Return Uncertainty Research Articles

On the evolution of heuristics and bounded rational behavior in random games

The emergence of heuristics, sophisticated behavior—such as higher levels of Theory of Mind—and substantive rationality in strategic situations can be studied using evolutionary game theory to jointly account for the interactions between players and their environments. Research thus far has been relatively constrained by limiting analyses to a small number of simple games and by focusing on selection operating over actions rather than rules or policies that prescribe behavior in a wide range of games. As a result, the existing literature has not adequately reconciled the significant evidence amassed in the behavioral game theory literature that people use bounded-rational strategies, rather than the normative prescription (Nash equilibrium). I systematically explore the differential costs of implementing decision policies and how evolution is influenced by key environmental characteristics. Detailed maps linking the performance of policies to 3,060 environments are presented demonstrating that the steady state distribution of policies under replicator dynamics is strongly dependent on: a) complexity costs, derived from the opportunity cost associated with the decision time to execute the policies at a process-level and b) the environmental characteristics such as the size of the game, the degree of payoff uncertainty and the degree of mutual interests or conflict between players. Evolution rarely selects for substantive rationality (Nash equilibrium), favoring instead a plethora of bounded-rational policies with varying levels of theory of mind (Level-k models), and in some environmental niches other heuristics such as maxmin or maximization of joint payoffs to players. An intriguing finding is that there exist non-trivial environmental niches with moderate to high complexity costs, where random behavior can be selected for in conjunction with a policy that best-responds to randomness (Level-1). I conclude that while bounded-rational policies do not conform to the standards of substantive rationality, they exhibit both procedural and ecological rationality once the complexity of decision processes and interactions with environmental characteristics are accounted for.

A Robust Crop Rotation Optimization Model With Water Scarcity and Net Return Uncertainty Considerations

The tactical, technical, and economic considerations are critical factors in evaluating crop rotation decisions in any agricultural system. This system suffers from uncertainties that are amplified during the multi-period rotation planning. This study considers the crop rotation problem with water supply/demand and net return uncertainties, which vary within the allowable rotation cycle. Robust optimization is the most relevant tool for elaborating uncertainty in different parameters related to agricultural activities. It makes the formulated model numerically tractable, primarily when implemented in complex agricultural problems. The main objectives of this work include deciding the optimal cropping plans, achieving a reasonable income for the farmer, and taking water uncertainties into account on a tactical basis. All the mentioned goals are integrated while respecting the agronomic constraints and satisfying specific demand. A powerful feature of robust optimization is its robustness level adjustment for the solution against uncertainty sets. In this situation, the relationships between optimal values, the budget of uncertainty, and the perturbation values were outlined with insights towards tradeoff decisions. The proposed model compares the performance at each perturbation level with insights toward proper managerial decisions.

Ortalama-Aşağı Yönlü Varyans Tabanlı Risk Ölçütleri ve Stokastik Getirili Portföy Optimizasyonu

The downside risk measure methods have gained in popularity within the frame of the Post-Modern Portfolio theory. Many studies have suggested different cosemivariance formulas with the downside risk measures. The purpose of this study is to compare the performances of the portfolio optimization models that apply different risk measures such as variance, semi-variance, and lower partial moment (LPM) with the different cosemivariance formulas. In the study, the Estrada (2007) and Nawrocki (1991) approaches were chosen to demonstrate the differences between different cosemivariance statistics used in the semi-variance risk measures. The results of the models are also compared with the mean-variance results. Sharpe and Sortino ratios are used as a comparison measure. In the study, efficient portfolios are created for investors having different risk attitudes with the LPM approach. Additionally, portfolio optimization is conducted by using the LPM approach with the stochastic modeling to avoid the uncertainty of portfolio returns. It was concluded that the Nawrocki model is beneficial to control the downside risk and it is a better choice as it includes the calculation of correlations between the assets and that the stochastic return model produces more conservative results compared to the deterministic model.

ADVANTAGES AND RISKS OF ISLAMIC INVESTMENT

In the Islamic context, investing is highly recommended so that the future can be guaranteed. Of course, investments made by Muslims must be in accordance with Islamic rules. Investing in economy Islamic concepts will provide a sense of security and comfort for Muslim investors, without fear of deviating from Islamic teachings. As a devout Muslim, of course, investment choices must be appropriate and in accordance with the concept of Islam. The difference between conventional Islamic investment lies in the benefits given. The advantages of Islamic investment are in the form of profit sharing, while the conventional concept is interest. In the teachings of Islam, interest is haram, because it does not recognize value for money. In the view of Islam, money will not developed by itself but must go through productive and ruleful efforts. The purpose of making this paper is to discuss the advantages and risks in Islamic investment. This paper uses a literature review approach that comes from journals, books, the internet, and other sources. The results show that the advantages of Islamic investment are riba-free, minimal risk, Islamic management, halal and promoting social activities. Meanwhile, the risks that may be faced by investors are the risk of losing capital, the risk of uncertainty of return, and the difficulty of selling investment products. From the results, it was found that currently Islamic investment products are favored by non-Muslims alike. The concept of profit sharing is considered more profitable than interest. It can be concluded that Islamic rules can now be accepted by various groups of people in the world.

A multiobjective credibilistic portfolio selection model. Empirical study in the Latin American integrated market

This paper extends the stochastic mean-semivariance model to a fuzzy multiobjective model, where apart from return and risk, also liquidity is considered to measure the performance of a portfolio. Uncertainty of future return and liquidity of each asset are modeled using L-R type fuzzy numbers that belong to the power reference function family. The decision process of this novel approach takes into account not only the multidimensional nature of the portfolio selection problem but also realistic constraints by investors. Particularly, it optimizes the expected return, the semivariance and the expected liquidity of a given portfolio, considering cardinality constraint and upper and lower bound constraints. The constrained portfolio optimization problem resulting is solved using the algorithm NSGA-II. As a novelty, in order to select the optimal portfolio, this study defines the credibilistic Sortino ratio as the ratio between the credibilistic risk premium and the credibilistic semivariance. An empirical study is included to show the effectiveness and efficiency of the model in practical applications using a data set of assets from the Latin American Integrated Market.

Evaluation Of Investment In IoT Startup at PT TMI

Smartphone revolution, the rise of OTT (Over the Top) technology, and growth of mobile application drive explosion in data demand and erosion of legacy service, which voice and SMS (Short Messaging Service) revenue. It forces mobile telecommunication operators to explore new revenue sources through new business development by taking the opportunity across technology, media, and telecommunication (TMT). Telkomsel Mitra Inovasi (TMI), Telkomsel Corporate Venture Capital (CVC), conducts non-organic business development through investment in an early-stage startup from TMT sectors. January 2020, TMI followed in Series B1 funding of the Internet of Things (IoT) startup. The investment evaluation utilizes two factors which capital gain and incremental revenue to existing Telkomsel business. There is uncertainty in financial return on high-risk investments in a new startup company, and existing Telkomsel IoT provides smart connectivity services. However, connectivity will become increasingly commoditized, declining from 9% of total IoT revenue in 2018 to 5% in 2025. Consequently, Telkomsel IoT should expand its role to seize the incremental revenue opportunities. This research project uses discounted cash flow (DCF), secondary data to predict expected financial return after capturing possible risk investment for sound management decisions.

Evaluation Of Investment In IoT Startup at PT TMI

Smartphone revolution, the rise of OTT (Over the Top) technology, and growth of mobile application drive explosion in data demand and erosion of legacy service, which voice and SMS (Short Messaging Service) revenue. It forces mobile telecommunication operators to explore new revenue sources through new business development by taking the opportunity across technology, media, and telecommunication (TMT). Telkomsel Mitra Inovasi (TMI), Telkomsel Corporate Venture Capital (CVC), conducts non-organic business development through investment in an early-stage startup from TMT sectors. January 2020, TMI followed in Series B1 funding of the Internet of Things (IoT) startup. The investment evaluation utilizes two factors which capital gain and incremental revenue to existing Telkomsel business. There is uncertainty in financial return on high-risk investments in a new startup company, and existing Telkomsel IoT provides smart connectivity services. However, connectivity will become increasingly commoditized, declining from 9% of total IoT revenue in 2018 to 5% in 2025. Consequently, Telkomsel IoT should expand its role to seize the incremental revenue opportunities. This research project uses discounted cash flow (DCF), secondary data to predict expected financial return after capturing possible risk investment for sound management decisions.

Analysing Extreme Risk in the South African Financial Index (J580) using the Generalised Extreme Value Distribution

The aim of this study is to model the probabilistic behaviour of unusually large financial losses (extreme-risk)and gains of the South African Financial Index (J580). Risk is defined as uncertainty in return in this paper. This study makes use of Extreme Value Theory (EVT) for the period years: 1995-2018 to build models that are used to estimate extreme losses and gains. The quarterly block maxima/minima of monthly returns are tted to the Generalised Extreme Value Distribution (GEVD). Return levels (maximum loss/gain) based on the parameters from the GEVD are estimated. A comparative analysis with the Generalised Pareto Distribution (GPD) is carried out. The study reveals that EVT provides an efficient method of forecasting potentially high risks in advance. The conclusion is that analysing extreme risk in the South African Financial Index helps investors understand its riskness better and manage to reduce the risk exposure in this portfolio.

Distributed Simulation Using Agents for the Internet of Things and the Factory of the Future

The adoption of the Internet of Things (IoT) and its related technologies has transformed the manufacturing industry and has significantly changed the traditional linear manufacturing supply chains into dynamic and interconnected systems. However, the lack of an approach to assess the economic feasibility and return uncertainties of an IoT system implementation, is blamed as the culprit for hindering its adoption rate. Using two distinctive case studies, this research investigates the use of distributed simulation of agent-based model (ABM) to address such gap in the literature. The first involves the economic feasibility of an IoT implementation in a very large retail warehouse facility, while the second case study proposes a framework able to generate and assess ideal or near-ideal manufacturing configurations and capabilities, and in establishing appropriate information messaging protocols between the various system components by using ABM in distributed simulation.

Housing and Economic Policy Uncertainty in the OECD Countries

This study is aimed at examining the dynamic relationships between housing prices return and economic policy uncertainty (EPU) using a panel vector auto-regression (PVAR) approach and annual data for a panel of 16 OECD countries over the period 2004-2018. The study includes economic growth, short-term interest rate, and population as additional covariates. Empirical results show that a positive shock to EPU leads to decrease in housing prices while the EPU shows only a weak response to housing price shocks. The results imply that EPU has robust predictive power for the housing market, implying the need for evaluating the associated risks. The panel Granger causality tests indicate strong and robust Granger causality from the EPU to housing prices, but not vice versa. The causal links also indicate that the effect of the EPU on is direct rather than indirect through other variables. Based on these outcomes, policy recommendations are made for real estate agents, portfolio managers, and policy makers.

Robust Optimization-Based Commodity Portfolio Performance

This paper examines the performance of a naïve equally weighted buy-and-hold portfolio and optimization-based commodity futures portfolios for various lookback and holding periods using data from January 1986 to December 2018. The application of Monte Carlo simulation-based mean-variance and conditional value-at-risk optimization techniques are used to construct the robust commodity futures portfolios. This paper documents the benefits of applying a sophisticated, robust optimization technique to construct commodity futures portfolios. We find that a 12-month lookback period contains the most useful information in constructing optimization-based portfolios, and a 1-month holding period yields the highest returns among all the holding periods examined in the paper. We also find that an optimized conditional value-at-risk portfolio using a 12-month lookback period outperforms an optimized mean-variance portfolio using the same lookback period. Our findings highlight the advantages of using robust optimization for portfolio formation in the presence of return uncertainty in the commodity futures markets. The results also highlight the practical importance of choosing the appropriate lookback and holding period when using robust optimization in the commodity portfolio formation process.

Stock Return Uncertainty and Life Insurance

Knightian uncertainty embedded in stock returns causes rising demand for life insurance, as the uncertainty averse agent seeks alternative investment channels. Life insurance demand of middle-aged agent is more sensitive to the uncertainty. Stock return uncertainty reduces the agent’s total wealth and subsequently the propensity of wealthy agent serving as an insurance seller. Rising demand and falling supply of life insurance imply that life insurance is more expensive in the presence of stock return uncertainty. Sensitivity of life insurance demand to the mortality rate and key stock return characteristics also changes with the uncertainty.

Evolutionary Stable Strategies in Games with Fuzzy Payoffs

Evolutionarily stable strategy (ESS) is a key concept in evolutionary game theory. ESS provides an evolutionary stability criterion for biological, social and economical behaviors. In this paper, we develop a new approach to evaluate ESS in symmetric two player games with fuzzy payoffs. Particularly, every strategy is assigned a fuzzy membership that describes to what degree it is an ESS in presence of uncertainty. The fuzzy set of ESS characterize the nature of ESS. The proposed approach avoids loss of any information that happens by the defuzzification method in games and handles uncertainty of payoffs through all steps of finding an ESS. We use the satisfaction function to compare fuzzy payoffs, and adopts the fuzzy decision rule to obtain the membership function of the fuzzy set of ESS. The theorem shows the relation between fuzzy ESS and fuzzy Nash equilibrium. The numerical results illustrate the proposed method is an appropriate generalization of ESS to fuzzy payoff games.

Selective attention to historical comparison or social comparison in the evolutionary iterated prisoner’s dilemma game

This paper investigates an evolutionary iterated prisoner’s dilemma (IPD) model of multiple agents, in which agents interact in terms of the pair-wise IPD game while adapting their attitudes towards income stream risk. Specifically, agents will become more risk averse (or more risk seeking) if their game payoffs exceed (or fall below) their expectations. In particular, agents use their peers’ average payoffs as expectations (social comparison) when their payoffs are lower than their peers’ averages, but use their own historical payoffs as expectations (historical comparison) when their payoffs are higher than their peers’ averages. Such selective attention to social comparison or historical comparison manifests a desire for continuous improvement of agents. Simulations are conducted to investigate the evolution of cooperation under the selective attention mechanism. Results indicate that agents can sustain a highly cooperative equilibrium when they consider selective attention in adjusting their risk attitudes. This holds true for both the well-mixed and the network-based games, even in the presence of uncertain game payoffs. The reason is that, selective attention can significantly induce agents to adhere to conditional cooperation as well as to identify uncertainty in payoffs, which enhances the risk-averse behavior of agents in the IPD game. As a result, high levels of cooperation can be attained.

THE EFFECTS OF EXTERNAL UNCERTAINTIES AGAINST MONETARY POLICY UNCERTAINTY ON IRANIAN STOCK RETURN VOLATILITY USING GARCH-MIDAS APPROACH

This study investigates the effect of two external uncertainties of US Economic Policy Uncertainty (EPU) and OPEC oil price uncertainty against domestic monetary policy uncertainty on Iran's stock return volatility. Reaching this goal, GARCH-MIDAS approach is employed that makes it possible using different variables with different frequencies during the period from January 2009 to September 2017. The research uses Iran's stock return with high frequency and other variables with low frequencies. The results of the GARCH-MIDAS model show that the increase in the US EPU, the OPEC's oil price uncertainty and Iran's monetary policy uncertainty increase volatility of Iranian stock returns. US EPU significantly impact on Iran's stock return volatility, which implies that the Iranian stock market has gradually merged into the global economy. However, oil price uncertainty has stronger effect on the stock return volatility than US EPU. In addition, monetary policy uncertainty is the strongest in affecting stock return uncertainty. Iranian policymakers can reduce the volatility of stock return by decreasing domestic monetary policy uncertainty.Keywords: US Economic Policy Uncertainty, Monetary policy, Oil Price, Iran's stock volatility, GARCH-MIDASJEL Classification: G12DOI: https://doi.org/10.32479/ijeep.9176

Secular Stagnation and Low Interest Rates Under the Fear of a Government Debt Crisis

In this study, we explain the driving forces behind the secular stagnation associated with a persistent decrease in interest rates. To do so, we employ a model that incorporates a crisis risk triggered by an accumulation of government debt. The model shows that the fear of large-scale taxation on capital and misallocations of capital in future debt crises explains almost half the economic slowdown in Japan over the past two decades. Over the same period, the government bond yield decreases, because the uncertainty in returns on capital makes investing in government bonds becomes less risky than investing in capital.

Tedarikçi seçimi için yeni bir aralık tip-2 hibrit bulanık kural tabanlı AHP sistemi

Bulanık karar vermenin ana çalışma alanı, belirsizlik altında karar vermektir. Çünkü belirsizliğe neden olan kriterlere, alternatiflere ve sonuçlara ilişkin sayısal değerler değil, sözel değerler mevcuttur. Tip-1 bulanık kümelerin üyelik işlevleri, kendisiyle ilgili bir belirsizliğe sahip değildir. Oysa tip-1 bulanık kümelere göre tip-2 bulanık kümeler ile aşırı aritmetik işlemlere ihtiyaç duyulurken; tip-2 bulanık kümeler, tip-1 bulanık kümeleri ve sistemleri yaygınlaştırarak üyelik fonksiyonlarını tanımlama konusunda daha fazla belirsizliği ele alabilmektedir. Tip-2 bulanık kümesi, üyelik fonksiyonlarının belirsizliğini bulanık küme teorisine dahil etmemizi sağlar. Bu nedenle, çok kriterli karar verme (MCDM) problemlerinin tip-2 bulanık sayılar ile entegre edilmesi karar verme sürecinde avantajlar sağlayacaktır. Öte yandan, karar vericinin etki derecesini yansıtmak için insan duyarlılığının kullanılmasını gerektiren karar verme sürecinin karma bir analizi bulanık kural tabanı ile ifade edilebilir. Analitik Hiyerarşi Süreci (AHP), aynı anda çeşitli ve çelişen kriterleri hesaba katan ve yaygın bir şekilde kullanılan MCDM yöntemidir. Ve AHP yöntemi, aynı zamanda karar vericilerin kişisel tercihlerini çözüm sürecine dahil etmelerini sağlayan bir yöntemdir. Amacımız, tip-2 bulanık kümeleri için yeni bir sıralama yöntemi ile birlikte bir Aralık Tip-2 Bulanık Kuralı Tabanlı AHP (AT2 BKT AHP ) yöntemini geliştirmektir. Önerilen metodu, Aralık Tip-2 Bulanık AHP (IT2 FAHP) metodu ile bir tedarikçi seçim problemine karşılaştırmalı olarak uygulayacağız. Ayrıca çalışma sonucunda tedarikçi seçimi sıralaması için ASP.NET ortamında C# programlama dili kullanılarak görsel bir uzman sistem tasarımı yapılmıştır.

The Return of Uncertainty: Public Lands in an Increasingly Unpredictable World

The Return of Uncertainty: Public Lands in an Increasingly Unpredictable World

Stochastic analysis of quality uncertainty and optimal acquisition strategies for engine remanufacturing

Returned used products vary widely in terms of their condition. For large used machinery, restoration processes are divided into reuse, remanufacture, recycle (3R) based on their condition. To quantify the environmental impacts of the 3R processing arising from the quality uncertainty of returns, this study presents a model that analyzes the carbon footprint at different processing nodes, and then establishes a quantitative relationship between environmental indexes and processing quantities at these nodes. Also, the overall condition of the returned cores can be directly reflected by processing quantities. As opposed to passive assessment, we then derive two optimal strategies to maximize the environmental benefit under different acquisition scenarios using stochastic analysis of the quantity distribution. The results, which were grounded with the data of engine remanufacturing, illustrate that prioritizing higher quality returns is not necessarily the best strategy. Rather, there exists an optimal overall quality coefficient that can maximize the comprehensive benefit of remanufacturing. Which provides the theoretical basis for managers to devise optimal acquisition strategy for maximal production efficiency with lower energy and resource input.

Closed-loop supply chain network design integrated with assembly and disassembly line balancing under uncertainty: an enhanced decomposition approach

In recent years, environmental concerns have increased the need for design and optimisation of closed-loop supply chain (CLSC) networks. Majority of the existing research papers consider the CLSC network designing and line balancing decisions separately. However, this approach may lead to sub-optimal designs due to the interdependency of these decisions. To this end, this paper investigates a CLSC network designing problem integrated with assembly and disassembly line balancing under demand and return uncertainty. The proposed CLSC network contains manufacturers, remanufacturers, assembly centres, intermediate centres (where disassembly lines are located), and customer centres. A new mixed integer non-linear programming model for the proposed problem is developed. Furthermore, an enhanced decomposition approach is developed to solve the proposed model. Computational results, based on randomly generated problem instances, show the efficiency of proposed enhanced decomposition approach. Specifically, results shows that the proposed enhanced decomposition approach leads to significantly smaller running times in comparison with an existing decomposition approach. Results also highlight the importance of integrating supply chain network designing and line balancing decisions.