Agricultural risks are exacerbated by a variety of factors ranging from climatevariability and change, frequent natural disasters, uncertainties in yields and prices, weakrural infrastructure, imperfect markets and lack of financial services including limited spanand design of risk mitigation instruments such as credit and insurance. Indian agriculture has little more than half (53%) of its area still rainfed and this makes it highly sensitive to vagaries of climate causing unstable output. Besides adverse climatic factors, there are man-made disasters such as fire, sale of spurious seeds, adulteration of pesticides and fertilizers etc., and all these severely affect farmers through loss in production and farm income, and are beyond the control of farmers. Hence, crop insurance' is considered to be the promising tool to insulate the farmers from risks faced by them and to sustain them in the agri-business. This paper critically evaluates the performance of recent crop insurance scheme viz., Pradhan Mantri Fasal Bhima Yojana (PMFBY) and its comparative performance with earlier agricultural insurance schemes implemented in the country. It is heartening that, the comparative performance of PMFBY with earlier schemes revealed that, the Government has definitely taken a leap forward in covering more number of farmers and bringing more area under crop insurance with the execution of this new scheme and on this front, it deserves the appreciation in fulfilling the objective for bringing more number of farmers under insurance cover. The use of mobile based technology, reduced number of Crop Cutting Experiments (CCEs) and smart CCEs, digitization of land record and linking them to farmers' account for faster assessment/settlement of claims are some of the steps that contributed for effective implementation of this new crop insurance scheme. However, inadequate claim payments, errors in loss/yield assessment, delayed claim payment, no direct linkage between insurance companies and farmers are the major shortcomings of this scheme. This calls for revamping the crop insurance program in India from time to time in tune with the dynamic changes in climatic factors on one hand and to provide a safety-net for farmers to mitigate losses arising from climatic shocks on the other. The future research avenues include: insuring the revenue of the farmer (Price × Yield) as in USA and more and more tenant farmers should be brought under insurance by doling out discounts for group coverage of farmers like in Philippines where 20 per cent discount in premium is given for a group of 5-10 farmers, 30 per cent for a group of 10-20 and 40 per cent for a group of >20 farmers.
Journal of the Korea Academia-Industrial cooperation Society
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v.17
no.4
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pp.480-488
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2016
As the subprime mortgage crisis spread globally, it depressed not only the financial market, but also the construction business in Korea. In fact, according to CERIK, the BSI of the construction businesses plunged from 80 points in December 2006 to 14.6 points in November 2008, and the extent of the depression in the housing sector was particularly serious. In this respect, this paper analyzes the influence of the financial market fluctuation on the housing market before and after the Global Financial Crisis using VECM. The periods from January 2000 to December 2007 and January 2008 to October 2015, before and after the financial crisis, were set as Models 1 and 2, respectively. The results are as follows. First, when the economy is good, the Gangnam housing market is an attractive one for investment. However, when it is depressed, the Gangnam housing market changes in response to the macroeconomic fluctuations. Second, the Gangbuk and Gangnam housing markets showed different responses to fluctuations in the financial market. Third, when the economy is bad, the effect of low interest rates is limited, due to the housing market risk.
Kim, Bong-Gu;Kim, Jeong-Hye;Kim, Se-Jong;Park, So-Deuk;Choi, Boo-Sull;Yeo, Soo-Kab
Korean Journal of Medicinal Crop Science
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v.6
no.3
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pp.232-238
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1998
To analyse the management and production of medicinal crops in Uisong region, cultural conditions and standard income of 147 farms were investigated. Location quotient of medicinal crops cultivated was high as following order ; Paeonia lactiflora > Cornus ofidnalis> Bupleurm falcatum > Anemarhena asphodeloides > Rehmannia glutinosa > Eucommia ulmoides > Paeonia suffruticosa > Angelica dahurica. The average cultivated area per farm was 1.92ha : 1.35ha of upland field, 0.56ha of paddy field. Distribution of agricultural land in each farm was average 10.2 fields in 3.1 locations. Ratio of labor input in the medicinal plant sector was 31.1 %. The number of medicinal crops cultivated was 36 species among 147 farms and 2.4 species per farm. Among the cultivated medicinal plant, peony (Paeonia lactiflora) was the most popular medicinal plant, which was cultivated in 30.72ha of 85 farms. Income from medicinal plants was high in order of Carthamus tinctorius, Polygonatum stenophyllum, Angelica genuilexa. Medicinal crops should be selected based on farm condition, risk level and price settlement in order to maximize productivity and income.
This study analyzed the information effect of KOSPI200 market and KOSPI200 futures market and volume synchronized probability of informed trading (VPIN). The data period is 760 days from July 8, 2015 to August 9, 2018, and the intraday trading data is used based on the trading period of the KOSPI 200 Index. The findings of the empirical analysis are as follows. First, as a result of regression analysis of the same parallax, when the level of VPIN is high, the return and volatility of KOSPI200 are high. Second, the KOSPI200 returns before and after the VPIN measurement and the return of the KOSPI200 future had a positive relationship with the VPIN. The cumulative returns of KOSPI200 futures were positive for about 15 minutes.Finally, we find that portfolios with high levels of VPIN showed high KOSPI200 and KOSPI200 futures return. These results confirmed the applicability of VPIN as a trading strategy index. The above results suggest that KOSPI200 and KOSPI200 futures markets will be able to explore volatility and price changes, and also be useful indicators of financial market risk.
In this paper, I investigate how international prices affect domestic prices and export prices in Korea by using vector error correction model(VECM) and estimate its impact on international trade. According to the empirical results, international prices, such as world raw material prices and oil prices, make stronger effects on domestic prices, in order of import, export, producer, and consumer prices. And recent years the effect of international raw material prices on domestic prices becomes larger. It implies importers, exporters and producers are more affected by international prices than consumers are. Therefore, the international trade, import and export, is affected by changes in international prices. Firms, especially importing and exporting companies, should do much efforts on risk managing about raw material prices variation, diversification of raw material suppliers, and oversea resources development. The government is needed to support on firms those efforts while doing its economic policies to cope with economic conditions and the price policy.
The Korea Emissions Trading Scheme ( K-ETS), which manages roughly 70% of the greenhouse gas emissions in South Korea, was initiated in 2015, after implementation of its 1st basic plan and the 1st allocation plan (2014) for the 1st phase (2015-2017). During the three and a half years since the launch of K-ETS, there have been critical policy change such as adjustment of the institutions involved, development and revision of the 2030 national GHG reduction roadmap, and change in the allocation plans. Moreover, lack of liquidity and fluctuation of carbon prices in the K-ETS market during this period has forced the Korean government to adjust the flexibility mechanism and auction permits of the market stability reserve. To evaluate the policy change in the K-ETS regarding conformance to its objectives, this study defines three objectives (Environmental Effectiveness, Cost Effectiveness and Economic Efficiency) and ten indicators. Evaluation of Environmental Effectiveness of K-ETS suggests that the national GHG reduction roadmap, coverage of GHG emitters and credibility of MRV positively affect GHG mitigation. However, there was a negative policy change implemented in 2017 that weakened the emission cap during the 1st phase. In terms of the Cost Effectiveness, the K-ETS policies related to market management and flexibility mechanism (e.g. banking, borrowing and offsets) were improved to deal with the liquidity shortage and permit price increase, which were caused by policy uncertainty and conservative behavior of firms during 2016-2018. Regarding Economic Efficiency, K-ETS expands benchmark?based allocation and began auction-based allocation; nevertheless, free allocation is being applied to sectors with high carbon leakage risk during the 2nd phase (2018-2020). As a result, it is worth evaluating the K-ETS policies that have been developed with respect to the three main objectives of ETS, considering the trial?and?error approach that has been followed since 2015. This study suggests that K-ETS policy should be modified to strengthen the emission cap, stabilize the market, expand auction-based allocation and build K-ETS specified funds during the 3rd phase (2021-2025).
Asia-Pacific Journal of Business Venturing and Entrepreneurship
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v.14
no.5
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pp.105-113
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2019
This study focuses on analyzing the key success factors of the traditional market by analyzing the impact on the business performance of merchants in the traditional market. Based on the existing research on entrepreneurship, psychological characteristics, capabilities, and physical characteristics of the market were considered as merchant characteristics. As a result, the risk characteristics and merchant pride, which are internal characteristics of merchants, have a significant effect on business performance. Among the competencies of merchants, product competency, customer management competency, and price competency were found to have a significant impact on business performance. Among the physical characteristics of the market, reputation and product diversity were found to have a significant effect on business performance. The results of this study are meaningful to empirically prove the relevance of the merchant's internal characteristics and capabilities, and the market's physical characteristics to the business performance of market merchants. Could be utilized. However, the limitation of this study is that there may be differences in each industry in the case of market merchant products. In future studies, empirical studies on the trader's relevance to business capability and business performance should be continued.
This study analyzes the earnings management that can occur in the process of public offering in the process of SMEs reducing cost of capital, risks and seeking opportunities for direct financing. Since a company is subject to strict supervision during the IPO process, it is possible to prevent the phenomenon that the company value evaluated in the market is underestimated, or to perform earnings management in consideration of overestimation. This study attempted to verify the degree of earnings management through discretionary accruals and actual earnings management values that can affect the earnings ratio of the IPO of a company. For this study, total accruals were calculated and analyzed through discretionary accruals, sales, costs, and actual earnings management adjustments from production activities. As a result of the analysis, discretionary accruals, which are the countermeasures for earnings management during the listing process, have a positive(+) relationship in both the stock price return and the sales adjustment value, which can be viewed as a factor that induces high valuation. As a result of this, there may be a risk of adverse selection for the benefit amount, and information asymmetry may exist for public offering stocks. This study can provide useful guidelines for evaluating corporate value to domestic SMEs and investors that do business with Chinese companies as well as China through the current and type of earnings management of Chinese listed companies.
The Journal of the Institute of Internet, Broadcasting and Communication
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v.22
no.2
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pp.83-88
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2022
The purpose of this study is to present an analysis and implications for the metaverse-based virtual real estate transaction service. Through blockchain-based technology and metaverse, the world we live in is expanding naturally. Therefore, changes in the environment and perceptions of market participants are also very important factors. The concept and thinking about the existing asset value change and investment are also changing. This means that you can generate profits through value and investment in intangible assets. The service user aspect is a case of investing in the future value of virtual real estate that if more users participate rather than the present value, the principle of supply and demand will be applied to increase the number of consumers and the price will naturally rise according to the principle of scarcity. The service provider provides a technical platform for the service to directly transact the portion of the virtual area considered of interest directly through the virtual real estate purchase business. As the number of participants increases as well as funds and transaction fees, various revenue models such as advertisements can be discovered and provided. It plays the role of providing jobs and information through new services. As a stakeholder, governments can exploit the emergence of new technologies and products to create people and services and secure economic benefits. Of course, various institutional supports should be provided so that new services can settle in the market while mitigating risk factors. This study is meaningful in that it contributes to the establishment of a domestic metaverse-based environment and related research and is utilized in the study of virtual space real estate services.
The Journal of the Convergence on Culture Technology
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v.8
no.5
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pp.697-703
/
2022
Due to the recent economic downturn caused by Covid-19 and the unstable international situation, many investors are choosing the derivatives market as a means of investment. However, the derivatives market has a greater risk than the stock market, and research on the market of market participants is insufficient. Recently, with the development of artificial intelligence, machine learning has been widely used in the derivatives market. In this paper, reinforcement learning, one of the machine learning techniques, is applied to analyze the scalping technique that trades futures in minutes. The data set consists of 21 attributes using the closing price, moving average line, and Bollinger band indicators of 1 minute and 3 minute data for 6 months by selecting 4 products among futures products traded at trading firm. In the experiment, DNN artificial neural network model and three reinforcement learning algorithms, namely, DQN (Deep Q-Network), A2C (Advantage Actor Critic), and A3C (Asynchronous A2C) were used, and they were trained and verified through learning data set and test data set. For scalping, the agent chooses one of the actions of buying and selling, and the ratio of the portfolio value according to the action result is rewarded. Experiment results show that the energy sector products such as Heating Oil and Crude Oil yield relatively high cumulative returns compared to the index sector products such as Mini Russell 2000 and Hang Seng Index.
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