Portfolio Risk Diversification Research Articles

The Application of Mathematical Analysis in Investment Planning

Investment serves as a means to cultivate assets and secure long-term profits. However, inadequate investment planning poses a substantial risk of significant losses. Consequently, precise analysis becomes imperative for making intelligent investment decisions. One effective analytical approach involves the application of mathematical concepts in investment planning. This article conducts a comprehensive review of existing literature pertaining to the utilization of mathematical analysis in investment planning. Common mathematical concepts employed in investment analysis encompass probability theory, statistics, portfolio theory, and options theory. Probability theory and statistics aid investors in comprehending and forecasting potential gains and losses from specific investments. The primary objective of investment planning is profit maximization through effective risk management, necessitating a mature and structured analysis. Mathematical analysis emerges as a valuable method, and its application in investment planning yields more accurate and efficient results. Techniques such as statistical analysis, portfolio theory, and probability analysis contribute to risk minimization and return maximization by considering factors like asset correlation and risk levels. Thus, the incorporation of mathematical analysis proves crucial for well-structured and successful investment planning. The fifth entry in the bibliography emphasizes the importance of careful and planned analysis in making investment decisions. Economic and financial factors affecting market and investment performance are explored, along with portfolio risk diversification techniques and investment control. The article underscores the significance of understanding investment objectives and investor profiles while discussing various investment instruments such as stocks, bonds, and mutual funds. Overall, the article provides insights into managing investment portfolios effectively for optimal profitability.

The Impact of Taxation on the Effective Tax Rate, Operating Risk, and Portfolio Risk Diversification Effectiveness under Risk Pooling

The Impact of Taxation on the Effective Tax Rate, Operating Risk, and Portfolio Risk Diversification Effectiveness under Risk Pooling

Asymmetric Effects of Energy Inflation, Agri-inflation and CPI on Agricultural Output: Evidence from NARDL and SVAR Models for the UK

This paper investigates the effects of inflation in the UK energy, agriculture and consumer sectors on agricultural output, using monthly data between February 2015 and October 2022. Existing studies on agricultural inflation – agflation – explore the impact on economic activity vis-a-vis unemployment, consumption, interest rates and agricultural production. In this paper, we consider some of the causes of agflation, particularly the role of energy prices that are of great importance at the time of writing, to the supply of food. In addition, we consider the broader context of energy price fluctuations and uncertainty. Our approach adopts a Non-Linear Autoregressive Distributed Lag (NARDL), Structural Vector Auto Regression model (SVAR), including impulse response analysis. Our findings suggest the increase in energy inflation agflation and CPI, adversely affect agricultural output, while decreases in energy inflation, agflation and CPI positively affect agricultural output in the UK. These should be of significant interest to hedge fund managers, institutional investors and economic policymakers, particularly with regard to hedging and portfolio risk diversification strategies.

Dependence structures among geopolitical risks, energy prices, and carbon emissions prices

This paper examines the short-, medium-, and long-run dependence structures for all distribution quantiles among carbon emissions prices, crude oil prices, natural gas prices, and geopolitical risks in Brazil, China, India, Russia, and South Africa from January 2003 to September 2019. The paper utilises the volatility spillover approach of Diebold-Yilmaz to identify the dependence structure among crude oil prices, natural gas prices, carbon emissions prices, and geopolitical risks within the variational mode decomposition-based copula method. It is observed that dependence structure across geopolitical risks and oil prices is time and frequency varying. It is also found that the dependence structure across geopolitical risks and oil prices is positive and valid at different periods and quantiles. The evidence has policy implications for hedging and portfolio risk diversification strategies and policymakers.

Sparse and risk diversification portfolio selection.

Portfolio risk management has become more important since some unpredictable factors, such as the 2008 financial crisis and the recent COVID-19 crisis. Although the risk can be actively managed by risk diversification, the high transaction cost and managerial concerns ensue by over diversifying portfolio risk. In this paper, we jointly integrate risk diversification and sparse asset selection into mean-variance portfolio framework, and propose an optimal portfolio selection model labeled as JMV. The weighted piecewise quadratic approximation is considered as a penalty promoting sparsity for the asset selection. The variance associated with the marginal risk regard as another penalty term to diversify the risk. By exposing the feature of JMV, we prove that the KKT point of JMV is the local minimizer if the regularization parameter satisfies a mild condition. To solve this model, we introduce the accelerated proximal gradient (APG) algorithm [Wen in SIAM J. Optim 27:124–145, 2017], which is one of the most efficient first-order large-scale algorithm. Meanwhile, the APG algorithm is linearly convergent to a local minimizer of the JMV model. Furthermore, empirical analysis consistently demonstrate the theoretical results and the superiority of the JMV model.

Mechanisms for protecting returns on private investments in public infrastructure projects

Despite the widespread attention for the private financing of infrastructure projects, actual empirical work on financing public-private partnerships remains limited. Especially the topics of return on equity and lenders’ cash flow control in relation to uncertainty are under-researched. The aim of this paper is to investigate and discuss the mechanisms applied by private financiers of infrastructure projects to protect their returns on investment. Using semi-structured interviews, the qualitative viewpoints of infrastructure financiers and their consultants on infrastructure investment are examined. The findings identify nine control mechanisms that financiers apply, including a range of asset and risk diversification portfolio strategies for their infrastructure investments, and reveal that they depend on governance mechanisms relating to the project environment, relations, knowledge and expertise. Hence, this study provides a better understanding of the actions and mechanisms applied to protect a return on infrastructure investments that leverage partnering strategies between public authorities and private investors in public infrastructure projects. This contributes to the debate on project financing under uncertainty and its implications for project governance in public private partnerships.

From Black Wednesday to Brexit: Macroeconomic shocks and correlations of equity returns in France, Germany, Italy, Spain, and the United Kingdom

AbstractThis paper investigates whether macroeconomic shocks, such as the UK's referendum decision to leave the European Union (“Brexit”), the 2008 Financial Crisis, the 1992 ERM Crisis (“Black Wednesday”), and the 1987 stock market crash (“Black Monday”), had a positive impact on portfolio risk diversification. We estimate weekly dynamic conditional correlations and then optimal sectoral portfolio allocations between 1973 and 2019. Our results show that correlations of equity returns increased as a consequence of economic integration among European countries from the mid‐1980s until the late 2000s, and decreased in the United Kingdom after Black Wednesday and the Brexit referendum. We tested the existence of a correlation change‐point on June 27, 2016 by applying Wied et al. (2012)'s [Econometric Theory, 28(3), 570–589] correlation structural break test, which we modified to account for dynamic conditional correlations. Application of this test confirms that the referendum date was a break‐point in nearly all UK manufacturing industries. The failure of Lehman Brothers and the 1987 stock market crash were also identified as structural breaks in equity correlations. Moreover, our findings suggest that the Brexit vote may constitute a long‐term trend reversal of the convergence of equity return correlations in European markets, akin to Black Wednesday, rather than a shock like the 1987 and 2008 financial crises, which merely intensified a historical upward trend in correlations of European equity returns.

Does style investing uniformly affect correlations in small and large markets?

Empirical and theoretical research concurs to show that style investing increases return correlations within assets that are classified into the same style. The theoretical model presented in this study addresses the question of how the correlation increases due to style investing depend on market size, and how they respond to economic downturns and to the incidence and awareness of style investing. The results show that correlation distortions caused by style investing are more robust for smaller markets. Further, the effect of style investing on correlations strengthens risk aversion, and hence during downturns. Market awareness, and incidence, of style investing also increase correlation distortions. The model yields closed-form analytical expressions for the correlation distortions caused by style investing, as well as for the effects of changes in risk aversion and in the incidence and awareness of style investing. Given the surge ETF-based style investing over the last two decades, the results have implications for portfolio risk diversification. This study predicts that the ability of risk mitigation through portfolio diversification diminishes particularly for small-market domestic investors as a result of the growing relevance of country-based ETF-based.

Quaternion Valued Risk Diversification.

Risk diversification is an important topic for portfolio managers. Various portfolio optimization algorithms have been developed to minimize portfolio risk under certain constraints. As an extension of the complex risk diversification portfolio proposed by Uchiyama, Kadoya, and Nakagawa in January 2019 (Yusuke et al. Entropy. 2019, 21, 119.), we propose a risk diversification portfolio construction method which incorporates quaternion risk. We show that the proposed method outperforms the conventional complex risk diversification portfolio method.

Financial markets of the LAC region: Does the crisis influence the financial integration?

This paper aims to analyse financial integration in the emerging markets of Latin America in the context of the dot-com and subprime financial crises. To do so, different approaches were adopted to answer two questions, namely: (i) the financial markets of Latin America show significant levels of integration in periods of financial crisis? and (ii) if there are persistent long memories in the data series, will portfolio risk diversification be called into question? The results obtained suggest that the markets are partially integrated in crisis and non-crisis periods. In addition, financial series do not present significant persistent long memories arising from the subprime crisis. The 2008 crisis was found to have a greater impact on the cross correlation coefficients of the Latin American stock markets than the dot-com crisis. In terms of conclusion, it is considered that the financial markets of Latin America were affected by the dot-com and subprime crises. However, there was a re-balance in these regional markets which could create conditions for possible diversification strategies.

Complex Valued Risk Diversification.

Risk diversification is one of the dominant concerns for portfolio managers. Various portfolio constructions have been proposed to minimize the risk of the portfolio under some constraints, including expected returns. We propose a portfolio construction method that incorporates the complex valued principal component analysis into the risk diversification portfolio construction. The proposed method was verified to outperform the conventional risk parity and risk diversification portfolio constructions.

A new approach for worst-case regret portfolio optimization problem

This paper considers the worst-case regret portfolio optimization problem when the distributions of the asset returns are uncertain. In general, the solution to this problem is NP hard and approximation methods that minimise the difference between the maximum return and the sum of each portfolio return are often proposed. Applying the duality of semi-infinite programming, the worst-case regret portfolio optimization problem with uncertain distributions can be equivalently reformulated to a linear optimization problem, and the established solution approaches for linear optimization can then be applied. An example of a portfolio optimization problem is provided to show the efficiency of our method and the results demonstrate that our method can satisfy the portfolio risk diversification property under the uncertain distributions of the returns.

Portfolio benefits of adding corporate credit default swap indices: evidence from North America and Europe

Employing main and sector-specific investment-grade CDS indices from the North American and European CDS market and performing mean-variance out-of-sample analyses for conservative and aggressive investors over the period from 2006 to 2014, this paper analyzes portfolio benefits of adding corporate CDS indices to a traditional financial portfolio consisting of stock and sovereign bond indices. As a baseline result, we initially find an increase in portfolio (downside) risk-diversification when adding CDS indices, which is observed irrespective of both CDS markets, investor-types and different sub-periods, including the global financial crisis and European sovereign debt crisis. In addition, the analysis reveals higher portfolio excess returns and performance in CDS index portfolios, however, these effects clearly differ between markets, investor-types and sub-periods. Overall, portfolio benefits of adding CDS indices mainly result from the fact that institutional investors replace sovereign bond indices rather than stock indices by CDS indices due to better risk-return characteristics. Our baseline findings remain robust under a variety of robustness checks. Results from sensitivity analyses provide further important implications for institutional investors with a strategic focus on a long-term conservative portfolio management.

Brexit and Correlations of Equity Returns in France, Germany, Italy, Spain and the U.K.

This paper investigates whether the UK's referendum decision to leave the European Union (Brexit) had a positive impact on portfolio risk diversification. We estimate weekly dynamic conditional correlations between 1973 and 2018, and then optimal sectoral portfolio allocations over the same period. Our results show that correlations of equity returns increased as a consequence of economic integration among European countries from the mid-1980s until the late 2000s, and decreased in the UK after Black Wednesday and the Brexit referendum. We tested the existence of a correlation change-point on 27th June 2016 by applying Wied, Kraemer, and Dehling (2012)'s correlation structural break test, which we modified to account for dynamic conditional correlations. Application of this test confirms that the referendum date was a break-point in a third of UK manufacturing industries. The failure of Lehman Brothers and the 1987 stock market crash were also identified as structural breaks in equity correlations. Moreover, our findings suggest that the Brexit vote may constitute a long-term trend reversal of the convergence of equity return correlations in European markets, akin to Black Wednesday, rather than a shock like the 1987 and 2008 financial crises, which merely intensified the historical upward trend in correlations of European equity returns.

Initial Coin Offering (ICO) Risk, Value and Cost in Blockchain Trustless Crypto Markets

On July 25th 2017 the SEC published guidance indicating that US securities laws may apply to token sales, effectively recognizing crypto coins associated with entities such as the DAO as a new asset class. In Mutual Distributed Ledgers, or Blockchains, trust is embedded and no explicit chain of trust is necessary. Smart contracts running on a Blockchain allow to create objects with various degrees of liquidity and to automate the operations of a fund, enabling trustless crypto markets. Despite great promise, the sources of uncertainty and risk in such trustless settings are not yet well understood; for instance “The DAO” (Decentralised Autonomous Organisation), which was the world’s first decentralised investment fund, went from being the largest crowdfunding event in history to get about a third of its assets compromised due to an attack from a shareholder. The dual nature of money shared by a Blockchain calls for a novel approach: a DAO is a listed entity by default, and its projects might be financial instruments as well, so we use network correlations to study portfolio risk diversification. Furthermore, automated corporations are essentially about decentralized intelligence, so we need to consider the strategic nature of the social world; for this we map the vector field and use signal processing to investigate volatility in traffic flows. The primary objective of the study is to determine factors that affect cash flows in decentralized applications, to enhance the understanding on whether decentralized organizations are perceived as truly “trustless entities”, or, if investors are rather forced to “trust in the design”. The target audiences of this paper are Government regulatory authorities, Banking sector and Stock markets.

Trustless Crypto-Markets: Perceptions of Value, Risk and Cost

Mutual Distributed Ledgers, or Blockchains, are a type of database that takes records and puts them in a block, where each block is chained to the next one using a cryptographic signature; in other words, trust is embedded, no explicit chain of trust is necessary. Smart Contracts using Blockchain technology are already being tested by consortiums of global banks in settlements of cross border payments, and by the general public in crowdfunding-like entities. Smart contracts not only allow to create objects with various degrees of liquidity, but also to automate the operations of a fund, enabling trust-less crypto markets. Despite great promise, the sources of uncertainty and risk in such trustless settings are not yet well understood; for instance “The DAO” (Decentralised Autonomous Organisation) which was the world’s first decentralised investment fund, went from being the largest crowdfunding event in history (reaching over $150M capitalization less than a month after its launch in May 2016) to get about a third of its assets compromised only weeks later due to an attack from a shareholder- after much deliberation, the community decided to hard fork (roll back the code) to recover the funds. In this paper we study the perception of value, risk and cost for Blockchain investments. But the dual nature of money shared by the Blockchain calls for a hybrid approach: since the DAO is a listed entity by default, and its projects are financial instruments as well, we use network correlations to study portfolio risk diversification. Furthermore, automated corporations are essentially about decentralized intelligence, so we need to consider the strategic nature of the social world and its irreducible complexity; for this we map the vector field and use signal processing to investigate volatility in traffic flows –a precursor to apply machine learning to the problem in the future. In short, we are proposing a method to investigate whether decentralized organizations are perceived as truly “trustless entities”, or, if investors are rather forced to “trust in the design”, and therefore the full cost of being trustless should be factored in.

Correlations and risk contagion between mixed assets and mixed-asset portfolio VaR measurements in a dynamic view: An application based on time varying copula models

In this paper, we apply time varying Gaussian and SJC copula models to study the correlations and risk contagion between mixed assets: financial (stock), real estate and commodity (gold) assets in China firstly. Then we study the dynamic mixed-asset portfolio risk through VaR measurement based on the correlations computed by the time varying copulas. This dynamic VaR-copula measurement analysis has never been used on mixed-asset portfolios. The results show the time varying estimations fit much better than the static models, not only for the correlations and risk contagion based on time varying copulas, but also for the VaR-copula measurement. The time varying VaR-SJC copula models are more accurate than VaR-Gaussian copula models when measuring more risky portfolios with higher confidence levels. The major findings suggest that real estate and gold play a role on portfolio risk diversification and there exist risk contagion and flight to quality between mixed-assets when extreme cases happen, but if we take different mixed-asset portfolio strategies with the varying of time and environment, the portfolio risk will be reduced.

Trade Finance: A Catalyst for Growth in Asia

While large businesses have resumed international trade at levels seen before the financial crisis, small- and medium-sized enterprises (SMEs) have not fared as well. For these firms — the backbone of economies everywhere — growth is impeded by the limited availability of bank loans to finance trade. The problem is especially acute for SMEs in Asia, the world’s largest trading region and the one most reliant on trade finance.This report points out the major impediments to financing in the region and recommends regulatory and procedural changes. It assesses the state of trade finance in Asia, paying particular attention to the ASEAN countries and the needs of SMEs. It emphasizes that to succeed, regional efforts to integrate trade law and procedures must be combined with the replacement of paper documents with electronic transactions, as well as standardized procedures across countries.For investors, the use of trade receivable assets, through securitization or direct investment, could be an attractive alternative in an environment of low interest rates. They offer appealing alpha yields, consistent returns, low volatility, “real economy” investment, and lower default rates than other interest-based assets. Also, the behavior of these assets can be uncorrelated to the market, offering portfolio risk diversification.

The Effectiveness of Portfolio Risk Diversification: An Additive Approach by Project Replication

This article proposes a probabilistic approach to project operational risk and project portfolio risk diversification. The analysis rests on a fundamental distinction between a fractional and an additive approach for constructing portfolios. Since the additive approach excludes variance as a measure of risk, the project's operational risk is defined by its probability of loss. Paradoxically, the effectiveness of any firm's portfolio risk diversification process will be negatively related to the operational risk of its representative project. We also present the conditions under which risk management and efficiency management can contribute to the firm's strategic imperative of lowering its operational risk.

Strategy of asset portfolio risk diversification through value drivers

The risk diversification of an asset portfolio of investments is underlying in the idea that all securities have an idiosyncratic behavior which allows compensating a specific stock loss by the gain achieved by other stock into the portfolio. However, we know that the portfolio selection process should excel for choosing assets capable of creating and generating value on the long term. Thus, the objective of this research was to verify if the portfolios selected through their value drivers present the diversification benefits that were determined in prior researches. We had used the data available at Economatica data base of the following Stock Exchanges: Argentina; Brazil; Chile; and Mexico. To select the portfolios by value drivers we used a model based upon the weighted factors decision matrix where the securities were hierarchized by their grades. The variables used as factors, were the Tobin’s Q, Beta, Leverage, Price/Earning Ratio, and the Price Sales Ratio. All portfolios were compared with that selected through Markowitz (1952) model. The results show us that the portfolios selected through value drivers have obtained the benefits of the diversification process convergent with prior researches. On the other hand, we verified that the stocks amount into portfolios constructed through Markowitz (1952) model have had high positive correlation with the stocks amount in the Stock Exchange what resulted in portfolios with 44 assets, for instance. For future studies we suggest: the using of generalized linear model instead the multiple regressions to figure out the factor weights; to use others fundamentalist variables; to apply this study in other Stock Exchanges.