Optimal Investment Research Articles

Optimal investment strategies for decarbonizing the Indian private road transport sector

The Indian government's COP26 emission reduction target has led to explore strategies to decarbonize India's private road transport sector. Adoption of novel vehicle options such as E85, electric, and CNG vehicles and strong network of public transportation are expected to reduce the emissions significantly. A system dynamics model for India's private road transport sector has been developed previously. This study expands that model by incorporating the dynamics between public and private road transportation and uses it to identify strategy for optimal incentive allocation for novel vehicle adoption to minimize the GHG emissions. The idea of epsilon-constraint method for multi objective optimization has been used in this work. The results suggested a trade off between investment in incentives and reduction in GHG emissions. Incentivization strategy prioritized electric cars and two-wheelers, as well as charging/CNG stations, to discourage the adoption of petrol vehicles till CNG infrastructure was established. The minimum GHG emissions achieved was 535.5 Mt CO2e by 2050 with an investment of 137.74 trillion Indian Rupee when public transportation was not considered. Upon considering public transportation, the minimum GHG emissions further reduced to 464.5 Mt CO2e by 2050 with reduced investment of 128.25 trillion Indian Rupee, indicating greater emission reduction benefits per unit investment. However, beyond a certain threshold, increase in public transportation resulted in increased incentive investment due to a feedback effect. This necessitates incorporating dynamic analysis into policy strategy. Other strategies such as carbon tax and renewable share in electricity grid proves very effective in reducing GHG emissions as well as incentive investments. However, despite reducing emissions COP26 emission target for 2030 was missed by 34%. Banning the purchase of new petrol and diesel vehicles, along with restrictions on the use of existing petrol and diesel vehicles, could help bridge this gap.

Investigating optimal green port investment strategies considering location-based externalities

ABSTRACT Green port development benefits the port communities but might make shippers in the hinterland face positive or negative externalities. Those externalities to shippers might be amplified or reduced by congestion, which more likely happens when ports have a farther hinterland location. Therefore, the location-based externalities should be considered when decide green effort in competing ports. In this paper, we establish a competition-based green effort decision-making model in different scenarios, focusing on the impact of location-based externalities. By comparing the green effort and welfare under different investment modes and different market power structure, we discuss the impacts of location-based externalities and the motivation for joint-investment in green port development. We find that (1) The positive location-based externalities decrease the port profit due to the non-exclusivity of green port services. Public port governance mode and the dominant market position can alleviate port’s losses. (2) The negative location-based externalities make smaller port contribute more green effort than the larger port. (3) As the positive location-based externality increase gradually, the joint-investment between ports with similar size achieves lower total welfare than the separate-investment. Our findings suggest the necessity for flexible adjustment of green port plans to mitigate conflicting interests between ports and hinterlands.

CEO Inside Debt and Corporate Investment Efficiency

ABSTRACTThis paper investigates whether and how the chief executive officer (CEO)'s inside debt holding influences a firm's investment policy. Our evidence on a sample of US S&P 1500 firms indicates that CEO inside debt can significantly improve investment efficiency and help to overcome both over‐investment and under‐investment, suggesting that the CEO's higher positions of inside debt can lead to optimal investment decisions. The results are robust when we use PSM, entropy balancing, the Heckman two‐stage method and the lagged value of the independent variables to mitigate the endogeneity concerns and other robustness checks. Furthermore, we document that the effectiveness of the CEO inside debt on investment is not sensitive to agency problems, as well as financial constraints. Overall, we confirm the importance of investigating the effect of managerial inside debt holdings on corporate capital investment and provide new insights into how inside debt mitigates agency problems.

Green Technology Investment and Production Decisions Considering Stochastic Demand and Firms' Decision Preferences Under Cap‐and‐Trade Regulation

ABSTRACTThis paper investigates how finite rational firms optimally respond to market potential under cap‐and‐trade regulation, considering stochastic demand. Using the mean–variance model framework, we develop an optimization model for green technology investment and production by finite rational firms with different decision‐making preferences. The main results indicate: (1) Under stable demand, firms investing in green technology gain more profits and consumer surplus, however, the effectiveness of carbon emission reduction depends on the market potential size. (2) Under stochastic demand, optimal decisions resulting from firms' varying decision preferences systematically deviate from those of risk‐neutral firms and often demonstrate firms' risk‐averse tendencies that lean towards conservatism. As external factors change, there can even be a reversal in technology investment with an increase in demand uncertainty that amplifies this systematic deviation. (3) Taking firms with different decision‐making preferences as the starting point, this study further analyses the distortion effect of the firm's risk attitude on the optimal technology investment and production decisions, enriching the related research on the joint decision‐making risk model of clean production. And it is more pertinent to the complex situation firms face in the real situation with decision‐making. (4) This study provides a theoretical basis and practical reference for the finite rational firms facing green technology investment choices. Considering the risk‐averse characteristics of firms, this study suggests that the government should establish a risk‐sharing mechanism to weaken the deviation of stochastic demand from the optimal decision‐making of firms or implement certain subsidy policies to protect the profit level of firms.

Dynamic Asset Allocation and Retirement Decision with Consumption Ratcheting and Effort Choice

This study examines the problem of choosing optimal consumption, investment, early retirement, and effort levels for an economic agent who is unwilling to reduce their consumption over time. The agent’s income depends on a fixed wage rate, and varies proportionally with their level of effort, which incurs disutility due to labor. By applying the dual-martingale method, we reformulate the problem into its dual form, dividing it into two distinct sub-problems: one focuses on selecting a consumption path that does not decrease, while the other determines the optimal timing for early retirement. Using this method, we find optimal strategies in the form of explicit closed-form solutions.

Optimal relation-specific investment, financing, and the supply chain capital structure under uncertainty

Optimal relation-specific investment, financing, and the supply chain capital structure under uncertainty

Optimal stock investment strategy using prediction models

Optimal stock investment strategy using prediction models

Optimal investment, consumption, and life insurance decisions for households with consumption habits under the health shock risk

. This article investigates the optimal investment, consumption, and life insurance strategies for households under the impact of health shock risk. Considering the uncertainty of the future health status of family members, a non homogeneous Markov process is used to model the health status of the wage earner. Drawing upon the theory of habit formation, we investigate the influence of different consumption habits on households’ investment, consumption, and life insurance strategies. Based on whether the wage earner is alive or not, we formulate and solve the corresponding Hamilton-Jacobi-Bellman (HJB) equations for the two scenarios of wage earner survival and wage earner’s demise, respectively, and obtain explicit expressions for the optimal investment, consumption, and life insurance strategies of households. Through sensitivity analysis of important parameters, it has been shown that the presence of health shocks within households has a negative impact on investment and consumption decisions, while the formation of consumption habits increases household propensity for precautionary savings.

Economic dispatch of microgrid generation-load-storage based on dynamic bi-level game of multiple stakeholders

During the participation of microgrid operators(MGO) and shared energy storage investors(SEI) in electricity market operations, unclear positioning of shared energy storage(SES) in the trading mechanism leads to decision-making limitations and mutual pricing constraints among stakeholders. Therefore, a dynamic bi-level game model based on multiple stakeholders is established in the paper. Considering the full life cycle investment costs, leasing costs, and load peak-shaving ancillary service revenue, establish a net revenue model for SEI. In the upper level, with SEI as leaders and MGO as followers, establishing a master-slave game model for optimizing SES leasing prices, and formulate leasing strategies. In the lower level, with MGO as leaders and cluster users as followers, establishing a master-slave game model for optimizing electricity prices and formulate scheduling strategies. A hybrid multi-strategy improved whale optimization algorithm based on simulated annealing(HSWMO) is proposed, combined with the theory of fixed points to solve the optimization problem of the upper and lower levels until obtaining the optimal solution that converges to a fixed point. Through case analysis, it is verified that the operational mode of SES as a market entity can bring higher economic benefits to multiple stakeholders such as MGO and cluster users. Meanwhile, the analysis from the perspective of SEI examines the optimal capacity investment and payback period for SES, providing effective reference for the comprehensive decision-making of SEI and MGO.

Robust optimization of regional biomass supply chain system design and operation with data-driven uncertainties

To address climate change and ensure energy security, biomass energy has become a popular renewable energy alternative to traditional fossil fuels. This study focuses on the strategic planning and tactical management problem of a regional biomass supply chain system with multiple feedstock and final products. A novel SVC-based data-driven robust optimization model is developed to provide the tradeoff solutions under uncertainties. Compared with the traditional robust optimization model, it can better depict the uncertain sets, reduce data redundancy, and provide less conservative strategies for decision makers according to their risk preferences. The proposed model is validated through a case study, Meizhou city in China. The results suggested the optimal investment scale and site for biorefineries and biomass power plants at the strategic planning level, as well as the feedstock supply network, inventory management, and production arrangement at the tactic management level. The optimal robust solutions can be derived by varying the envelope level of the uncertain sets. Moreover, sensitivity analysis is performed to investigate the influences of the variations of key parameters. It is found that the produced bioethanol and electricity lack cost advantages in the current situation, even with a 30 % reduction in main cost parameters. Insufficient biomass yield may require extra capital investment to satisfy bioenergy demand but with a higher supply cost. Thus, a high and long-term subsidy is necessary to facilitate the sustainable development of biomass and the low-carbon transition of the energy sector.

Monetizing Positive Externalities to Mitigate the Infrastructure Underinvestment Problem

Many cities struggle with financing their infrastructure projects. When decision makers cannot fully capture the benefits of their investments, there is a risk of underinvestment. Hong Kong’s transit operator created a model where it not only collects fare revenues but also engages in property management, leveraging the positive effects of public transport on nearby property values. In the article titled “Monetizing Positive Externalities to Mitigate the Infrastructure Underinvestment Problem,” the authors present a stochastic Stackelberg game of timing to examine the reasoning behind this approach. The issue is complex because the operator faces a two-dimensional optimal stopping problem that cannot be simplified by changing the numéraire. The authors determine the operator’s optimal investment strategy through the use of a “penalized problem” and provide comparative statics. They also identify the conditions in which capitalizing on positive externalities can encourage infrastructure investment. Other management challenges share similar structures.

Interpretable machine learning model for predicting activist investment targets

This research presents a predictive model to identify potential targets of activist investment funds—entities that acquire significant corporate stakes to influence strategic and operational decisions, ultimately enhancing shareholder value. Predicting such targets is crucial for companies aiming to mitigate intervention risks, activist funds seeking optimal investments, and investors looking to leverage potential stock price gains. Using data from the Russell 3000 index from 2016 to 2022, we evaluated 123 model configurations incorporating diverse imputation, oversampling, and machine learning techniques. Our best model achieved an AUC-ROC of 0.782, demonstrating its capability to effectively predict activist fund targets. To enhance interpretability, we employed the Shapley value method to identify key factors influencing a company’s likelihood of being targeted, highlighting the dynamic mechanisms underlying activist fund target selection. These insights offer a powerful tool for proactive corporate governance and informed investment strategies, advancing understanding of the mechanisms driving activist investment decisions.

Research on the Value Creation Mechanism of Green-Driven Products in the Internet+ Era

In order to improve the value of green-driven products, this paper studies the value creation mechanism of green-driven products in the Internet+ era. Under the framework of the classic Cournot output game, based on the bounded rationality assumption of the participants, this paper constructs a novel Cournot duopoly investment game model, and analyzes the dynamic adjustment mechanism of the participants' investment. The decision variable of participating enterprises is to select the optimal investment amount, and each production enterprise makes investment decisions in the next period according to the observed marginal profit of the current period to maximize the profit. Through calculation and analysis, it can be known that three boundary equilibriums and one interior point equilibrium of the discrete dynamic model system are obtained in this paper. The experimental analysis shows that the value creation mechanism of green-driven products proposed in this paper can effectively promote the value of green-driven products.

Optimal investment strategies under the relative performance in jump-diffusion markets

AbstractWe work on a portfolio management problem for one agent and a large group of agents under relative performance concerns in jump-diffusion markets with the CRRA utility function. Herein, we define two wealth dynamics: the agent’s and the group’s wealth. We measure the performances of both the agent and the group with preferences linked to the group performance. Therefore, we have stochastic optimal control problems for both the representative agent and the group to determine what the group does and the agent’s optimal proportion in the portfolio relative to the group’s performance. Further, our framework assumes that the agent’s performance does not affect the group, while the group affects the agent’s utility. Moreover, we investigate special cases where all agents in the market are homogeneous in their risk aversion and relative performances. We explore the qualitative behavior of the agent and show some numerical results depending on her relative performance consideration and risk tolerance degree.

Blockchain-enabled integrated three-layer bio-circular economy model with wastewater treatment, emissions, and controlled cheese spoilage

ABSTRACT Regulatory and market forces compel companies to integrate transparency and sustainability into their operations. In response to the pressing need, the study proposes a blockchain-enabled, sustainable, integrated three-layer inventory model for the cheese industry under carbon cap-and-trade policy. The ultimate aim is to maximize the integrated total profit of the system with optimal investment in green technology. Prior studies have neglected to account for blockchain costs and spoilage rate control, whereas our findings demonstrate that strategic investments in preservation technology yield substantial reductions in spoilage rates. Results indicate that the downstream end of the supply chain, retail, also plays a crucial role in maintaining total profitability, indicating the significance of collective inventory management along with sustainability initiatives. This study concludes that technology-driven sustainability initiatives, coupled with effective spoilage management, can optimize sustainability outcomes in the cheese supply chain without compromising financial performance.

Financing of the company's investment activity in the face of growing risks

The article examines the impact of globalization and economic reforms on enterprise management, focusing on the need to modernize production facilities, automate processes and use information technology. The role of investment as a key tool for promoting economic growth of enterprises, increasing their competitiveness and adaptation to new challenges of the globalized economy is considered. Particular attention is paid to the analysis of investment risks, their classification and methods of minimization, which allows enterprises to reduce negative impacts in the implementation of investment projects. Effective management of investment risks and determination of optimal investment strategies are critical factors for attracting new investments and achieving sustainable economic growth. The legal framework governing investment activity in Ukraine is defined, and approaches to investment management in accordance with international financial reporting standards are summarized. Thus, investment activity is considered not only as a source of economic benefit for enterprises, but also as a factor contributing to the economic stability of the national economy.

Optimal Consumption and Investment with Income Adjustment and Borrowing Constraints

In this paper, we address the utility maximization problem of an infinitely lived agent who has the option to increase their income. The agent can increase their income at any time, but doing so incurs a wealth cost proportional to the amount of the increase. To prevent the agent from infinitely increasing their income and borrowing against future income, we additionally consider a non-negative wealth constraint that prohibits borrowing based on future income. This utility maximization problem is a mixture of stochastic control, where the agent chooses consumption and investment, and singular control, where the agent chooses a non-decreasing income process. To solve this non-trivial and challenging problem, we derive the Hamilton–Jacobi–Bellman (HJB) equation with a gradient constraint using the dynamic programming principle (DPP). Then, using the guess-and-verify method and a linearization technique, we obtain a closed-form solution to the HJB equation and, based on this, find the optimal strategy.

Real Options Analysis of Constructed Wetlands as Nature-Based Solutions to Wastewater Treatment Under Multiple Uncertainties: A Case Study in the Philippines

Constructed wetlands (CWs) are man-made ecosystems that mimic the properties of natural wetlands. They are being utilized to treat various types of wastewater, from domestic to agricultural, municipal, commercial, and industrial effluents. Despite their economic viability and environmental benefits, their widespread adoption is challenged with several uncertainties, including public support, technology learning, and the impacts of climate change. This study proposes a valuation framework that considers these uncertainties to analyze the feasibility of CWs. Using existing CWs in the Philippines as a case, this study employs the real options approach to (1) evaluate the feasibility of CW projects using cost–benefit analysis, (2) calculate the value of postponing decisions to implement CWs projects using real options analysis, and (3) identify the optimal investment decisions for CWs considering the opportunity costs of waiting and uncertainties in public support and the impacts of climate change. Results found that the project is feasible with a net present value of USD 88,968. Yet, the real options value at USD 208,865 indicates that postponing the project may be a more optimal decision. Considering the cost of waiting, the valuation identified the threshold at 5.56% to immediately implement the project. The calculated values increase with uncertainty in public support but decrease with uncertainty in climate change’s impacts. Yet, these uncertainties prolong the decision to implement CW projects until they are resolved. The findings from this case study provide a basis for recommendations to support the adoption of CWs as nature-based water treatment for a more sustainable future.

Probability weighting and equity premium prediction: Investing with optimism

AbstractEmpirically motivated theoretical models of probability weighting which overweight tail events are finding many applications in finance. However, probability weighting has not yet been applied to equity premium prediction or to constructing optimal market timing investment strategies. We show that a measure of market optimism from a representative agent asset pricing model with probability weighting can be used to construct optimal dynamic investment strategies that outperform the buy‐and‐hold strategy and strategies generated by 17 leading equity premium predictors. We further show that this theory‐based measure of market optimism predicts the equity premium and market Sharpe ratio in‐sample and out‐of‐sample. The predictability is not subsumed by disaster probabilities, market sentiment, or market skewness. Our results indicate that our theory‐based measure provides a distinct channel for predicting aggregate stock returns.

On penalized goal-reaching probability minimization under borrowing and short-selling constraints

Abstract We consider a robust optimal investment–reinsurance problem to minimize the goal-reaching probability that the value of the wealth process reaches a low barrier before a high goal for an ambiguity-averse insurer. The insurer invests its surplus in a constrained financial market, where the proportion of borrowed amount to the current wealth level is no more than a given constant, and short-selling is prohibited. We assume that the insurer purchases per-claim reinsurance to transfer its risk exposure to a reinsurer whose premium is computed according to the mean–variance premium principle. Using the stochastic control approach based on the Hamilton–Jacobi–Bellman equation, we derive robust optimal investment–reinsurance strategies and the corresponding value functions. We conclude that the behavior of borrowing typically occurs with a lower wealth level. Finally, numerical examples are given to illustrate our results.