Dynamic Investment Research Articles

Pricing and dynamic service policy for an imperfect production system: Extended Pontryagin’s maximum principle for interval control problems

Pontryagin’s maximum principle is one of the most important topics of control theory. It plays a crucial role in solving variational problems in an alternative way. In this paper, Pontryagin’s maximum principle is extended in order to solve interval valued control problems (IVCPs). To serve this purpose, firstly all the formal definitions (viz. IVCP, interval ranking and optimizer of IVCP etc.) are presumed. Further, the necessary and sufficient condition, i.e., Pontryagin’s principles are extended in interval environment in order to solve an IVCP. The second part of this work presents an application of the proposed extension of Pontryagin’s maximum principle for IVCPs. Then, an imperfect production inventory problem is considered by assuming flexibility of all the involved parameters in interval environment. The proposed production problem mainly addresses a joint optimal policy for pricing, dynamic service investment and reworked/salvaged under interval flexibility. The IVCP related to the proposed model is solved using extended Pontryagin’s maximum principle and the interval optimization problem corresponding to the model is solved using improved c-r optimization technique. Further, a numerical example is taken and solved using the sparrow search algorithm (SSA) in order to illustrate the proposed theoretical results and validate the proposed model. Finally, sensitivity analyses are carried out w. r. to various system parameters in order to evaluate some implications to the manager.

Digital Currency Price Prediction using Machine Learning

Abstract: Coming into the 21st century, the views towards finance and investments have drastically shifted from traditional assets like gold, land, and property to assets in the digital domain, like investing in various stocks, mutual funds, currencies, etc. The more recent developments of technology and newer investment options have brought various block-chained digital currencies to the forefront. Digital currency options offer massive gains but are very dynamic and quick-moving investments, making predicting the future values for maximum gains difficult, thereby reducing the confidence of even seasoned investors. While digital currencies saw massive gains in the past decade, research in deep learning has seen equivalent growth in terms of efficiency, required computation, and prediction rate. In this project, we explored various digital currencies, using multiple machine learning models from extended trees to time series analysis, only to use Long Short-Term Memory (LSTM) model to get accurate predictions for the tested parameters. While there is a risk of overfitting the dataset, given that this project uses APIs to get real-time data, the risk is mitigated by the fact that it’s giving precise outputs for unseen data.

Dynamic investment in online advertising of multi-oligopoly competitive enterprises with spillover effect

Dynamic investment in online advertising of multi-oligopoly competitive enterprises with spillover effect

Optimal design of carbon utilization business model and dynamic investment decision-making in complex conditions

Optimal design of carbon utilization business model and dynamic investment decision-making in complex conditions

Across-time risk-aware strategies for outperforming a benchmark

We propose a novel objective function for constructing dynamic investment strategies with the goal of outperforming an investment benchmark at multiple points of evaluation during the investment time horizon. The proposed objective is intuitive, easy to parameterize, and directly targets a favorable tracking difference of the actively managed portfolio relative to the benchmark. Under stylized assumptions, we derive closed-form optimal investment strategies to guide the intuition in more realistic settings. In the case of discrete rebalancing with investment constraints, optimal strategies are obtained using a neural network-based numerical approach that does not rely on dynamic programming techniques. Compared to the targeting of a favorable tracking difference relative to the benchmark only at some fixed time horizon, our results show that the proposed objective offers a number of advantages: (i) The associated optimal strategies exhibit potentially more attractive asset allocation profiles, in that less extreme positions in individual assets are taken early in the investment time horizon, while achieving a similar terminal terminal wealth distribution. (ii) Across-time risk awareness leads to more robust performance and a higher probability of benchmark outperformance during the investment horizon in out-of-sample testing. The resulting strategies therefore exhibit desirable characteristics for active portfolio managers with periodic reporting requirements.

Study on Energy Flow Characteristics of Solar–Gas Combined Heating System for Settling Tank of Oilfield

Heating furnaces fueled by fossil fuels are commonly utilized in oilfields to provide heat to the settling tank, which heats the layer of crude oil. However, this traditional heating method consumes a significant amount of oil and gas resources, resulting in low energy utilization and environmental pollution. As the water content of the extracted crude oil increases over time, the operating costs of the settling tanks also continue to increase. Therefore, it is crucial to develop and implement clean and efficient heating technologies to facilitate the efficient operation of settling tanks. This paper proposes a solar–gas combined heating technology for settling tanks. A simulation model for the solar–gas combined heating system for the settling tank is constructed, considering the overall perspective of the system. The simulation model analyzes the impact of the control strategy for the oil collection period of the settling tank on the system performance. This analysis covers various aspects including the heat collection of the solar collector, the heat supply of the gas boiler, and the heat storage and release of the phase-change heat storage tank. The results demonstrate that when the oil collection cycle is Scheme E (4:00–8:00), the collector achieves the highest annual cumulative heat collection, the gas boiler provides the lowest annual total heat supply, and the phase-change heat storage tank exhibits the highest heat storage and release efficiency. Over the course of the system’s 15 year service life, the settling tank solar–gas combined heating system saves 727,988.69 MJ of energy annually, resulting in total energy-saving costs of CNY 397,007. The dynamic investment payback period is estimated at 9.14 years, and the system reduces CO2 emissions by 753,069.8 kg.

Employee Performance Implications of CSR for Organizational Resilience in the Banking Industry: The Mediation Role of Psychological Empowerment

Corporate social responsibility (CSR) has been found to be important in boosting organizations’ sustainability and resilience against crisis. Although employees constitute key internal stakeholders for CSR, limited attention has been paid to them. The purpose of this research is to examine how employee perceptions of CSR activities affect employee performance through their sense of psychological empowerment. Drawing upon a sample of 203 employees in the Cypriot banking sector, a structured questionnaire was administered to measure employee performance, psychological empowerment, and CSR activities as perceived by employees. The analysis of data, based on path modeling using the partial least squares (PLS) approach, confirms the mediating role of psychological empowerment between CSR activities (philanthropic, ethical, and environmental) and job performance. This study contributes to the theoretical evolvement of the CSR literature, as it established the mediating role that psychological empowerment plays between perceived CSR and job performance. The findings suggest that CSR should be treated not just as a pressing obligation but as a dynamic investment in organizational effectiveness, sustainability, and resilience because positive employee perceptions of CSR can contribute to staff empowerment and indirectly to job performance.

Retracted: Dynamic Index Optimal Investment Strategy Based on Stochastic Differential Equations in Financial Market Options

Retracted: Dynamic Index Optimal Investment Strategy Based on Stochastic Differential Equations in Financial Market Options

Impact analysis of COVID-19 on Nigerian workers’ productivity using multiple correspondence analysis

As the COVID-19 pandemic became a global health concern, many business activities have had to adjust to the protocols required to keep people safe, thereby altering the work structures of many professionals. With data gathered from 466 respondents in Nigeria, of which approximately 70% are from the South-West, this study shows how the factors associated with the health crisis have affected work productivity during this period. The snowball survey research design techniques with the two-way interaction model were employed. Multiple Correspondence Analysis was used to analyse and understand multiple and pairwise qualitative factors that influence productivity. The first part of the analysis identified boredom, remuneration, internet availability, fear of COVID-19 and depressing news of COVID-19 as the factors that had significant impacts on workers’ productivity. The second part of the analysis shows how the categories of the five significant factors were either associated or not with productivity. An analysis of each of these factors showed that fear of the disease was associated with slight productivity but access to internet facilities and remuneration were strongly associated with improved work productivity, while boredom and depressing news about COVID-19 were associated with non-productivity during this period. Further evidence also showed that training and new skills acquisition might improve workers’ productivity much more. We, therefore, recommend dynamic skills acquisition, training, and investment in tools and services that will enhance flexibility with the changing work structure that comes because of global crises.

Performance investigation of a solar/biomass based multi-generation system in pig farm

Intensive pig farm usually needs a large amount of energy, renewable energy supply system contributes to reducing the reliance of fossil fuel. In this study, load prediction of piggery considering different breeding characteristics and climate condition are carried out. An innovative solar/biomass hybrid multi-generation system combined with biomass combustor, ice thermal energy storage, absorption chiller, evacuated flat plate collector, photovoltaic panel and thermal energy storage is proposed. The operation strategy of following cooling demand is designed for proposed system, which considers the feature of high cooling load of piggery. The influences of key parameters on thermodynamic, economy and environment performances are investigated, thermodynamic operation performances of multi-generation system on different typical days are analyzed. Moreover, non-dominated sorted genetic algorithm is used for tri-objective optimization to obtain the optimal operating parameters and performances. Under the optimal condition, exergy and energy efficiency of integrated system are 19.05% and 53.59%, respectively. Compared with separation system, CO2 emission reduction ratio and dynamic investment payback period of multi-generation system are 70.39% and 5.12 years, respectively. In summary, this study offers a novel way for multiple energy coupling poly-generation system in intensive pig farm so as to obtain optimal performance in operation and scheduling.

Exotic option pricing model of the Black–Scholes formula: a proactive investment strategy

The option is an important derivative tool in financial market, and after decades of development, the option has emerged in various forms. This paper studies an exotic option with a proactive investment strategy. Compared with the classic option theory, we assume that the option holders continuously trade the underlying assets according to a predetermined investment strategy. Taking the European call option as an example, we first give some assumptions and define the loss function in terms of a logarithmic investment strategy. Then, the specific pricing expression of the exotic option is derived from the Black-Scholes option pricing formula. Next, numerical simulations are presented to visualize the mechanism of the exotic option in 2D and 3D forms by selecting appropriate parameters. The results indicate that the exotic option has a significant price advantage (up to 43.9% under specific parameter settings) over the classic option. Moreover, the empirical results illustrate a perfect fit between 50 ETF (issued by the Shanghai Stock Exchange) and our exotic option. The new proposed exotic option extends the Black-Scholes option theory from a no-trading condition (do not buy or sell underlying assets during the validity period) to a dynamic investment condition and has important practical significance in real life.

Cash holdings, ambiguity aversion, and investment puzzles

We consider a real options model with ambiguity to investigate how cash holdings and ambiguity aversion affect a firm’s dynamic investments. First, we prove a unique positive ambiguity coefficient exists when ambiguity exceeds it such that entrepreneurs believe the project is “too valueless to invest in”. Second, the coupons demanded by creditors increase with ambiguity, and cash holdings reduce the ambiguity premium. Our research provides a new explanation as to why companies abandon investment and hold more cash under the influence of the COVID-19 pandemic.

Dynamic volatility spillovers and investment strategies between crude oil, new energy, and resource related sectors

Promoting green and low-carbon development with new energy, and resource related sectors is an important way for mankind to deal with global climate change. With the marketization of new energy, the public and regulators have paid extensive attention to market relevance and risk contagion in China. In order to analyze the risk contagion mechanism, this paper examines the dynamic conditional correlation and the volatility spillover effect between crude oil, new energy, and resource related sectors. In addition, we compared the optimal diversification strategy by calculating hedging ratios and portfolio weights. The main results are as follows：First, new energy and resource related sectors have high dynamic correlation and the volatility spillover effect is significant. Second, from the perspective of net spillover index, new energy is the largest net volatility transmitter and WTI is the largest net volatility receiver. Third, when new energy is a long (short) position, the hedging efficiency of the portfolio with new energy vehicles using the hedging ratio strategy is the greatest. And when new energy is long, taking a short position in new energy vehicles is the most effective hedging strategy, but the most expensive hedging strategies are found in resource related sectors.

Beating a Benchmark: Dynamic Programming May Not Be the Right Numerical Approach

We analyze dynamic investment strategies for benchmark outperformance using two widely used objectives of practical interest to investors: (i) maximizing the information ratio (IR), and (ii) obtaining a favorable tracking difference (cumulative outperformance) relative to the benchmark. In the case of the tracking difference, we propose a simple and intuitive objective function based on the quadratic deviation (QD) from an elevated benchmark. In order to gain some intuition about these strategies, we provide closed-form solutions for the controls under idealized assumptions. For more realistic cases, we represent the control using a neural network (NN) and directly solve a sampled optimization problem, which approximates the original optimal stochastic control formulation. Unlike the typical approach based on dynamic programming (DP), e.g., reinforcement learning, solving the sampled optimization with an NN as a control avoids computing conditional expectations and leads to an optimization problem with a small number of variables. In addition, our NN parameter size is independent of the number of portfolio rebalancing times. Under some assumptions, we prove that a traditional DP approach results in a high-dimensional problem, whereas directly solving for the control without using DP yields a low-dimensional problem. Our analytical and numerical results illustrate that, compared with IR-optimal strategies with the same expected value of terminal wealth, the QD-optimal investment strategies result in comparatively more diversified asset allocations during certain periods of the investment time horizon.

Brazilian REITs: Are They an Opportunity for Diversification and Performance?

We study the dynamic diversification benefits of Brazilian real estate investment trusts (BR-REITs) by analyzing their complex dynamic relationship with stock and government bond indices. We estimate the assets’ conditional variance–covariance matrix using a vector autoregressive multivariate dynamic conditional correlation GARCH model with Student’s t distribution (VAR-DCCt MGARCH) and a global minimum variance portfolio. We find that BR-REITs provide strong risk-adjusted performance and persistent diversification benefits for Brazilian investors. Furthermore, these diversification benefits are not impacted by the market performance of stocks and bonds. Nevertheless, our results show that the BR-REITs’ conditional correlations with stocks and bonds are dynamic; thus, BR-REIT investors should employ dynamic investment strategies that account for time variation in REITs’ diversification benefits. Our results suggest that Brazilian investors, particularly long-term investors, would secure significant performance and diversification benefits, lowering their portfolios’ short-term volatility, by investing in BR-REITs.

Equity Investment Decisions of Operating Firms: Evidence from Property and Liability Insurers

During the 2007–2009 financial crisis, almost 10% of Property and Liability (P&L) insurers completely liquidated their equity portfolios, and more than half of them never resumed equity market investments. In contrast, those P&L insurers that continued investing in equities after the crisis, increased their portfolio allocation substantially. To understand these findings, we develop and estimate models that explain P&L insurers’ dynamic equity investment decisions, in terms of firm, group, and market characteristics over the period 2002–2018. We study three different approaches to equity investments, a pure investment strategy, internal capital market contributions, and an outsourcing option and find that the factors driving the decision to invest in equities differ from those that explain the extent of their equity investments. Moreover, we find that while equity portfolio losses drive the decision to temporarily cease investments in equities, the decision to permanently exit equity markets is driven by both equity market losses and underwriting losses. These findings shed some light on the factors driving the demand for equity investments by operating firms.

Age, but not an immune challenge, triggers terminal investment in the Pacific field cricket, Teleogryllus oceanicus.

The terminal investment hypothesis proposes that, when individuals are faced with a threat to survival, they will increase investment in current reproduction. The level of the threat necessary to elicit terminal investment (the dynamic terminal investment threshold) may vary based on other factors that also influence future reproduction. Here, we tested whether there is an interactive effect of age and an immune challenge on the dynamic terminal investment threshold in the Pacific field cricket, Teleogryllus oceanicus. We measured the courtship call, mating attractiveness, ejaculate size, and offspring production of T. oceanicus males. We found only limited support for the dynamic terminal investment threshold: there was no consistent evidence of a positive interaction between male age and immune challenge intensity. However, we found evidence for age-related terminal investment: older males produced a larger spermatophore than younger males. Older males also had a slower calling rate compared to younger males, suggesting a potential trade-off between these two pre- and post-copulatory traits. As some, but not all, reproductive traits responded plastically to cues for terminal investment, our research highlights the importance of considering a broad range of pre-and post-copulatory traits when exploring the potential for terminal investment to occur.

Orbital debris and the market for satellites

This paper studies the economic consequences of orbital debris for commercial outer-space activities. Spacecraft launches and other outer-space human activities produce pollution (i.e., orbital debris), which represent a hazardous negative externality increasing the risk of collision and the destruction of satellites. We regard outer space as a global common resource, where firms operating satellites maximize profits and do not internalize the social cost of orbital pollution. We develop a dynamic investment model for satellites and simulate the calibrated model to estimate how debris affects the optimal quantity of satellites and launches, and the number of satellites destroyed by collisions. We find that the optimal quantity of satellites is a negative function of the amount of debris. The paper derives a simple expression for the maximum number of satellites to prevent the Kessler syndrome. For the baseline calibration of the model, the estimated threshold for the maximum number of satellites in orbit is about 72,000. The model is simulated to study the effects of a decline in the launch cost and the increasing number of satellites per launch.

Application of improved meta-heuristic algorithms for green preservation technology management to optimize dynamical investments and replenishment strategies

In this study, an application of green preservation technology to obtain optimal pricing and replenishment policies is developed. The decreasing value in waste is considered along with retailer dynamic promotional and green preservation technology investments under a price-promotion model with ramp-type demand. To maximize total profits, the study aims to clean the environment while simultaneously optimizing selling price, replenishment schedule, order quantity, green preservation technology investment, and dynamic investment rate. Pontryagin’s maximum principle is adopted to obtain the optimal dynamic investment rate for waste reduction. Additionally, simulated annealing, particle swarm optimization, and BAT algorithms are individually applied to obtain an optimal decision for waste reduction via green preservation technology. Results showed that the investment rate in promotion is significantly affected by price changes and that the investment in green preservation technology is affected by the nature of the product. Extensive computational experiments are performed to validate the proposed model. Under Ramp-type demand, price differentiation is more rewarding than the uniform pricing of the retailer. Results demonstrate the significant role of dynamic investment strategy. It has invested more based on the low-price sensitivity in the second period, and the optimal investment follows a reverse trend.

Dynamic pricing and investment for fashion products under reference effect

AbstractIn this study, we discuss on the dynamic pricing and investment strategy for fashion products which decay in value, such as fashion clothes. The products are sold by an enterprise under a monopoly market in a finite horizon. Due to the obsolescence of fashion products, their fashion level decreases over time. Obviously, the selling price has a negative effect on demand, while the fashion level has a positive effect. Moreover, we introduce a reference value, which is used to indicate consumers' requirements for fashion level. We assume that investment on products performance or goodwill can reduce consumers' requirements for fashion level, an optimal control model is established. To maximize the enterprise's total profit, we obtain the trajectories of the optimal pricing and investment strategy by utilizing the Pontryagin's maximum principle. The optimal strategy is to gradually lower the selling price and then slightly raise it at the end of the sales period and reduce investment as products become obsolete. Afterwards, we provide a numerical example to illustrate our conclusions. Through the sensitivity analysis of the main parameters, we capture the influence of the parameters on an optimal decision. Moreover, some management implications are given.