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This paper aims to contribute to formulating the methodological framework for a paradigm of Islamic economics, using the development of the conventional economics, theoretical and mathematical methods.

The study based on the inductive and mathematical methods to contribute to economic theory within the methodological framework for Islamic Economics, by using the return rate of Musharakah rather than the interest rate in influence the economic activity and monetary policy.

Via replacement, the concept of the interest rate by the return rates of Musharakah. It concludes that the central bank can control the monetary policy, economic activity and the efficient allocation of resources by using the return rates of Musharakah through the framework of Islamic economy.

The study is a contribution to formulate the methodological framework for a paradigm of Islamic economics, where it investigates the impact of return rates of Musharakah on the money market and monetary policy, by the mathematical methods used in the conventional economy. Also, the study illustrates the importance of further studies that examine the methodological framework for Islamic Economics.

The study aims to contribute to formulating the Islamic economic theory, through the return rate of Musharakah financing instead of the interest rate, and its effectiveness of the monetary policy. As well as reformulating the concepts of the investment function, the present value and the marginal efficiency rate of investment according to the Islamic economy approach.

The purpose of this paper is to implement a genetic algorithmic geared toward building an optimized investment portfolio exploring data set from stocks of firms listed on the Nigerian exchange market. To provide a research-driven guide toward portfolio business assessment and implementation for optimal risk-return.

The approach was to formulate the portfolio selection problem as a mathematical programming problem to optimize returns of portfolio; calculated by a Sharpe ratio. A genetic algorithm (GA) is then applied to solve the formulated model. The GA lead to an optimized portfolio, suggesting an effective asset allocation to achieve the optimized returns.

The approach enables an investor to take a calculated risk in selecting and investing in an investment portfolio best minimizes the risks and maximizes returns. The investor can make a sound investment decision based on expected returns suggested from the optimal portfolio.

The data used for the GA model building and implementation GA was limited to stock market prices. Thus, portfolio investment that which to combines another capital market instrument was used.

Investment managers can implement this GA method to solve the usual bottleneck in selecting or determining which stock to advise potential investors to invest in, and also advise on which capital sharing ratio to reduce risk and attain optimal portfolio-mix targeted at achieving an optimal return on investment.

The value proposition of this paper is due to its exhaustiveness in considering the very important measures in the selection of an optimal portfolio such as risk, liquidity ratio, returns, diversification and asset allocation.

This study aims to determine whether, by means of the application of genetic algorithms (GA) through the traditional technical analysis (TA) using moving average convergence/divergence (MACD), is possible to achieve higher yields than those that would be obtained using technical analysis investment strategies following a traditional approach (TA) and the buy and hold (B&H) strategy.

The study was carried out based on the daily price records of the NASDAQ financial asset during 2013–2017. TA approach was carried out under graphical analysis applying the standard MACD. GA approach took place by chromosome encoding, fitness evaluation and genetic operators. Traditional genetic operators (i.e. crossover and mutation) were adopted as based on the chromosome customization and fitness evaluation. The chromosome encoding stage used MACD to represent the genes of each chromosome to encode the parameters of MACD in a chromosome. For each chromosome, buy and sell indexes of the strategy were considered. Fitness evaluation served to defining the evaluation strategy of the chromosomes in the population according to the fitness function using the returns gained in each chromosome.

The paper provides empirical-theoretical insights about the effectiveness of GA to overcome the investment strategies based on MACD and B&H by achieving 5 and 11% higher returns per year, respectively. GA-based approach was additionally capable of improving the return-to-risk ratio of the investment.

Limitations deal with the fact that the study was carried out on US markets conditions and data which hamper its application in some extend to markets with not as much development.

The findings suggest that not only skilled but also amateur investors may opt for investment strategies based on GA aiming at refining profitable financial signals to their advantage.

This paper looks at machine learning as an up-to-date tool with great potential for increasing effectiveness in profits when applied into TA investment approaches using MACD in well-developed stock markets.

This study aims to investigate the response of green investments of emerging countries to own-market uncertainty, oil-market uncertainty and COVID-19 effect/geo-political risks (GPRs), using the tail risks of corresponding markets as measures of uncertainty.

This study employs Westerlund and Narayan (2015) (WN)-type distributed lag model that simultaneously accounts for persistence, endogeneity and conditional heteroscedasticity, within a single model framework. The tail risks are obtained using conditional standard deviation of the residuals from an asymmetric autoregressive moving average – ARMA(1,1) – generalized autoregressive conditional heteroscedasticity – GARCH(1,1) model framework with Gaussian innovation. For out-of-sample forecast evaluation, the study employs root mean square error (RMSE), and Clark and West (2007) (CW) test for pairwise comparison of nested models, under three forecast horizons; providing statistical justification for incorporating oil tail risks and COVID-19 effects or GPRs in the predictive model.

Green returns responds significantly to own-market uncertainty (mostly positively), oil-market uncertainty (mostly positively) as well as the COVID-19 effect (mostly negatively), with some evidence of hedging potential against uncertainties that are external to the green investments market. Also, incorporating external uncertainties improves the in-sample predictability and out-of-sample forecasts, and yields some economic gains.

This study contributes originally to the green market-uncertainty literature in four ways. First, it generates daily tail risks (a more realistic measure of uncertainty) for emerging countries’ green returns and global oil prices. Second, it employs WN-type distributed lag model that is well suited to account for conditional heteroscedasticity, endogeneity and persistence effects; which characterizes financial series. Third, it presents both in-sample predictability and out-of-sample forecast performances. Fourth, it provides the economic gains of incorporating own-market, oil-market and COVID-19 uncertainty.

The traditional one-stage constant growth formula has two main underlying assumptions: a company will be able to maintain its competitive advantage for completed investments in perpetuity, and each year in the future, it will be able to generate new investment opportunities with the same competitive advantage, which will also remain in perpetuity. The purpose of this paper is to develop a model that limits the duration of the competitive advantage.

A new model is developed, and it is used to value a public company.

In this study, the author introduces an alternative formula considering the duration of the competitive advantage, imposing a restriction on the fact that extraordinary returns cannot be sustained forever, and also separates the part of the value explained by the current investments from the portion of value created by future investments.

The traditional one-stage constant growth model used to determine the continuing value of a company has limitations regarding the duration of the competitive advantage. The developed formula corrects the problem limiting the time extraordinary returns will remain over time.

National cultures significantly explain cross-country differences in the relation between asset growth and stock returns. Motivated by the notion that managers in individualistic and low uncertainty-avoiding cultures have a higher tendency to overinvest, this study aims to show that the negative relation between asset growth and stock returns is stronger in countries with such cultural features. Once the researchers control for cultural dimensions, proxies associated with the q-theory, limits-to-arbitrage, corporate governance, investor protection and accounting quality provide no incremental power for the relation between asset growth and stock returns across countries. Evidence of this study highlights the importance of the overinvestment hypothesis in explaining the asset growth anomaly around the world.

A controversy about whether liberalization through market opening is a necessary and sufficient condition for a stable and balanced growth in the developing countries was retriggered by the 2008 global financial crisis. This paper aims to analyze 1) the impact of market openness on the economic growth and financial development, 2) the dynamic correlation between the compositional change in foreign investments and the returns of domestic financial markets, 3) the effect of foreign portfolio investment on the stock market activity (liquidity and profitability). Our empirical findings infer that the income level has a positive relationship with financial openness and the foreign portfolio investments cause price fluctuations in the domestic stock market. These results imply that the precautionary and effective policies such as prudential regulations on the short-term capital transactions are strongly needed to emerging markets in order to prevent the excessive fluctuations in the financial markets over the macroeconomic fundamentals.

This paper demonstrates that present value (PV) models can be viewed as multiperiod extensions of accrual income statements (AISs). Failure to include AIS details in PV models may lead to inaccurate estimates of earnings and rates of return on assets and equity and inconsistent rankings of mutually exclusive investments. Finally, this paper points out that rankings based on assets and equity earnings and rates of return need not be consistent, requiring financial managers to consider carefully the questions they expect PV models to answer.

AISs are used to guide the construction of PV models. Numerical examples illustrate the results. Deductions from AIS definitions demonstrate the potential conflict between asset and equity earnings and rates of return.

PV models can be viewed as multiperiod extensions of AISs. Mutually exclusive rankings based on assets and equity earnings and rates of return need not be consistent.

PV models are sometimes constructed without the details included in AISs. The result of this simplified approach to PV model construction is that earnings and rates of return may be miscalculated and rankings based as asset and equity earnings and rates of return are inconsistent. Tax adjustments for asset and equity earnings may be miscalculated in applied models.

This paper provides guidelines for properly constructing PV models consistent with AISs.

PV models are especially important for small to medium size firms that characterize much of agricultural. Providing a model consistent with AIS construction principles should help financial managers view the linkage between building financial statements and investment analysis.

This is the first paper to develop the idea that the PV model can be viewed as a multiperiod extension of an AIS.

This study examines the role of behavioural factors, such as confidence, optimism, pessimism and rational expectation, in affecting investment decisions in the Pakistani stock market.

Using daily trading data of Karachi Stock Exchange-100 index from January 2012 to December 2015, different regression models, including descriptive statistics and stationarity tests, are performed.

Results indicate that stock market trading has suffered from pessimistic behaviour of investors. In the first model, the authors find a positive sign of confidence and negative sign of optimism with the trading volume. The second model shows a positive role of confidence and rational expectations in affecting the trading volume in daily, Monday and Friday samples. The results of the third model show a negative sign of both optimism and rational expectation with the trading volume. Furthermore, the next model shows a negative sign of confidence combined with pessimism while testing their relationship with the trading volume. Finally, results of the final model suggest that optimism negatively affects the trading volume, and on the other hand, pessimism has a positive impact on the trading volume.

The method and empirical testing of behavioural biases and their relationship with economic variable used in this study seem to be a promising way to better understand the role of psychology in deriving financial decisions for academics and policymakers.

This study uses secondary data for measuring behavioural biases and decomposes the effect between rational expectation and behavioural biases.

This study aims to fill the gap in previous research that focuses on the superficial aspects of equity crowdfunding (ECF) campaigns and financial practices by examining financial literacy aspects, such as due diligence and valuation, in terms of factors that influence Japanese individual investors' investments in ECF.

The status of information disclosure in ECF campaigns is checked. In addition, the feasibility of the initial due diligence and valuation using this information is verified. Specifically, the lack of financial literacy hypothesis is developed and (1) expected market capitalization in the final fiscal year of the business plan and (2) expected returns on investment (IRR: internal rate of return) are estimated.

ECF campaigns in Japan disclose information equivalent to that obtained by professional venture capitalists. Analysis of the disclosed business plan allows for initial due diligence and valuation. By contrast, due diligence reveals that some projects are unlikely to be listed even if their business plans are met, and others have low IRRs. In addition, a stock acquisition rights project, in which even professional investors are unable to calculate IRRs, is completed at the same rate as a common stock project; this suggests that individual investors lack financial literacy.

Analyzing ECF from financial literacy aspects, such as due diligence and valuation, is unique. Such aspects are essential for private equity investments but have not been addressed in previous studies.