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The purpose of this paper is to study the problem of optimal Ramsey taxation in a finite-planning-horizon, representative-agent endogenous growth model including government expenditures as a productive input in capital formation and also with hidden actions.

Technically, Malliavin calculus and forward integrals are naturally introduced into the macroeconomic theory when economic agents are faced with different information structures arising from a non-Markovian environment.

The major result shows that the well-known Judd-Chamley Theorem holds almost surely if the depreciation rate is strictly positive, otherwise Judd-Chamley Theorem only holds for a knife-edge case or on a Lebesgue measure-zero set when the physical capital is completely sustainable.

The author believes that the approach developed as well as the major result established is new and relevant.

On May 17, 2012, the social networking company Facebook Inc. fixes its initial public offering (IPO) price at $38.00 a share. Over the next couple of months, contrary to expectations raised by previous IPOs, the stock price crashes more than 50 per cent. Immediately, the question arises whether the issuer’s or the stock market’s pricing of the share are in line with the firm’s fundamentals. Thus, the purpose of this paper is to determine the company value in close proximity to the date of IPO.

As Facebook is an archetypal internet growth company, it is evaluated using the Schwartz/Moon model. This approach features significant advantages over traditional valuation models and more adequately captures the characteristics of growth companies.

As of September 30, 2012, the fundamental share value determined was $26.53, which exceeded the market price per share of $22.66 by 22.48 per cent, but was far less than the IPO stock price. The subsequent sensitivity analysis reveals the robustness of the result to key input parameters.

The results raise doubts about the IPO price of Facebook. Furthermore, this paper is of value from a more conceptual perspective in that an extended version of the Schwartz/Moon model is provided. Beyond extensions previously discussed in the subject-based literature, the authors include stochastic interest rates (as an additional source of uncertainty) and investigate their valuation effects.

The idea of using stochastic control methods for theoretical studies of portfolio management has long been standard, with maximum expected utility criteria commonly being used. But in recent years a new kind of criterion, the risk sensitive criterion, has emerged from the control theory literature and been applied to portfolio management. This paper studies various economic properties of this criterion for portfolio management, thereby providing justification for its theoretical and practical use. In particular, it is shown that the risk sensitive criterion amounts to maximizing a portfolio's risk adjusted growth rate. In other words, it is essentially the same as what is commonly done in practice: find the best trade‐off between a portfolio's average return and its average volatility.

This paper aims to explore the effects of illiquidity on portfolio weight and return dynamics.

Using a novel continuous-time framework, the paper makes two key contributions to the literature on asset pricing and illiquidity. The first is to study the effects of illiquidity on portfolio weight dynamics. The second contribution is to analyze how illiquidity affects the risk/return dynamics of a portfolio.

The numerical results highlight that investors should be prepared for potentially large and skewed variations in portfolio weights and can be away from optimal diversification for a long time when adding illiquid assets to a portfolio. Additionally, the paper shows that illiquidity increases portfolio risk. Interestingly, this effect gets more pronounced when the return correlation between the illiquid and liquid asset is low. Thus, there is a correlation effect in the sense that illiquidity costs, as measured by the increase in overall portfolio risk, are inversely related to the return correlation of the assets.

This is the first paper that highlights that the increase in portfolio risk caused by illiquidity is inversely related to the return correlation between the liquid and illiquid assets. This important economic result contrasts with the widely used argument that the benefit of adding illiquid (alternative) assets to a portfolio is their low correlation with (traditional) traded assets. The results imply that the benefits of adding illiquid assets to a portfolio can be much lower than typically perceived.

The purpose of this paper is to model the announcement returns of merging firms based on managerial overconfidence about merger synergy.

The paper applies continuous‐time real options techniques and game theoretic concepts. Managerial overconfidence and strategic interaction between the bidder and the target are incorporated into the model.

This model implies that: abnormal returns to bidding shareholders will be negative with a high degree of managerial overconfidence; combined returns to shareholders are usually positive; and both the bidder's and the target's abnormal returns are related to industry characteristics, the degree of managerial overconfidence, and the way merger synergies are divided.

This paper, for the first time, reconciles theoretically the following stylized facts: combined returns to shareholders are usually positive; and returns to the acquirer are, on average, not positive. In addition, the model generates new predictions relating these returns to industry characteristics and the degree of managerial overconfidence.

This paper aims to provide a theoretical conception that establishes growth rate dynamics for co-operatives and studies Moroccan co-operatives’ start-ups and closures, by analyzing the co-operatives’ growth rate speed of adjustment (SOA).

This paper documents the basic patterns of entry and exit flow for agricultural, artisanal, housing and fishery co-operatives; highlights, with econometric tests, whether co-operatives’ growth rate is mean reverting or a unit root random walk; and estimates the growth rate adjustment speed, using a quadratic interval reverting model to capture both the upward and downward speeds of adjustment.

The empirical results indicate that co-operatives’ growth rate is significantly mean reverting for all sectors. Also, it concludes that the upward and downward adjustment speeds are significantly different within and between sectors, with negative indicator for artisanal co-operatives. The paper discusses these results, which are of interest to academics and policymakers.

The study does not investigate the causes of the growth rate SOA. Further, in-depth work with the results of this study would help scholars and policymakers to get close to the accurate research questions that characterize the mean reverting and affects the adjustment processes for Moroccan co-operatives.

The suggested model – with upward and downward adjustment speeds– could be valuable for policymakers’ strategies on co-operatives’ emergence.

The paper moves policymakers closer to social work and socio-economic trends to explain the empirical regularities of co-operatives’ dynamics. The model could be of value to avoid a volatile rate of entries and exits, to ensure continuity, to avoid fast failure of co-operative memberships and then to achieve the social inclusion.

The paper provides empirical evidence and results for co-operatives’ start-ups and closures adjustment speed and determines the conditions in which government policy must be clarified and specified. To the best of the authors’ knowledge, this paper is the first empirical analysis for the co-operatives’ SOA over entry and exit dynamics.

Facing the challenges posed by the pandemic of COVID-19, this paper aims to contribute to the resilience of businesses through the development of a real options approach (ROA) that provides alternatives and opportunities for a decision process under situations when future events and outcomes are unknown and not capable of being known from current information.

This paper involves a stochastic modelling process in generating a set of absolute option values, using available data and scenarios from the COVID-19 pandemic event. The modelling and simulations using ROA suggest how strategic portfolios resolve the growing problem during the endemic to all but in the most isolated societies.

This study finds the emergent correlation between circuit breakers and lockdowns, which have brought about a “distorted gravity” effect (inverse growth of global businesses and trades). However, “time-to-build” real options (i.e. deferral, expand, switch and compound exchange) start to function in the adaptive-transformative capabilities for growth opportunities of both government and corporate sectors. Significantly, some sectors grow faster than others while the compound exchange remains primarily challenging. Clearly, the government and corporate sectors are entangled, inevitably, the decoherence allows for the former to change uncertainty in the latter; therefore, government sector options change option values in the corporate sector.

The ROA by empirically focusing on both government and corporate sectors demonstrates under conditions of uncertainty how options in decision-making generate opportunities that hitherto have not been recognised and exercised upon by research in the immediate context of the COVID-19 pandemic. Importantly, the ROA provides an insightful concatenation (capability–behaviour approach) that drives resilience.

The software reliability models to describe the reliability growth phenomenon are formulated by any stochastic point process with state‐dependent or time‐dependent intensity function. On the other hand, to deal with the environmental data, which consists of covariates influencing times to software failure, it may be useful to apply the Cox’s proportional hazards model for assessing the software reliability. In this paper, we review the proportional hazards software reliability models and discuss the problem to determine the optimal software release time under the expected total software cost criterion. Numerical examples are devoted to examine the dependence of the covariate structure in both the software reliability prediction and the optimal software release decision.

The purpose of this paper is to study the asset allocation problem for a pension fund which maximizes the expected present value of its wealth augmented by the prospective mathematical reserve at the death time of a representative member.

The paper applies the stochastic optimization technique in continuous time. In order to present an explicit solution it considers the case of both deterministic interest rate and market price of risk.

The paper demonstrates that the optimal portfolio is always less risky than the Merton's (1969‐1971) one. In particular, the asset allocation is less and less risky until the pension date while, after retirement of the fund's representative member, it becomes riskier and riskier.

The paper shows the best way for managing a pension fund portfolio during both the accumulation and the decumulation phases.

The paper fills a gap in the optimal portfolio literature about the joint analysis of both the actuarial and the financial framework. In particular, it shows that the actuarial part strongly affects the behaviour of the optimal asset allocation.

The purpose of this paper is to apply a numerical simulation of stochastic processes to the problem of real estate investment appraisal.

These uncertain operating costs are integrated into an enhanced dynamic simulation. To model the dynamics in the uncertainty of the cost schedule, a range of different types of stochastic processes is used. The operating costs are classified by cost drivers and an appropriate stochastic process is determined for each of the derived cost clusters. To optimise the capital structure in this application, heuristic optimisation with genetic algorithms is used.

The application of the model to real world investment situations shows that linear and deterministic modelling underestimates the risk‐generating effect of uncertain operating expenses, which often can lead to inefficient investment decisions.

In a further application of the model, the authors demonstrate the effect of uncertain operating costs on the optimal capital structure of real estate investments.

In contrast to models in the literature that are usually focussed on the income side, here the focus is on the uncertain dynamics of real estate operating costs as a key factor affecting return.