Real estate derivatives as financial instrument – possibility prospects of usage in Poland

The government bond (GB) has become the most attractive investment portfolio option, even though many macroeconomic factors affect the bond yield. This paper aims to investigate the determining factor of local currency government bond yield by considering the inflation rate, credit default swap, stock market index, exchange rate, and volatility index. This study used 240 data panel from the Bloomberg stock market in the form of data panel covering Southeast developing countries, namely Indonesia, Thailand, Malaysia, and the Philippines, for five years or sixty months from January 2015 to December 2019. Data analysis used recursive models and multivariate regression techniques using EViews software. The random effect model results revealed that change in the foreign exchange rate and volatility indexes affected, partially and simultaneously, the changes in the stock market index. The result also showed that changes in the stock market index, inflation rate, and credit default swap affected, partially and simultaneously, government bond yield changes. These results suggest that the government bond yield could be managed by controlling volatility index, foreign exchange rate, stock market index, inflation rates, and credit default swaps. This finding could provide an insight into the policymaker and fiscal authority on managing the risk of government bonds under control during high volatility or even making it reasonably lower. This result could contribute to the current research in the field of financial management.

Acknowledgment
It is the author’s pleasure to thank Muhammad Aulia SE MSc CSA® from the Ministry of Finance of Republic Indonesia, for his invaluable contribution to encourage this study and also to share the data required for this paper. He also delivers essential insights into improving the quality of this work. This research received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors.

The stock market represents complex systems where multiple agents interact. The complexity of the environment in the financial markets in general has encouraged the use of modeling by multi-agent platforms and particularly in the case of the stock market.
In this paper, an agent-based simulation model is proposed to study the behavior of the volume of market transactions. The model is based on the case of a single asset and three types of investor agents. Each investor can be a zero intelligent trader, fundamentalist trader or traders using historical information in the decision making process. The goal of the study is to simulate the behavior of a stock market according to the different considered endogenous and exogenous variables.

2020 revealed the vulnerability of the healthcare systems in most countries. It also highlighted their failure to generate serious progress in the fulfillment of Sustainable Development Goal 3 (SDG 3): Ensure healthy lives and promote welfare for all at all ages. One of the key problems inhibiting its progress is the lack of financial resources. Based on a comprehensive meta-analysis of the literature related to SDG 3 and its investment, it aims to demonstrate that lack of appropriate academic support is a part of the failure to generate serious progress in the fulfillment of SDG 3. To do this academic literature published in the period 2010–2019 is analyzed. SciVal Elsevier, VosViewer, and Google Trends tools are applied for analysis. The results show that there is a significant interest in the academic circles on SDG 3 alone. However, this interest is concentrated toward its medical aspects while economic aspects, including investment, are poorly represented. This study shows that the reason for the current investment gap in SDG 3 is the lack of academic support to provide a theoretical, methodological, and analytical framework for tackling the financing problem for SDG 3.