Individual Trading Research Articles

Influence of Online Apps in Fostering Agri-Enterprise Development along the Agricultural Value Chain in Kenya

Influence of Online Apps in Fostering Agri-Enterprise Development along the Agricultural Value Chain in Kenya

An Examination of the Weekdays’ Anomaly in the Trading Behavior of Institutional Investors in the Post-Demonetization and GST Regime in India

This study analyzed the trading activities of foreign portfolio investors (FPIs) and Indian mutual funds (IMFs) across weekdays. The present study aimed to enrich the literature related to the efficient market hypothesis and day-of-the-week anomaly present in the trading behavior of FPIs and IMFs across weekdays. The study examined the daily purchasing, selling, and net investing activities of FPIs and IMFs in equity instruments of the Indian capital market for 3.1 years, beginning November 1, 2016 and ending November 30, 2019. During this period, the Indian capital markets adjusted to the up-and-down sentiments of market players in the context of demonetization and GST regimes. This study aimed to achieve two objectives, that is, examining the day-of-the-week effect on trading activities of FPIs and IMFs and comparing the trading patterns of FPIs and IMFs on individual trading days with the rest of the weekdays with the help of autoregressive dummy variable regression, ANOVA, and independent-sample t - test. It was empirically determined by the present study that there was a day-of-the-week effect present in the behaviors of both foreign and domestic institutional investors. Monday, Thursday, and Friday were ascertained to have the most significant impact on the trading activities of institutional investors. Hence, individual investors can avail the opportunities to reap extraordinary returns from the Indian capital markets by closely monitoring institutional investors’ trading activities.

Liability for Right Holders to Electronic Marks (E-Commerce) on the Commercialization of Individual Trade Actions in Electronic Business Transactions

The type of research used in this research is normative legal research. So, in fact, the principle of proportionality is an alternative solution for electronic brand rights holders (e-commerce), which provides legal protection based on the first to file principle system given to registered trademark rights holders who have good intentions, are preventive or repressive. On the other hand, it’s necessary to guarantee legal certainty to be able to provide accountability when there are ties or agreements in electronic business transactions in the field of trade and other trading businesses, so as to guarantee a sense of security and comfort in investing and doing business in the world of digitalization and e-commerce.

Novel Hybrid Stochastic-Robust Optimal Trading Strategy for a Demand Response Aggregator in the Wholesale Electricity Market

The close interaction between the electricity market and the end-users can assist the demand response (DR) aggregator in handling and managing various uncertain parameters simultaneously to reduce their effect on the aggregator's operation. As the DR aggregator's main responsibility is to aggregate the obtained DR from individual consumers and trade it into the wholesale market. Another responsibility of the aggregator is proposing the DR programs (DRPs) to the end-users. This article proposes a model to handle these uncertainties through the development of a novel hybrid stochastic-robust optimization approach that incorporates the uncertainties around wholesale market prices and the participation rate of consumers. The behavior of the consumers engaging in DRPs is addressed through stochastic programming. Additionally, the volatility of the electricity market prices is modeled through a robust optimization method. Two DRPs are considered in this model to include both time-based and incentive-based DRPs, i.e., time-of-use and incentive-based DR program to study three sectors of consumers, namely industrial, commercial, and residential consumers. An energy storage system is also assumed to be operated by the aggregator to maximize its profit. The proposed mixed-integer linear hybrid stochastic-robust model improves the evaluation of DR aggregator's scheduling for the probable worst-case scenario. Finally, to demonstrate the effectiveness of the proposed approach, the model is thoroughly simulated in a real case study.

V-Shaped Disposition Effect, Stock Prices, and Post-Earnings-Announcement Drift: Evidence from Korea

This study investigates the impact of the V-shaped disposition effect on asset prices in the Korean stock market, which is characterized by a high proportion of retail investors. By utilizing a specified dataset containing stock-level information on the trading activities of different types of investors, we find evidence to support the presence of V-shaped net selling propensity in the Korean stock market. In addition, we find that net selling pressure has a positive effect on the cross-section of subsequent stock returns, and this relationship appears only when accounting for individual trading. Furthermore, this net selling propensity of retail investors delays the incorporation of good news into stock price, while helps stock price reflect its bad news. We show that good (bad) news lead to positive (negative) drifts in stock prices following earnings announcements in the presence (paucity) of investors exhibiting the V-shaped disposition.

The Epps effect under alternative sampling schemes

Time and the choice of measurement time scales is fundamental to how we choose to represent information and data in finance. This choice implies both the units and the aggregation scales for the resulting statistical measurables used to describe a financial system. It also defines how we measure the relationship between different traded instruments. As we move from high-frequency time scales, when individual trade and quote events occur, to the mesoscales when correlations emerge in ways that can conform to various latent models; it remains unclear what choice of time and sampling rates are appropriate to faithfully capture system dynamics and asset correlations for decision making. The Epps effect is the key phenomenology that couples the emergence of correlations to the choice of sampling time scales. Here we consider and compare the Epps effect under different sampling schemes in order to contrast three choices of time: calendar time, volume time and trade time. Using a toy model based on a Hawkes process, we are able to achieve simulation results that conform well with empirical dynamics. Concretely, we find that the Epps effect is present under all three definitions of time and that correlations emerge faster under trade time compared to calendar time, whereas correlations emerge linearly under volume time.

Africa’s Trade with China and US: Has COVID-19 Changed the Trends of Trade?

Africa’s trade with China and the US is one of the international issues affecting development in the continent. This paper, therefore, examines the effects of COVID-19 on Africa’s trade with the two countries by investigating whether the pandemic has changed the trends of the trade. The article explores the responses of the individual trade of China and the US with Africa to their own shocks, without and with the pandemic, using the vector autoregressive (VAR) model and monthly data covering 1970m01 (January 1970) to 2020m07 (July 2020). The results show that China’s trade performs better while responding to a shock to America’s trade than America’s trade does while responding to a shock to China’s trade, without and with COVID-19. This finding suggests that China has a stronger trade footing in Africa and that COVID-19 had not changed the trends of Africa’s trade with China and America, even with the impact of the pandemic on China. China’s dominant trade status in Africa is probably due to the country’s large investment and aid in the continent. The key policy focus of Africa on trading with China and the US should therefore be how to achieve optimum trilateral trade thresholds in the face of potential trade-offs.

Ambiguity about volatility and investor behavior

We relate time-varying aggregate ambiguity about volatility (V-VSTOXX) to individual investor trading. We use the trading records of more than 100,000 individual investors from a large German online brokerage from March 2010 to December 2015. We find that an increase in ambiguity is associated with increased investor activity. It also leads to a reduction in risk-taking, which does not reverse over the following days. Ambiguity averse investors are more prone to ambiguity shocks. These results replicate when using the dispersion of professional forecasters as a long-term measure of ambiguity and are robust when controlling for newspaper- or market-based ambiguity measures.

Preparing for market disruption: circuit breakers and discretionary trading halts

Purpose This article provides a resource for traders and other market participants by providing an overview of certain automatic circuit breaker mechanisms and discretionary powers that the U.S. Securities and Exchange Commission (SEC), Financial Industry Regulatory Authority (FINRA) and the U.S. president, as applicable, can exercise to pause or stop the trading of individual securities or trading activities across exchanges during extreme market volatility, each of which can cause interruptions to trading activity. Design/methodology/approach This article surveys automatic and discretionary mechanisms to halt trading activity under extreme market conditions. In particular, the article examines automatic cross-market circuit breakers, limit up-limit down pauses, the alternative uptick rule, as well as discretionary authority to stop short selling of particular securities and to stop trading across exchanges. Findings The article concludes that market participants must be cognizant not only of automatic cross-market circuit breakers, but also several other forms of potential market disruptions that may occur due to increased market volatility during the COVID-19 pandemic and beyond. Originality/value By exploring various mechanisms that respond to market disruption, this article provides a valuable resource for traders and other market participants looking to identify and respond to potential interruptions to their trading activity.

Peer-to-peer energy trading of net-zero energy communities with renewable energy systems integrating hydrogen vehicle storage

This study presents peer energy trading management approaches in a net-zero energy community with fundamental units of university campus, commercial office and high-rise residential building groups as per actual energy consumption and simulation data. Hybrid solar photovoltaic and wind turbine systems are developed for power supply to the diversified community integrated with three hydrogen vehicle storage groups based on the TRNSYS platform. An individual peer energy trading price model is proposed for the diversified community to allocate an individual peer trading price to each building group according to its intrinsic energy characteristic and grid import price. The time-of-use peer trading management strategies are further developed for both uniform and individual energy trading price modes to improve the grid flexibility and economy. The study results indicate that the peer energy trading management in the individual trading price mode improves the renewable energy self-consumption ratio by 18.76% and load cover ratio by 11.23% for the net-zero energy community compared with the peer-to-grid trading. The time-of-use trading management in the individual trading price mode can reduce the net grid import energy by 8.93%, grid penalty cost by 142.87%, annual electricity cost by 14.54%, and equivalent carbon emissions by 8.93% (982.36 tCO2), respectively. This comprehensive feasibility study on the typical community with the proposed peer trading price model and management strategies provides significant guidance for renewable energy and hydrogen storage applications in large-scale communities within high-density urban contexts.

Longitudinal study of medical downgrades in the Royal Air Force

IntroductionAs the focus of the Royal Air Force (RAF) shifts from sustained to contingency operations and the number of personnel is reduced, the burden of retained, medically downgraded personnel may...

A New Deep Learning-Based Zero-Inflated Duration Model for Financial Data Irregularly Spaced in Time

In stock trading markets, trade duration (i. e., inter-arrival times of trades) usually exhibits high uncertainty and excessive zero values. To forecast conditional distribution of trade duration, this study proposes a hybrid model called “DL-ZIACD” for short, which addresses the problem of excessive zero values by a zero-inflated distribution. Meanwhile, dynamics of the distribution time-varying parameters are captured by a specially designed deep learning (DL) architecture in which the behavioral patterns of large traders and small individual traders are represented separately by different blocks. The proposed hybrid model takes advantage of the strong fitting ability of deep learning methods while allowing for providing a probabilistic output. This paper empirically applied the established model to a large-scale dataset, containing 9,900,000 transactions of the Chinese Shenzhen Stock Exchange 100 Index (SZSE 100) constituents. To the best of our knowledge, no previous studies have applied conditional duration models to a dataset of such a large scale. For both the central location forecasting and the extreme quantile forecasting, our proposed model exhibited significant superiority over the benchmark models, which indicates that our DL-ZIACD model can provide accurate forecasts in conditional duration distribution.

Individual investor attention to stock split and the disposition effect

PurposeThis paper investigates whether individual investors are attentive to stock splits and whether higher split ratios (stronger private information signals) reduce the disposition effect.Design/methodology/approachThis study employs stock split events and transaction data in the Indonesia Stock Exchange (IDX) from January 2004 to December 2017. The authors measure individual investors' attention using buy-initiated trades. To test the effect of split signal on disposition effect, the authors regress individual investors' sell-initiated trades on past stock returns.FindingsUnlike Birru (2015), the authors find that individual investors are attentive to stock splits, especially when stock split ratios are high. In turn, stock splits tend to weaken the disposition effect. The higher the stock split ratios, the weaker the disposition effect.Research limitations/implicationsThis study has a limitation in that the authors exclude all stock splits with dividend events around the split date. These stock splits cover 37% of all splits in Indonesia.Practical implicationsPractically, individual investors should look for stock-related information to reduce disposition bias.Originality/valueTo the best of authors’ knowledge, this study is the first to test individual investors' attention on stock splits based on their buy-initiated trades. This study is also the first to test the impact of stock split ratios on the disposition effect reduction. This study's findings enrich the scant literature on individual investors' attention and how to reduce their disposition effect bias.

Features of determining the market value of retail real estate and individual trade related properties during pre-trial evaluation and forensic examination

The present article deals with the specifics of valuation of retail property and individual trade related properties on the basis of the international experience and as recommended by International Valuation Standards and RICS (The Royal Institution of Chartered Surveyors (Great Britain)) valuation standards (Red Book). The present article is justified as currently Russia lacks a standard, uniform for the valuers or legal experts, to be used for the purposes of valuation of similar subjects. At the same time, methodical literature is insufficient while there are numerous property disputes that call for pre-court valuations and expert evidence of valuation of such subjects, including numerous litigations arising out of bankruptcy or establishing cadaster value to the amount of market value. The author reviews the existing approaches to valuation of real estate in accordance with both the international and national standards and awards professional recommendations pertaining to the use of the income approach to value retail real properties and individual trade related properties. The definitions and metrics of the above real properties’ groups are described separately. Also, the author provides guidelines for inquiry of the documents and information necessary for the acquisition of the data to be used in the course of valuation and expert evidence. All pricing factors are described in detail in the present article against the examples of retail real properties and individual trade related properties (say, hotel) and explanation of their effect on the market value in case the income approach is applied is provided.

Does air pollution influence investor trading behavior? Evidence from China

Building on the research linking environmental factors to investor mood, we posit that there is a negative relation between air pollution and individual trading strategies. Through an analysis of unique individual transaction data, our results show that air pollution negatively influences individual investors' propensity to buy and positively influences investors' propensity to sell. We find obvious heterogeneity effects across different investor, stock and city characteristics. The effects are even larger for investors with less investment experience and for those living in heavily polluted cities. This study is crucial for establishing an association between air pollution and individual trading activities.

Market Timing Skill and Trading Activity in Taiwan’s Retail-Dominated Futures Market

There has been substantial research on performance persistence among professional and retail investors. These studies typically employ infrequently sampled data on portfolio holdings and returns, making it difficult to distinguish skill from luck, let alone differentiate between superior security selection and market timing ability. Based on 10 years of comprehensive account-level data comprising 61 million trades made by investors in Taiwan’s retail-dominated futures market, the authors confirm that institutions consistently earn alpha at the expense of behaviorally biased individual traders. The authors introduce an approach for separating overconfident traders from skilled market timers. This novel skill measure interacts prior performance with past trading volume. Investors identified as highly skilled subsequently earn a net-of-cost average annual return of 115%. The authors’ results contribute in two ways: (1) introducing a new measure for assessing high-frequency trading skill and (2) validating the intuition that significant alpha can be harvested by active investors in retail-dominated markets. <b>TOPICS:</b>Futures and forward contracts, emerging markets, manager selection, performance measurement <b>Key Findings</b> ▪ The authors employ comprehensive data on 61 million individual trades made by investors in Taiwan’s financial futures market over a 10-year period to confirm that behaviorally biased retail investors consistently lose to institutional investors. ▪ They demonstrate weak performance persistence and a nonlinear relationship between past trading volume and future performance, characterized by overconfidence on the part of a vast majority of traders and rational learning about skill by the most active traders. ▪ The authors describe a method for inferring true market timing ability from a combination of data on prior performance and past trading volume and identify a small subset of skilled traders who subsequently earn extraordinary profits after accounting for transaction costs.

Liquidity in the Time of COVID

While the 2008 shifted the attention from individual trades to netting-set counterparty risk, the evolving 2020 storyline is driven by liquidity risk at the funding-set level. The COVID turmoil brings General Wrong Way Risk (GWWR) to the fore while the impending IBOR transition amplifies portfolio-wide liquidity risk by nominally decoupling fixing rates from funding costs. This confluence of circumstances reopens the never quite abated debate on the “black art of FVA”.

Governing the fashion industry (through) intellectual property assets: systematic assessment of individual trade marks embedding sustainable claims

With an upsurge of international movements calling for greater environmental and social responsibility, the fashion industry is witnessing a proliferation of socio- and nature-inspired trade marks, conveying subtle and nuanced messages related to intangible and—possibly—sustainable business practices. These IP assets allow companies to transfer information on the so-called credence attributes, which empower consumers to select products reflecting, not only their instrumental preferences, but also their values. In such a context, trade marks are leading the shift from official regulatory regimes to information-based forms of private governance that merge elements of IP, human rights, and environmental law. The prominent role of trade marks as a governance tool in the fashion industry is not an isolated phenomenon, but is rather part of a wider shift from public regulation to non-state market-driven schemes, where the latter are seen among the few viable responses to overcome political and economic barriers to transnational business...

Greed and individual trading behavior in experimental asset markets.

This dataset accompanies the article: Hoyer, K., Zeisberger, S., Breugelmans, S. M., & Zeelenberg, M. (2021). Greed and individual trading behavior in experimental asset markets. Decision, 8(2), 80. Article abstract: Greed has been shown to be an important economic motive. Both the popular press as well as scientific articles have mentioned questionable practices by greedy bankers and investors as one of the root causes of the 2008 global financial crisis. In spite of these suggestions, there is as of yet no substantive empirical evidence for a contribution of greed to individual trading behavior. This article presents the result of 15 experimental asset markets in which we test the influence of greed on trading behavior. We do not find empirical support for the idea that greedier investors trade fundamentally differently from their less greedy counterparts in markets. These findings shed light on the role of greed in trading and the emergence of asset market bubbles in specific, and of the financial crisis in general. Directions for future research are discussed.

Keynes's trading on Wall Street: did he follow the same behaviour when investing for himself and for King's?

In the last few years Keynes's investment activity, both as an individual trader and as a manager of institutions’ portfolios, has attracted attention in the specialised literature. Recently his investments on Wall Street, in particular – both on his own account (Cristiano, Marcuzzo and Sanfilippo 2018) and on behalf of King's College, Cambridge (Chambers and Kabiri 2016) – have been analysed, and the evident connection with his theoretical analysis of the functioning of the financial markets contained in chapter 12 of The General Theory has been duly stressed. This article aims to contribute to a more comprehensive understanding of Keynes's trading behaviour on Wall Street by providing a detailed comparison of his investment choices when he traded for himself and for King's. There are similarities, as might be expected, but also significant differences, well worth investigating. As far as the differences are concerned, one of the most striking is to be seen, for instance, in his attitude when, after a period of bull market in 1936, he had to face the spring 1937 burst of the speculative bubble and subsequent recession. Analysis of his behaviour in this specific case reveals that the event took him by surprise but his reaction differed with regard to his personal investments and the King's investments. The prevalence of a ‘buy and hold’ strategy, which, according to Chambers and Kabiri's reconstruction (2016), marked Keynes's behaviour in general (and also in this particular case) when he invested on behalf of King's, was not always his typical choice when the investments were undertaken on his own account. A tentative explanation of this result, which is also grounded on some different features characterising the two portfolios and not sufficiently investigated in previous studies, is at last provided in the article.