Trade Research Articles

Machine Learning based Financial Stock Market Trading Strategies with Moving Average, Stochastic Relative Strength Index and Price Volume Actions for Indian and Malaysian Stock Market

The study related to a new and very powerful stock, index and commodities trading strategy based on machine learning with Moving Average (MA), Stochastic Relative Strength Index (SRSI) and Price Volume (PV) analysis to generate three types of financial market or stock trading signals such as buy, sell and no trade. Moving averages and moving average crossover are widely used to smooth price data and identify trends, whereas Stochastic RSI is a powerful oscillator that measures the relative strength of recent stock prices. Combination of multiple indicators in machine learning can improve strategies and provide more accurate decision for investors and traders which generate financial worth. This model is very much useful for Indian and Islamic stock markets.

Bidding Strategy for Wind and Thermal Power Joint Participation in the Electricity Spot Market Considering Uncertainty

As the proportion of new energy sources, such as wind power, in the electricity system rapidly increases, their participation in spot market competition has become an inevitable trend. However, the uncertainty of clearing price and wind power output will lead to bidding deviation and bring revenue risks. In response to this, a bidding strategy is proposed for wind farms to participate in the spot market jointly with carbon capture power plants (CCPP) that have flexible regulation capabilities. First, a two-stage decision model is constructed in the day-ahead market and real-time balancing market. Under the joint bidding mode, CCPP can help alleviate wind power output deviations, thereby reducing real-time imbalanced power settlement. On this basis, a tiered carbon trading mechanism is introduced to optimize day-ahead bidding, aiming at maximizing revenue in both the electricity spot market and carbon trading market. Secondly, conditional value at risk (CVaR) is introduced to quantitatively assess the risks posed by uncertainties in the two-stage decision model, and the risk aversion coefficient is used to represent the decision-maker’s risk preference, providing corresponding strategies. The model is transformed into a mixed-integer linear programming model using piecewise linearization and McCormick enveloping. Finally, the effectiveness of the proposed model and methods is verified through numerical examples.

ANALISIS FAKTOR–FAKTOR YANG MEMPENGARUHI FOREIGN DIRECT INVESTMENT DI NEGARA BERKEMBANG KAWASAN ASIA

Foreign Direct Investment (FDI) holds a crucial role, benefing not only the investor's home country but also contributing to the prospery of the host nations, especially the developing countries in the Asian region, which stand as the largest recipients of global FDI. This research aims to pinpoint the factors influencing FDI inflows in Asian developing countries from 2012 to 2019. Employing panel data analysis techniques, the study reveals that market size, trade openness, and infrastructure significantly drive FDI inflows. Conversely, human capal and taxation are identified as hindering factors, while the perception of corruption does not notably impact FDI. By enhancing our comprehension of the dynamics shaping FDI trends in Asian developing nations, this research provides valuable insights for policymakers and stakeholders. serves as a guide for those seeking to create an environment conducive to foreign investment, facilating sustainable economic growth and development in the region.

The research of river basin ecological compensation based on water emissions trading mechanism.

By integrating the successful case of the European Union emissions trading system, this study proposes a water emissions trading system, a novel method of reducing water pollution. Assuming that upstream governments allocate initial quotas to upstream businesses as the compensation standard, this approach defines the foundational principles of market trading mechanisms and establishes a robust watershed ecological compensation model to address challenges in water pollution prevention. To be specific, the government establishes a reasonable initial quota for upstream enterprises, which can be used to limit the emissions of upstream pollution. When enterprises exceed their allocated emissions quota, they face financial penalties. Conversely, these emissions rights can be transformed into profitable assets by participating in the trading market as a form of ecological compensation. Numerical simulations demonstrate that various pollutant emissions from upstream businesses will have various effects on the profits of other businesses. Businesses in the upstream region received reimbursement from the assigned emission rights through the market mechanism, demonstrating that ecological compensation for the watershed can be achieved through the market mechanism. This novel market trading system aims at controlling emissions management from the perspectives of individual enterprises and ultimately optimizing the aquatic environment.

Analyzing the influence of web search behavior on electricity market price: a case study of Japan electric power exchange

The Japan Electric Power Exchange (JEPX) has introduced a feed-in premium to promote the trading of renewable energy electricity in the market; thus, the exchange has become increasingly important for RE companies to maintain profitability in market trading. However, electricity prices are not only affected by directly measurable factors such as electricity demand, fuel prices, and weather but also by corporate bidding strategies, social conditions, and other human behaviors, making it difficult to predict electricity prices. Given that electricity demand is related to human behavior, this study focuses on web search behavior and clarifies the relationship between keyword search volumes and electricity market prices in Japan. Correlation and vector autoregression analyses results show a moderately strong positive correlation between the logarithmic difference of the keyword search volume and that of the electricity price. In addition, we find that the logarithmic difference of the electricity price tends to increase when that of the keyword search volume on the previous day increases. These results suggest that search volumes of specific keywords can be effective explanatory variables for area price prediction models and can help identify signs of price spikes.

A Monte Carlo approach for capacity and delay analyses of multiple interacting airports in Istanbul metroplex

AbstractThe Istanbul metroplex airspace, home to Atatürk (LTBA), Sabiha Gökçen (LTFJ), and Istanbul (LTFM) international airports, is a critical hub for international travel, trade and commerce between Europe and Asia. The high air traffic volume and the proximity of multiple airports make air traffic management (ATM) a significant challenge. To better manage this complex air traffic, it is necessary to conduct detailed analyses of the capacities of these airports and surrounding airspace. In this study, Monte Carlo simulation is used to determine the ultimate and practical capacities of the airport and surrounding airspace and compare them to identify any differences or limitations. The traffic mix, runway occupancy time and traffic distribution at airspace entry points are randomised variables that directly impact airport and airspace capacities and delays. The study aims to determine the current capacities of the runways and routes in the metroplex airspace and project the future capacities with the addition of new facilities. The results demonstrated that the actual bottleneck could be experienced in airspace, rather than runways, which was the focus of the previous literature. Thus, this study will provide valuable insights for stakeholders in the aviation industry to effectively manage air traffic in the metroplex airspace and meet the growing demand.

Exploring the Relationship Between Google Trends and Cryptocurrency Metrics

Abstract Bitcoin and Ethereum are the two largest cryptocurrencies in the world by market capitalization and trading volume and the most popular despite high price fluctuations. This paper analyzes the relationship between Bitcoin and Ethereum metrics and the internet search interest on cryptocurrencies. As the literature shows, Google searches signal investor attention and Google Trends has proven useful for nowcasting economic and financial indicators. We aim to find the impact of Google Trends on Bitcoin and Ethereum prices, trading volumes and market capitalization since 2015 and discuss the potential correlations and patterns that may exist between these metrics and Google search interest. Through correlation and time-series analysis, we provide insights into the dynamics of this relationship and its implications for understanding cryptocurrency market behavior. The interest in cryptocurrencies tracked by Google Trends is a good indicator of measuring the social interest in the cryptocurrency market that drives a price movement. On the other hand, the price fluctuations of Bitcoin and Ethereum generate media and social attention and increase the interest in these cryptocurrencies. We also observe a positive effect of Google Trends values on trading volumes. The findings could help investors to understand the cryptocurrencies dynamics and build their trading strategies and could be of special interest to policymakers.

Can call auction reduce closing price manipulation in the stock market?

ABSTRACT This paper tests whether the new trading mechanism reduces closing price manipulation in the Chinese stock market. The introduction of the closing call auction on the Shanghai Stock Exchange on 20 August 2018 can be considered a quasi-natural experiment. Using data from 2017 to 2018 for all companies listed on the main board of the Shanghai and Shenzhen Stock Exchanges, we provide robust evidence that the implementation of call auction on the Shanghai Stock Exchange can effectively reduce closing price manipulation in stock market. We further investigate the impact of various factors, including firm industry, ownership structure, secondary market trading, equity structure, and financial structure, on the effectiveness of call auction in mitigating closing price manipulation. Moreover, the mechanism study indicates that the introduction of closing call auction would improve the operation efficiency and information efficiency of stock market, thus reducing the closing price manipulation. Specifically, our results reveal that the closing call auction policy is effective in reducing manipulation and provides theoretical support for stock market institutional construction.

Perceived Behavioral Factors and Individual Investor Stock Market Investment Decision: Multigroup Analysis and Major Stock Markets Perspectives

The study aims to examine the impact of various behavioral biases such are overconfidence, representativeness, availability, anchoring and herding, and their effects on individual investment decisions in the case-developed country context of China. To achieve this, data was meticulously gathered from 362 participants active in the Shanghai stock market. Employing advanced analytical tools, particularly the Smart PLS 3.3.2 software and structural equation modelling (SEM), this study rigorously scrutinized the intricate relationships between behavioral biases and investment decisions. The findings of this study notably reveal that all examined behavioral biases exert a significant positive impact on investment decisions within the Anxin, Haitong, Shanxi, and China Galaxy stock markets. Remarkably, no substantial disparities in the effects of these biases on stock market trading were observed among these markets. Importantly, these findings bear exceptional significance within the context of a developed country like China. The implications extend to a wide spectrum of stakeholders, including government entities, regulatory bodies, practitioners, the academic community, industry professionals, and researchers. Regulatory authorities can leverage these insights to refine their strategies, practitioners can fine-tune their investment advisory approaches, and academia and researchers can build upon these findings to deepen the understanding of behavioral finance in the realm of stock market investments.

EXCHANGE RATE REGIMES AND ECONOMIC POLICIES: AN INDIAN PERSPECTIVE

This research paper provides a comprehensive analysis of exchange rate regimes (ExRRs) and their implications for economic policies particularly for the Indian economy. The study investigates the relationship between different ExRRs, including fixed, floating, and managed float systems, and their impact on macroeconomic policies which are drivers of economic growth. We have recognised four different regimes for the Indian rupee on the basis of level of flexibility of the exchange rate. In India, before liberalisation, fixed exchange rate system was followed but after economic liberalisation of early 1990s, the Reserve Bank of India (RBI) started intervening in the currency market to regulate the exchange rate. The exchange rate was made comparatively more flexible since the global financial crisis of 2008. After 2013,the exchange rate was efficiently and regularly managed by adopting the currency market intervention methhod. The RBI has acted in an asymmetric manner to reply to the EMP. When there was pressure to appreciate, the RBI acted by buying the foreign exchange reserves whereas rupee depreciation was adopted in case of vice-versa. The present study discusses the broader implications of ExRRs and economic policies for global economic governance, financial market stability, trade and investment flows, policy innovation, and public perception. It provides valuable insights for policymakers, central banks (CBs), financial institutions, and researchers, informing policy formulation processes in the dynamic global economic landscape.

Commercial Corridor Development Strategy through the Application of the Walkable Commercial Strip Concept in Urban Area of Jember City

Walkability is an essential concept to consider when planning a sustainable city. This study aims to determine the walkability development strategy of the Jember City commercial corridors urban area based on people's and experts' perceptions of the Walkable Commercial Strip concept. The study was conducted in the urban area of Jember City Golden Triangle. The methods of analysis used in this study are ordinal logistic regression and AHP. Based on people's perceptions, the concepts that have the highest odds of influencing the first corridor's walkability level are the ones related to the available amenities variable, while the concept that has the highest odds of influencing the second and the third corridors' walkability level is the concept that is related to the walking path modal conflict variable. The order in which corridors have the highest development priority starts with the first corridor, Gajah Mada - Sultan Agung Street, followed by the second corridor, Ahmad Yani Street, and ends with the third corridor, Trunojoyo Street – HOS Cokroaminoto Street. The walkability development strategy for the urban area of Jember City commercial corridors is to start the order of development according to the order of priority and apply the development concepts that have the highest opportunity to influence the walkability level of each corridor based on people's perception.

CRYPTOCURRENCY MARKET DYNAMICS: TRENDS, RISK AND REGULATORY CHALLENGES

The cryptocurrency market is a rapidly evolving landscape, characterized by its innovative nature and potential for significant economic disruption. This abstract delves into the intricate dynamics of the cryptocurrency market, focusing on the latest trends, inherent risks, and the burgeoning regulatory challenges that shape its future. Recent years have witnessed a surge in cryptocurrency adoption, with digital assets becoming increasingly mainstream. But there have been risks associated with this increase as well. One distinguishing characteristic of the market is still its volatility, which is fueled by mood in the market and speculative trading. Offers particular risks as well, such as worries about security and the possibility of illegal activity. Global regulatory organizations are struggling to provide comprehensive frameworks while encouraging creativity. The SEC’s recent actions against high-profile entities for offering unregistered securities highlight the intensified scrutiny within the sector. Moreover, policy adjustments by major exchanges, such as Hash Key Exchange’s halt on transactions with Binance, reflect the complex interplay between market operations and regulatory compliance. This abstract emphasizes the necessity of a well-rounded strategy that protects investors without impeding the technological breakthroughs that cryptocurrencies offer. As participants in navigating the cryptocurrency ecosystem effectively.

To examine the impact of canal irrigation systems on agricultural productivity and rural livelihoods in Sikh-ruled Punjab.

An examination of the effect that canal irrigation systems have had on agricultural output and rural life in Punjab, which is dominated by the Sikhs, finds that these systems have had a transformational influence on the socio-economic landscape of the province. During the time when the Sikhs were in power, and notably during the reign of Maharaja Ranjit Singh, large canal networks were constructed. These networks considerably increased agricultural production and contributed to the expansion of the economy. Through the provision of a consistent water supply, these irrigation systems made it possible to cultivate crops throughout the whole year, which resulted in increased agricultural yields and variety. The installation of canal irrigation systems in Punjab resulted in significant alterations to the region's socioeconomic landscape. As a result of increased agricultural productivity, not only was food security assured, but excess produce was also made available for commerce, which contributed to the improvement of regional economy. Economic activities and the creation of revenue for rural populations were further strengthened as a result of the availability of water for irrigation, which encouraged the growing of cash crops like as cotton and sugarcane. The canal networks were crucial in the transformation of rural life by being responsible for the creation of job possibilities in agriculture and other related industries. Enhanced agricultural output led to an increase in population growth in canal-irrigated regions, which in turn led to the establishment of new communities and the construction of new infrastructure. This demographic transition also made it easier for market towns and trade centres to come into existence, which in turn assisted in the development of commercial activity and regional integration. During the time when the Sikhs ruled Punjab, the building of canal irrigation systems had a complex influence, including the enhancement of agricultural output, the stimulation of economic expansion, and the transformation of rural life circumstances. These improvements created the groundwork for the agricultural success and economic resilience that Punjab would experience in the decades that followed from that point on.

통화옵션과 국채선물이 원달러환율에 미치는 영향

In this study, the impact of currency options(volatility) and KTB futures prices on the USD/KRW exchange rate was divided into before and after COVID-19 and a comparative analysis was conducted using cross-sectional regression analysis and VECM. The analysis results are as follows. First, looking at the results of the regression analysis, the currency option market showed that only the one-year volatility of the currency option affected the USD/KRW exchange rate in all periods. However, both 3-year and 10-year KTB futures had no significant impact before COVID-19, but appeared to have a statistically significant impact on the exchange rate starting after COVID-19. Second, cointegration exists in all time series before and after COVID-19, and in particular, it can be seen that the cointegration correlation is stronger after COVID-19 than before. Third, the results of the VECM analysis showed that the influence of KTB futures had no significance before COVID-19, but became significant after COVID-19. Fourth, the results of the shock response analysis showed that the impact of shocks in the options market and KTB futures market on the USD/KRW exchange rate was greater after COVID-19 than before and had a long lasting effect. Fifth, the results of the variance decomposition of forecast errors for the USD/KRW exchange rate also showed that the influence on KTB futures increased more after COVID-19 than before. Understanding foreign exchange is very important not only for exports and imports, but also for international trade and global economic activities. In the future, we hope that more in-depth research on the foreign exchange market and international trade will continue.

Operational decisions of photovoltaic closed-loop supply chains with industrial distributed photovoltaic subsidy policy in China

Photovoltaic (PV) generation, as a clean and renewable energy technology, aligns with the global needs for energy transition and sustainable development. Due to its industrial distributed PV subsidy support policy, China has witnessed rapid growth in distributed PV industrial projects, leading to the formation of a mature market trading mechanism. This paper, focusing on China’s industrial distributed PV and its user, aims to explore how the PV system manufacturer (PSM) and PV system service provider (PSSP) can optimize the combination of “recycling mode & power structure” to simultaneously achieve multiple performance improvements, including those in economy, society, and environment (ESS) in the photovoltaic closed-loop supply chain (PV-CLSC), in consideration of the government’s PV subsidy policy. Therefore, by using three game-theoretical approaches including Nash game existed between the PSM and the PSSP under equal power and the Stackelberg game respectively led by PSM and PSSP, the optimal decisions of the PSM and PSSP, and the effective government subsidies under different combinations are obtained. Conclusions show that: To achieve individual optimal economic performance, both PSM and PSSP, as recyclers, invariably prefer a dominant position and choose to conduct recycling activities independently. For social welfare and subsidy efficiency, the government consistently tends to choose the PSM recycling mode in which the PSM and PSSP are expected to be in an equal power structure. Both in the PSM recycling and PSSP recycling modes, the government subsidy is smaller when two members are under the equal position than that respective under the dominant position, and in the latter scenario, the one with the advantage can mainly obtain the difference in the increased government subsidy.

Indirect effects of trading restrictions

Stock market trading restrictions affect prices and liquidity directly through constraints on investors' transactions and indirectly by altering the information environment. We isolate this indirect effect by analyzing how stock market restrictions affect corporate bond yields. Exploiting the staggered reductions of trading restrictions in the Chinese stock market as a quasi-natural experiment, we document that the easing of trading restrictions on a firm's stock decreases its corporate bond spreads. This effect is stronger for firms with less transparency or lower credit ratings. Our evidence suggests that the effect is likely due to improved stock price informativeness.

Невзаимозаменяемые токены (NFT): технология, экосистема и рынок активов

The article considers non- fungible tokens as one of the types of digital financial assets. The purpose of the article is to study the modern NFT ecosystem and analyze the parameters of the NFT market. The indicators published in the analytical reports of the NFTGO consulting company, as well as scientific publications, were used. The definitions of the term "non- fungible token" are summarized, the criterion for classifying NFT objects is formulated; the participants of the NFT market are considered, the distinctive features of this market are highlighted. Based on the results of a quantitative analysis of the indicators of market capitalization and trading volume, conclusions were drawn about the NFT market in 2022. The elements of the NFT ecosystem are characterized, among which the development of NFT finance is the most promising.

Dual toeholds regulated CRISPR-Cas12a sensing platform for ApoE single nucleotide polymorphisms genotyping

Single nucleotide polymorphisms (SNPs) are closely associated with many biological processes, including genetic disease, tumorigenesis, and drug metabolism. Accurate and efficient SNP determination has been proved pivotal in pharmacogenomics and diagnostics. Herein, a universal and high-fidelity genotyping platform is established based on the dual toeholds regulated Cas12a sensing methodology. Different from the conventional single stranded or double stranded activation mode, the dual toeholds regulated mode overcomes protospacer adjacent motif (PAM) limitation via cascade toehold mediated strand displacement reaction, which is highly universal and ultra-specific. To enhance the sensitivity for biological samples analysis, a modified isothermal recombinant polymerase amplification (RPA) strategy is developed via utilizing deoxythymidine substituted primer and uracil-DNA glycosylase (UDG) treatment, designated as RPA-UDG. The dsDNA products containing single stranded toehold domain generated in the RPA-UDG allow further incorporation with dual toeholds regulated Cas12a platform for high-fidelity human sample genotyping. We discriminate all the single-nucleotide polymorphisms of ApoE gene at rs429358 and rs7412 loci with human buccal swab samples with 100% accuracy. Furthermore, we engineer visual readout of genotyping results by exploiting commercial lateral flow strips, which opens new possibilities for field deployable implementation.

Can the Difference of the Transfer Trice of Industrial Land "Bidding, Auctions and Listings" Promote the Transformation and Upgrading of Regional Industries?

The purpose of this study is to explore the impact of the difference in the transfer price of industrial land on the regional industrial transformation and upgrading under the "bid and auction" system. Research methods: panel data fixed effect model. Research results: Improving the differentiation of industrial land transfer price is conducive to regional industrial transformation and upgrading, and this conclusion has passed a variety of robustness tests. Research conclusions: First, formulate and improve the promotion of industrial land transfer price differentiation strategy. The second is to establish and improve the enterprise entry and exit mechanism to improve the efficiency of industrial land resource allocation. The third is to further improve the secondary market trading system of industrial land, and actively explore the circulation mechanism of stock industrial land to ensure the reasonable flow and efficient use of industrial land resources.

The Possible Introduction of Digital Currency Exchange in Bangladesh: A Legal Analysis

Digital currency is the most interesting and demanding currency medium over the world. Digital currency means crypto currency and which means Bitcoin, NFT Ethereum, etc. Day by day those digital currencies are increasing in the crypto market. In Bangladesh this currency medium is not approved yet. But this digital currency can change the whole view of Bangladesh's perspective if it’s approved by the government. This digital currency can play an influential role in e-commerce and business and can change massively for the economy's growth. The acceptance of digital currency in Bangladesh is now a matter because this is an important issue in this globalized world. All the western countries approve of the digital currency dealing system which is binding by their law and they trust in their highly configured block chain security for this. The Russia-Ukraine war makes it more important to approve it because many economic issues and crises over the world arise. We know digital currency has no central control in terms of security. That is why the regulatory framework is very much necessary before approval. There is a large scope for digital currency in Bangladesh for use in different fields. Especially in e-commerce business or any kind of trading in the international market this digital currency can be the best transaction system. Right now, in Bangladesh, there is no specific law for digital currency exchange. But it should be approved to improve the economy in this globalized world. This paper tries to find out why this digital currency approval is important for Bangladesh and how it’s security can be ensured through law.