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The classical Neyman-Pearson lemma studies the optimal test for discriminating between two probability measures and has important applications in various fields. Especially, Neyman-Pearson lemma can be regarded as a tool for solving stochastic control problems with constraints in the economic and financial fields. In this paper, we study the Neyman-Pearson theory for convex expectations (convex risk measures) on $ L^{\infty}(\mu) $. Without assuming that the level sets of penalty functions are weakly compact, a new approach is proposed to find a representative pair $ (Q^{\ast}, P^{\ast}) $ such that the optimal tests are just the classical Neyman-Pearson tests between the representative probabilities $ Q^{\ast} $ and $ P^{\ast} $. The key observation is that the feasible test set is compact in the weak$ ^{\ast} $ topology by a generalized result of Banach-Alaoglu theorem. Then the minimax theorem can be applied and the representative probability $ Q^{\ast} $ is found first. Secondly, under the probability $ Q^{\ast} $, we find the representative probability measure $ P^{\ast} $ by solving a dual problem. Finally, we apply our results to a shortfall risk minimizing problem in an incomplete financial market. [ABSTRACT FROM AUTHOR]

This paper presents the analysis of the existence of equilibria in a two-period general equilibrium model with incomplete financial markets and real assets by means of a variational inequality approach. A definition of fictitious equilibrium is presented and it is shown to be equivalent to the definition of equilibrium under a suitable rank condition of the return matrix. Then the fictitious equilibrium is characterized in terms of a generalized quasi-variational inequality involving Grassmannian manifolds. The chosen variational inequality is constituted by two parts: the former one relates to the individuals' maximization problems and the latter one exploits the market clearing conditions. [ABSTRACT FROM AUTHOR]

The paper introduces U-S chance spaces, a new framework based on uncertainty theory and sub-linear expectation theory, to depict human uncertainty and sub-linear features, simultaneously. These spaces can be used to analyze the characteristics of uncertain random variables and study investments and other related issues in incomplete financial markets. Within the framework, sub-linear expectation theory describes the randomness in financial behaviors, while uncertainty theory describes the uncertainty associated with government macro-control or experts' opinions. The main achievement of this paper is the derivation of the Kolmogorov law of large numbers for uncertain random variables under U-S chance spaces. Examples are provided, and the theorems can be applied to uncertain random variables that are functions of random variables with symmetric or asymmetric distributions and uncertain variables with symmetric or asymmetric distributions. In some cases, when both random and uncertain variables are symmetric, the limit in the law exhibits the form that is characterized by symmetrical uncertain variables. [ABSTRACT FROM AUTHOR]

We consider the problem of pricing in a large market, which arises as a limit of small markets within which there are finitely many traded assets. We show that this framework allows accommodating both marginal-utility-based prices (for stochastic utilities) and arbitrage-free prices. Adopting a stochastic integration theory with respect to a sequence of semimartingales, we introduce the notion of marginal-utility-based prices for the large (post-limit) market and establish their existence, uniqueness and relation to arbitrage-free prices. These results rely on a theorem of independent interest on utility maximisation with a random endowment in a large market that we state and prove first. Further, we provide approximation results for the marginal-utility-based and arbitrage-free prices in the large market by those in small markets. In particular, our framework allows pricing asymptotically replicable claims, where we also show consistency in the pricing methodologies and provide positive examples. [ABSTRACT FROM AUTHOR]

Current methodologies for finding portfolio rules under the Merton framework employ hard-to-implement numerical techniques. This work presents a methodology that can derive an allocation à la Merton in a spreadsheet, under an incomplete market with a time-varying dividend yield and long-only constraints. The first step of the method uses the martingale approach to obtain a portfolio rule in a complete artificial market. The second step derives a closed-form optimal solution satisfying the long-only constraints, from the unconstrained solution of the first step. This is done by determining closed-form Lagrangian dual processes satisfying the primal-dual optimality conditions between the true and artificial markets. The last step estimates the parameters defined in the artificial market, to then obtain analytical approximations for the hedging demand component within the optimal portfolio rule of the previous step. The methodology is tested with real market data from 16 US stocks from the Dow Jones. The results show that the proposed solution delivers higher financial wealth than the myopic solution, which does not consider the time-varying nature of the dividend yield. The sensitivity analysis carried out on the closed-form solution reveals that the difference with respect to the myopic solution increases when the price of the risky asset is more sensitive to the dividend yield, and when the dividend yield presents a higher probability of diverging from the current yield. The proposed solution also outperforms a known Merton-type solution that derives the Lagrangian dual processes in another way. [ABSTRACT FROM AUTHOR]

How should the government respond to automation? We study this question in a heterogeneous agent model that takes worker displacement seriously. We recognize that displaced workers face two frictions in practice: reallocation is slow and borrowing is limited. We analyze a second best problem where the government can tax automation but lacks redistributive tools to fully alleviate borrowing frictions. The equilibrium is (constrained) inefficient and automation is excessive. Firms do not internalize that automation depresses the income of automated workers early on during the transition, precisely when they become borrowing constrained. The government finds it optimal to slow down automation on efficiency grounds, even when it does not value equity. Quantitatively, the optimal speed of automation is considerably lower than at the laissez-faire. The optimal policy improves efficiency and delivers meaningful welfare gains. [ABSTRACT FROM AUTHOR]

Arrow and Pratt developed the risk aversion theory for utility functions. We present a novel framework in this paper: risk aversion in an incomplete market influenced by government regulation. The characteristics of an incomplete market and government regulation are described by sub-linear expectation theory and uncertainty theory, respectively. In this framework, we give the expressions of expectations of risk and prove Jensen's inequality. Then we introduce the risk premium, find its approximate value range, and prove Pratt's theorem in this case. Finally, a special type of risk aversion (decreasing risk aversion) and some operations that preserve decreasing risk aversion are given. [ABSTRACT FROM AUTHOR]

Road cabotage within the EU, as a share of domestic transport of goods, varies greatly across member states. This can partly be attributed to EU's regime for consecutive cabotage. In addition to economic factors that reflect incomplete market integration, spatial factors appear to affect the impact of the current regime. The impact seems stronger for geographically large and centrally located countries with interregional homogeneity in trade. This may reflect that foreign hauliers under such conditions can utilize the characteristics of their standardized long-range trucks better, or because the likelihood of successfully fixing three favourable long-distance cabotage assignments within the seven days limit increases. Potential amendments to regulations in order to equalize the impact of EU's consecutive cabotage regime across member states' spatial characteristics include removing the limits to the number of trips within the seven days' time frame or shortening the time frame for carrying out the current maximum of three trips. • EU's « three-in-seven » road haulage cabotage rule affects member states unevenly across spatial characteristics. • The domestic market effect appears stronger for large countries with interregional homogeneity in trade. • The study argues for reforms like the rejected EC's 2017 proposal of no restrictions to the number of cabotage assignments. [ABSTRACT FROM AUTHOR]

Severance savings accounts (SSA) is an important government program aimed at protecting laid-off workers and stimulating savings. We analyze the distributive and aggregate effects of SSA in a rich life-cycle model with heterogeneous agents and incomplete markets. The model is estimated to be consistent with micro and macro data from Brazil. Our analysis reveals that, despite a decrease in voluntary savings, the policy expands aggregate savings, output, and wages, leading to long-run welfare gains. We show that although better risk sharing is important for our findings, the bulk of the gains come from improved efficiency as labor productivity increases and labor supply is reallocated towards highly educated workers and the early stages of the life cycle where agents are generally poorer and leisure is less valued. Interestingly, most of the gains we find accrue to less educated agents as the distribution of this group is skewed towards the informal sector, and they do not directly incur the additional burden from the increase in contributions. We also explore an alternative policy design in which households are allowed to access their severance savings accounts only after retirement, as in a defined contribution pension system. We find that despite greater uncertainty in medical costs later in life, households prefer a more flexible system that provides access to the SSA fund during working-age and after retirement. [ABSTRACT FROM AUTHOR]

We present a nonparametric method to recover a bound on ex ante dispersion of beliefs (DBB) from asset prices with minimal assumptions. DBB constrains the dispersion among all possible distributions in an economy, consistent with observed prices and subject to a good-deal bound. In model-based economies, DBB effectively tracks belief heterogeneity and serves as a diagnostic tool for evaluating model calibrations. Empirically, DBB relates to common proxies of belief dispersion, offering a real-time, market-implied disagreement measure. Our versatile approach applies to both complete and incomplete markets represented by any asset class. This paper was accepted by Kay Giesecke, finance. Supplemental Material: The online appendix and data files are available at https://doi.org/10.1287/mnsc.2022.01587. [ABSTRACT FROM AUTHOR]

The price of a safe asset reflects not only the expected discounted future cash flows but also future service flows, since retrading allows partial insurance of idiosyncratic risk in an incomplete markets setting. This lowers the issuers' interest burden. As idiosyncratic risk rises during recessions, so does the value of the service flows bestowing the safe asset with a negative β. The resulting exorbitant privilege resolves government debt valuation puzzles and allows the government to run a permanent (primary) deficit without ever paying back its debt, but the government faces a debt Laffer curve. [ABSTRACT FROM AUTHOR]

Copyright of Revue d'Économie Régionale & urbaine is the property of Librairie Armand Colin and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

We provide conditions for the feasibility of robust Pareto-improving (RPI) policies when markets are incomplete and the interest rate is below the growth rate. We allow for arbitrary heterogeneity in preferences and income risk and a wedge between the return to capital and bonds. An RPI improves risk sharing and can induce a more efficient level of capital. Elasticities of aggregate savings to changes in interest rates are the crucial ingredients to the feasibility of RPIs. Government debt may complement rather than substitute for capital in an RPI. Our analysis emphasizes the welfare-improving qualities of government bonds versus explicit redistribution. (JEL D52, E43, E62, H20, H63) [ABSTRACT FROM AUTHOR]

Compared to the distributions of earnings, the distributions of wealth in the US and many other countries are strikingly concentrated on the top and skewed to the right. To explain the income and wealth inequality, we provide a tractable heterogeneous‐agent model with incomplete markets in continuous time. We separate illiquid capital assets from liquid bond assets and introduce jump risks to capital income, which are crucial for generating a thicker tail of the wealth distribution than that of the labor income distribution. Under recursive utility, we derive optimal consumption and wealth in closed form and show that the stationary wealth distribution has an exponential right tail that closely approximates a power‐law distribution. Our calibrated model can match the income and wealth distributions in the US data including the extreme right tail of the wealth distribution. [ABSTRACT FROM AUTHOR]

The strategic decisions of the manufacturer and the retailer directly affect the stability of the supply chain system. The delay and incompleteness of the market information greatly increase the complexity and variability of the decision-making process. In order to solve this problem, by using the nonlinear dynamics theory, this paper constructs a discrete dynamic model with a time delay. The sufficient conditions for the existence and the local asymptotic stability are obtained. The delayed threshold provides a helpful judgment basis for the supply chain members' decisions and the system stability. In addition, the manufacturer's quality strategy is divided into the static and dynamic cases. Based on these cases, the influence of corporate social responsibility (CSR) and decision-making adjustment speed on system stability is discussed. The results show that when a dynamic quality strategy is adopted, the increase in CSR preference can effectively restrain the destabilized system and improve the benefits of supply chain members. [ABSTRACT FROM AUTHOR]

There are two important dimensions that matter when we write down a model economy of a country that is open to international financial markets. The first one is its size, and the second one is its asset market structure. Small open economies are price takers so the analysis happens in partial equilibrium, while countries that are "sufficiently" large can affect international prices and the analysis happens in general equilibrium. The second important dimension is the asset market structure. If markets are complete there is full risk sharing, while if markets are incomplete there is not. In this paper I explore how these two dimensions--size and market structure--affect the conditions for the existence and the uniqueness of the equilibrium in economic models, and discuss how to achieve those conditions when they are not present. I finish by discussing how these implications change when a tax on the return to net foreign assets is introduced, generating endogenous incomplete markets. [ABSTRACT FROM AUTHOR]

We investigate the stability of the Epstein–Zin problem with respect to small distortions in the dynamics of the traded securities. We work in incomplete market model settings, where our parametrization of perturbations allows for joint distortions in returns and volatility of the risky assets and the interest rate. Considering empirically the most relevant specifications of risk aversion and elasticity of intertemporal substitution, we provide a condition that guarantees the convexity of the domain of the underlying problem and results in the existence and uniqueness of a solution to it. Then, we prove the convergence of the optimal consumption streams, the associated wealth processes, the indirect utility processes, and the value functions in the limit when the model perturbations vanish. [ABSTRACT FROM AUTHOR]

In this paper, we explore the connection between a single index model under the real-world probability measure and martingale pricing via minimal relative entropy or Esscher transform, within the context of a one-period market model, possibly incomplete, with multiple risky assets and a single risk-free asset. The minimal relative entropy martingale measure and the Esscher martingale measure coincide in such a market, provided they both exist. From their Radon–Nikodym derivative, we derive a portfolio of risky assets in a natural way, termed portfolio G. Our analysis shows that pricing using the Esscher or minimal relative entropy martingale measure is equivalent to a single index model (SIM) incorporating portfolio G. In the special case of elliptical returns, portfolio G coincides with the classical tangency portfolio. Furthermore, in the case of jointly normal returns, Esscher or minimal relative entropy martingale measure pricing is equivalent to CAPM pricing. [ABSTRACT FROM AUTHOR]

We derive a Clark-Ocone-Haussmann (COH) type formula under a change of measure for L 1 -canonical additive processes, providing a tool for representing financial derivatives under a risk-neutral probability measure. COH formulas are fundamental in stochastic analysis, providing explicit martingale representations of random variables in terms of their Malliavin derivatives. In mathematical finance, the COH formula under a change of measure is crucial for representing financial derivatives under a risk-neutral probability measure. To prove our main results, we use the Malliavin-Skorohod calculus in L 0 and L 1 for additive processes, as developed by Di Nunno and Vives (2017). An application of our results is solving the local risk minimization (LRM) problem in financial markets driven by pure jump additive processes. LRM, a prominent hedging approach in incomplete markets, seeks strategies that minimize the conditional variance of the hedging error. By applying our COH formula, we obtain explicit expressions for locally risk-minimizing hedging strategies in terms of Malliavin derivatives under the market model underlying the additive process. These formulas provide practical tools for managing risks in financial market price fluctuations with L 1 -additive processes. [ABSTRACT FROM AUTHOR]

We consider the operation of a non-financial corporation and present a novel risk-management framework that supports the joint optimization of the firm's operational and financial decisions. Specifically, we study the problem of maximizing the firm's operating profits when these profits depend on movements in the financial markets, and where the decision maker—the firm's manager—is risk averse. Critically, our framework (i) imposes risk aversion through a generic class of risk constraints, and (ii) considers explicitly the differences that can exist between the shareholders' and manager's beliefs about future market risks. Together, these aspects allow us to remove speculation so that financial instruments can only be used for hedging purposes. We analyze our problem in an incomplete financial market setting and consider different informational assumptions. Within this framework, we characterize the optimal financial hedging strategy so that the problem reduces to a constrained maximization over operational policies. Our results show how financial hedging can be effectively used to expand the set of admissible operating policies, and identify conditions under which the risk constraint can be completely ignored when solving for an optimal operating policy. We illustrate our methodology in the context of an exporter firm which faces exchange rate risk in trading. [ABSTRACT FROM AUTHOR]

Income interventions with pro-poor targeting is a common fiscal policy around the world. However their distributional effects on consumption and savings are not well understood. Motivated by the Mahatma Gandhi National Rural Employment Guarantee Act (MGNREGA), we use longitudinal data on income and consumption of Indian households to estimate distributional effects of such interventions in a model with endogenous consumption and savings distribution, where households face uninsured income risks. In the model, a standard scheme of interventions that consistently targets low-income cohorts, has small distributional impacts on targeted and non-targeted cohorts alike. In contrast, a fiscally-equivalent scheme that changes the expected income profile of the targeted households in the same initial cohort irrespective of their future incomes, generates larger effects by changing income mobility for both the targeted and non-targeted cohorts. This mobility-based channel generates consumption responses even though the magnitude of the shock is lesser for the initially targeted cohort, as it more than offsets the effect from permanent income shock. Quantitatively, such an intervention in the order of 0.6 percent of output, approximating the Indian scenario, increases consumption share of the targeted cohort by nearly 2.5 percent, five times as large as the effect of standard interventions. The distributional effects are similar to those arising from a counterfactual policy of universal basic income. [ABSTRACT FROM AUTHOR]

In the allocation of resources toward public infrastructure, spending on maintenance is typically neglected. Using a heterogeneous agent model, we find that reallocating funding away from new infrastructure investment and toward maintenance raises the effectiveness of existing public infrastructure and thus yields gains in GDP and in aggregate welfare. Richer households experience larger welfare gains than poorer households. A reallocation that takes funding away from maintenance is found to have adverse effects on GDP and aggregate welfare. Raising new funding with taxation yields larger positive benefits if this additional spending is divided between maintenance expenditures and investment in new infrastructure. Giving in to the "Tyranny of the Ribbon" by policymakers, that is, raising new funding to be spent only on new infrastructure, is shown to be the worse option. [ABSTRACT FROM AUTHOR]

The purpose of this paper is to illustrate the pricing of options in an incomplete market using the new consistent uplifted martingale measure methodology introduced by Grigorian and Jarrow [2024, Filtration Reduction and Incomplete Markets, Frontiers of Mathematical Finance, 3(1), 78–105; 2023, Filtration Reduction and Completeness in Brownian Motion Models. Working Paper, Cornell University; 2024, Filtration Reduction and Completeness in Jump-Diffusion Models. Working Paper, Cornell University]. We apply it to an incomplete market where a stock has stochastic volatility. Two valuation formulas are generated, depending upon whether the trader is more concerned about volatility or price risk in the construction of a partial replicating portfolio for the option's payoff. [ABSTRACT FROM AUTHOR]

A derivative is a financial asset whose future payoff is a function of underlying assets. Pricing a financial derivative involves setting up a market model, finding a martingale ("fair game") probability measure for the model from the existing asset prices, and using that probability measure to price the derivative. When the number of underlying assets and/or the number of market outcomes in the model is large, pricing can be computationally demanding. In this work, we first formulate the pricing problem in a linear algebra setting, including the realistic setting of incomplete markets where derivatives do not have a unique price. We show that the problem can be solved with a variety of quantum techniques such as quantum linear programming and the quantum linear systems algorithm. While in previous works the martingale measure is assumed to be given, here it is extracted from market variables akin to bootstrapping, a common practice among financial institutions. We discuss the quantum zero-sum game algorithm and the quantum simplex algorithm as viable subroutines. For quantum linear systems solvers, we formalize a new market assumption milder than market completeness, which allows the potential for large speedups. Towards prototype use cases, we conduct numerical experiments motivated by the Black–Scholes–Merton model. [ABSTRACT FROM AUTHOR]

This research is devoted to studying a geometric Brownian motion with drift switching driven by a 2 χ 2 Markov chain. A discrete-time multiplicative approximation scheme was developed, and its convergence in Skorokhod topology to the continuous-time geometric Brownian motion with switching has been proved. Furthermore, in a financial market where the discounted asset price follows a geometric Brownian motion with drift switching, market incompleteness was established, and multiple equivalent martingale measures were constructed. [ABSTRACT FROM AUTHOR]

Copyright of International Journal of Disciplines Economics & Administrative Scienves Studies is the property of International Journal of Disciplines in Economics & Administrative Sciences Studies and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

We study the currency risk premium and the forward premium bias in a two‐country New Keynesian model with production, no physical capital, and recursive utility. Monetary policy follows an interest rate feedback rule and exogenous total factor productivity (TFP) growth follows a long‐run risk process with stochastic volatility, which we estimate from data. With cross‐country heterogeneity in TFP and monetary policy, reasonable currency risk premia emerge under complete and incomplete markets but the forward premium bias is trivial. We diagnose the challenge faced by this fairly standard production model to explain the forward premium bias. [ABSTRACT FROM AUTHOR]

Due to its unique flavor, extremely high nutritional value, and health functions, Aronia has great development and utilization prospects. To fill the gap of incomplete market research in the Aronia industry in China and promote the development of the Chinese Aronia industry, this article retrieved Aronia-related companies through Tianyan Data. Results showed that the number of market entities engaged in the Aronia industry in China had been increasing year by year in the past 20 years, reaching growth peaks in 2016 and 2018, respectively. From the perspective of spatial distribution, Liaoning (32.89%), Jilin (18.86%), and Shandong (16.23%) were its main operating regions. Most enterprises (55%) had a registered capital of less than 5 million yuan, with a minority of Aronia enterprises owning trademarks (26.64%) and patents (10.48%). Until 2022, a total of 178 Aronia enterprises in China were in a state of survival and normal operation, with 50 being cancelled, revoked, rescinded, and dissolved. Currently, the main problems faced by the industry included a relatively single variety and cultivation mode, a low level of product deep processing, and insufficient brand recognition and effectiveness. At present, the domestic Aronia industry in China is still in its infancy. It is necessary to call on enterprises to integrate planting, processing, and sales, enrich product categories, develop new products, build leading enterprises, and improve the establishment of related industries. [ABSTRACT FROM AUTHOR]

Copyright of Balkan & Near Eastern Journal of Social Sciences (BNEJSS) is the property of Balkan & Near Eastern Journal of Social Sciences (BNEJSS) and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Concepts are introduced and applied for analyzing and selecting arbitrage portfolios in the face of uncertainty about initial positions and risk preferences. A stochastic arbitrage opportunity is defined as a zero-cost investment portfolio that enhances every feasible host portfolio for all admissible utility functions. The alternative to the existence of such investment opportunities is the existence of a solution to a dual system of asset pricing restrictions based on a class of stochastic discount factors. Feasible approaches to numerical optimization and statistical inference are discussed. Empirical results suggest that equity factor investing is appealing for all risk-averse stock investors with a wide range of initial position and sufficiently low transactions costs by mixing multiple factor portfolios with high after-cost appraisal ratios, low mutual correlation, and negative exposures to the relevant host portfolios. These findings weaken the case for risk-based explanations for the profitability of factor investing. This paper was accepted by Kay Giesecke, finance. Supplemental Material: The data files are available at https://doi.org/10.1287/mnsc.2023.4892. [ABSTRACT FROM AUTHOR]

Merchants need not fear platform entry because that can raise merchants' profits by resolving quality uncertainty for consumers. Merchants are wary of a platform's competitive entry reducing sales and margins. Profit-maximizing platforms seek to provide credible quality information to gain consumer trust and confidence. Can a platform enter so that resulting multisender prices alleviate consumers' uncertainty by signaling quality? Can merchants also benefit from platform entry? We provide answers by analyzing strategic platform and merchant pricing under quality uncertainty. A modeling innovation is a leader-follower framework for platform-merchant competition. Consumers resolve uncertainty using both platform and merchant prices. Using what we label perfect Bayes-consistent beliefs, we identify perfect Bayesian equilibrium that satisfies the intuitive criterion, and also out-of-equilibrium beliefs that are unprejudiced. A substantive finding is that platform entry can raise merchant profits when the quality is high by moving the equilibrium from pooling to separating, and supporting higher prices. Another strategic consequence of platform entry could be a separating equilibrium with incomplete market coverage due to price distortion moving to one of complete market coverage due to seller competition. Indeed, conditions exist in our model for an equilibrium outcome identical to complete information. Finally, facing entry cost, a platform may choose to enter only with high quality but quality revelation remains price dependent and not based on mere entry. History: Yuxin Chen served as the senior editor for this article. Funding: Y. Qiu was supported by the Natural Science Foundation of China [Grant 71902142] toward completion of this paper. Supplemental Material: The online appendix is available at https://doi.org/10.1287/mksc.2021.0227. [ABSTRACT FROM AUTHOR]

This paper sets up a small open new Keynesian economy model with constrained households and incomplete markets to address the driving forces of business cycles in Korea. It shows that there exists a substantial fraction of constrained households who cannot have access to financial market. Furthermore, the estimated model reveals that a TANK model is better than a RANK model in explaining business cycles in Korea. The effect of domestic productivity shock on Korean economy has dominated in the variations of output, while the contribution of the foreign productivity shock to the variations of output and inflation has increased after the Asian financial crisis. The monetary policy shock has dominated the variation of inflation at short and medium horizons. [ABSTRACT FROM AUTHOR]

This paper demonstrates the benefits, from an expected utility perspective, of including a derivative into the universe of tradeable assets under the affine GARCH model proposed by Heston and Nandi (Rev Financ Stud 13(3):585–625, 2000. https://doi.org/10.1093/rfs/13.3.585). For this purpose, we first introduce a Power Option into the market, derive its value and moment generating function thanks to the affine GARCH structure. We then expand on the results presented by Escobar-Anel et al. (Oper Res Perspect 9:100216, 2022) by solving for the optimal investment allocations into the stock, a cash account and the option. We show that investors who are able to include a derivative indeed outperform those who only invest into the stock and the bank account. In this spirit, investors who fail to include, even a low level of exposure to the derivative, could see up to 7% annual wealth-equivalent losses. This confirms findings in continuous-time models dating to Liu and Pan (J Financ Econ 69(3):401–430, 2003). An empirical analysis on the S &P500 confirms the superiority in terms of Sharpe ratio, and maximum drawdown of portfolios with options, in-sample and out-of-sample. [ABSTRACT FROM AUTHOR]

Recent theoretical advances suggest that capital income risk, rather than earnings uncertainty, is the key determinant of fat-tailed behavior of stationary wealth distributions. I provide novel insights into this issue by studying an incomplete market model with general time and state separable preferences, where parental altruism and unobservable idiosyncratic shocks engender non-linear bequest rules. I analytically pin down conditions on the preference structure and other model's primitives under which optimal bequest behavior hinders intergenerational wealth transmission for any degree of capital income risk, causing the dynamics of wealth to converge to a unique (stationary) distribution with thin tails. These results imply, in particular, that (i) the stochastic properties of labour income risk (as shaped by, e.g. fiscal policies) may play a role in defining the structure of the upper tail of the limiting distribution of wealth, and that (ii) matching empirically documented fat tails with choice theoretic frameworks of wealth dynamics requires joint restrictions on preferences and calibrated earnings processes to be met. [ABSTRACT FROM AUTHOR]

Classical indifference valuation, a widely studied approach in incomplete markets, uses critically the a priori knowledge of the characteristics (arrival, maturity, payoff structure) of the projects in consideration. This assumption, however, may not accommodate realistic scenarios in which projects, not initially anticipated, arrive at later times. To accommodate this, we employ forward indifference valuation criteria, which by construction are flexible enough to adapt to such "non-anticipated" cases while yielding time-consistent indifference prices. We consider and analyze in detail two representative cases: valuation adjustments due to incoming non-anticipated project and the relative forward indifference valuation of new projects in relation to existing ones. [ABSTRACT FROM AUTHOR]

Implementing reverse logistics in the construction industry is considered a crucial method to achieve a circular economy. Despite a wealth of research focusing on improving reverse logistics systems, businesses still encounter challenges during the implementation process. Therefore, this study conducted a systematic literature review utilizing bibliometric methods to analyze 623 articles on reverse logistics in the construction industry published on Web of Science from 1995 to 2023. Additionally, a comprehensive review of 56 high-quality literature on obstacles to implementing reverse logistics in the construction industry and optimizing reverse supply chains was conducted. This review uncovered the current status and challenges of implementing reverse logistics in the construction industry and proposed potential solutions to address these issues. The main findings of this study include: (1) increasing academic interest in construction waste reverse logistics, with Chinese scholars leading the way and publications predominantly in environmental and construction journals, with limited coverage in logistics journals; (2) the primary obstacles to implementing reverse logistics in the construction industry lie in supply chain management, such as lacking deconstruction designs, incomplete recycling markets, difficulties in evaluating the quality of secondary materials, and insufficient supply chain integration; (3) proposing a framework for a construction industry reverse logistics supply chain ecosystem, aiming to establish a platform to facilitate online collection of construction waste, online transactions of secondary materials, end-to-end monitoring, and data analytics for consultation. [ABSTRACT FROM AUTHOR]

We present and solve an optimal asset allocation problem under a weighted limited expected loss (WLEL) constraint. This formulation encompasses the risk management problem with a limited expected loss (LEL) constraint as a specialized instance and offers a pertinent internal risk management instrument for firms. We observe that a WLEL constraint makes the optimizing investor pursue less volatile payoffs than the unconstrained Merton solution. Compared to the LEL-constrained problem with the same weighted default threshold, the WLEL optimal terminal wealth displays a less dispersed distribution with a smaller variance, suggesting a more secure risk management framework. Conducting a comprehensive equilibrium analysis in the presence of a WLEL risk manager, we validate the relatively conservative investment approach undertaken by the WLEL manager. Subsequently, we expand our findings to encompass broader incomplete market settings, wherein the uniqueness of the equivalent local martingale measure is not assured. [ABSTRACT FROM AUTHOR]

The effectiveness of the stock market agents with complete information and incomplete information on market trends, prices and demand for stocks and the effect of employees' behavior on the lack of information on employees with complete information (mass behavior survey) have been investigated in this research. For this purpose, by providing a researcher made questionnaire in relation to the stock exchange, using the statistical inference, the analysis of the results of the research has been done and the validity of the presented relationships has been investigated using analytical hieratical approach (AHP). Because in this article, the impact of information on traders' behavior. The 30 of traders have been selected as a sampling sample for Iran Koodro's and Pars Petro-chemical shares in the period of 2022. According to the current questionnaire and its results and practical observations, it can be concluded that transactions with sufficient information on prices are more effective than transactions with full information. Consequently, companies with incomplete information are more successful in the short run. [ABSTRACT FROM AUTHOR]

We show how a heterogeneous agent New Keynesian (HANK) model with incomplete markets and portfolio choice can be estimated in state space using a Bayesian approach. To render estimation feasible, the structure of the economy can be exploited and the dimensionality of the model automatically reduced based on the Bayesian priors. We apply this approach to analyze how much inequality matters for the business cycle and vice versa. Even when the model is estimated on aggregate data alone and with a set of shocks and frictions designed to match aggregate data, it broadly reproduces observed US inequality dynamics. (JEL D31, D52, E12, E32, E52, E62) [ABSTRACT FROM AUTHOR]