In macroeconomics, decision making is highly sensitive and significantly influences the financial and business world, where the interest rate is a crucial factor. In addition, the interest rate is used by the governments to manage the monetary policy. There is a need to design an efficient algorithm for interest rate prediction. The analysis of the social media sentiment impact on financial decision making is also an open research area. In this study, we deploy a deep learning model for the accurate forecasting of the interest rate for the UK, Turkey, China, Hong Kong, and Mexico. For this purpose, daily data of the interest rate and exchange rate covering the period from Jan 2010 to Oct 2019 is used for all the mentioned countries. We also incorporate the input of the twitter sentiments of six mega-events, namely the US election 2012, Mexican election 2012, Gaza under attack 2014, Hong Kong protest 2014, Refugee Welcome 2015, and Brexit 2016. Our results provide evidence that the error of the deep learning model significantly decreases when event sentiment is incorporated. A notable improvement has been observed in the case of the Hong Kong interest rate, i.e., a 266% decline in the error after incorporating event sentiments as an input in the deep learning model.

Over the last thirty years, Asian countries have become a chief player in the worldwide scene. Pakistan is facing an acute energy disaster since last decade that impacts on social and economic development. Sustainable energy supply is an essential feature for the economic growth of any society. From the last five years, Pakistan is facing a shortfall between 4,000-5,000 megawatt. This study inspects the association between energy security, energy crisis, energy demand, energy supply, and renewable potential in Pakistan. It also evaluates the final energy demand-supply gap, provincial renewable energy distribution, sectorial distribution, and policy recommendation for future energy. For this study, we applied renewable and non-renewable energy scenarios during 2014-2035 and Market-Allocation method to prove the energy situation in Pakistan. The outcomes show that renewable resources are the best option in reducing energy risk, import cost, and enhance environmental and economic sustainability. With the objectives of our key findings, targeted suggestions and policies are given.

This study uses panel co-integration methods and Granger causality examines to scrutinize the dynamic causal relationship between carbon dioxide (CO2) emissions, gross domestic product (GDP), renewable energy (RE), agriculture value added (AVA) and population for the thirteen developed and developing Asia Pacific countries (APCs) covering the period 2005-2017. The results evaluate in two ways: in the short-run, Granger causality test (GCT) is operating from AVA to GDP and express bidirectional causation among GDP and agriculture. In the distant future, there is causality from RE and Population to CO2emissions. The short-run causality is important due to the agriculture sector which causes in boosting GDP while economic development, population and clean energy (including waste and combustible) raise CO2 emissions causes in the reduction of production and services. The research finds out that reduction in AVA, GDP increase, uncontrolled population and lack of attention on clean energy are interrelated in creating emissions. Policy recommendation insights that Asian Pacific establishments should control the population, less use of fossil fuel, encourage clean energy technologies such as solar and wind to fight with global warming.

Purpose: The aims of this study to find the web disclosure as mediating role in the relationship between paradox of choice, investor experience, financial literacy and investment decision making.. Design/Methodology/Approach: Data were obtained from the 200 respondents for recent empirical investigation. The structural equation model is employed for analyzing the data. Findings: The novel findings suggest that paradox of choice, investor experience, and financial literacy have direct positive effect on investment decision making. Moreover, the findings recommend that web disclosure acts as a mediator between paradox of choice, investor experience, financial literacy and investment decision making Implications/Originality/Value: The novel findings recommend that an important policy implication of web information disclosure for the investor.

The paper re-examines the principle of the bird-in-hand under the dynamic situation in the emerging spots market in Pakistan. Our sample consisted of 100 KSE—100 companies dating 2009–2024. The abnormal returns are separated out using an event study model and a rolling window version of the CAPM, and we have constructed a new Dividend Announcement Factor (DAF) to capture systematic variation associated with the payout signals. The evidence proves the bird-in-hand preference defined by cumulative abnormal returns around announcement dates is highly positive. As opposed to conventional yield preference models, the size of the dividend yield is not correlated with the abnormal returns, depicting that the presence of a signal is more important than its strength. The inclusion of DAF in the CAPM increases the explanatory power by an average of 2.84%. These findings imply that current payouts are more important to investors in high-uncertainty markets; the impact, however, seems to be caused by apparent binary signal and not yield maximization. We have also discussed the limitations regarding event clustering and potential omitted variable bias.