - were considered. It was also assumed that the individual sub-criteria will be based on public sources of information, and as the calculation apparatus, capable of obtaining synthetic final assessment, fuzzy logic will be used. The main reason for developing this model was to fulfill the gap in the scope of synthetic measure of corporate reputation that would provide higher degree of objectivity by relying on "hard" (not from surveys) and publicly available data. It should be also noted that results obtained on the basis of proposed corporate reputation assessment method give possibilities of various internal as well as inter-branch comparisons and analysis of corporate reputation impact.

Keywords: corporate reputation, fuzzy logic, fuzzy model, stock market investors

Procedia PDF Downloads 210

Authors: Fatma Ismailia, Malek Saihi

Abstract:

This research provides an explanation of exchange incentives on the Tunis stock market from a behavioural point of view. The elucidation of the anomalies of excessive volume of transactions and that of excessive volatility cannot be done without the recourse to the psychological aspects of investors. The excessive confidence has been given the predominant role for the explanation of these phenomena. Indeed, when investors store increments, they become more confident about the precision of their private information and their exchange activities then become more aggressive on the subsequent periods. These overconfident investors carry out the intensive exchanges leading to an increase of securities volatility. The objective of this research is to identify whether the trading volume and the excessive volatility of securities observed on the Tunisian stock market come from the excessive exchange of overconfident investors. We use a sample of daily observations over the period January 1999 - October 2007 and we relied on various econometric tests including the VAR model. Our results provide evidence on the importance to consider the bias of overconfidence in the analysis of Tunis stock exchange specificities. The results reveal that the excess of confidence has a major impact on the trading volume while using daily temporal intervals.

Keywords: overconfidence, trading volume, efficiency, rationality, anomalies, behavioural finance, cognitive biases

Procedia PDF Downloads 386

Authors: Razan Salem

Abstract:

Gender plays a vital role in the stock markets because men and women differ in their behavior when investing in stocks. Accordingly, the role of gender differences in investment behavior is an increasingly important strand in the field of behavioral finance research. The investment behaviors of women relative to men have been examined in the behavioral finance literature, mainly for comparison purposes. Women's roles in the stock market have not been examined in the behavioral finance literature, however, particularly with respect to the Arab region. This study aims to contribute towards a better understanding of the investment behavior of Arab women (in regards to their risk tolerance, investment confidence, and investment literacy levels) relative to Arab men; using a sample from Arab women and men investors living in Saudi Arabia and Jordan. In order to achieve the study's main aim, the researcher used non-parametric tests, as Mann-Whitney U test, along with frequency distribution analysis to analyze the study’s primary data. The researcher distributed close-ended online questionnaires to a sample of 550 Arab male and female individuals investing in stocks in both Saudi Arabia and Jordan. The results confirm that the sample Arab women invest less in stocks compared to Arab men due to their risk-averse behaviors and limited confidence levels. The results also reveal that due to Arab women’s very low investment literacy levels, they fear from taking the risk and invest often in stocks relative to Arab men. Overall, the study’s main variables (risk tolerance, investment confidence, and investment literacy levels) have a combined effect on the investment behavior of Arab women and their limited participation in the stock market. Hence, this study is one of the very first studies that indicate the combined effect of the three main variables (which are usually studied separately in the existing literature) on the investment behavior of women, particularly Arab women. This study makes three important contributions to the growing literature on gender differences in investment behavior. First, while the behavioral finance literature documents evidence on gender differences in investment behaviors in many developed countries, there are very limited studies that investigate such differences in Arab countries. Arab women investors, generally, are ignored from the behavioral finance literature due probably to cultural barriers and data collection difficulties. Thus, this study extends the literature to include Arab women and their investment behaviors when trading stock relative to Arab men. Moreover, the study associates women investment literacy and confidence levels with their financial risk behaviors and participation in the stock market. This study provides direct evidence on Arab women's investment behaviors when trading stocks. Overall, studying Arab women investors is important to investigate whether the investment behavior identified for Western women investors are also found in Arab women investors.

Keywords: Arab women, gender differences, investment behavior, stock markets

Procedia PDF Downloads 156

Authors: Dongwan Kang, Joohyung Oh, Chaetae Im

Abstract:

Advancement of communication technologies and smart devices in the recent times is leading to changes into the integrated wired and wireless communication environments. Since early days, businesses had started introducing environments for mobile device application to their operations in order to improve productivity (efficiency) and the closed corporate environment gradually shifted to an open structure. Recently, individual user's interest in working environment using mobile devices has increased and a new corporate working environment under the concept of BYOD is drawing attention. BYOD (bring your own device) is a concept where individuals bring in and use their own devices in business activities. Through BYOD, businesses can anticipate improved productivity (efficiency) and also a reduction in the cost of purchasing devices. However, as a result of security threats caused by frequent loss and theft of personal devices and corporate data leaks due to low security, companies are reluctant about adopting BYOD system. In addition, without considerations to diverse devices and connection environments, there are limitations in detecting abnormal behaviors such as information leaks which use the existing network-based security equipment. This study suggests a method to detect abnormal behaviors according to individual behavioral patterns, rather than the existing signature-based malicious behavior detection and discusses applications of this method in BYOD environment.

Keywords: BYOD, security, anomaly behavior detection, security equipment, communication technologies

Procedia PDF Downloads 295