Search results

The purpose of this paper is to investigate how to determine optimal investing stopping time in a stochastic environment, such as with stochastic returns, stochastic interest rate and stochastic expected growth rate.

Transformation method was used for solving optimal stopping problem by providing a way to transform path‐dependent problem into a path‐independent one. Based on option pricing theory, optimal investing stopping time was thought of as an optimal executed timing problem of American‐style option.

First, the authors transform a path‐dependent stop timing problem to a path‐independent one with transformation under very general conditions, to directly use the existing conclusion of optimal stopping time literature. Second, when dynamics of capital growth is homogeneous, the authors changed the two dimensional optimal stop timing problem into a single dimension problem based on the assumption of zero exercise costs. Third, the authors investigated the comparative dynamics about asset selling boundary on asset value, state variable and return predictability. With constant discount rate and growth rate, the optimal selling timing depends on the simple comparison between capital cost and growth rate.

The paper's contributions to analysis method may be as follows. The authors demonstrate how to transform a path‐dependent stopping problem into a path‐independent one under general conditions. The transform method in this article can be applied to other path‐dependent optimal stopping problems. In particular, a Riccati ordinary differential equation for the transformation is set up. In most examples commonly met in finance, the equation can be solved explicitly.

One of the agency conflicts between investors and managers in fund management is reflected by risk‐taking behaviors led by their different goals. The investors may stop their investments in risky assets before the end of the investment horizon to minimize risk, while the managers may do so to entrench their reputation so as to pursue better opportunities in the labor market. This study aims to consider a one principal‐one agent model to investigate this agency conflict.

The paper derives optimal asset allocation strategies for both parties by extending the traditional dynamic mean‐variance model and considering possibilities of optimal early stopping. Doing so illustrates the principal‐agent conflict regarding risk‐taking behaviors and managerial investment myopia in fund management.

This paper not only paves the way for further studies along this line, but also presents results useful for practitioners in the money management industry.

According to the theoretical analysis and numerical simulations, the paper shows that potential early stop can make the agency conflict worsen, and it proposes a way to mitigate this agency problem.

As one of the exploratory studies in investigating agency conflict regarding risk‐taking behaviors in the literature, this study makes multiple contributions to the literature on fund management, asset allocation, portfolio optimization, and risk management.

This survey explores the application of real options theory to the field of health economics. The integration of options theory offers a valuable framework to address these challenges, providing insights into healthcare investments, policy analysis and patient care pathways.

This research employs the real options theory, a financial concept, to delve into health economics challenges. Through a systematic approach, three distinct models rooted in this theory are crafted and analyzed. Firstly, the study examines the value of investing in emerging health technology, factoring in future advantages, associated costs and unpredictability. The second model is patient-centric, evaluating the choice between immediate treatment switch and waiting for more clarity, while also weighing the associated risks. Lastly, the research assesses pandemic-related government policies, emphasizing the importance of delaying decisions in the face of uncertainties, thereby promoting data-driven policymaking.

Three different real options models are presented in this study to illustrate their applicability and value in aiding decision-makers. (1) The first evaluates investments in new technology, analyzing future benefits, discount rates and benefit volatility to determine investment value. (2) In the second model, a patient has the option of switching treatments now or waiting for more information before optimally switching treatments. However, waiting has its risks, such as disease progression. By modeling the potential benefits and risks of both options, and factoring in the time value, this model aids doctors and patients in making informed decisions based on a quantified assessment of potential outcomes. (3) The third model concerns pandemic policy: governments can end or prolong lockdowns. While awaiting more data on the virus might lead to economic and societal strain, the model emphasizes the economic value of deferring decisions under uncertainty.

This research provides a quantified perspective on various decisions in healthcare, from investments in new technology to treatment choices for patients to government decisions regarding pandemics. By applying real options theory, stakeholders can make more evidence-driven decisions.

Decisions about patient care pathways and pandemic policies have direct societal implications. For instance, choices regarding the prolongation or ending of lockdowns can lead to economic and societal strain.

The originality of this study lies in its application of real options theory, a concept from finance, to the realm of health economics, offering novel insights and analytical tools for decision-makers in the healthcare sector.

In this paper, we view an individual's annuitization decision as an American style call option whose underlying asset is financial wealth, which controls the distance to annuitization. We then derive a certain threshold of wealth over which the individual is optimal to annuitize all of her wealth. We particularly focus on the effects of liquidity constraints on the individual's optimal annuitization decision, concerning their effects on the optimal investment and consumption strategies. We show that the annuitization decision can be significantly affected by the extent to which individual borrowing is constrained. More specifically, the optimal decision is for the individual to annuitize earlier with the tighter liquidity constrains she is exposed to than initially planned. This is particularly relevant to today's pandemic situation especially with the growing concern about cutting credit limits.

The authors formulate India’s energy targets in light of pushing for renewable energy sources and reducing the dependence on imported coal. Share of imported coal in electricity generation has been approximately 10 per cent in recent years. While investments in renewables have grown in recent years as seen in installed capacities, coal-fired electricity generation has grown because of rising demand for electricity. The purpose of this study is to find a planner solution when high global coal prices force greater investments in renewable energies.

The authors use real options approach where global coal prices are the stochastic variable. They present an optimal stopping problem and solving the problem backward, the revenues from continuing with the current energy generation mix and those from replacing imported coal with wind and solar is compared for each period.

The “trigger price” for global coal prices when it is optimal for the social planner to invest in additional wind and solar capacities is found. Trigger prices is the threshold when investment must be undertaken whatever be the future evolution of coal prices; this gives the problem a value of waiting. India cannot afford to wait to invest if faced with strict short-term goals.

The work evaluates India’s domestic targets and its Paris Agreement goals in light of using more of wind and sun and replacing imported coal. Various data sources (government reports, research articles) are consulted to predict shares of electricity from various sources in future and the authors find the operating costs and the investment costs associated with switching to renewables.

In this study, we analyze the power of the individual return-to-volatility security performance heuristic (ri/stdi) to simplify the identification of securities to buy and, consequently, to form the optimal no short sales mean–variance portfolios. The heuristic ri/stdi is powerful enough to identify the long and shorts sets. This is due to the positive definiteness of the variance–covariance matrix – the key is to use the heuristic sequentially. At the investor level, the heuristic helps investors to decide what securities to consider first. At the portfolio level, the heuristic may help us find out whether it is a good idea to invest in equity to begin with. Our research may also help to integrate individual security analysis into portfolio optimization through improved security rankings.

This study aims to generalize the following result of McDonald and Siegel (1986) on optimal investment: it is optimal for an investor to invest when project cash flows exceed a certain threshold. This study presents other results that refine or extend this one by integrating timing flexibility and changes in cash flows with time-varying transition probabilities for regime switching. This study emphasizes that optimal thresholds are either overvalued or undervalued in the absence of time-varying transition probabilities. Accordingly, the stochastic nature of transition probabilities has important implications to the search for optimal timing of investment.

The purpose of this paper is to present a clear path to securitize the longevity risk with two distinct swaps in order to inspire a new Chinese life market.

Studies on longevity risk securitization consist of three aspects, respectively, instrument design, pricing methodology and mortality projection. The swaps designed are referenced, respectively, to vanilla and complex survivor swaps (Dowd et al., 2006; Lin and Cox, 2005). Methods applied are RHH model and Gompertz law for mortality projection, as well as two-factor Wang transformation for pricing.

This paper figures out the market price of risk in Chinese annuity market, checks for the sensitivity of the price to parameters and tests the hedging effects by Monte Carlo simulation.

Based on the theoretical and numerical results, this paper suggests an effective way to possibly witness the birth of New Life Market in China.

In this chapter we present a continuous time model with reversible abatement capital in order to analyze the effects of environmental policies on the value of the firm and investment decisions. We show that the effects depend on what sort of future policy are implemented. We focus on investment effects of changes in corrective taxes to control the use of polluting inputs, and subsidies to promote abatement investment. We show that (1) while taxes have a depressive effect on capital accumulation, subsidies boost investment; (2) the impact of these policies on the value of the firm is ambiguous. This latter result has important empirical implications insofar as investment are based on the average value of the firm rather than the (unobservable) marginal value.

This paper aims to analyze the impact of the degree of local government decision-making competition on the optimal investment amount, investment location and investment failure of innovative investment enterprise under multiple risk appetite type of innovative investment enterprise. This paper also points out three regulation paths that central government could use to avoid the influence of local government decision-making competition on the validity of enterprise innovation investment (EII).

Based on analysis frame of government competition about unitary government states, this paper builds duopoly decision model to analyze influence of local government decision-making competition on EII. Considering information asymmetry and multiple risk appetite type of decision-maker, this paper analyzes influence of local government decision-making competition on location selection, the optimal investment amount, identification of investment failure and exit mechanism of EII according to different relationship between reference points of local government decision-making competition and EII.

The optimal investment amount of EII has positive correlation with risk appetite type of decision-maker, local government decision-making competition. Identification of investment failure and exit are divided into three phases. The boundary conditions are directly related to risk appetite type and amount of local government subsidy. Regional factor endowment and degree of preferential policy are main factors attracting enterprise investment. Local governments should analyze the interests of EII. There are three paths to avoid vicious competition among local governments: unified planning, revising of audit index, increasing penalties for failure of policies.

With rapid development of China's new urbanization process, urban economy has become an important carrier of economic development. Attracting foreign direct investment is an important measure to promote urban economic growth, and EII is the most important one. However new urbanization would lead to local government decision-making competition and then influence EII. Through analyzing influence of local government decision-making competition on EII, theory guidance could be provided to decision makers of innovation investment.