Long-term Returns Research Articles

UISA: User Information Separating Architecture for Commodity Recommendation Policy with Deep Reinforcement Learning

Commodity recommendation contributes an important part of individuals’ daily life. In this context, deep reinforcement learning methods have demonstrated substantial efficacy in enhancing recommender systems’ performance. Nevertheless, several recommender systems directly utilize original feature information as a foundational element for decision-making, which seems simplistic and low efficient. Furthermore, the incorporation of sequential decision-making adds complexity to the task of recommendation. In pursuit of maximizing the long-term sequential returns of recommender systems, our study introduces a novel architecture, named User Information Separating Architecture (UISA). This framework is tailored to align with classic reinforcement learning algorithms and aims to extract the user’s interest value through the discrete processing of both static and dynamic user information. Through integration with deep reinforcement learning, the architecture is oriented towards the maximization of long-term profit and is applicable in sequential recommendation scenarios. We conduct experimental assessments by combining the proposed architecture with proximal policy optimization (PPO) and deep deterministic policy gradient (DDPG) algorithms. The outcomes illustrate marked improvements in commodity recommendation, showcasing enhancements ranging from approximately 5% to 40% in both reward and click-through rate metrics across a self-constructed JDEnv environment and the Virtual Taobao environment. Through comparison experiments, the UISA models demonstrate comparable performance.

The Causality between Analysts’ Recommendations and Corporate M&As

Abstract This study examines the role of analysts' recommendations in mergers and acquisitions (M&As), focusing on their impact on payment methods and acquirers' long-term performance. The findings reveal that acquirers with strong buy or buy recommendations are more likely to use 100% stock payment, consistent with the overvaluation hypothesis. Conversely, those with strong sell or sell recommendations tend to prefer cash payment. Notably, acquirers with higher recommendation scores exhibit better long-term market performance. This finding suggests that analysts' recommendations before M&A announcements do not fully incorporate the deal's potential impact on long-term value creation. Moreover, acquirers with buy recommendations experience significantly lower long-term returns, highlighting the disconnect between analysts' recommendations and long-term performance. These findings contribute to understanding the information content and limitations of analysts' recommendations in the M&A context. JEL classification numbers: G34, G24, G14. Keywords: Mergers and acquisitions, Analysts' recommendations, Payment methods, Information quality, Overvaluation hypothesis.

Is the market biased in M&A, dividend payment, and share repurchase events?

Companies with excess capital can opt to: pay dividends to shareholders, buy back treasury shares for short-term shareholder benefits, or pursue M&A investments for long-term shareholder returns. Using difference in differences approach of event research methods combined with unique manually collected data sets, this paper investigates the market bias for three events: M&A, share repurchase, and dividend payment. The results show that information was leaked to the outside 1 day before it was officially announced at all events. When observing the company's performance 3 years after the event announcement, we also find that the market reaction is biased in M&A and stock dividend payment events, but accurate in the cash dividend payment and share repurchases. In addition, the market has the strongest and longest reaction to the news of the company buying back shares; has the weakest reaction to the stock dividend payment; has the shortest reaction to cash dividend payment; has a negative reaction to the acquisition company's stock, and has a positive reaction to the target company's stock. Our research has provided empirical evidence on the market response to published information, and supports CEOs make the most accurate choices when the company has an excess cash flow.

A strategic roadmap for combating barriers negating the implementation of prefabricated net-zero carbon buildings

In the global push for carbon neutrality and the emergence of net-zero carbon buildings (NZCBs), the lack of substantial progress in achieving NZCB goals due to unaddressed barriers is a pressing issue. While there are ongoing initiatives for NZCB, a crucial research gap exists in the thorough examination of specific barriers and their interconnected complexities, impeding progress in the NZCB agenda. This study aims to fill this gap by identifying and investigating the barriers negating the implementation of Prefabricated NZCBs through a systematic literature review and analyzing their relationships using Interpretative structural modeling (ISM) analysis. Additionally, the study aims to provide a strategic roadmap to overcome the barriers that impede the successful implementation of prefabricated NZCBs. The findings reveal that the regulatory barriers, including regulations, policies, and implementation efforts, emerge as the most significant, followed closely by uncertainties related to long-term financial returns and payback periods. The study concludes that the acceleration of NZCB goals depends on addressing these identified barriers and underscores the imperative for collaboration among government bodies, supply and demand sectors, and end users. Policymakers are urged to integrate these findings into their guidelines for promoting NZCB. The implications of this research are substantial, offering a path forward that prioritizes regulatory obstacles and addresses the most crucial barriers, ultimately propelling the NZCB agenda and contributing to a more sustainable and environmentally friendly future.

Critic-Guided Decision Transformer for Offline Reinforcement Learning

Recent advancements in offline reinforcement learning (RL) have underscored the capabilities of Return-Conditioned Supervised Learning (RCSL), a paradigm that learns the action distribution based on target returns for each state in a supervised manner. However, prevailing RCSL methods largely focus on deterministic trajectory modeling, disregarding stochastic state transitions and the diversity of future trajectory distributions. A fundamental challenge arises from the inconsistency between the sampled returns within individual trajectories and the expected returns across multiple trajectories. Fortunately, value-based methods offer a solution by leveraging a value function to approximate the expected returns, thereby addressing the inconsistency effectively. Building upon these insights, we propose a novel approach, termed the Critic-Guided Decision Transformer (CGDT), which combines the predictability of long-term returns from value-based methods with the trajectory modeling capability of the Decision Transformer. By incorporating a learned value function, known as the critic, CGDT ensures a direct alignment between the specified target returns and the expected returns of actions. This integration bridges the gap between the deterministic nature of RCSL and the probabilistic characteristics of value-based methods. Empirical evaluations on stochastic environments and D4RL benchmark datasets demonstrate the superiority of CGDT over traditional RCSL methods. These results highlight the potential of CGDT to advance the state of the art in offline RL and extend the applicability of RCSL to a wide range of RL tasks.

Task-Oriented Self-Imitation Learning for Robotic Autonomous Skill Acquisition

The inferior sample efficiency of reinforcement learning (RL) and the requirement for high-quality demonstrations in imitation learning (IL) will hinder their application in real-world robots. To address this challenge, a novel self-evolution framework, named task-oriented self-imitation learning (TOSIL), is proposed. To circumvent external demonstrations, the top-K self-generated trajectories are chosen as expert data from both per-episode exploration and long-term return perspectives. Each transition is assigned a guide reward, which is formulated by these trajectories. The guide rewards update as the agent evolves, encouraging good exploration behaviors. This methodology guarantees that the agent explores in the direction relevant to the task, improving sample efficiency and asymptotic performance. The experimental results on locomotion and manipulation tasks indicate that the proposed framework outperforms other state-of-the-art RL methods. Furthermore, the integration of suboptimal trajectories has the potential to improve the sample efficiency while maintaining performance. This is a significant advancement in autonomous skill acquisition for robots.

Why Liquidity Matters: A Financial Planning and Investment Discussion for Plastic Surgeons.

Plastic surgeons should understand the importance of maintaining liquidity as part of a robust household financial planning and investment strategy. Although investors rightly focus on achieving solid long-term returns, our experience suggests that many plastic surgeons often pay too little attention to liquidity management in their outlook, and some may experience stress as a result. This article discusses why liquidity management matters both in terms of each surgeon's unique career and in the context of today's dynamic investment opportunities and risks. We also discuss how best to understand the trade-offs and costs associated with household debt. Finally, we present simple self-diagnostic questions to help surgeons assess whether their current financial planning addresses key liquidity risks. This article belongs to a series that introduces relevant wealth and investment subjects for practicing plastic surgeons, students in plastic surgery, and support function professionals. This discussion is not meant to be exhaustive nor constitutes investment advice regarding any asset class, strategy, or examples cited herein.

What explains foreign portfolio investment inflows to BRICS countries?

Large and volatile foreign portfolio investment (FPI) inflows raise financial instability concerns and create several macroeconomic challenges for developing countries. Identifying the factors driving FPI inflows is therefore essential for formulating appropriate policies to manage these inflows efficiently. This study uses a GM-FMOLS panel cointegration approach to examine and identify such factors for BRICS countries, the leading recipients of FPI inflows among all developing countries. The study finds that the 10-year US Treasury bond yield exerts a significant negative influence on FPI inflows. These bonds provide risk-free long-term returns to portfolio investors; hence, a rise in the yield on such bonds prompts them to readjust their portfolios away from assets in developing countries to US Treasuries, leading to a decline in FPI inflows. The study further finds that a thriving domestic stock market, a higher interest rate differential, an appreciating domestic currency, an improvement in the recipient country’s creditworthiness, and a greater degree of trade openness are conducive to FPI inflows. However, a rising consumer price index, higher foreign output growth, and greater global financial volatility discourage these inflows.

Investigating the Co-Movement and Asymmetric Relationships of Oil Prices on the Shipping Stock Returns: Evidence from Three Shipping-Flagged Companies from Germany, South Korea, and Taiwan.

In the last 2 years, there has been a significant upswing in oil prices, leading to a decline in economic activity and demand. This trend holds substantial implications for the global economy, particularly within the emerging business landscape. Among the influential risk factors impacting the returns of shipping stocks, none looms larger than the volatility in oil prices. Yet, only a limited number of studies have explored the complex relationship between oil price shocks and the dynamics of the liner shipping industry, with specific focus on uncertainty linkages and potential diversification strategies. This study aims to investigate the co-movements and asymmetric associations between oil prices (specifically, West Texas Intermediate and Brent) and the stock returns of three prominent shipping companies from Germany, South Korea, and Taiwan. The results unequivocally highlight the indispensable role of oil prices in shaping both short-term and long-term shipping stock returns. In addition, the research underscores the statistical significance of exchange rates and interest rates in influencing these returns, with their effects varying across different time horizons. Notably, shipping stock prices exhibit heightened sensitivity to positive movements in oil prices, while exchange rates and interest rates exert contrasting impacts, one being positive and the other negative. These findings collectively illuminate the profound influence of market sentiment regarding crucial economic indicators within the global shipping sector.

Almost Perfect Shadow Prices

Shadow prices simplify the derivation of optimal trading strategies in markets with transaction costs by transferring optimization into a more tractable, frictionless market. This paper establishes that a naïve shadow price ansatz for maximizing long-term returns, given average volatility yields a strategy that is, for small bid–ask spreads, asymptotically optimal at the third order. Considering the second-order impact of transaction costs, such a strategy is essentially optimal. However, for risk aversion different from one, we devise alternative strategies that outperform the shadow market at the fourth order. Finally, it is shown that the risk-neutral objective rules out the existence of shadow prices.

Benefits of farmer managed natural regeneration to food security in semi-arid Ghana

Promoting Farmer Managed Natural Regeneration (FMNR) aims to increase the productive capacities of farmer households. Under FMNR, farmers select and manage natural regeneration on farmlands and keep them under production. While FMNR contributes to the wealth of farming communities, its contribution to household food security has rarely been researched. We, therefore, used a mixed-methods approach to address the research gap by measuring FMNR’s contribution to food security among farmer households in the Talensi district of Ghana. We adopted the Household Dietary Diversity Score (HDDS) and Food Consumption Score (FCS) to estimate food security status among 243 FMNR farmer households and 243 non-FMNR farmer households. Also, we performed a Chi-square test of independence to compare the frequency of each food group (present vs not present) between FMNR adopters and non-FMNR adopters to establish the relationship between adopting FMNR and consuming the FCS and HDDS food groups. Our results reveal that FMNR farmer households are more food secure than non-FMNR farmer households. The HHDS of the FMNR farmer households was 9.6, which is higher than the target value of 9.1. Conversely, the HHDS of the non-FMNR farmer households was 4.3, which is lower than the target value of 9.1. Up to 86% and 37% of the FMNR farmer households and non-FMNR farmer households fell within acceptable FCS; 15% and 17% of FMNR farmer households and non-FMNR farmer households fell within borderline FCS. While none of the FMNR farmer households fell within poor FCS, 46% of non-FMNR farmer households fell within poor FCS. Adopting FMNR is significantly related to consuming all food groups promoted and benefiting from FMNR practices. The paper recommends enabling farmers in semi-arid environments to practice and invest in FMNR for long-term returns to food security.

Exchange rate hedged deposit account as a macroprudential monetary policy instrument

Purpose - In the aftermath of the 2008 global financial crisis, central banks have resorted to macro discretionary monetary policies in order to prevent the risks that the fragility of macroeconomic indicators in national economies may pose on financial stability. Accordingly, in December 2021, the CBRT initiated a comprehensive monetary policy process that will provide long-term and permanent returns in the fight against high inflation and high exchange rates, and introduced the "Currency Protected Deposit" instrument to encourage and support real persons to make their investment preferences in TL. The liraization process and exchange rate-protected deposits are aimed to make a lasting contribution to price stability in the medium term. In this study, the purpose of the Exchange Rate Protected Deposit (ERD) scheme and its impact on macroeconomic indicators will be evaluated for the 2021-2023 period. Methodology - After explaining the implementation, characteristics and the need for the KKM, the impact of the utilization rate of the KKM on the exchange rate and interest rates in the December 2021-December 2023 period is evaluated.. Findings - With the KKM implementation, which aims to contribute to strengthening macro financial stability by supporting Turkish lira time deposits, the utilization rate of the KKM is seen to have contributed to the strengthening of the monetary transmission mechanism through the increase in the policy rate, the increase in the demand for Turkish lira instruments, and the rise in loan and deposit rates together. Turkish lira deposits are on the rise while FX-protected deposits are on the decline. Conclusion - It is observed that the KKM' implementation contributed to the lira appreciation process and partially contributed to the recovery in exchange rates between December 2021 and July 2023. Keywords: Currency protected deposit, macroprudential monetary policy, exchange rate JEL Codes: H30, E52, F31

Effect of long-term straw return on organic matter transformation by hydroxyl radical during paddy soil oxygenation

The generation of hydroxyl radicals (OH) mediated by Fe(II) has drawn increasing amounts of attention due to its significant role in the transformation of soil organic carbon (SOM) during redox fluctuations in paddy soil. This study further examined the effect of long-term (since 1984) straw return on Fe(II) on driving OH formation and SOM transformation upon paddy soils oxygenation. We found that long-term straw return could inhibit the OH and CO2 production in abiotic processes. The OH production decreased from 190.4 to 133.4 µM as the straw return amount increased from 0 to 19.16 t·hm−2·year−1. Moreover, 14.7–38.6 % of the CO2 production was associated with OH during oxygenation. By combining radical quenching and OM extraction, we determined that straw return could increase O2 reduction to H2O2 through a two-electron transfer pathway. Based on chemical extraction, Mössbauer spectra and multilinear regression model, we demonstrated that straw return resulted in more active Fe(II) species that controls the OH production. The results of 3DEEMs and FT-ICR MS showed that oxidative transformation can be accomplished by the introduction of OH to aromatic structures or olefins through ring opening and hydroxylation mechanisms. And OM at high straw return concentrations was likely oxidized by OH into bioavailable aliphatic compounds. Therefore, this study highlights the underappreciating effects of long-term straw return on Fe(II) oxidation in driving OH generation and SOM transformation in paddy soil redox fluctuation events.

THE ROLE OF ESG DISCLOSURE PRACTICES IN INVESTMENT DECISIONS

Purpose: This study explores the role of ESG disclosure practices on investment decisions, focusing on how this information is used by investors for risk assessment and informed choice. It is essential for expanding knowledge about the monetary advantages of sustainable activities. In order to support investors, enhance their ESG practices and promote a more ethical and sustainable business environment, the research attempts to provide insightful analysis and actionable suggestions. Design: This paper delivers a thorough examination of the role served by ESG disclosure practices during the entire process of investment decision-making. Moreover, it furnishes insights pertaining to the advantages, challenges, opportunities for enhancement, and prospective developments linked to these practices. Finding: The findings from the case study unveil novel perspectives on how ESG disclosure practices influence investment decision-making, offering potential assistance to investors in refining their strategies and cultivating a financial system with a stronger emphasis on sustainability. This significantly expands ESG integration knowledge, offering valuable insights for stakeholders pursuing a sustainable financial future. Originality value: ESG disclosure has a crucial part in investment decisions by providing valuable information about a companys ESG performance. This information helps assess risks and opportunities, identify investment themes, and determine effective choices. Companies with robust ESG disclosure attract and retain investors, while investors factoring in ESG considerations enhance their potential for long-term returns. Paper type: Case Study KEYWORDS: ESG (Environmental, Social, and Governance), Investment decision, SWOT Analysis, individual investors, ESG integration.

Effects of Straw Return Duration on Soil Carbon Fractions and Wheat Yield in Rice–Wheat Cropping System

In China’s subtropical rice–wheat cropping system, the changes in the soil organic carbon (SOC) pool due to long-term straw return and its connection with crop yield remain unclear. This study aims to provide insights into establishing a sensible straw return system by evaluating the differences in the distribution and variation rates of SOC, light fraction organic carbon (LFOC), heavy fraction organic carbon (HFOC), particulate organic carbon (POC), and mineral-associated organic carbon (MOC) in the 0–20 cm soil layer under different durations of straw return. Additionally, the study analyzes the relationship between the changes in SOC and its fractions and wheat yield. The experiment was conducted in 2019 in a rice–wheat rotation field with ten years of straw return treatments: no straw return (NR) or 1, 2, 3, 4, 5, 6, 7, 8, 9 year(s) of straw return (SR1–9), and an additional treatment in 2020 (10 years of straw return, SR10). The results revealed that with an increase in the duration of straw return, the contents of SOC, LFOC, HFOC, and POC gradually increased, showing the highest increments of 45.88%, 187.22%, 41.55%, 97.89%, and 28.21%, respectively, compared to the NR treatment. However, after eight years of straw return, the compound annual increase in soil organic carbon and its components was lower than in years 1–8, indicating a trend of diminishing increments. The SOC content and its variation were significantly correlated with the content and variation of LFOC, HFOC, POC, and MOC, with the highest sensitivity observed for the variation in LFOC, indicating the strong influence of the duration of straw return. The SOC and its fraction contents showed significant positive correlations with wheat yield, with the highest contribution to wheat yield increase attributed to an increase in LFOC content. In summary, straw return enhances the 0–20 cm deep soil carbon pool, with LFOC being the most sensitive indicator, reflecting the influence of the duration of straw return on soil carbon pools.

Survivorship outcomes in patients treated with immune checkpoint inhibitors: a scoping review.

Immune checkpoint inhibitors (ICIs) have become a central part of cancer care. However, the survivorship outcomes in patients treated with ICIs are understudied. Therefore, we conducted a scoping review to evaluate the current status of the field and to establish research gaps regarding survivorship outcomes with ICIs in real-life cohorts. We used the Web of Science, PubMed, and Embase databases to systematically filter published studies with real-life cohorts from January 1, 2010, until October 19, 2022. Studies evaluating at least one survivorship outcome in ICI-treated patients were included. A total of 39 papers were included. Quality of life (QoL) (n = 23), toxicity burden (n = 16), and psychosocial issues (n = 9) were the most frequently evaluated survivorship outcomes. Anti-PD-1/PD-L1 monotherapy and a response to treatment were associated with better QoL. In addition, the ICIs were associated with grade 3 or higher immune-related adverse events (irAEs) in 10-15% and late/long-term irAEs in 20-30% of the survivors. Regarding psychosocial problems, over 30% of survivors showed evidence of anxiety and depression, and 30-40% of survivors reported neurocognitive impairments. The survivors treated with ICIs have impairments in most survivorship domains. Further research is needed to gather data on the understudied survivorship outcomes like late and long-term effects, fertility, financial toxicity, and return to work in survivors treated with ICIs. Available evidence demonstrates that a significant portion of survivors treated with ICIs have a significant toxicity burden, lower QoL than the general population, and a high rate of psychosocial problems.

Equities and Cash Holdings: A Long-Term Analysis of Turkish Construction Firms

Being at the first sight bank credits have been implicit in leverage, and among the significant determinants of long-term returns along with cash for many sectors. However, equities could have been neglected in this perspective. A sustainable proportional level of equities with the help of a return variable may alter the expectations on bank credit effect, and in this context; this study aims to reveal whether there exists a set of identical determinants for cash holdings in the case of the Turkish construction sector. By assessing a set of aggregate data from the balance sheets of the businesses in this very sector, we have eliminated most of the variables and written two models in which an alternative return indicator is considered an extra independent to significantly presume cash and cash equivalents in the selected sector. We therefore conclude that both return on assets and return on equities could be used interchangeably. In the analysis, the essential variables are revealed as equities on assets and the ratio of bank credits in the short-term on current liabilities. The study also asserts robust results for both independent returns with the same set of predictors in which bank credits are not alone in a leading role, however, equities stand to be qualified as a sustainable contributor to liquidity as well.

Long-term Functional and Pain Outcomes Following Arthroscopic Partial-Thickness Rotator Cuff Tear Completion and Repair

Objective: There remains little consensus on the optimal treatment approach for partial-thickness rotator cuff tears and few studies have examined the long-term outcomes of different surgical repair techniques. The purpose of this study is to identify the long-term functional and pain outcomes of arthroscopic tear completion followed by repair. The authors hypothesize that this technique will allow patients to have long-term pain relief and return to a pre-injury level of function. Methods: Patients (n=16) who underwent arthroscopic tear completion and repair for a partial-thickness rotator cuff tear were included in this case series. Each patient returned for a one-time follow-up visit, with an average follow-up time of 7.09 years, at which time physical and neurological exams were performed, quality of life was assessed through subjective questionnaires, American Shoulder and Elbow Society (ASES) and the University of California at Los Angeles (UCLA) shoulder scores were obtained, and magnetic resonance imaging was performed. Results: The average ASES score was 85.3, with 81% of patients reporting that they were able to return to a pre-injury level of function. Half of the patients reported the highest possible UCLA shoulder score of 35. Physical examination showed that patients had excellent strength and range of motion. Magnetic resonance imaging demonstrated continuity of the repair in all but one patient. However, 25% of patients reported return of symptoms since surgery, including pain and limited mobility. Conclusion: At an average of 7.09 years follow-up, most patients were found to have full mobility, pre-injury level of activity, and maintenance of rotator cuff integrity in the surgically treated shoulder. However, one fourth of patients reported return of symptoms. The authors conclude that the tear completion and repair technique can lead to long-term functional improvement, but has less favorable results in terms of subjective pain level and quality of life.

Analysis of the Relationship between Financial Behavior and Short- and Long-Term Returns among Moroccan Investors: A Behavioral Finance Approach

The efficient market hypothesis (EMH) theory has been vigorously challenged for its inability to explain certain anomalies, stimulating the development of behavioral finance. This discipline, emerging over the past thirty years, provides a new perspective on the analysis of financial markets, highlighting the behavioral biases of investors. Faced with this issue, our study aims to evaluate the impact of behavioral biases on Moroccan financial markets by testing the hypothesis that these biases influence investment decisions and short- and long-term performance. Thus, we seek to understand how the behaviors of Moroccan investors, influenced by psychological biases, can affect financial returns in a context where the efficient market hypothesis is being questioned

EV Charging Command Fast Allocation Approach Based on Deep Reinforcement Learning With Safety Modules

Efficient real-time management of electric vehicle (EV) charging in a charging station (CS) is vital to the integration of large-scale EVs in power grids. It faces critical challenges such as frequent changes in the grid’s dispatch commands, the complexity of EVs’ costs, and the uncertainties in the EVs’ charging/traveling behaviors and in the future dispatch commands. To tackle these challenges, this paper proposes a deep reinforcement learning (DRL)-based allocation approach that optimally and efficiently allocates the grid’s commands to the EVs and controls their charging in real time. It includes two stages. Stage 1 includes a data-driven EV cost quantification method, which efficiently quantifies the EVs’ flexibility contributions with long-term return consideration. Stage 2 proposes a high sample efficiency DRL-based allocation method, which optimizes the EVs’ charging and addresses the EV-and grid-related uncertainties. The proposed allocation has a fast computational speed. Finally, to address the security risk due to DRL’s stochastic exploratory actions, two safety modules are developed which ensure the EV charging security and the allocation accuracy. The effectiveness and efficiency of the proposed strategy are verified by comparing its performance against multiple benchmark approaches.