• Asia pacific journal of information systems
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• 제30권1호
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• pp.31-52
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• 2020

Stock markets are popular investment avenues to people who plan to receive premium returns compared to other financial instruments, but they are highly volatile and risky due to the complex financial dynamics and poor understanding of the market forces involved in the price determination. A system that can forecast, predict the stock prices and automatically create a portfolio of top performing stocks is of great value to individual investors who do not have sufficient knowledge to understand the complex dynamics involved in evaluating and predicting stock prices. In this paper the authors propose a Stock prediction, Portfolio Generation and Selection model based on Machine learning algorithms, Artificial neural networks (ANNs) are used for stock price prediction, Mathematical and Statistical techniques are used for Portfolio generation and Un-Supervised Machine learning based on K-Means Clustering algorithms are used for Portfolio Evaluation and Selection which take in to account the Portfolio Return and Risk in to consideration. The model presented here is limited to predicting stock prices on a long term basis as the inputs to the model are based on fundamental attributes and intrinsic value of the stock. The results of this study are quite encouraging as the stock prediction models are able predict stock prices at least a financial quarter in advance with an accuracy of around 90 percent and the portfolio selection classifiers are giving returns in excess of average market returns.

• International Journal of Computer Science & Network Security
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• 제22권3호
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• pp.67-76
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• 2022

COVID-19 struck labor markets around the world, exposing and exacerbating the gender inequalities within the human capital structure. The last, in its turn, jeopardizes the return of the national economies to the growth trajectory undermined by pandemic impact. The authors assume that COVID-19 disproportionately affected the employment rates of women and men, which led to increased gender inequality in the labor market, which, in turn, affected GDP growth rates in the EU. To prove this hypothesis two research questions are discovered: 1) whether there was a different correlation between the number of COVID-19 cases in the EU and indicators of the labor market for women and men; and 2) whether there was a link between the growth of gender inequality in the EU labor market and the GDP dynamics in these countries. The analysis of the correlation between the number of cases of COVID-19 and indicators of the labor market in the EU revealed faster growth of women's unemployment rates compared to men's ones as the COVID-19 incidence unfolded. Multiple linear regression and factor analysis have been used to investigate the influence of gender inequality in the labor market on GDP dynamics. Despite the methodological limitations, the proposed model is both a sound argument and an analytical basis in favor of gender-responsive economic recovery backed by the systematic and consistent gender equality policy of a government.

• Bulletin of the Korean Chemical Society
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• 제35권5호
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• pp.1285-1293
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• 2014

Several interesting features in trajectory were observed in the direct dynamics study of formaldehyde dissociation above radical dissociation limit. The hydrogen atom deliberately placed on the radical dissociation path can turn around at some distance from C without completion of dissociation and return to HCO moiety, colliding with it just as in a radical-radical recombination and producing a highly energized molecule. Excursion of a hydrogen atom to a distance of 6-8 bohrs and migration of a hydrogen atom back and forth between C and O are two of the most interesting features exhibited by the energized molecule. A series of excursions is seen to lead to a different kind of dissociation resembling roaming-like dissociation characterized by high vibrational excitation of $H_2$ fragment. It is suggested that excursion occurs due to involvement of two different force field systems that exhibit discontinuity in 6-8 bohrs from HCO moiety. We argue that roaming is a non-zero impact parameter version of the excursion.

• Communications for Statistical Applications and Methods
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• 제21권5호
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• pp.445-459
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• 2014

This paper investigates the dependence structure of Korean financial markets (stock, foreign exchange (FX) rates and bond) using copula-GARCH and dynamic conditional correlation (DCC) models. We examine GJR-GARCH with skewed elliptical distributions and four copulas (Gaussian, Student's t, Clayton and Gumbel) to model dependence among returns, and then employ DCC model to describe system-wide correlation dynamics. We analyze the daily returns of KOSPI, FX (WON/USD) and KRX bond index (Gross Price Index) from $2^{nd}$ May 2006 to $30^{th}$ June 2014 with 2,063 observations. Empirical result shows that there is significant asymmetry and fat-tail of individual return, and strong tail-dependence among returns, especially between KOSPI and FX returns, during the 2008 Global Financial Crisis period. Focused only on recent 30 months, we find that the correlation between stock and bond markets shows dramatic increase, and system-wide correlation wanders around zero, which possibly indicates market tranquility from a systemic perspective.

• Asia pacific journal of information systems
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• 제9권3호
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• pp.93-110
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• 1999

The previous studies regarding the stock returns have advocated that industry effects exist over entire industry. As the industry categories are more rigid, the demand for predicting the industry sectors is rapidly increasing. The advances in Artificial Intelligence and Neural Networks suggest the feasibility of a valuable computational model for stock returns prediction. We propose a sector-factor model for predicting the return on industry stock index using neural networks. As a substitute for the traditional models, neural network model may be more accurate and effective alternative when the dynamics between the underlying industry features are not well known or when the industry specific asset pricing equation cannot be solved analytically. To assess the potential value of neural network model, we simulate the resulting network and show that the proposed model can be used successfully for banks and general construction industry. For comparison, we estimate models using traditional statistical method of multiple regression. To illustrate the practical relevance of neural network model, we apply it to the predictions of two industry stock indexes from 1980 to 1995.

• 대한기계학회:학술대회논문집
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• 대한기계학회 2008년도 추계학술대회A
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• pp.1784-1787
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• 2008

Molecular dynamics (MD) simulations are used to analyze behavior of copper nanowires under cyclic loading. The embedded atom method (EAM) potential is employed to represent atomic interaction. Cyclic load is applied in two ways (Forward Tension / Reverse Compression and Forward Compression / Reverse Tension). The results show that dislocations are piled up as a result of plastic deformation during alternate tensile and compressive loading. After cyclic loading with a change of direction, yield stress decreases in consequence of the effect by the dislocation pileups. On the other hand, under FC/RT cyclic load, phase transformation represent associated with mechanical twinning. And copper nanowire can return to almost former undeformed condition during tensile loading at 300K.

• International Journal of Automotive Technology
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• 제7권2호
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• pp.187-193
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• 2006

When emergency evasion during running is required, a driver sometimes causes a vehicle to drift, that is, a condition in which the rear wheels skid due to rapid steering. Under such conditions, the vehicle enters a very unstable state and often becomes uncontrollable. An unstable state of the vehicle induced by rapid steering was simulated and the effect of differential steering assistance was examined. Results indicate that, in emergency evasion while cornering and during which the vehicle begins to drift, unstable behavior like spins can be avoided by differential steering assistance and both the stability and control of the vehicle is improved remarkably. In addition, reduction of overshoot during spin evasion by the differential steering assistance has been shown to enable the vehicle to return to a state of stability in a short time in emergency evasion during straight-line running. Moreover, the effectiveness of differential steering assistance during emergency evasion was confirmed using a driving simulator.

• KDI Journal of Economic Policy
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• 제15권4호
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• pp.155-173
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• 1993

주식수익율(株式收益率)의 조건부분산(條件附分散)의 움직임을 모형화(模型化)하기 위하여 Engle(1982)의 ARCH(Autoregressive Conditional Heteroskedasticity)모형(模型)을 효시(嚆矢)로 많은 종류의 모형(模型)이 제시되어 왔다. 이 가운데서 Nelson(1991)의 EGARCH(Exponential Generalized ARCH)는 종래의 모형(模型)에 비하여 여러가지 장점(長點)을 지니고 있는 모형(模型)이다. 그러나 EGARCH에서는 비기대수익율(非期待收益率)(unexpected return)이 조건부분산(條件附分散)에 미처는 규모효과(規模效果)(magnitude effect)와 비대칭효과(非對稱效果)(asymmetry effect)의 영향(影響)이 동일한 동태(動態)(dynamics)를 보인다고 가정(假定)하고 있다. 본(本) 논문(論文)은 이 가정(假定)을 완화하였을 때 규모효과(規模效果)와 비대칭효과(非對稱效果)가 매우 다른 동태(動態)를 가지며, 특히 규모효과(規模效果)의 영향은 오래 지속되는 반면 비대칭효과(非對稱效果)는 비교적 빠르게 사라짐을 보여준다.

• Ocean Systems Engineering
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• 제13권3호
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• pp.225-245
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• 2023

In the present paper, a numerical and experimental analysis for a wave energy converter under extreme environmental conditions is carried out. After the definition of design waves, including a 100-year return period stochastic sea state and a deterministic rogue wave condition, a numerical analysis using potential theory and a RANS equations solver are compared with experiments carried out at the Seakeeping Basin at the Technical University of Berlin. Results are discussed with special emphasis on the limits of potential theory methods for the evaluation of extreme wave conditions and the use of the presented methodology for early design stages.

• Wind and Structures
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• 제9권4호
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• pp.297-313
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• 2006

The concentration of air pollution along roads is higher than the surrounding area because ventilation efficiency has decreased due to the high-density use of space along roads in recent years. In this study, ventilation efficiency around a heavily traffic road covered by an elevated highway and hemmed in along its side by buildings is evaluated using Visitation Frequency (VF, the frequency for pollutant to return to the objective domain) and Purging Flow Rate (PFR, the air flow rate for defining the local domain-averaged concentration). These are analyzed using Computational Fluid Dynamics (CFD) based on the standard $k-{\varepsilon}$ model. The VF and PFR characteristics of four objective domains are analyzed in terms of the changes in wind direction and arrangements of the fencing dividing up and down direction in the road center under the elevated highway. The resulting VFs are more than 1.0 for all cases, which means that pollutants return to the objective domain restricted by the elevated highway and side buildings. The influence of the arrangement of the buildings around the objective domain and the structure in the domain on the VF is substantial. In cases where there are no obstacles under the elevated highway, the local air exchange rate in the domain tends to be improved. Using these indices, the urban ventilation efficiencies between different urban areas can be compared easily.