Investment Management and Financial Innovations
ISSN / EISSN : 18104967 / 18129358
Current Publisher: LLC CPC Business Perspectives (10.21511)
Total articles ≅ 428
Latest articles in this journal
Published: 11 July 2019
Investment Management and Financial Innovations, Volume 16, pp 1-9; doi:10.21511/imfi.16(3).2019.01
Abstract:The research examines the role of discussion in investors’ decision in a step-by-step information setting. Several studies present that disclosure strategy stimulates order-effect bias, but simultaneous information decreases the impact of that bias. This bias makes people weigh more heavily to recent observations than they do to older ones. Using step-by-step information, a recency effect is expected to be found. This study uses an experimental method. The participants are the representation of non-professional investors in the stock market because of a lack of knowledge and experience. Participants are also a reflection of the customer easiness in registering to be stock traders. The role of discussion between participants is a new feature of this experiment. After evaluating participants’ decision in a discussion, the experiment shows that an individual’s choice after discussion produces more bias, although they already learn the information before the discussion. The research finds that (1) using the within-subject sample, group discussion produces overvaluation (undervaluation) in positive (negative) sequential information, (2) there is bigger price revision when negative sequential information is presented. This study suggests disclosure strategies for companies. Considering a recency bias, companies must present step-by-step information when they disclose good news, but they must avoid step-by-step disclosures when giving bad news. The second practical implication is for investors; they need to think about the benefits of joining an investor club, since the discussion exacerbates recency bias. These results are expected to contribute to finance literature.
Published: 5 July 2019
Investment Management and Financial Innovations, Volume 16, pp 383-394; doi:10.21511/imfi.16(2).2019.32
Abstract:In recent years, China’s mutual fund market has grown exponentially. With hundreds of new funds introduced into the market each year, an essential question to ask is whether this voluminous growth promotes funds’ efficiency, as funds compete for investment. To overcome the drawbacks of traditional portfolio performance metrics, this study utilizes a non-parametric model, data envelopment analysis (DEA), to assess the relative efficiency of equity and hybrid funds for 2016–2018. The empirical results show that despite the development in the fund industry, only a small portion of the funds are fully efficient. While efficiency improvement is observed in equity funds, the efficiency in hybrid funds actually deteriorates. On average, equity funds are more efficient and persistent in performance than hybrid funds. The empirical results also indicate that the primary areas of inefficiency are downside risk management and fund fee structures. For hybrid funds, fund size is also related to efficiency performance. The findings of this study offer implications for how to strengthen the development and stability of the Chinese mutual fund market.
Published: 5 July 2019
Investment Management and Financial Innovations, Volume 16, pp 370-382; doi:10.21511/imfi.16(2).2019.31
Abstract:Improving the efficiency and performance of microfinance investments is essential to achieve its objectives in terms of economic and social development. One parameter that influences such a performance is the kind of the activity exercised by the micro-entrepreneurs. The aim of this paper is to provide a decision-making guide to help both microfinance institutions and investors to choose the appropriate Islamic banking contract with respect to each sector of activity. To attain this goal, an Intuitionistic Fuzzy TOPSIS evaluation is conducted in collaboration with Moroccan Islamic finance experts and practitioners. The proposed approach has the advantage to deal with the lack of quantitative historical data, as well as the uncertainty of the decision makers’ judgments. The suggested work will be helpful for the Moroccan participative banks and for the future Islamic microfinance institutions as well.
Published: 4 July 2019
Investment Management and Financial Innovations, Volume 16, pp 355-369; doi:10.21511/imfi.16(2).2019.30
Abstract:The paper examines the bias introduced by metaorder limit prices when measuring quality of execution services on financial market. While evaluating the quality of execution services, observed execution costs should be adjusted for metaorder participation rate, size and duration to ensure that they are comparable across execution service providers. One of the exogenous factors which may bias measured execution costs are the different metaorder limit prices in the sample. Currently, there are no proposed methods to normalize for this bias. In the research, the difference in execution costs for metaorders with different limit prices was examined by implementing a limit order book simulation model. It was discovered that the difference in metaorder limit prices is a source of significant heterogeneity in the execution cost distribution. However, we were able to prove that when market agents trade with constant intensities, the difference in execution costs for metaorders with different limit prices is fully explained by their realized participation rate. As a result, financial institution may assess quality of execution services for metaorders without any reservations about differences in metaorders limit prices as long as execution costs are adjusted for different participation rates.
Published: 27 June 2019
Investment Management and Financial Innovations, Volume 16, pp 336-347; doi:10.21511/imfi.16(2).2019.28
Abstract:The purpose of this study is to examine dividend policy on both the controlling and non-controlling shareholders based on assumptions according to theories of life cycle, and free cash flow.The sample for this study is 241 listed firm in Indonesia Stock Exchange during the period from 2010 to 2015. This study divides the sample based on quartiles and analyzes it by conducting logistic regression with significant rate at 0.05. This study provides the evidences that: (1) firms as dividend payers tend not distribute their dividend for controlling shareholders and non-controlling shareholders while the composition for both shareholders are almost equal; (2) firms as dividend payers also have tendency not to distribute dividend on controlling shareholders when this shareholders have largest percentage of ownership; and (3) firms as dividend payers tend not distribute dividend on non-controlling shareholders while they have lowest retained earnings.The findings imply that life cycle theory and free cash flow theory can explain the behavior of dividending policy on controlling shareholders and non-controlling shareholders depend on their circumstances.The study uses alternative measurement for non-controlling shareholders as this variable together with controlling shareholders are moderating the other independent variables for testing the model of dividend policy.
Published: 27 June 2019
Investment Management and Financial Innovations, Volume 16, pp 348-354; doi:10.21511/imfi.16(2).2019.29
Abstract:FinTech innovations are one of strategic decisions to increase the profitability of a company. This study determines the level of profitability of companies before and after the emergence of FinTech products. The authors focused on companies that have launched FinTech products and published their financial reports. The study sample consisted of 17 FinTech products from 16 companies in Indonesia. The limited number of the sample was caused by not all of them having published its financial reports, while we have checked 157 FinTech companies. An event study approach using paired sample T-test is utilized. The period used in this study is four years, covering two years before and two years after the company launched FinTech products. Data were obtained from IDX, FinTech.id, and company web-pages. The results clearly showed that there was a significant influence on return on assets (ROA), but no significant difference in return on equity (ROE). This finding gives more contribution to the FinTech industry about the company’s profitability impact of launching FinTech product.
Published: 25 June 2019
Investment Management and Financial Innovations, Volume 16, pp 326-335; doi:10.21511/imfi.16(2).2019.27
Abstract:The objective of the research carried out is to understand the impact of selected economic variables (such as Crude Oil Price, GDP, Industrial Production, Exchange Rates, and Inflation) on credit rating of Indian companies.The sample comprises of 120 rating observations during the period 2012–2016 for a total of 24 companies of India.Measurement of central tendency – descriptive statistics is used where credit rating is used as dependent variable and five economic factors viz. Crude Oil Price, GDP, Industrial Production, Exchange Rates, and Inflation as the independent variables. Results from the analysis indicate that the credit rating responds in both linear, as well as nonlinear manner, to selected economic factors. Economic factors such as GDP, Industrial Production, and Exchange Rates have a linear relationship to credit rating, whereas Crude Oil price and Inflation have a non-linear impact upon the credit rating.
Published: 24 June 2019
Investment Management and Financial Innovations, Volume 16, pp 295-312; doi:10.21511/imfi.16(2).2019.25
Abstract:Forecasting companies long-term financial health is provided by Credit Rating Agencies (CRA) such as S&P, Moody’s, Fitch and others. Estimates of rates are based on publicly available data, and on the so-called ‘qualitative information’. Nowadays, it is possible to produce quite precise forecasts for these ratings using economic and financial information that is available in financial databases, utilizing statistical models or, alternatively, Artificial Intelligence techniques. Several approaches, both cross section and dynamic are proposed, using different methods. Artificial Neural Networks (ANN) provide better results than multivariate statistical methods and are used to estimate ratings within all the range provided by the CRAs, obtaining more desegregated results than several proposed models available for intervals of ratings. Two large samples of companies ‘public data’ obtained from Bloomberg are used to obtain forecasts of S&P and Moody’s ratings directly from these data with high level of accuracy. This also permits to check the published rating’s reliability provided by different CRAs.
Published: 24 June 2019
Investment Management and Financial Innovations, Volume 16, pp 313-325; doi:10.21511/imfi.16(2).2019.26
Abstract:This paper examines the effect of industry-wide factors such as product market competition on corporate tax avoidance. Specifically, the focus is on the moderating role of corporate governance in the relationship between product market competition and tax avoidance. To conduct an empirical analysis, a sample of public companies that are listed on the Korea Stock Exchange between 2001 and 2016 is used. The empirical analyses provide the following results. First, product market competition is negatively related to tax avoidance. This suggests that competitive markets act as external corporate governance mechanisms and discipline managers to decrease tax avoidance. Second, the negative association between product market competition and tax avoidance is more pronounced for firms with more independent board of directors and firms with audit committee consisting of outside directors. These findings imply that product market competition acts more effectively when the firm has strong internal governance mechanisms such as board independence and audit committee independence. Therefore, we provide evidence on a complementary relationship between internal governance system and product market competition. The results may be of interest to policy makers and regulators like Korea Fair Trade Commission and Financial Supervisory Service who are involved in promoting market competition, monitoring any abuse of market dominance, and supervising financial reporting quality.
Published: 20 June 2019
Investment Management and Financial Innovations, Volume 16, pp 260-269; doi:10.21511/imfi.16(2).2019.22
Abstract:The development of the corporate securities market and the effective use of tools for its regulation cannot be achieved without models and methods of economic and mathematical modeling. The aim is to analyze and systematize the structural and temporal characteristics of the corporate securities market in Ukraine by applying economic and mathematical modeling methods. In the paper, linear interpolation is used to assess the temporal characteristics of corporate securities under market uncertainty. Descriptive and simulation modeling methods are also applied to carry out a formal description of the process of evaluating the structural characteristics of securities. The result of the study involves developing a descriptive model to analyze the structural and temporal characteristics of the Ukrainian corporate securities market. The approbation of the proposed model makes it possible to draw the following conclusions. First, Perspektiva Stock Exchange, Ukrainian Exchange and PFTS – the First Stock Trading System, are the most important trading platforms. They are determined by the monthly bidding dynamics and can belong to the same group – active players in the corporate securities market of Ukraine. Second, in terms of endogenous priorities, the development of the corporate securities market is mostly influenced by inflation rates (consumer price index), economic development indicators (key branches production index) and interest rates on alternative financial instruments (new deposit interest rates of deposit-taking corporations). Third, the rate of corporate securities issue and the native currency rate do not significantly affect the corporate securities market development, in particular, the former is characterized by a slight negative impact, and the latter – by a slight positive impact on the price dynamics.