Decision Making in Real Estate: Portfolio Approach

An investment policy is suggested about assets on real estate markets. Such analysis recommends investments in non-financial assets and optimization of the results from such decisions. The formalization of the investment policy is based on the portfolio theory for asset allocation. Two main criteria are applied for the decision making: return and risk. The decision support is based on Mean-Variance portfolio model. A dynamical and adaptive investment policy is derived for active portfolio management. Sliding procedure in time with definition and solution of a set of portfolio problems is applied. The decision defines the relative value of the investment to which real estates are to be allocated. The regional real estate markets of six Bulgarian towns, which identify the regions with potential for investments, are compared. The added value of the paper results in development of algorithm for a quantitative analysis of real estate markets, based on portfolio theory.

Decision Support for Portfolio Management by Information System with Black–Litterman Model

An algorithm is derived for the development of portfolio decision-support information service. The algorithm allows being automated evaluations for the definition and solution of portfolio problems. Small set of historical data of asset returns with limited set of assets are used for the portfolio, which is the case for no institutional portfolio manager. The algorithm applies analytical relations for decreasing the computational workload for the estimation of the market parameters due to the limited number of assets. The subjective expert views in the Black–Litterman (BL) model are defined from additional assessment of historical data of the asset returns. The algorithm makes comparisons of the results for active portfolio management from the mean variance (MV) model, the BL one and the equal-weighted investment strategy. Benefits of the algorithm are the usage of small set of historical data and limited number of assets, which are proved in investment rolling horizon.

Mean–variance combining rules that outperform naïve diversification

The mean–variance framework developed by Markowitz (1952). Portfolio selection, The Journal of Finance, 7(1), 77–91 is still the major model used nowadays in asset allocation and active portfolio management. However, the estimated mean–variance rules often fail to deliver superior performance compared with the simple naïve rule (the equally weighted portfolio) due to the problem of estimation errors. In this paper, I propose a portfolio construction method that is effective in dealing with estimation errors in the optimization process. Particularly, I specify the portfolio weights as an optimal combination of the equally weighted portfolio and a sample zero-investment portfolio. I show analytically that the proposed method alleviates the problem of estimation errors and dominates naïve diversification. I suggest two implementable versions of the combining method and show, empirically, their good performances relative to the naïve rule. The newly developed rules work well, particularly, for portfolios with a medium and high number of assets. Moreover, the outperformance persists generally even in the presence of transaction costs. Since the combinations are theory-based, my study may be interpreted as reaffirming the usefulness of the Markowitz portfolio theory in practice.

Profitability and Risk of Selected Forms of Investment on the Polish Capital Market

Subject and purpose of work: The subject of this study concerns profitability and risk of selected forms of investment on the Polish capital market. The aim of the study was to compare profitability and risk of active and passive investment portfolios. Materials and methods: The research material consisted of the rates of return on investments in the undervalued shares and growth shares included in the WIG-20 index and the results of the Lyxor WIG 20 UCITS ETF fund in 2014-2019. The study compares the rates of the return and standard deviations of returns of the portfolios managed actively and passively. Results: The analysis of the rates of return of the created investment portfolios indicates a higher profitability and a lower risk of the passive form of investment consisting in the purchase of an ETF fund. Among active strategies the growth investing strategy showed a higher profitability and a lower risk. Conclusions: Passive forms of investment are an effective alternative to active portfolio management.

Applications of Game- Theory in Active Strategic Portfolio Management- the Case of Hedge - Funds Adaptation for the Real Constraints in Romanian Capital Market

The application is focused on strategies for portfolio management in the case of hedge-funds for emerging markets taking into account the severe constraints for a real-world implementation. In the case of Romanian capital market, the design of a hedge-fund architecture should respond to the typical constraints for using alternative strategies. Beyond the liquidity problems there exits only a limited set of alternative instruments and strategies with impact on diversification, on the functionality and efficiency. The objective is to develop a better understanding of alternative actions and innovations for real adaptation of the architecture of a hedge-fund at these emerging market conditions, especially the lack of short and hedging instruments and the liquidity problems. Based on this new innovative framework that could capture the value of multiple rotating satellite sub-portfolio paradigm, as an active strategy, it is possible to build a different paradigm for active portfolio management in a dynamic manner. Based on an adequate dynamic of rotation of these sub-portfolios it results an optimal risk- return-liquidity profile for the whole hedge-fund portfolio, adaptable for different contexts.

Aspects Regarding a New Methodology for Active Portfolio Management of Hedge Funds Alternative in Emerging Markets-the Case of Romanian Capital Market in the Actual Context of Post-Crisis Recovery

In emerging markets, the processes in portfolio management should be adapted according to the typical constraints (market liquidity aspect and other market imperfections)that limits the use of alternative instruments / strategies and diversification capabilities. The aim is to develop a new way to understand and implement innovative solutions in real portfolio management in the case of Romanian capital market. The innovation is based on a scalable hedge-fund (HF) structure that capture different alternative instruments. This HF architecture represents a versatile dynamic AIF, equipped with capabilities to integrate the synergies between diversification based on alternative instruments but also the diversification based on alternative strategies and it integrates a core thematic sub-portfolio and 2-4 satellite rotating sub-portfolios capable to compensate the impossibility to use short sales and leverage strategies.

Sovereign Wealth Funds: Lessons of Coronacrisis

The paper deals with the sovereign wealth funds’ (SWFs) reactions to the economic and geo-political turbulence of 2020 emerged from COVID 19 pandemic. In recent decade, SWFs as state-run investment vehicles have proved to be the fastest growing group of institutional investors and have noticeably strengthened their role in the global financial system. According to the latest estimates, their cumulative AUM reached 9.1 billion US dollars as of December 2020. There are persuasive evidences that top 10 SWFs from Norway, China, Singapore, Persian Gulf and some other nations have evolved into full-fledged market-driven investors with an active portfolio management strategy. The fact that they continue to contribute the lion’s share (around 2/3) into the integral figures of SWFs’ performance as a group explains why the pandemic failed to undermine their progress. Also, it should be taken in mind that, in contrast to GFC of 2008–2009, the recent coronacrisis was featured by a seemingly surprising gap between the deep recession in real sector businesses and eventual growth of basic indexes of capital markets. Generally, this turned good for the financial market community, including many SWFs. For instance, the world’s largest Norwegian GPFG, despite an urgent sellout of some of its assets in order to help the national government in financing somewhat undermined state budget in the situation of deep slump at world oil market, reported, by the end of the year, the 10.9% operational profit and 8.2% increment of AUM (in terms of local currency). In the upcoming years, we may see the state funds vehicles to increasing change the whole landscape of the global investment playfield. It is highly likely that the post-COVID turbulent environment will increasingly push the SWFs not only to seek for viable alternatives to the increasingly fading traditional fixed-income instruments but to fundamentally change the mandates and the modes of operation. The traditional stabilization and saving state investment funds will step down in favor of a subgroup of the so called strategic SWFs, such as Singaporean Temasek, Chinese CIC, Saudi PIF, Indian NIIF, Malaysian Khazanah, Turkish TVF, Bahraini Mubadala, and Russian RDIF. Basically, they are charged to operate as the catalysts of national economic and social development. It may be expected that in the near future this category of state investors will see a growing number of newcomers.

Volatility Connectedness between Clean Energy Firms and Crude Oil in the COVID-19 Era

The work investigates the volatility connectedness between oil price and clean energy firms over the period 2011–2020 (including the COVID-19 outbreak). Using the volatility spillover models, and dynamic conditional correlation, we are able to identify the volatility spillover effect between these financial markets and its implications for portfolio diversification. The results indicate a significant change in both static and dynamic volatility connectedness around the COVID-19 outbreak. For instance, total connectedness index changes from 21.36% (pre-COVID-19) to 61.23% (COVID-19). This finding shows the strong effect of the COVID-19 pandemic on these financial markets. Furthermore, we show how the WTI oil from the volatility transmitter (before the outbreak of the pandemic) becomes a risk receiver after the start of the global pandemic COVID-19. Our findings indicate that recent pandemic intensified volatility spillovers, supporting the financial contagion effects. Finally, we determine the optimal hedge ratios and portfolio weights. The estimates provided suggest the need for active portfolio management, taking into account the distinct characteristics of each sector and thus, the firm. For example, the optimal weight analysis shows how the clean sector has become important in optimal diversification strategies. Our results can be used for portfolio decisions and regulatory policymaking, particularly in the current context of high uncertainty.