Brand portfolio strategies effects on consumers' attitude

PurposeThe aim of this study is to determine the effects of brand components (CBBE, brand fit, brand image, brand reputation, brand familiarity) on consumers brand portfolio attitude via perceived risk (for two main portfolio strategies).Design/methodology/approachThe study used a structured questionnaire to collect primary data from 636 consumers who made purchases from companies using house of brand (318) and branded house strategy (318). By conducting reliability and validity analysis, the model of this study was tested with confirmatory factor analysis and path analysis methods, using structural equation modeling.FindingsAccording to the results of the path analysis, the effects of CBBE and brand reputation on brand attitude were confirmed for both house of brand and branded house strategy. Moreover, the full and partial mediating effect of perceived risk was proven in the relationships.Research limitations/implicationsOne of the limitations of the study is determining a portfolio of brands for each strategy and collecting data for these brands. In addition, since the number of consumers using brand portfolios could not be reached in the study, data could be collected using the purposeful convenience sampling method. For this reason, it is thought that research conducted with the data obtained through systematic sampling methods can yield more reliable results.Practical implicationsManagers of companies with a brand portfolio should work on a main strategy that enhances CBBE and brand reputation regardless of the strategy they use. After these two variables, the variable that portfolio managers need to address is brand fit.Originality/valueIt will offer different perspectives in terms of understanding which portfolio strategy is needed, and which predecessors and outputs can be produced. Also, the findings of the research will produce important results to reduce the perceived risks of consumers and increase their positive attitudes toward brand portfolios.

PORTFOLIO INSURANCE UNDER ROUGH VOLATILITY AND VOLTERRA PROCESSES

Affine Volterra processes have gained more and more interest in recent years. In particular, this class of processes generalizes the classical Heston model and the more recent rough Heston model. The aim of this work is hence to revisit and generalize the constant proportion portfolio insurance (CPPI) under affine Volterra processes. Indeed, existing simulation-based methods for CPPI do not apply easily to this class of processes. We instead propose an approach based on the characteristic function of the log-cushion which appears to be more consistent, stable and particularly efficient in the case of saffine Volterra processes compared with the existing simulation techniques. Using such approach, we describe in this paper several properties of CPPI which naturally result from the form of the log-cushion’s characteristic function under affine Volterra processes. This allows to consider more realistic dynamics for the underlying risky asset in the context of CPPI and hence build portfolio strategies that are more consistent with financial data. In particular, we address the case of the rough Heston model, known to be extremely consistent with past data of volatility. By providing a new estimation procedure for its parameters based on the PMCMC algorithm, we manage to study more accurately the true properties of such CPPI strategy and to better handle the risk associated with it.

Understanding heuristics-based financial decision-making using behavioral portfolio strategies

PurposeThrough a portfolio choice model, the study empirically examines the influence of the heuristic simplification through peak-end rule (PER) and the associated neglect of the duration of the experience. The portfolio strategy adopted involves optimizing portfolios to capture the impact of heuristic-driven investors' experience of good and bad states. The study attempts to validate PER in an empirical context and is expected to generate trading rules, which would exploit pricing errors emerging out of the use of heuristics by investors.Design/methodology/approachThe empirical approach adopted in the study primarily examines returns to portfolios sorted according to various hedonic evaluation rules. Behavioral portfolios are constructed using hedonic experiences as conditioning variables.FindingsThe results imply that there is continued investor demand for such assets in the short run. An equal weight portfolio based on a three-month hedonic evaluation earns an average monthly return of 2.77% over the next 12 months.Originality/valueThe authors’ study may perhaps be the first attempt to use the peak-end heuristic in portfolio construction.

Approaches to shaping portfolio strategies based on the socially responsible investing concept

Subject. The article considers formulation of portfolio strategies that rest on the concept of socially responsible investing. Objectives. The purpose of this study is to analyze approaches to shaping the portfolio strategies based on the principle of socially responsible investing in the Russian stock market. Methods. The study employs general scientific research methods; logical, comparative, and statistical analyses; graphical analysis techniques. Results. We formulated and tested two strategies of socially responsible investing, i.e. Short ESG Ranking of Russian Companies and Long ESG Ranking of Russian Companies. The testing demonstrated below market return for the entire period. Thus, the strategies cannot be considered effective. To increase profitability, we proposed to optimize the strategies by including ESG-related debt instruments. Green bonds enabled to significantly increase profitability and outstrip OFZ yields. Despite the fact that according to the testing, the effect of both strategies turned out to be worse than IMOEX and MOEXBC indices, the strategies can be considered as relevant and acceptable for portfolio simulation. Conclusions. Under the current conditions in the financial markets caused by serious shocks during the coronavirus pandemic and significant changes in the monetary policy of the Bank of Russia, the proposed strategies can be used by socially responsible institutional investors to shape investment policy and by individuals to manage funds in individual investment accounts. New bonds of Russian issuers in the sustainable development sector of the Moscow Exchange expanded the list of ESG instruments. They can serve as an effective optimization tool.

Analyzing the efficiency of portfolio strategies based on the dividend yield concept: Evidence from the Russian stock market

Subject. The article focuses on the formation and management of the securities portfolio. In developed economies, various strategies are used to manage portfolios. The tendencies permeate the practice of portfolio managers and in the domestic market. Objectives. We analyze the efficiency of portfolio management strategies based on the dividend yield concept in order to find the most appropriate one for the Russian market for mid-term investment. Methods. The study is based on general methods of logic, comparative and statistical analysis, graphical and indicative comparative analysis. Results. Having tested strategies based on the dividend yield concept, we suggested using an improved mid-term strategy, which may suit many investors, including institutional ones. The article presents our suggestions on the improvement of a strategy for creating and managing a securities portfolio in the Russian stock market, which is based on the Dogs-of-the-Do principle. Conclusions and Relevance. Drawing upon the dividend yield concept, the proposed strategy ensures the average yield exceeding those of DOW 5 and DOW 10 strategies, bank deposit and investment in federal loan bonds. However, it is inferior to IMOEX and MOEXBS due to the lose of the portfolio balance once a year. Securities within the strategy make up ETF to lure more investors. The inclusion of FXUS increased the average annual yield by 2.45 percent. The addition of FXMM significantly reduces foreign currency risks. To optimize the strategy, there should be REPO with the central counterpart and CCP-cleared REPO, which raises its yield through arbitrage transactions.

Optimal portfolios in the presence of stress scenarios A worst-case approach

Insurance companies and banks regularly have to face stress tests performed by regulatory instances. To model their investment decision problems that includes stress scenarios, we propose the worst-case portfolio approach. Thus, the resulting optimal portfolios are already stress test prone by construction. A central issue of the worst-case portfolio approach is that neither the time nor the order of occurrence of the stress scenarios are known. Even more, there are no probabilistic assumptions regarding the occurrence of the stresses. By defining the relative worst-case loss and introducing the concept of minimum constant portfolio processes, we generalize the traditional concepts of the indifference frontier and the indifference-optimality principle. We prove the existence of a minimum constant portfolio process that is optimal for the multi-stress worst-case problem. As a main result we derive a verification theorem that provides conditions on Lagrange multipliers and nonlinear ordinary differential equations that support the construction of optimal worst-case portfolio strategies. The practical applicability of the verification theorem is demonstrated via numerical solution of various worst-case problems with stresses. There, it is in particular shown that an investor who chooses the worst-case optimal portfolio process may have a preference regarding the order of stresses, but there may also be stress scenarios where he/she is indifferent regarding the order and time of occurrence.

Transfer Entropy Approach for Portfolio Optimization: An Empirical Approach for CESEE Markets

In this paper, we deal with the possibility of using econophysics concepts in dynamic portfolio optimization. The main idea of the research is that combining different methodological aspects in portfolio selection can enhance portfolio performance over time. Using data on CESEE stock market indices, we model the dynamics of entropy transfers from one return series to others. In the second step, the results are utilized in simulating the portfolio strategies that take into account the previous results. Here, the main results indicate that using entropy transfers in portfolio construction and rebalancing has the potential to achieve better portfolio value over time when compared to benchmark strategies.

The Features of Building a Portfolio of Trading Strategies Using the SAS OPTMODEL Procedure

The article describes the original information technology of the algorithmic trading, designed to solve the problem of forming the optimal portfolio of trade strategies. The methodology of robust optimization, using the Ledoit–Wolf shrinkage method for obtaining stable estimates of the covariance matrix of algorithmic strategies, was used for the formation of a portfolio of trade strategies. The corresponding software was implemented by SAS OPTMODEL Procedure. The paper deals with a portfolio of trade strategies built for highly-profitable, but also highly risky financial tools—cryptocurrencies. Available bitcoin assets were divided into a corresponding proportion for each of the recommended portfolio strategies, and during the selected period (one calendar month) were used for this research. The portfolio of trade strategies is rebuilt at the end of the period (every month) based on the results of trade during the period, in accordance with the conditions of risk minimizing or income maximizing. Trading strategies work in parallel, being in a state of waiting for a relevant trading signal. Strategies can be changed by moving the parameters in accordance with the current state of the financial market, removed if ineffective, and replaced where necessary. The efficiency of using a robust decision-making method in the context of uncertainty regarding cryptocurrency trading was confirmed by the results of real trading for the Bitcoin/Dollar pair. Implementation of the offered information technology in electronic trading systems will allow risk reduction as a result of making incorrect decisions or delays in making decisions in a systemic trading.