• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.20 no.1
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• pp.174-192
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• 2021

The LIDAR sensor, which provides higher cognitive performance than cameras and radar, is difficult to apply to ADAS or autonomous driving because of its high price. On the other hand, as the price is decreasing rapidly, expectations are rising to improve existing autonomous driving functions by taking advantage of the LIDAR sensor. In level 3 autonomous vehicles, when a dangerous situation in the cognitive module occurs due to a sensor defect or sensor limit, the driver must take control of the vehicle for manual driving. If the driver does not respond to the request, the system must automatically kick in and implement a minimum risk maneuver to maintain the risk within a tolerable level. In this study, based on this background, a LIDAR-based LKS MRM algorithm was developed for the case when the normal operation of LKS was not possible due to troubles in the cognitive system. From point cloud data collected by LIDAR, the algorithm generates the trajectory of the vehicle in front through object clustering and converts it to the target waypoints of its own. Hence, if the camera-based LKS is not operating normally, LIDAR-based path tracking control is performed as MRM. The HAZOP method was used to identify the risk sources in the LKS cognitive systems. B, and based on this, test scenarios were derived and used in the validation process by simulation. The simulation results indicated that the LIDAR-based LKS MRM algorithm of this study prevents lane departure in dangerous situations caused by various problems or difficulties in the LKS cognitive systems and could prevent possible traffic accidents.

• The Korean Journal of Financial Management
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• v.24 no.2
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• pp.41-79
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• 2007

This study examines the expiration-day effects of stock index futures and options in the Korean stock market. The so-called 'expiration-day effects', which are the abnormal stock price movements on derivatives expiration days, arise mainly from cash settlement. Index arbitragers have to bear the risk of their positions unless they liquidate their index stocks on the expiration day. If many arbitragers execute large buy or sell orders on the expiration day, abnormal trading volumes are likely to be observed. If a lot of arbitragers unwind positions in the same direction, temporary trading imbalances induce abnormal stock market volatility. By contrast, if some information arrives at market, the abnormal trading activity must be considered a normal process of price discovery. Stoll and Whaley(1987) investigated the aggregate price and volume effects of the S&P 500 index on the expiration day. In a related study, Stoll and Whaley(1990) found a similarity between the price behavior of stocks that are subject to program trading and of the stocks that are not. Thus far, there have been few studies about the expiration-day effects in the Korean stock market. While previous Korean studies use the KOSPI 200 index data, we analyze the price and trading volume behavior of individual stocks as well as the index. Analyzing individual stocks is important for two reasons. First, stock index is a market average. Consequently, it cannot reflect the behavior of many individual stocks. For example, if the expiration-day effects are mainly related to a specific group, it cannot be said that the expiration of derivatives itself destabilizes the stock market. Analyzing individual stocks enables us to investigate the scope of the expiration-day effects. Second, we can find the relationship between the firm characteristics and the expiration-day effects. For example, if the expiration-day effects exist in large stocks not belonging to the KOSPI 200 index, program trading may not be related to the expiration-day effects. The examination of individual stocks has led us to the cause of the expiration-day effects. Using the intraday data during the period May 3, 1996 through December 30, 2003, we first examine the price and volume effects of the KOSPI 200 and NON-KOSPI 200 index following the Stoll and Whaley(1987) methodology. We calculate the NON-KOSPI 200 index by using the returns and market capitalization of the KOSPI and KOSPI 200 index. In individual stocks, we divide KOSPI 200 stocks by size into three groups and match NON-KOSPI 200 stocks with KOSPI 200 stocks having the closest firm characteristics. We compare KOSPI 200 stocks with NON-KOSPI 200 stocks. To test whether the expiration-day effects are related to order imbalances or new information, we check price reversals on the next day. Finally, we perform a cross-sectional regression analysis to elaborate on the impact of the firm characteristics on price reversals. The main results seem to support the expiration-day effects, especially on stock index futures expiration days. The price behavior of stocks that are subject to program trading is shown to have price effects, abnormal return volatility, and large volumes during the last half hour of trading on the expiration day. Return reversals are also found in the KOSPI 200 index and stocks. However, there is no evidence of abnormal trading volume, or price reversals in the NON-KOSPI 200 index and stocks. The expiration-day effects are proportional to the size of stocks and the nearness to the settlement time. Since program trading is often said to be concentrated in high capitalization stocks, these results imply that the expiration-day effects seem to be associated with program trading and the settlement price determination procedure. In summary, the expiration-day effects in the Korean stock market do not exist in all stocks, but in large capitalization stocks belonging to the KOSPI 200 index. Additionally, the expiration-day effects in the Korean stock market are generally due, not to information, but to trading imbalances.

• Asia Marketing Journal
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• v.11 no.3
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• pp.31-56
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• 2009

As the competition intensifies and the market matures, marketers are more and more concerned with the relationship marketing. Many of the previous researches have pointed out that not all of the consumers are relationship-oriented. But none of the previous research has systematically investigated this issue. This research investigated the relationship among the three concepts: consumers' intrinsic characteristics, perceived importance of relational benefits, and relationship building intention with the salesperson. In this research the perceived importance of relational benefits is treated as mediating variable in the relationship between consumers' intrinsic characteristics and relationship building intention with the salesperson. The conceptual model in this study can be depicted as follows. From the consumers' perspective relational benefits can be defined as "the additional benefits consumers can receive in addition to core services through the long-term relationship with the service provider." And in this study two kinds of relational benefits are adopted by reviewing the previous research: confidence benefits and social benefits. Relational benefit received from the salesperson is very important to predict consumers' relationship building intention with the salesperson. The more relational benefits consumer wants from the salesperson, the more relationship building intention he/she has. From this point two hypotheses are derived as follows. Hypothesis 1: As the perceived importance of confidence benefit from the salesperson increases, the relationship building intention with the salesperson increases. Hypothesis 2: As the perceived importance of social benefit from the salesperson increases, the relationship building intention with the salesperson increases. In this study four individual characteristics(risk taking tendency, variety-seeking tendency, product knowledge, trust orientation) are hypothesized to influence the perceived importance of confidence benefits from the salesperson. And three individual characteristics(interpersonal orientation, price consciousness, trust orientation) are hypothesized to influence the perceived importance of social benefits from the salesperson. These 7 hypotheses are as follows. Hypothesis 3: As the risk taking tendency increases, the perceived importance of confidence benefits from the salesperson decreases. Hypothesis 4: As the variety-seeking tendency increases, the perceived importance of confidence benefits from the salesperson decreases. Hypothesis 5: As the product knowledge increases, the perceived importance of confidence benefits from the salesperson decreases. Hypothesis 6: As the trust orientation increases, the perceived importance of confidence benefits from the salesperson increases. Hypothesis 7: As the interpersonal orientation increases, the perceived importance of social benefits from the salesperson increases. Hypothesis 8: As the price consciousness increases, the perceived importance of social benefits from the salesperson decreases. Hypothesis 9: As the trust orientation increases, the perceived importance of social benefits from the salesperson increases. The whole model in this study can be depicted as follows: Data were collected from the 396 consumers who actually trade stocks through the salesperson and were analyzed using structural equation model. The analysis results show that consumers' perceived importance of relational benefits(confidence benefit and social benefit) play the roles of mediating variables in the causal relationship between consumers' inherent characteristics and their relationship building intention with the salesperson. As for the individual characteristics, the influences of variety-seeking tendency, trust orientation, and price consciousness are statistically significant. It was found that variety-seeking tendency has a significant negative effect on the perceived importance of confidence benefit, and that trust orientation has a significant positive effect on the perceived importance of both of confidence and social benefit. Finally it was also found that, on the contrary to the influence direction suggested in the hypothesis, price consciousness has a significant positive effect on the perceived importance of social benefit.

• The Journal of Information Systems
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• v.25 no.4
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• pp.87-104
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• 2016

Purpose As the smartphone market arrived at its saturation, from world leading information and communications technologies (ICT) businesses to startups, companies are competing to develop innovative wearable device products and suitable contents. Utility, technology, design, price, and various killer contents development targeting every customer's need should be considered for a success in the wearable device market. Design/methodology/approach Prior studies on innovation technology of ICT field have mainly focused on the innovation diffusion theory, expectation confirmation theory, and technology acceptance model, this study suggested the innovation resistance factors of adopting the smart wearable devices based on the innovation resistance model and theory of perceived risk. The model comprises the following two characteristics factors: 1) innovation characteristics which include perceived relative advantages, perceived compatability, perceived complexity, and perceived risk, 2) consumer characteristics which include attitudes towards innovation and existing products (i.e., mobile devices and analog watches). This study developed an extended innovation resistance model to explain the intention to acceptance of wearable devices consumers and collected 284 online survey responses from the non-consumers of the wearable devices. Findings The findings of this study suggest that perceived relative advantage, perceived compatibility, perceived complexity, perceived risk, attitudes towards innovation and attitudes towards existing analog watches affected the innovation resistance which has negative influence on the intention to adoption of wearable devices.

• Proceedings of the Safety Management and Science Conference
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• 2005.05a
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• pp.379-392
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• 2005

The size of state in Korea is like Israel, this country's venture capital is ruled by government. This venture capital's character is below: the concentration on research of venturer affect positively at quality of products. This paper lies with venture capital's risk character & performance. The results show that Korean venture capitals have lager unsystematic risk than systematic risk, which implies they specialize in specific business and/or regional areas instead of diversification. The Sharpe & Jensen measures reveal that the performances of Korean venture capitals are very low relative to even the market portfolio(Kospi) and Kosdaq Venture Index. Contrary to this, Venture firm's performance according to Entrepreneurship will cause to push up stock price.

• Communications for Statistical Applications and Methods
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• v.29 no.1
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• pp.85-101
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• 2022

Derivative-linked securities (DLS) is a type of derivatives that offer an agreed return when the underlying asset price moves within a specified range by the maturity date. The underlying assets of DLS are diverse such as interest rates, exchange rates, crude oil, or gold. A German 10-year bond rate-linked DLS and a USD-GBP CMS rate-linked DLS have recently become a social issue in Korea due to a huge loss to investors. In this regard, this paper accounts for the payoff structure of these products and evaluates their prices and fair coupon rates as well as risk measures such as Value-at-Risk (VaR) and Tail-Value-at-Risk (TVaR). We would like to examine how risky these products were and whether or not their coupon rates were appropriate. We use Hull-White Model as the stochastic model for the underlying assets and Monte Carlo (MC) methods to obtain numerical results. The no-arbitrage prices of the German 10-year bond rate-linked DLS and the USD-GBP CMS rate-linked DLS at the center of the social issue turned out to be 0.9662% and 0.9355% of the original investment, respectively. Considering that Korea government bond rate for 2018 is about 2%, these values are quite low. The fair coupon rates that make the prices of DLS equal to the original investment are computed as 4.76% for the German 10-year bond rate-linked DLS and 7% for the USD-GBP CMS rate-linked DLS. Their actual coupon rates were 1.4% and 3.5%. The 95% VaR and TVaR of the loss for German 10-year bond rate-linked DLS are 37.30% and 64.45%, and those of the loss for USD-GBP CMS rate-linked DLS are 73.98% and 87.43% of the initial investment. Summing up the numerical results obtained, we could see that the DLS products of our interest were indeed quite unfavorable to individual investors.

• The Journal of Asian Finance, Economics and Business
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• v.9 no.4
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• pp.53-62
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• 2022

Disposition Effect (DE) is one of the many investment biases, wherein the investors sell the profitable stocks rather quickly and they tend to hold on the loss making stocks. Various factors related to the DE are the character of investors applying risk management which is also influenced by the social media, Salient Shock (COVID-19), and in the specific case of Indonesia, the phenomenon of rumor stocks wherein the price can rise as much as up to 8500%. The study aims to provide empirical evidence regarding the DE with specific explanatory factors, namely investor behavior and rumors. Data was obtained through a questionnaire sent to 248 Indonesian Stock Exchange Investors (IDX) during the period October-November 2021 by using Ordinary Least Square (OLS) method. The results show: Generation Z, women, and investors with a low education has a greater DE, risk-takers tend to have lower DE, and professionals have negative DE. Implementation of risk management will reduce DE. Social Media and the COVID-19 situation positively affect DE. Especially on stock rumors, there is evidence that investors who own rumor stocks will have a low DE. The results indicate the need for: (i) risk management, especially for Z Generation, women and low education Investors, (ii) to provide positive information so that information on social media can be responded to positively.

• The Journal of the Convergence on Culture Technology
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• v.7 no.3
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• pp.365-374
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• 2021

Recently, the high growth rate and advantages of the crowdfunding market have also led to increased participation of brands and companies, and this also applies to fashion business. Risk has been noted to be a key factor in consumer behavior in crowdfunding. With the high-risk context of crowdfunding where supporters inevitably bear to pay full amount of price before receiving the actual products. Factors enhancing or inhibiting perceived risk of crowdfunding need to be explored. The past literature on perceived risk and consumer attitudes in crowdfunding has expanded, but it has rarely covered the context of experience goods such as fashion products. In addition, the platform characteristics in relation to perceived risk should be addressed. The current study attempts to address the effect of the perceived amount of information offered in a fashion crowdfunding project on perceived risk and the intention to participate in the project. For the experiment of this study, a fictitious crowdfunding page for fashion products was set as the stimuli. A total of 240 Korean participants were recruited and their responses were statistically analyzed using SPSS 24.0 software. In the results, the greater the amount of detailed information about the fashion crowdfunding project, the higher the intention to participate the project. The greater the amount of information provided, the lower the perceived risk of consumers. Moreover, the lowered perceived risk affected the intention of participate. Perceived risk has a partial mediation in the relationship between the amount of information and intention to participate. Theoretical and managerial implications are discussed.

• Management & Information Systems Review
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• v.30 no.4
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• pp.147-173
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• 2011

It is generally accepted that there are momentum effects in the short term and reversal effects in the long term, which makes abnormal excess returns in the major stock markets in the world. In Korea stock market, however, the previous studies demonstrate that contrarian strategies based on reversal effects are more effective than momentum strategies following momentum effects in the short term as well as in the long term. This paper examines wether contrarian strategies are still effective In Korea stock market from 1980 to 2009, and the short term reversals may be changed after the foreign exchange crisis in 1997-1998. Moreover, this paper investigates how contrarian profits are shown considering the state of market. In my research, unlike previous studies, I find that both of contrarian strategies using price change and price level cannot gain excess risk adjusted returns in Korea stock market from 1980 to 2009, but this result is due to the fact that reversal effects existed before the foreign exchange crisis but momentum effects does after the foreign exchange crisis in 1997-1998. Specially, after the foreign exchange crisis, it is confirmed momentum strategies using 52 week high price, that is, price level are more effective than momentum strategies using price change. And following the strategies using 52 week high price after the foreign exchange crisis, the momentum is not only observed in the up market but also in the down market, which is different with the results of the studies regarding to American market, where the momentum is just found in the up market.

• Journal of Intelligence and Information Systems
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• v.28 no.4
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• pp.157-177
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• 2022

Investors are trading stocks by keeping a close watch on the order information submitted by domestic and foreign investors in real time through Limit Order Book information, so-called price current provided by securities firms. Will order information released in the Limit Order Book be useful in stock price prediction? This study analyzes whether it is significant as a predictor of future stock price up or down when order imbalances appear as investors' buying and selling orders are concentrated to one side during intra-day trading time. Using classification algorithms, this study improved the prediction accuracy of the order imbalance information on the short-term price up and down trend, that is the closing price up and down of the day. Day trading strategies are proposed using the predicted price trends of the classification algorithms and the trading performances are analyzed through empirical analysis. The 5-minute KOSPI200 Index Futures data were analyzed for 4,564 days from January 19, 2004 to June 30, 2022. The results of the empirical analysis are as follows. First, order imbalance information has a significant impact on the current stock prices. Second, the order imbalance information observed in the early morning has a significant forecasting power on the price trends from the early morning to the market closing time. Third, the Support Vector Machines algorithm showed the highest prediction accuracy on the day's closing price trends using the order imbalance information at 54.1%. Fourth, the order imbalance information measured at an early time of day had higher prediction accuracy than the order imbalance information measured at a later time of day. Fifth, the trading performances of the day trading strategies using the prediction results of the classification algorithms on the price up and down trends were higher than that of the benchmark trading strategy. Sixth, except for the K-Nearest Neighbor algorithm, all investment performances using the classification algorithms showed average higher total profits than that of the benchmark strategy. Seventh, the trading performances using the predictive results of the Logical Regression, Random Forest, Support Vector Machines, and XGBoost algorithms showed higher results than the benchmark strategy in the Sharpe Ratio, which evaluates both profitability and risk. This study has an academic difference from existing studies in that it documented the economic value of the total buy & sell order volume information among the Limit Order Book information. The empirical results of this study are also valuable to the market participants from a trading perspective. In future studies, it is necessary to improve the performance of the trading strategy using more accurate price prediction results by expanding to deep learning models which are actively being studied for predicting stock prices recently.