Improve Investment Performance Research Articles

Exploring the synergy of human-computer interaction in financial decision-making

With the rapid development of technology, the combination and complementarity of artificial intelligence (AI) and human expertise in finance is becoming increasingly important. This research focuses on the synergistic effect of human-computer interaction (HCI) in financial decision-making, analyzes the operation mode of financial decision-making, lists examples of the combination of related fields and artificial intelligence technology, and focuses on showing that human-computer interaction technology enhances user experience and benefits in financial activities. Ability to invest in performance. Emerging features such as personalized financial services, intuitive user interfaces, and real-time feedback can dramatically improve user experience, research shows. Integrating artificial intelligence and professional knowledge can improve investment performance, assist risk management and decision support. The study emphasizes the importance of human-computer complementarity and balance, which has important reference value for financial institutions to adjust plans, policy makers to modify laws and regulations, and researchers to improve user experience and enhance investment results.

Small Portfolio Construction with Cryptocurrencies

In this paper, we describe and apply different models of portfolio construction in the selection between a small number of big-cap cryptocurrencies. Our purpose is to select the minimum riskiness between cryptocurrencies, comparing different risk measures and maximum diversification. We build our models without the constraints of the expected returns. Without relying on expected returns, we have the same condition on the comparison between them. Cryptocurrencies are not common stock or other assets indexed in the market but it is interesting to study how diversification can significantly improve investment performance. We first give the methodology to use high-frequency observation data, in the numeral approximation especially in the novel application of the Risk parity models, used with different risk measures we can achieve a very good result, from the position of gaining and variation. Since Risk parity models divide the weights of the asset in equal risk contribution proportion, it is suggested to use a small number of cryptocurrencies, otherwise their performance will be close to the uniform portfolio. To the traditional Mean Variance model, and the alternative, Expected shortfall/Conditional Value at Risk, we use three versions of Risk Parity with two different risk measures and a naive risk parity. The uniform portfolio is used as a benchmark for selection comparison with the other portfolio models. We give the conditions for the Risk Parity with the Expected shortfall/Conditional Value at Risk (CVaR) to guarantee convergence with the numerical approximation. In the end, we study the tradeoff between each model and which is more suitable for a small cryptocurrency portfolio.

The Study of Personal Finance Setting Financial Goals for Improved Investment Performance

The Study of Personal Finance Setting Financial Goals for Improved Investment Performance

Investment Strategy, Manager Characteristics, and Corporate Governance Effects on Mutual Fund Performance: A Study of PT Asuransi Jiwasraya (Persero) During Period of 2013-2018

This study aims to examine the relationships between investment strategies, investment manager characteristics, and corporate governance on the investment performance of PT Asuransi Jiwasraya (Persero)’s mutual funds investment from 2013 to 2018. The year 2013 marked the introduction of a new bancassurance product, which necessitated PT AJS to generate higher returns on investment in a short-term period. The sudden change in management in 2018 brought the mismanagement case to public attention. The analysis utilized a cross-sectional multilinear regression approach, allowing for the examination of multiple independent variables and their relationship with the dependent variable. Data for the study is collected from various sources, including annual reports, financial reports, prospectuses, and court documents. The relationships are assessed using seven regression models, with measures such as mean return, standard deviation, beta, Sharpe ratio, Treynor ratio, Jensen’s Alpha, and state loss as the dependent variables. The regression models are estimated using SPSS software, and assumptions of linearity, independence of errors, homoscedasticity, and absence of multicollinearity are checked to ensure the validity of the analysis. Hypothesis testing is conducted to determine the statistical significance of the relationships, and measures such as R-squared, adjusted R-squared, and F-statistic are used to assess the overall goodness-of-fit of the models. The findings indicate that the models for mean return, Treynor ratio, Jensen’s Alpha, and state loss are statistically significant, demonstrating a strong correlation and high explanatory power. The results suggest that value investing and smaller market capitalization of constituent stocks have a positive association with investment performance. Additionally, reducing the presence of dividend-paying and suspect stocks is beneficial for investment performance. Factors such as management fees, education background, and years of experience show significant positive relationships, while investment horizon, asset size, and past performance have significant negative relationships with investment performance. The age of the investment manager does not exhibit a significant relationship. Furthermore, corporate governance demonstrates a negative relationship with investment performance. These findings provide valuable insights for improving investment performance and offer important lessons to prevent similar cases of mismanagement of investment funds in the future.

Effect of Prospect Factor and Herding Effect on Individual Investment Performance in Nigeria: Moderating Role of Financial Literacy

Investors exhibit irrational behavior when making an investment decision. The decision-making process itself is considered to be a cognitive process, as the investors have to make a decision based on various alternatives available to them. Prior studies had shown that the investors’ decision-making was adversely affected by the various behavioral factors. This study was carried forward to identify the moderating role of financial literacy (FL) on the effect of prospect factor (PF) and herding effect (HE) on investment performance. The population of study was 3,706 and the sample size was the active investors resident in Kaduna metropolitan within the first quarter of 2023. Thus, 460 structured questionnaires were administered and 349 were returned valid. A convenient sampling technique was adopted in this study, and a primary data was collected from the respondents using both the online Google form and self-administered questionnaire with the help of research assistants. A 7-point Likert-type scale ranging from ‘1’ “Extremely Agree” to ‘7’ “Extremely Disagree” was employed. Smart-PLS 4 and SPSS 20 version was used to analyses the data and explained the demographic characteristics of the individual respectively. Findings from this study revealed that prospect factor and financial literacy have positive and significant influence on individual investment performance, while the herding effect is found to have a negative and insignificant influence on individual investment performance. Furthermore, the moderating role of financial literacy revealed that prospect factor and herding effect have an insignificant negative effect on individual investment performance. The study recommends that individual investors should have high levels of financial literacy. It has been empirically proven that FL help investors make better investment decision, in addition to satisfaction in their investment performance. Also, the investors should maintain the use of prospect behavioral biases when making investment decision as it has improved investment performance.

Which Types of Investments Benefit from Retaining the Flexibility to Terminate?

Firms can choose to make investments while retaining the option to terminate them prior to completion. This flexibility can mitigate uncertainty about the investment that is present at the time of its initial funding. However, this flexibility can also detrimentally alter actions within the firm that are necessary for the investment’s success, such as whether scarce firm resources are allocated to the investment. This paper develops a set of hypotheses which predicts flexibility may not improve investment performance when the investment generates limited early-stage learning and requires certain types of resources. These hypotheses are empirically tested in a data set of new U.S. television programs, comparing programs that receive commitment in the form of a straight-to-series order with programs that are flexibly developed through a piloting process. This paper contributes to the literatures on innovation, entrepreneurship and real options by identifying which investment types will benefit most from flexibility. Supplemental Material: The e-companion is available at https://doi.org/10.1287/stsc.2021.0095 .

Which Types of Investments Benefit from Retaining the Flexibility to Terminate?

Firms can choose to make investments while retaining the option to terminate them prior to completion. This flexibility can mitigate uncertainty about the investment that is present at the time of its initial funding. However, this flexibility can also detrimentally alter actions within the firm that are necessary for the investment’s success, such as whether scarce firm resources are allocated to the investment. This paper develops a set of hypotheses which predicts flexibility may not improve investment performance when the investment generates limited early-stage learning and requires certain types of resources. These hypotheses are empirically tested in a data set of new U.S. television programs, comparing programs that receive commitment in the form of a straight-to-series order with programs that are flexibly developed through a piloting process. This paper contributes to the literatures on innovation, entrepreneurship and real options by identifying which investment types will benefit most from flexibility. Supplemental Material: The e-companion is available at https://doi.org/10.1287/stsc.21.0095 .

Using Heatmap Visualization to assess the performance of the DJ30 and NASDAQ100 Indices under diverse VMA trading rules.

We investigate whether using various VMA trading rules would improve investment performance due to the flexibility of VMA trading rules and the aid of Heatmap Visualization. Previously, investors frequently chose the best performance derived from limited VMA trading rules. However, our new design, which can display all results using Heatmap Visualization, shows that the NASDAQ100 index outperforms the DJ30 index and that weekly data outperforms daily data when measured by annualized return. These findings may be useful to those who trade index ETFs tracking the DJ30 and NASDAQ100 indices, as well as investors making investment decisions, and may contribute to the existing literature by evaluating the outcomes of VMA trading rules and providing insights for index ETF investors using a heatmap matrix, which is rarely explored and presented in the relevant literature.

IMPACT OF EMOTIONS ON INVESTMENT DECISIONS OF INDIVIDUAL INVESTORS IN VIETNAM STOCK MARKET

To improve investment performance and achieve long-term returns, investors need to control their emotions. The article studies the impact of emotions on individual investors' decision to buy and sell securities, including two main expressions: loss aversion and regret aversion. The article uses descriptive statistical methods and analyzes data through the results of a survey of 150 individual investors on the Ho Chi Minh City Stock Exchange. The results show that investors' decisions are influenced by loss aversion and regret aversion. Investors often feel stress when losing, they keep losing stocks for a long time because they hope the price can rise again, but when they make a profit, they sell their shares very quickly to take profits because they are afraid of regret if they lose their profits, which reduces investment efficiency, even leads to losses. To improve investment results, investors need to control their emotions well through careful planning and disciplined execution of the plan.

Digital economy and business investment efficiency: Inhibiting or facilitating?

The digital economy’s integration with the real-world economy has revealed its remarkable ability to transform and promote traditional industries and form new economic development momentum. This paper studies the impact of digital economy development on corporate investment efficiency based on data from China’s listed companies from 2007 to 2019. There are three key findings. (1) Digital economy development can effectively improve corporate investment efficiency, mainly by inhibiting their overinvestment. (2) The digital economy’s impact mechanism for improving corporate investment efficiency lies in its ability to improve investment performance by reducing transaction costs and optimizing resource allocation, which, in turn, inhibits overinvestment. (3) The promotional effect of digital economy development on investment efficiency shows significant variability across different types of firms. These findings have particular reference value for promoting the digital development of China’s real industries and improving their investment efficiency.

The Evaluation of Mean-Detrended Cross-Correlation Analysis Portfolio Strategy for Multiple risk Assets.

The fractal characteristics of the security market were considered in portfolio strategy optimization. First, the detrended cross-correlation analysis was adopted to measure the fractal correlation of different securities. Second, the fractal correlation was embedded into the mean-variance criterion of the modern portfolio theory. Third, the mean-detrended cross-correlation analysis portfolio strategy of multiple risk assets was constructed, and the analytic solution of the strategy was given. Finally, the evaluation results revealed that the constructed the mean-detrended cross-correlation analysis portfolio strategy clearly improved investment performance, thus achieving the goal of optimizing the multiple risk asset portfolio strategy.

Financial Literacy on Investment Decisions: A Reference to Undergraduate Students in Butwal

The presence of information and abilities that enable informed and efficient money management is known as financial literacy. The country's financial improvements and economic expansion are being aided by financial literacy. In light of these changes, it's critical to evaluate if the younger generation, particularly students who are viewed as the future investors, movers, and transformers of the economy, has the requisite understanding of financial principles. This study examines the impact of financial literacy on investing decisions among undergraduate in the Butwal area. A total of 500 students from different universities of Butwal areas are participated in this study. The current study used a few characteristics to evaluate students' financial literacy, such as their knowledge of financial products, their ability to access financial goods, their knowledge of money management, their understanding of financial investment options, and their financial abilities. The goal of the study was to determine how a student's level of financial literacy affects his or her financial beliefs, choices, and behaviors. The results showed that undergraduates investing decisions were favorably and significantly impacted by knowledge with financial product. Financial abilities were the most important component when it came to the many aspects of financial literacy. The researcher concludes by offering some recommendations for financial institutions and decision-makers in order to raise financial literacy levels and improve investment performance.

Fractal statistical measure and portfolio model optimization under power-law distribution

An effective portfolio selection model is constructed on the premise of measuring accurately the risk and return on assets. According to the reality that the tail of returns on assets obey power-law distribution, this paper firstly builds two fractal statistical measures, fractal expectation and fractal variance, to measure the asset returns and risks, inspired by the method of measuring curve length in the fractal theory. Then, by incorporating the fractal statistical measure into the return-risk criterion, a portfolio selection model based on fractal statistical measure is established, namely the fractal portfolio selection model, and the closed-form solution of the model is given. Finally, through empirical analysis we find that the fractal portfolio selection model is effective and can improve investment performance.

Portfolio optimization with behavioural preferences and investor memory

In this paper, we investigate the performance of behavioural portfolio strategies. We incorporate the short-term and long-term memory of the investor, thus recasting the behavioural portfolio choice process in a dynamic setting. We evaluate the out-of-sample performance of a behavioural investor in relation to both a naïve investor who invests in an equally weighted portfolio and a rational investor, who maximises expected mean-variance utility. We report a number of findings. First, from an expected utility perspective, neither the rational investor nor the CPT investor achieves a risk-adjusted return or certainty equivalent return that significantly outperforms that of the naïve investor. Second, from a CPT utility perspective, the behavioural investor outperforms both the rational and naïve investors. Third, the CPT investor typically displays highly concentrated, lottery-like asset allocations, low turnover and highly stable portfolio allocations. Fourth, the addition of the investor's memory into the portfolio choice process increases both diversification and turnover, leading to improved investment performance. Finally, by allocating more weight to positively skewed assets and increasing portfolio concentration, the probability weighting function has more impact than the utility function on the behavioural investor's performance. Our results are robust to the choice of reference return, estimation sample size, probability estimates, the probability weighting function and portfolio weight constraints.

Patent predictive price-to-book ratio (PB) on improving investment performance -- Evidence in China

Patent is strongly meaningful for most countries’ technology development and economy growth. China is the world largest patent application country and has the world No.2 stock market. In this research, China listed companies (A-shares) in Shanghai main board, Shenzhen main board, GE board, and SME board from 2016 to 2018 were applied to discuss the prediction ability of patent indicators to financial performance. The patent prediction equations for quantitatively predicting the price-to-book ratio (PB) by patent indicators were constructed via Granger Causality test and time series regression. The stock selection criteria based on the patent predictive PB were further discussed. The traditional value investors consider stocks with PB values under 3.0 are undervalued. It was found that most stock portfolios selected by either the lower predictive PB or the higher predictive PB growth rate had higher performance above the traditional PB investment strategy. The criteria also worked well on GE board and SME board even though these stock boards were seriously impacted to decline by the China-US trade conflict. Though the overall economic environment fluctuated, the patent prediction algorithm proposed was proved to be useful to discover good stock portfolios and improve traditional PB investment strategy

Stochastic Bounds for Reference Sets in Portfolio Analysis

A stochastic bound is a portfolio that stochastically dominates all alternatives in a reference portfolio set instead of a single alternative portfolio. An approximate bound is a portfolio that comes as close as possible to this ideal. To identify and analyze exact or approximate bounds, feasible approaches to numerical optimization and statistical inference are developed based on linear programming and subsampling. The use of reference sets and stochastic bounds is shown to improve investment performance in representative applications to enhanced benchmarking using equity industry rotation and equity index options combinations. This paper was accepted by Kay Giesecke, finance.

Does Value Averaging Strategy Improve Investment Performance? Evidence from the Korean Fund Market

This study analyzes whether a value averaging (VA) strategy, which adjusts the amount of investment each period to achieve the target amount of investment in risk assets, as a modified form of a dollar cost averaging (DCA) strategy, improves investment performance. Using 18.5 years of fund market data in Korea from 2001 to June 2019, we compare the investment performance of VA strategy relative to two alternatives: DCA strategy, which invests a certain amount in each period, and Buy-and-Hold (BH) strategy, which refers to half-and-half asset allocation between risky and risk-free assets and has an expected return which is the same as that of DCA in the ex-ante sense. Our historical performance analysis reveals that the VA strategy has lower average return and higher standard deviation compared to the BH strategy and has lower average return and lower standard deviation compared to the DCA strategy. These findings are in stark contrast to the claims made by advocates of VA strategy that the strategy improves investment performance.

Is Exclusion Effective?

Many believe that investors can contribute to a more sustainable world by divesting from firms with the worst sustainability profiles. However, exclusion comes down to a transfer of ownership from sustainability-minded investors to other investors, and it is not obvious how this is supposed to lead to changes for the better in society. This article critically examines the arguments for exclusion and concludes that the effectiveness of exclusion policies is questionable. Investors may well achieve more by exerting influence as an active shareholder through voting and engaging with firms. TOPICS:ESG investing, portfolio theory, portfolio construction Key Findings • Excluding firms with the worst sustainability profiles boils down to a transfer of ownership. It is not obvious how this is supposed to lead to changes for the better in society. • We challenge the effectiveness of four frequently used arguments in favor of exclusion policies: increasing a firm’s cost of capital, pushing a firm out of business, improving investment performance, and signaling stakeholders to change behavior. • Altogether, the effectiveness of exclusions is questionable. Investors may well achieve more by exerting influence as an active owner, through voting and engaging with firms.

Information Sharing and Investment Performance in the Venture Capital Network Community: An Empirical Study of Environmental-Social-Governance Start-Ups

Information sharing plays a significant role in improving investment performance in the venture capital network community, which serves as an important requirement for the venture capital network to expand to the meso-level and promote its healthy development. Given the important role of Environmental-Social-Governance (ESG) start-ups in promoting sustainable development, this paper selects a sample of ESG start-ups in China to explore the relationship between venture capital network community information sharing and investment performance. We also examine the intermediary role of investment capability in this relationship. Empirical results show that venture capital network community information sharing, from both the prospective of breadth and depth, has a significant positive impact on investment performance of ESG start-ups. We also find that the investment capability, such as scouting and coaching, plays a partial intermediary role in affecting investment performance by community information sharing. This research helps to reveal the relationship between venture capital network community information sharing and investment performance. The results provide a theoretical basis and managerial insights for improving investment performance of ESG start-ups.

The Value of sustainability

As the market place becomes increasingly competitive and there is a need to be able to differentiate oneself as a high performer. Andrew Vaughan the CEO of Redevco stated‘Greening ourportfolio over the next two years is not only environmentally the right thing to do, it also makes soundbusiness sense.’Buildings built and/or managed to sustainability standards, such as BREEAM have been shown to minimise risk and generate maximum profit via:• High and continuous rental income;• Low operating & maintenance cost;• Low depreciation.UK valuers do not think we are paying a premium for green buildings but having to give a discount because the building is not performing well. This gives a convincing business case for new build where the certification process leads to a high-performance building.However, what about the existing building stock?Is the operational environmental performance of an asset reflected by its investment performance?This paper describes a new research project which aims to test the Hypothesis –Better operational performance in-use leads to improved investment performance of commercial offices. Improved operational performance goes “hand-in-hand” with environmental performance; where the performance can be illustrated by certification and labelling schemes.