Rational Traders Research Articles

Global wheat planting suitability under the 1.5°C and 2°C warming targets.

The potential distribution of crops will be impacted by climate change, but there is limited research on potential wheat distributions under specific global warming targets. This study employed the Maxent model to predict the potential distribution of wheat under the 1.5°C and 2°C warming targets based on data from the Inter-Sectoral Impact Model Intercomparison Project (ISI-MIP) multimodel ensemble, and the effect of global warming on wheat planting suitability was analyzed. Our results indicated global warming would significantly change wheat planting suitability. Over half of the areas experienced changes in wheat planting suitability under two warming targets, and the effect became more pronounced with increasing temperatures. Additionally, global warming might promote wheat planting in more regions. The area with an increase in wheat planting suitability was observed to be 9% higher than those experiencing a decrease on average. Moreover, global warming could exacerbate the disparity between global wheat supply and demand in countries/regions. Traditional wheat-producing countries/regions are poised to benefit from the warming effects of climate change, while less developed and wheat import-dependent countries/regions may face greater challenges in achieving wheat self-sufficiency. To address this potential challenge, the promotion and inter-regional exchange of agronomic technologies, and the development of more rational trade standards are urgently needed. Since socioeconomic factors have a significant impact on wheat cultivation, further investigation is required to determine how the wheat planting distribution may change in the future under the combined impact of climate change, supply-demand relationship, and policy.

ДІЯЛЬНІСТЬ ПІДПРИЄМСТВ ХАРЧОВОЇ ПРОМИСЛОВОСТІ В УМОВАХ ВІЙНИ ТА ПЕРСПЕКТИВИ ЇХ ПОДАЛЬШОГО ФУНКЦІОНУВАННЯ

The article substantiates that the food industry provides the vital needs of the population in food products, the social stability of society, is a source of foreign exchange earnings, given the food potential of Ukraine. The main factors that led food industry enterprises to a crisis economic state in the conditions of military operations are summarized: military aggression on the territory of Ukraine, which caused the loss or damage of production facilities, and therefore economic ties, lack of workers, insecurity of material resources, destruction of logistics; decrease in demand for food industry products; an increase in the cost of production and a decrease in the profit of enterprises; lack of investment sources and stoppage of investment projects; disruption of logistics chains; the destruction of the transport infrastructure in conditions of extreme importance of the effective functioning of the transport market and the formation of a rational trade. It is proposed to develop a set of measures at the level of both government structures and enterprises, aimed at improving the economic conditions of business entities and the final results of activities: state stimulation of industrial in-depth processing of agricultural raw materials and revitalization of the development of processing enterprises; facilitating access procedures for national producers to foreign food markets; creation of investment platforms with convincing motivational components; softening of the terms of credit provision of investment activities of enterprises; development of lending programs under favorable conditions for the rapid development of enterprises; formation of alternative sources of replenishment of electricity for industrial production in case of urgent need, including opportunities for bilateral international cooperation; formation of innovation incubators; diversification of production and orientation of production, including to meet the needs of the Armed Forces and territorial defense; introduction of world experience in ensuring conditions and restoration of ecological production; financial and insurance support of entrepreneurial initiatives.

Feedback Trading, Investor Sentiment and the Volatility Puzzle: An Infinite Theoretical Framework

This article constructs a behavioral financial model that provides feedback on both historical prices and company fundamentals without considering asset liquidation to discuss the long-term impact of investor sentiment and feedback trading on asset price fluctuations. The research conclusion shows that the abnormal volatility of asset prices is captured by the value effect, the cognitive bias effect, the sentiment shock effect, and the trading inductive effect. The value effect is the volatility of asset prices that is completely determined by fundamental factors; the higher the degree of cyclical fluctuations in fundamental factors, the higher the volatility of prices. The bias effect refers to investors’ misreading of basic information and trends in asset prices; the greater the instability of emotional shocks, the greater the abnormal volatility of asset prices. The trading inductive effect is also called the Keynes effect, which reflects the role played by rational traders.

A systematic literature review and bibliometric analysis of noise trading

PurposeThis comprehensive study aims to take a punctilious approach intended to present qualitative and quantitative knowledge on the emerging concept of noise trading and identify the emerging themes associated with noise trading.Design/methodology/approachThis study combines bibliometric and content analysis to review 350 publications from top-ranked journals published from 1986 to 2020.FindingsThe bibliometric and content analysis identified three major themes: the impact of noise traders on the functioning of the stock market, traits of noise traders and different proxies used to measure the impact of noise trading.Research limitations/implicationsThis study undertakes research papers related to the field of finance, published in peer-reviewed journals and that too in the English language.Practical implicationsThis study shall accommodate rational traders, portfolio consultants and other investors to gain deeper insights into the functioning of noise traders. This will further help them to formulate their trading/investment strategies accordingly.Originality/valueThe successful combination of the bibliometric and content analysis revealed major gaps in the literature and provided future research directions.

Research on the Three-Stage Trading Strategy of Gold and Bitcoin Using Technical Indicators and A LSTM Model

In recent years, in pursuit of higher returns, people began to try the combination of bitcoin and gold. This study explored how to use the current and past prices of gold and bitcoin to get the best investment strategies for the next day to get the maximum return. The obtained historical price data of gold and bitcoin from 2016 to 2021 are divided into three stages according to the time axis, namely, stage Ⅰ (1st day-300th day), stage Ⅱ (300th day-400th day) and stage III (400th day-1825th day). Different methods are used for each stage to determine the trading strategy. In stage I, a comprehensive index is constructed by using four technical indexes closely related to the formulation of daily strategies in the financial market, such as moving average convergence and divergence, deviation rate, stochastic index and detrended price oscillator, and the trading strategy is determined by using this comprehensive index. In stage II, the four technical indicators and product prices in stage I are used as training sets, and the daily trading strategy is given by using the decision tree classification model. In the third stage, the long-term and short-term memory neural network is used to develop the future price prediction model of gold and bitcoin, and the trading strategies of gold, bitcoin and cash asset portfolios are formulated according to the dynamic optimization results of different types of traders' risk tolerance. The results show that during the five years from September 11, 2016 to September 10, 2021, the whole strategy created a net profit of $170,381 for aggressive traders and $7,694 for rational traders. After verification, our strategy is effective and robust, and its volatility is relatively small. The research provides theoretical guidance for investors on how to choose portfolios and trade to get the maximum return.

Optimal social welfare: A many-to-many data transaction mechanism based on double auctions

With the development of Big Data and the Internet of Things (IoT), the data value is more significant in both academia and industry. Trading can achieve maximal data value and prepare data for smart city services. Due to data's unique characteristics, such as dispersion, heterogeneity and distributed storage, an unbiased platform is necessary for the data trading market with rational trading entities. Meanwhile, there are multiple buyers and sellers in a practical data trading market, and this makes it challenging to maximize social welfare. To solve these problems, this paper proposes a Social-Welfare-Oriented Many-to-Many Trading Mechanism (SOMTM), which integrates three entities, a trading process and an algorithm named Many-to-Many Trading Algorithm (MMTA). Based on the market scale, market dominated-side and market fixed-side, simulations verify the convergency, economic properties and efficiency of SOMTM.

The profitability effect: Insight from a dynamic perspective

This study dynamically captures the trend changes in a firm's profitability over a period and explores the impact of the firm's profitability growth and acceleration on the cross-section of stock returns. The empirical evidence reveals a significantly positive dynamic profitability growth and an acceleration premium in the Chinese stock market, which are still robust in the out-of-sample test. The significantly positive predictive information contained in the dynamic profitability (DP) is not subsumed under the profitability level at a certain point in time. Moreover, the first-order DP growth has the strongest pricing power among the profitability strategies. We can obtain a higher excess return while simultaneously combining the dynamic and static profitability factors. In addition, this study provides ample evidence for the source of profitability anomalies, based on the behavioral finance framework. The findings under this framework indicate the substantial contribution of irrational mispricing, rather than rational pricing based on risk compensation or Q-theory, to the premium. This paper comprehensively explores the DP anomalies (fundamental characteristics of a firm), thus providing a novel perspective to better understand the pricing mechanisms of the emerging stock market and cultivate investors' philosophy on rational trading.

Investment Performance: Emotional Beasts are Dragging into the Darkness of the Castle

The study documented the way forwards to sustain investment performance, and answered that why emotional beasts (e.g. small investors) are irrational in managing their investment performance, in Pakistan stock exchange (PSX). For this, reasons and challenges are identified to give solutions by testing the intervening link of non-cognitive individual differences (NCIDs) of small investors between investor’s personality traits and investment performance. Using multi-stage cluster sampling, the responses of small investors (n = 248) were taken and structural equation modelling (SEM) was used to draw an inference between constructs. Our result traced mediating role of NCIDs between investor’s personality traits and investment performance. The findings extended the notion that small investors are the emotional investors and emotional disparities in the behavior of small investors are making PSX market conditions as slippery. In return to these inconsistencies, PSX is generating lower rate of return and a weak form of investment efficiency, on regular basis. Therefore, this is important to review and revise PSX’ investment mechanism and offer a sustainable and viable business plan for effective PROI acquisition, enhancing investor base by listing the maximum number of new companies, rigorously teaching and training small investors and updating databases accordingly. Our recommendations would be helpful to uplift the confidence in small investors’, depth in PSX asset base, market efficiency and rational trading. By achieving these proponents in PSX highly guarantees a strong investment performance and to turn the horde of such emotional beasts into a team of rational investors.

The impact of trading behavioral biases on market liquidity under different volatility levels: Evidence from the Chinese commodity futures market

AbstractThis paper investigates a sample of 15 Chinese commodity futures to examine the impact of trading behavioral biases on market liquidity under different volatility levels. We construct a measure of shocks driven by news on market fundamentals to capture rational trading behavior and a measure of irrational trading behavior from excess skewness, excess kurtosis, and excess turnover. We find that herding causes deterioration in liquidity mainly by affecting order imbalance, whereas overtrading improves market liquidity by increasing market depth. The disposition effect is identified only when volatility is higher, after a distinction is made between up and down markets.

Location optimization of a competitive distribution center for urban cold chain logistics in terms of low-carbon emissions

Owing to the fast economic and social development in Wuhan, the demand for cold chain logistics is increasing rapidly. Currently, the scale of the existing distribution centers cannot fully meet this demand, so building new ones would seem necessary. Research rarely considers consumer choice from the perspective of competition between new and existing cold chain distribution centers, and the low-carbon concept is rarely considered when a competitive site is selected. This paper therefore puts forward a model to assist the decision-making process regarding the choice of location where cold chain logistics facilities might be sited. Based on a bi-level programming method, this model is constructed where the upper level of government aims to determine an optimal location and scale for a cold chain distribution center as well as a rational trading policy regarding carbon emissions to minimize the total social cost of the whole logistics system. The lower level adopts the demand user equilibrium model, which considers the demands of logistics users when choosing between new and existing cold chain distribution centers, so as to minimize the cost incurred by each logistics user. We use the cloud particle swarm optimization algorithm to solve the model and decide a suitable location for a new center in Wuhan, the principal city in the Hubei Province, in China. The study reveals that: (1) The high demand is equivalent to the high number of new distribution centers; (2) The high attractiveness of these centers is equal to their high total scale; (3) Changes in carbon emissions trading prices have an impact on the scale, total carbon emissions, and total social cost of new cold chain distribution centers; (4) The carbon emissions quota policy has an impact on the scale of the location chosen for a new cold chain distribution center, total carbon emissions, and total social costs. This article provides a scientific basis regarding decisions concerning the location of new cold chain distribution centers by the government, and provides some ideas for energy conservation improvement and carbon emissions reduction by the whole society.

Inflation and Risky Investments

The paper uses a Walrasian two-period financial market model with informed and uninformed constant absolute risk averse (CARA) rational investors and noise traders. The investors allocate their initial wealth between risky assets and risk-free fiat money. The analysis concentrates on the effects of decreasing value of money, or inflation, on the rational investors’ behavior and the asset market. The main findings are the following: Inflation does not affect the informed investors’ prediction coefficient but makes that of the uninformed investors diminish. Inflation does not affect rational investors’ risk but makes the asset price more sensitive to fundament-based and sentiment-based shocks. Inflation changes the market price of the risky asset rise; while it has no effects on the informed investors’ demand of the risky asset, it does affect the uninformed investors’ demand. Finally, inflation makes the asset market more volatile.

Efficiency and Revenue in Linear-Quadratic Double Auctions

We study uniform-price double auctions augmented with a class of subsidy schemes. Using these subsidies, any profile of linear demand schedules can be implemented as an equilibrium outcome. By revenue equivalence, all other mechanisms which implement linear auction equilibria are essentially equivalent to some subsidy scheme in our class. We show that, under a linear dependency condition on primitives, fully efficient, budget balanced, and individually rational trade is possible. Thus, the welfare loss from equilibria in uniform-price auctions without subsidies is a non-fundamental distortion, which can be fixed with better mechanism design. However, we show that monopolist trading platforms have incentives to reduce allocative efficiency to increase revenue, even as the number of traders becomes large.

Object reachability via swaps under strict and weak preferences

The \textsc{Housing Market} problem is a widely studied resource allocation problem. In this problem, each agent can only receive a single object and has preferences over all objects. Starting from an initial endowment, we want to reach a certain assignment via a sequence of rational trades. We first consider whether an object is reachable for a given agent under a social network, where a trade between two agents is allowed if they are neighbors in the network and no participant has a deficit from the trade. Assume that the preferences of the agents are strict (no tie among objects is allowed). This problem is polynomially solvable in a star-network and NP-complete in a tree-network. It is left as a challenging open problem whether the problem is polynomially solvable when the network is a path. We answer this open problem positively by giving a polynomial-time algorithm. Then we show that when the preferences of the agents are weak (ties among objects are allowed), the problem becomes NP-hard even when the network is a path. In addition, we consider the computational complexity of finding different optimal assignments for the problem under the network being a path or a star.

Prospect Theory and Currency Returns: Empirical Evidence

We empirically investigate the role of prospect theory in the foreign exchange market. Using the historical distribution of exchange rate changes, we construct a currency-level measure of prospect theory value and find that it negatively forecasts future currency excess returns. High prospect theory value currencies significantly underperform low prospect theory value currencies. The predictability is higher when arbitrage is limited and during periods of excess speculative demand of ir- rational traders. These findings are consistent with the hypothesis that investors mentally represent currencies by their historical distributions or charts and evaluate the distribution in the way described by prospect theory.

A Behavioral Interpretation of the Nav Discount Puzzle in Listed Real Estate Companies

Executive Summary The net asset value (NAV) discount is a long standing puzzle in the listed real estate context. In this paper, we extend the literature's rational and noise trader explanations by exploring the influence of specific irrational behaviors. Based on behavioral biases identified in the stock and real estate markets, we hypothesize the existence of a relation between lagged NAV growth and the NAV discount. The findings provide initial evidence of trend-chasing behavior between the dual real estate markets. The results have broader implications for the perception of the relation between public and private real estate markets.

Imposing tariff or implementing subsidy?

PurposeIn the context of the trade war in full swing, the global supply chain systems have experienced a serious shock and become very vulnerable. The purpose of this paper is to explore the intertwining effects between the export-supporting subsidy policy and the import-deterring tariff policy to develop better insights for trade policy-making under the intra-industry-trade (IIT) conflicts. The research results may provide the trade policy makers and international businesses with better insights in making rational trade policy and business decisions.Design/methodology/approachTwo-stage game-/bargaining-theoretical models for the dual competing international supply chains with a unilateral/bilateral tariff imposing or subsidy implementing under six different scenarios of IIT conflict are developed, analyzed and compared. On this basis, the corresponding numerical analyses are conducted to assess the impact of the tariff and subsidy policies and derive the trade policy implications and business insights.FindingsThe research results indicate that: (1) the bilateral subsidy implementing from both governments is the best policy for all stakeholders in two countries, which would lead to the highest profits, social welfare and consumer surplus than those of the other scenarios; (2) the bilateral tariff imposing of both governments is the worst policy for all stakeholders in two countries, which would lead to the lowest profits, social welfare and consumer surplus than those of the other scenarios; (3) the fair trade scenario without tariff imposing and subsidy implementing turns out to be the second-best trade policy for the governments. Under the World Trade Organization rule and fair-trade principles, the bilateral subsidy policy is not allowed in most of the cases. Thus, adopting a fair-trade policy may be the most appropriate trade policy for two trading countries.Originality/valueThe modeling approach developed for this study is original and innovative due to the following characteristics. First, based on three trade policy alternatives – fair trade, tariff imposing and subsidy implementing – of two generic governments under IIT conflict, nine different combinations of three policy alternatives are defined. Second, excluding the symmetrical combinations, six IIT conflict scenarios under various tariff/subsidy policy pairs ranging from no conflict to high conflict are assumed for two dual competing international supply chains. Third, a novel two-stage game-/bargaining-theoretical modeling approach is applied to investigate the optimal/equilibrium decisions regarding pricing, ordering quantity and their critical economic outcomes for all possible trade policy scenarios. Fourth, this study lays down a research foundation for the future trade conflict study using a game-theoretical modeling approach.

A Study on Application of the Behaviourial Finance in Investment Decisions

Financial markets are influenced by various factors but the most important factors is the reaction as well as perception of the people. Basically there are two discipline of financial market study i.e., Traditional finance and the new development called Behaviourial finance.Traditional finance foundation is truly based on efficient market concept&Behavioral finance argues that some financial phenomena can plausibly be understood using models in which some agents are not fully rational. The field has two building blocks: limits to arbitrage, which argues that it can be difficult for rational traders to undo the dislocations caused byless rational traders; and psychology, which catalogues the kinds of deviations from full rationality we might expect to see. We close by assessing progress in the field and speculating about its future course. In this paper an attempt has been made to highlight the shortcomings of the traditional finance theories as pointed out by behavioural finance supporters and also a discussion on the significance of behavioural finance. While conventional academic finance emphasizes theories such as modern portfolio theory and the efficient market hypothesis, the emerging field of behavioral finance investigates the psychological and sociological issues that impact the decision-making process of individuals, groups, and organizations. This paper will discuss some general principles of behavioral finance including the following: overconfidence, financial cognitive dissonance, the theory of regret, and prospect theory. In conclusion, the paper will provide strategies to assist individuals to resolve these “mental mistakes and errors” by recommending some important investment strategies for those who invest in stocks and mutual funds

Market Efficiency, the Cost of Capital, and Information Disclosure Quality

This paper explores the two-period noisy rational expectations claim in a model with short-horizon traders who have constant absolute risk aversion (CARA) preferences. A coherent framework is presented, showing how, when asset information is heterogeneous and includes both private and public signals, the precision of information disclosure reflects fundamentals, and liquidity trading in perfect competition. Under the noisy REE framework with unique linear expectations equilibrium in asset market, the results of model indicate that even in the presence of the Keynesian beauty contest influence, higher precision of public information disclosure still improves the efficiency level in financial market, and the cost of capital is positively related to the risk aversion of traders and the risky asset supply upon the perfectly competitive and information-related conditions. Meanwhile, if the market participants are sensitive to the public information disclosure, there is a crowding-out effect that decreases the incentives of agents to private information and thus narrowing the gap between rational traders.

Public News and Market Liquidity: Evidence from the CDS Market

This paper examines the effects of public news releases on the market liquidity in one of the most important OTC derivatives markets — the CDS market. We document that, at the time of news releases, the bid-ask spread is wider, the number of quotes is larger, and the number of dealers is greater. Earnings announcements have particularly strong effects on liquidity while news related to credit ratings has no significant effects. Moreover, the bid-ask spread only increases on news release days and reverts to normal levels several days after news releases. Finally, the effect of news on liquidity is stronger for negative, fundamental, and unscheduled news, and is more pronounced among firms with higher information asymmetry. Our findings are consistent with models of rational trade in Kim and Verrecchia (1994).

Bubbles and crashes: A laboratory experiment

Most lab experiments carried out on asset price bubbles have been based upon theoretical models that do not factor in a bubbling equilibrium. The aim of this paper is to propose a lab experiment which uses a model with bubbling equilibrium as its benchmark; to specify we used a modified version of the model built by Abreu and Brunnermeier (2003). In both models the asymmetries of information regarding the existence of the asset price bubbles induce rational traders to perpetuate the bubbles. In our experiment we found that human traders are, most of the time, risk averse, they suffer impatience and do not necessarily react appropriately to coordination messages (even though the presence of said messages affects their behavior) and sometimes they clearly behave irrationally. Last but not least, during the experiment we also found that the human traders could adapt their strategies to optimal equilibrium strategies, so long as these strategies were not too complex - but not all human traders have the same ability to execute this adaptation process.