Portfolio Allocation Model Research Articles

Dynamic portfolio optimization with the MARCOS approach under uncertainty

This paper introduces a dynamic portfolio selection approach that integrates the robustness of interval type-2 fuzzy sets (IT2FSs) with the flexibility of the MARCOS (Measurement of Alternatives and Ranking according to COmpromise Solution) method, offering a novel framework for asset evaluation amidst uncertainty. The IT2FSs enhance the adaptability of asset criteria representation, while the innovative application of MARCOS within the IT2FS environment refines the asset selection process. The weighted semi-absolute deviation metric is embraced to capture portfolio risk characteristic, which ingeniously harnesses the utility function values derived from the IT2F-MARCOS framework to delineate the anticipated return profile. On this basis, a dynamic bi-objective portfolio allocation model with realistic constraints and dynamic risk preference is formulated to rebalance portfolio periodically. Empirical evidence demonstrates the robustness and effectiveness of this approach compared to benchmark indexes, different allocation strategies, and the TOPSIS-based selection method, offering significant advancements in portfolio optimization for investors navigating uncertain markets. This study endeavors to contribute to the field of portfolio management, providing a thoughtful approach that enhances both theoretical understanding and practical application.

Capital Commitment

ABSTRACTTwelve trillion dollars are allocated to private market funds that require outside investors to commit to transferring capital on demand. We show within a novel dynamic portfolio allocation model that ex‐ante commitment has large effects on investors' portfolios and welfare, and we quantify those effects. Investors are underallocated to private market funds and are willing to pay a larger premium to adjust the quantity committed than to eliminate other frictions, like timing uncertainty and limited tradability. Perhaps counterintuitively, commitment risk premiums increase with secondary market liquidity, and they do not disappear when investments are spread over many funds.

Errors and Challenges Associated with Investing in EMU Government Bonds

This article highlights some of the main practical errors and challenges associated with investing in Economic and Monetary Union (EMU) government bonds and the difficulties in implementing EMU government bond strategies. These challenges refer to both portfolio allocation and to factor bond portfolios. Different country economic fundamentals, central bank policy, market timing, market risks, model and management risks, liquidity, and idiosyncratic country risks as well as spillover effects should be considered when investing in individual EMU government bonds. These essential properties of EMU bonds are not adequately addressed in portfolio allocation models (e.g., the tracking error or the mean–variance optimization) applied to single bond portfolios from equity investing. The main EMU government bond disparities are associated with country risks, which can be generalized to the main difference between core and periphery country yield spreads.

Dynamic portfolio allocation for financial markets: A perspective of competitive-cum-compensatory strategy

Portfolio allocation is an important research branch in the realm of financial management and financial engineering. In this paper, a dynamic portfolio allocation problem considering the competitive-cum- compensatory relationship among decision objectives is discussed. Interval type-2 fuzzy numbers that provide more flexibility for processing uncertainty are innovatively utilized to characterize asset returns. To capture the behavioral characteristics of investors’ bounded rationality, prospect theory with dynamic updating of loss aversion rate and reference wealth is introduced. The expected semi-absolute deviation and the entropy function based on the Minkowski measure are adopted to describe the risk and diversification degree of portfolio allocation, respectively. With this description, a dynamic multi-objective portfolio allocation model is formulated. Regarding the multi-dimensional characteristics of the problem, competitive-cum-compensatory strategy-based fuzzy goal programming is embedded in the whole optimization process; thus, the model is transformed into a single-objective form for the solution. Several interesting conclusions are drawn from empirical studies in two financial markets. The robustness and superiority of the proposed model are verified by multi-angle comparison and sensitivity analysis. This research not only enriches and extends the field of dynamic portfolio allocation in the fuzzy context, but also offers an effective means for the optimization of multi-objective portfolio models.

An asymmetric PROMETHEE II for cryptocurrency portfolio allocation based on return prediction

Portfolio allocation, portfolio selection, and portfolio optimization are recognized as three crucial problems in the financial field. Using different criteria in addition to return and risk in the portfolio allocation problem based on the multi-criteria decision-making (MCDM) methods makes it more practical in the real world. The emergence of new and volatile assets such as cryptocurrencies has recently increased the need to use portfolio allocation models. In order to reduce inequalities and alleviate poverty as one of the sustainable development goals, cryptocurrency portfolio construction leads to sustainable income and wealth. This paper proposes a cryptocurrency portfolio allocation model based on the asymmetric Preference Ranking Organization Method for Enrichment Evaluation (PROMETHEE II) method using eight criteria and nine cryptocurrencies. To reduce the uncertainty of the problem, the return prediction obtained from the Auto-Regressive Integrated Moving Average (ARIMA), the Long Short-Term Memory (LSTM), and the Random Forest Regression (RFR) models as return-related criteria and has been used from the SlideVaR, along with the Value at Risk (VaR) and the Conditional Value at Risk (C-VaR) as risk-related criteria to consider investor insight from the market situation. It is also proposed that an asymmetric preference function be proposed to consider gain and loss asymmetry as a behavioral phenomenon in the model. The out-of-sample performance of the proposed model in the last three months of 2021 confirms the superiority of the proposed model in terms of average return (= 0.017) and standard deviation (= 0.036) among other proposed models.

A soft robust methodology to devise hedging strategies in renewable energy trading based on electricity options

Supply contracts play an important role in competitive electricity markets. They help ensure supply adequacy and hedge against market power, among other benefits. However, when variable renewable energy is involved, the mixture of uncertainty in energy production with a high volatile spot market poses a risk difficult to manage. Within this context, call/put options are suitable hedging instruments to cover production imbalance with respect to supply contracts. To efficiently balance the cost/benefit of a set of energy options in a portfolio composed by renewable sources short in supply contracts, a precise definition of the probabilistic nature of the spot market price should be available. However, it is recognized that in practice agents only have an imprecise approximation of the “true” underlying process. Thus, decisions are made under ambiguity, which challenges the practical application of standard pure stochastic-programming methods for the optimal composition of electricity contracts. In this work, we propose a risk- and ambiguity-constrained portfolio allocation model that defines the optimal composition of call/put options and renewable sources to back a supply contract. A case study with realistic data from the Brazilian electricity market is presented to illustrate the applicability of the proposed portfolio allocation methodology. Comparing with two benchmark, we found an increase of roughly 20% and 42% on the average revenue and at least 40% on the average of the 5% worst-case revenue scenarios for different spot price probability distributions.

Financial Risk Meter for emerging markets

In this paper, the daily systemic risk measure FRM (Financial Risk Meter) is proposed for emerging markets (FRM@EM). The FRM@EM is applied to capture systemic risk behavior embedded in the returns of the 25 largest EMs’ Financial Institutions (FIs), covering the BRIMST (Brazil, Russia, India, Mexico, South Africa, and Turkey), and thereby reflects the financial linkages between these economies. The results indicate that the FRM of EMs’ FIs reached its maximum during the US financial crisis following the COVID-19 crisis. In addition, we find that the Macro factors explain the BRIMST's FIs with various degrees of sensibility. Moreover, we propose a robust and well-diversified tail-event and cluster risk-sensitive portfolio allocation model named uplifted hierarchical risk parity (upHRP) and compare it to more classical approaches. Results indicate that the upHRP approach provides better diversification. Moreover, the upHRP portfolio overweights low-central FIs and underweights high-central ones.

Determinants of banks’ liquidity: A French perspective on interactions between market and regulatory requirements

Abstract The paper investigates the impact of solvency and liquidity regulation as well as market shocks on banks’ balance sheet structure. It contributes in particular to the debate on the use of liquidity buffers by banks, as initiated by Goodhart’s (2008), “last taxi” argument. The volatility of long-term markets observed during the Covid-19 pandemic shows that periods of sharp increase in risk aversion still result in liquidity strains for banks. The latter react differently depending on the diversity of their funding sources and their risk profile. Indeed, during a crisis, due to interactions between funding and market liquidity, as well as regulatory constraints, one may wonder whether banks may increase or decrease liquidity. According to a simple portfolio allocation model banks’ liquidity increases when the regulatory constraint is binding, as banks hoard extra liquidity, while they do not if the regulatory constraint is not binding. We show that in times of crisis, measured by large deviations of a financial variable capturing international markets’ risk aversion, French banks actually decreased the liquidity coefficient, with our results mostly driven by less liquid banks. However, while we do find that the solvency ratio has a weakly significant effect on the liquidity coefficient, we were not able to establish a firm causal relationship between the two variables on the basis of Granger causality tests.

FRM Financial Risk Meter for Emerging Markets

The fast-growing Emerging Market (EM) economies and their improved transparency and liquidity have attracted international investors. However, the external price shocks can result in a higher level of volatility as well as domestic policy instability. Therefore, an efficient risk measure and hedging strategies are needed to help investors protect their investments against this risk. In this paper, a daily systemic risk measure, called FRM (Financial Risk Meter) is proposed. The FRM@ EM is applied to capture systemic risk behavior embedded in the returns of the 25 largest EMs’ FIs, covering the BRIMST (Brazil, Russia, India, Mexico, South Africa, and Turkey), and thereby reflects the financial linkages between these economies. Concerning the Macro factors, in addition to the Adrian & Brunnermeier (2016) Macro, we include the EM sovereign yield spread over respective US Treasuries and the above-mentioned countries’ currencies. The results indicated that the FRM of EMs’ FIs reached its maximum during the US financial crisis following by COVID -9 crisis and the Macro factors explain the BRIMST’ FIs with various degrees of sensibility. We then study the relationship between those factors and the tail event network behavior to build our policy recommendations to help the investors to choose the suitable market for investment and tail-event optimized portfolios. For that purpose, an overlapping region between portfolio optimization strategies and FRM network centrality is developed. We propose a robust and well-diversified tail-event and cluster risk-sensitive portfolio allocation model and compare it to more classical approaches.

The size and destination of China’s portfolio outflows

ABSTRACT China’s large financial system is relatively closed, raising concerns that liberalization of China’s capital account could have disruptive effects on the global financial system. We estimate a portfolio allocation model to estimate an economy’s foreign portfolio investment, using panel data for 39 economies. We estimate the model separately for equity and debt securities holdings. We find that portfolio allocation to a foreign economy depends on the destination economy’s market size, gravity variables, governance indicators and capital controls in source and destination economies. We then construct a counterfactual scenario of China’s overseas portfolio investment allocations in 2015 if China had liberalized capital outflows. The analysis indicates that China’s holdings of overseas portfolio assets would have been large at 13% to 29% of Chinese GDP, or 5 to 12 times its actual levels. These asset holdings would have been predominantly from the world’s deepest financial markets: the United States, euro area and Japan. Emerging-market economies would have received relatively little additional portfolio inflows from China, suggesting that liberalization of China’s portfolio outflows may not prove disruptive to the global financial system.

Determinants of Banks’ Liquidity: A French Perspective on Interactions between Market and Regulatory Requirements

The paper investigates the impact of solvency and liquidity regulation on banks' balance sheet structure. The Covid-19 pandemics shows that periods of sharp increase in risk aversion often result in liquidity strains for banks due to the volatility of long-term funding markets.According to a simple portfolio allocation model banks’ liquidity increases when the regulatory constraint is binding. We provide evidence, using the “liquidity coefficient” implemented in France ahead of Basel III's Liquidity Coverage Ratio, of a positive effect of the solvency ratio on the liquidity coefficient. We also show that in times of crisis, measured by financial variables, French banks actually decreased the liquidity coefficient, with the transmission channel materialising mainly on the liability side.

Financial Development, Exchange Rate Fluctuations and Debt Dollarization

This paper examines how financial development influences the debt dollarization of nonfinancial firms in a sample of emerging market economies (EMEs). The macroeconomic channels are identified from an optimal portfolio allocation model and assessed empirically using the accounting information of nonfinancial firms from 21 EMEs during 2009–2017. The results show that financial development, measured by the private credit-to-GDP ratio, mainly reduces the influence of exchange rate volatility in determining a firm's debt currency composition, among other channels. Furthermore, the effect of exchange rate volatility becomes statistically insignificant beyond an estimated threshold credit-to-GDP ratio of 100 percent.

The role of self-financing in introducing innovative development in construction organizations

The article discusses and defines the concept of self-financing which unlike statutory reserves is not necessarily displayed in a balance sheet and may take different forms of investment.It is pointed out that one of the main principles of generating investment resources of an organization is the principle of correspondence between attracted investment resources and investments needed, which is based on calculations of the total of real and financial investments.It was found that the problem of financial and credit support of innovative development through self-financing relates to the portfolio allocation model of scarce investments between the elements of organization. Such an approach results in a situation in which some innovative projects receive insufficient investment resources.The concept called “routinization of innovation” is considered as a stage of the innovation process which is characterized by the accumulation of constantly reproduced traditions. The savings achieved through this should be spent on the routine of innovation.The possibilities of using self-financing are examined. It is viewed as the main tool for introducing innovative development in building organizations under current conditions. Reasons for lack of effectiveness of this tool are described. The methodology for calculating the range within which self-financing is considered to be reasonable is presented.It is proved that in order to facilitate the effective operation of an organization, given the process and structure of self-financing, its innovative adaptation should reflect the ability to perform all the functions (including the logistics of resources) arising from innovative development of the organization.

Between Nonlinearities, Complexity, and Noises: An Application on Portfolio Selection Using Kernel Principal Component Analysis.

This paper discusses the effects of introducing nonlinear interactions and noise-filtering to the covariance matrix used in Markowitz’s portfolio allocation model, evaluating the technique’s performances for daily data from seven financial markets between January 2000 and August 2018. We estimated the covariance matrix by applying Kernel functions, and applied filtering following the theoretical distribution of the eigenvalues based on the Random Matrix Theory. The results were compared with the traditional linear Pearson estimator and robust estimation methods for covariance matrices. The results showed that noise-filtering yielded portfolios with significantly larger risk-adjusted profitability than its non-filtered counterpart for almost half of the tested cases. Moreover, we analyzed the improvements and setbacks of the nonlinear approaches over linear ones, discussing in which circumstances the additional complexity of nonlinear features seemed to predominantly add more noise or predictive performance.

A Dynamic Model of Strategic Allocation of Sovereign Wealth Funds

This article draws on stylized facts to build a dynamic portfolio allocation model of sovereign wealth funds (SWF). We show that a traditional dynamic Merton allocation model allows for the stylized evidence that, on the one hand, the shares of monetary assets in such funds grow with the risk aversion of the state-investor in time, and on the other hand, these funds include the presence or absence of hedge funds correlated to the financial situation. One weakness of this model is its prediction of a lower risk/riskier asset ratio for sovereign stabilization funds and generational savings sovereign funds. This result contradicts the stylized fact of a lower risk/riskier asset ratio in stabilization funds than in generational savings funds. A dynamic model inspired by the theoretical framework of Bajeux-Besnainou et al. [1] is compatible with all the stylized facts.

Financial Development, Exchange Rate Fluctuations and Debt Dollarization: A Firm-Level Evidence

This paper examines how financial development influences the debt dollarization of nonfinancial firms in a sample of emerging market economies (EMEs). The macroeconomic channels are identified from an optimal portfolio allocation model and assessed empirically using the accounting information of nonfinancial firms from 21 EMEs during 2009-2017. The results show that financial development, measured by the private credit-to-GDP ratio, mainly reduces the influence of exchange rate volatility in determining a firm's debt currency composition, among other channels. Furthermore, the effect of exchange rate volatility becomes statistically insignificant beyond an estimated threshold credit-to-GDP ratio of 100 percent.

Endogenous Life‐Cycle Housing Investment and Portfolio Allocation

AbstractThis paper develops a life‐cycle portfolio allocation model to address the effects of housing investment on the portfolio allocation of households. The model employs a comprehensive housing investment structure, Epstein–Zin recursive preferences, and a stock market entry cost. Furthermore, rather than resorting to calibration we estimate the value of the relative risk aversion and elasticity of intertemporal substitution. The model shows that housing investment has a strong crowding out effect on investment in risky assets throughout the life‐cycle. We further find that the effect of the presence of housing investment on households portfolio allocation is larger than the effect of having EZ recursive preferences.

Optimal Allocation of QoS and Web Services in Cloud Computing

Cloud computing is a great model of demand and supply in information communication and services. It represents a complex infrastructure and provides a dynamic, distributed, heterogeneous and autonomous platform for solving problems in business, science and technology. This paper proposes a cloud computing environment that supports dynamic application service composition model. We develop a Quality of Service (QoS) based framework for effective web services allocation. In computing, the service consumer is projected to provide the QoS requirements as part of service discovery query. The cloud as marketplace for trading instances of web services can be bought or leased by web applications. We found that using dynamic decision-making management approach relaying on dynamic portfolio allocation model mainly used in finance, one can achieve the purpose of saving resources by reducing costs of quality of services and eliminating risks related to different services simultaneously.

Distributing Chairs and Seats in Committees: A Parliamentary Perspective

This article presents an argument for committee assignments based not on the traditional congressional theories, but on elements central to parliamentary systems: government formation. The argument of the article is that it is necessary to include the link between committees and cabinet governance for understanding parliamentary committees. This is tested on 40 years of committee assignments from the Danish parliament. The findings suggest that an approach inspired by a classic portfolio allocation model works best in explaining the distribution of seats and chairs between parties. Shadowing of coalition partners appears to matter little, if at all.

The role of self-financing in introducing innovative development in construction organizations

The article discusses and defines the concept of self-financing which unlike statutory reserves is not necessarily displayed in a balance sheet and may take different forms of investment. It is pointed out that one of the main principles of generating investment resources of an organization is the principle of correspondence between attracted investment resources and investments needed, which is based on calculations of the total of real and financial investments. It was found that the problem of financial and credit support of innovative development through self-financing relates to the portfolio allocation model of scarce investments between the elements of organization. Such an approach results in a situation in which some innovative projects receive insufficient investment resources. The concept called “routinization of innovation” is considered as a stage of the innovation process which is characterized by the accumulation of constantly reproduced traditions. The savings achieved through this should be spent on the routine of innovation. The possibilities of using self-financing are examined. It is viewed as the main tool for introducing innovative development in building organizations under current conditions. Reasons for lack of effectiveness of this tool are described. The methodology for calculating the range within which self-financing is considered to be reasonable is presented. It is proved that in order to facilitate the effective operation of an organization, given the process and structure of self-financing, its innovative adaptation should reflect the ability to perform all the functions (including the logistics of resources) arising from innovative development of the organization.