Search

In 2014, FERC adopted a new theory of capital markets for the purpose of setting authorized returns-on-equity: that all observed dividends and interest rates were anomalous and therefore unreliable indicators of the returns necessary for investors to hold the stocks and bonds of transmission owners. The new theory, used to justify higher authorized ROEs, rejected evidence of fundamental conditions in capital markets and explicitly adopted arguments by investor-owned utilities regarding unreliable markets. After a judicial remand, FERC abandoned the new theory, but consumers in New England and the Midwest were arbitrarily charged hundreds of millions of dollars over several years due to unjust and unreasonable rates for transmission service. [ABSTRACT FROM AUTHOR]

In the traditional portfolio models, the return rates of risky assets are usually defined as random variables or fuzzy variables. However, when some events such as financial crises or wars occur that can cause instability in financial markets, the results of these assumptions are not always satisfactory. Therefore, some scholars try to use uncertain variables to express the return rates. In this paper, a two-factor uncertain portfolio problem under optimistic value criteria is studied, where we use the optimistic value instead of expected value to describe the investment return and study the impact of economic circumstance factor and corporation's specificity factor on the return rates. Firstly, a two-factor optimistic value-variance-entropy model with background risk is constructed, in which the total investment return consists of the risky asset return and the background asset return. Then, considering the investors with two kinds of risk preferences, a three-step method is applied to convert the bi-objective optimization model. Moreover, a moment estimation method is used to process the expert-estimated data on the return rates. Finally, a numerical simulation is presented for showing the applicability of our models and solution method. • We use optimistic value to represent the return rather than expected value. • The multiple factors and background risk are considered simultaneously. • Three-step method is used to convert the model into two single-objective models. [ABSTRACT FROM AUTHOR]

With the development of financial market, people invest their savings into different financial products to increase return. However, financial market is an extremely complex system, where investment opportunities and risk often coexist. For investors, it is necessary to take effective measures to avoid risk while obtaining considerable return. In recent decades, actively managing investment in the form of a portfolio is widely accepted by investors. In this paper, we propose a new three-objective Sortino ratio-expected shortfall-turnover rate (SR-ES-TR) portfolio optimization (PO) model. The Sortino ratio is used to measure the risk-adjusted rate of return. The expected shortfall is used to measure the tail risk of a portfolio. Portfolio liquidity risk is characterized by turnover rate. We constructed a portfolio of ten stocks and solved the SR-ES-TR model by the novel MOPSO-SODE algorithm. Compared with other four multi-objective algorithms, the better performance and validity in solving SR-ES-TR model by MOPSO-SODE algorithm have been verified. • Established a three-objective SR-ES-TR portfolio optimization model with liquidity ratio. • Designed a MOPSO-SODE algorithm based on the MOPSO framework. • Verified the effectiveness of the MOPSO-SODE algorithm in solving SR-ES-TR model. [ABSTRACT FROM AUTHOR]

Abstract The aim of this study is to analyze whether managers, practitioners and individual investors could obtain higher risk-adjusted returns by allocating their investments to funds that integrate specific levels of socially responsible (SR) criteria in their portfolios. This is achieved by comparing the performance of mutual funds according to their SR characteristics: environmental, governance, social, and sustainability attributes. For a large sample of 3920 equity SR mutual funds around the world, performance is measured using a multifactor model that incorporates relevant benchmarks according to the fund investment objectives, and using Carhart's (1997) methodology to measure mutual fund performance persistence. In general, fund performance is not significant, the average being negative and close to zero. Funds achieving relatively high levels of SR attributes in their portfolios seem to experience overall worse performances. This evidence is, however, mainly driven by the behavior of worst-performing funds. Moreover, investing in the previous best SR funds could lead investors to greater overall returns in most areas and levels of SR attributes considered. This evidence highlights the role of managers in enhancing the returns of a portfolio with a well-defined SR investment policy. Therefore, there is no incompatibility between pursuing higher ethical (and sustainable) values as well as greater financial performances from investments—provided managers have the skills necessary to choose the right SR funds. Highlights • We compare the performance of socially responsible (SR) funds. • Funds with high SR attributes experience overall worse performances. • Investing in the previous best SR funds leads to greater overall returns. • The evidence highlights managers' role for designing SR investment policies. • Ethical and sustainable values are compatible with greater performances. [ABSTRACT FROM AUTHOR]

Abstract Using stock market returns of two stock exchanges in China, this paper employs MF-DCCA to investigate the non-linear cross-correlation between individual investor sentimentand Chinese stock market return. We find that there exists a power-law cross-correlation between individual investor sentiment and Chinese stock market return, and the cross-correlations are significantly multifractal. In addition, the cross-correlation between individual investor sentiment and Shenzhen Component Index (SZSE) return is more anti-persistent than that between individual investor sentiment and Shanghai Composite Index (SSEC) return, implying that individual investor sentiment has a stronger impact on small stocks. Besides, long-range correlations, fat-tailed distribution and extreme value all contribute to the multifractality for cross-correlation between individual investor sentiment and SSEC return, while long-range correlation is the main source of multifractality for the cross-correlation between individual investor sentiment and SZSE return. Highlights • Cross-correlation between investor sentiment and stock return is investigated. • Yu'ebao Sentiment Index and Shenzhen stock market return is more anti-persistent. • The sources of multifractal features are investigated. [ABSTRACT FROM AUTHOR]

The optimal investment ratios for a set of stocks and other financial products can be obtained by the conventional portfolio theory based on quantitative data such as returns and risks. However, quantitative data are sometimes unavailable, thus qualitative information provided by experts or decision makers should be used. Based on the foregoing, we propose new portfolio selection approaches based on such qualitative information which is represented herein as hesitant fuzzy elements. For general investors and risk investors, we develop two qualitative portfolio models based on the max-score rule and the score-deviation trade-off rule, respectively. Furthermore, the deviation and score trisection approaches are developed to distinguish the three types of risk investors, which also help to construct the corresponding qualitative portfolio models. In addition, we investigate the investment opportunities and efficient frontiers of these proposed qualitative portfolio models. Also, the specific portfolio selection processes are provided. Finally, an example of selecting the optimal portfolio of risk investment is provided. On the basis of the above study and example, we can conclude that the proposed qualitative portfolio models used for the three types of risk investors are effective. The given portfolio selection processes can be reasonably used in practical qualitative risk investment. [ABSTRACT FROM AUTHOR]

In this paper, we advocate the provincial TV audience rating as the novel proxy for the provincial investor sentiment (PIS) and investigate its relation with stock returns. The empirical results firstly show that the PIS is positively related to stock returns. Secondly, we provide direct evidence on the existence of home bias in China by observing that the provincial correlation coefficient is significantly larger than the cross-provincial correlation coefficient. Finally, the PIS can explain a large proportion of provincial comovement. To sum up, all these findings support the role of the non-traditional information sources in understanding the “anomalies” in stock market. [ABSTRACT FROM AUTHOR]

Housing demands are partially driven by participant's sentiment, but the literature on housing economics rarely acknowledges that fact. This paper aims to investigate the role of market sentiment in housing market. A sentiment index is developed to capture the aggregate investor behavior and thus market scenario. In empirical application, using elaborate transaction records during 1991–2011 (more than two million registrations) in Hong Kong, the sentiment index is established. Generally, investors in housing market are more likely to be sentiment-influenced. In trading process, a delaying effect on the expected waiting time (duration) from buy to sell is found. Furthermore, market sentiment quantified by sentiment index is an efficient predictor of price level, return rate of price and trading volume. Meanwhile, sentiment remarks the significant role in long-run development of housing market. The approach and implications of this study may serve as a reference for the relevant authorities to stabilize and improve the environment of housing market. [ABSTRACT FROM AUTHOR]

• A cloud theory-based multi-objective portfolio selection model is proposed. • The crisp numerical characteristics of the cloud model theory are defined. • The acceptance and rejection functions with variable risk appetite are constructed. • A compromise programming approach is utilized to aggregate the objectives. • Several schemes as per investors' preferences regarding all objectives are devised. This study proposes a cloud theory-based multi-objective portfolio selection model with variable risk appetite, which incorporates four objectives of mean, variance, skewness, and liquidity constrained by several realistic constraints. Cloud model theory is employed to characterize the return rates and liquidity of assets due to the superiority of simultaneously capturing the ambiguity and randomness of information. The crisp numerical characteristics of the cloud model are defined to obtain the crisp form of the proposed model. To highlight and portray the investors' risk (averse-neutral-seeking) appetites, the generalized acceptance and rejection functions are modeled by using the extreme values of each objective and introducing a variable risk appetite parameter. Thus the corresponding model is transformed with the objective functions of maximizing acceptance and minimizing rejection, which is solved through the compromise programming approach. The extended model provides investors with an opportunity to adjust risk parameters according to current market status. Moreover, the preference ratio vector is introduced when optimizing, which provides investors with overall control over the preferences regarding all objectives, so that investors can derive optimal portfolios well compatible with their expectations through customized weighting schemes. A real-world empirical application is presented to demonstrate the effectiveness of the proposed model [ABSTRACT FROM AUTHOR]