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This paper aims to examine the effect of both inflation rate and interest rate on stock prices using quarterly data on non-financial firms listed in DJIA30 and NASDAQ100 for the period 1999-2016. The stock duration model is used to measure the sensitivity in variations in inflation rates and interest rates on stock prices.

The authors use standard statistical tools that include Johansen cointegration test, linearity, normality tests, cointegration regression, Granger causality and vector error correction model.

The results of panel Johansen cointegration analysis show that cointegration exists between the stock prices, the changes in stock prices due to inflation rates and the changes in stock prices due to real interest rates. The results of cointegration regression show that inflation rates are negatively associated with stock prices, the real interest rates and stock prices are positively associated, changes in real interest rates and inflation rates Granger cause significant changes in stock prices, significant speed of adjustment to long run equilibrium between observed stock prices and real interest rates and significant speed of adjustment to long run equilibrium between changes in stock prices due to real interest rates and changes in inflation rates.

This paper contributes to the empirical literature in three ways. The paper examines the effects of inflation and interest rates on stock prices differently from other related studies by separating inflation from real interest rates. The paper examines the causality between stock prices, interest and inflation rates. This paper offers significant updated validity to extended literature that a negative association exists between stock prices and inflation rates. This validity can be considered as an existence a theory of stock prices, inflation rates and interest rates.

The purpose of this paper is to examine the effect of economic policy uncertainty (EPU) of China on investment opportunities in five ASEAN economies.

This paper employs advanced empirical approaches, such as Multivariate DCC-GARCH and Continuous Wavelet Transform (CWT) to test the research objective. The period of analysis involved monthly data from 2003 until 2019.

This paper provides evidence where the Malaysian stock market to be the least exposed to risks emanating from Chinese EPU, followed by Singapore, the Philippines, Thailand and Indonesia. Results for investment opportunities based on time horizon suggest, for a short-term holding period, investors are better off investing in Singapore and Indonesia, while, for medium-term holding periods, all ASEAN markets appear lucrative except for the Philippines.

From a managerial perspective, the outcome or findings of this study are expected to aid the retail and institutional investors in designing better strategies on diversifying a stock portfolio with different holding periods.

Theoretically, the findings of this study contribute fresh insights into an emerging strand of literature focusing on the transmission of regional policy. Methodologically as well, this study is a novel venture to the best of authors' knowledge.

The purpose of the paper is to examine the differences in the impact of financial stress in advanced and emerging economies.

The authors employ a panel vector autoregression model (PVAR) for a comparative analysis of the relationship between financial stress, economic growth and monetary stability in 14 advanced and emerging economies. A homogeneous measure of financial stress is constructed and measured as an index that provides signals of stress episodes in an economy.

The impact of financial stress shocks is greater on the economic growth of advanced economies; likewise, financial stress shocks are significant only in advanced economies. The interbank interest rate is negatively affected by financial stress in emerging economies. In general, the results show a clear view of the importance of financial stability and the economic relevance of financial stress measures in the context of macro-prudential regulation.

The results can be extended to monetary policy to implement measures that mitigate the impact of future financial crises.

The study aims to determine the long and short-term causal relationships between the variables associated with the adjustment of monetary policy and the stock market in India in the presence of structural breaks.

The study employed the autoregressive distributed lag (ARDL) bounds test and the Error Correction Model to assess long- and short-term causal relationships. The study also used non-frequentist Bayesian inferences for the validity of estimation robustness. The Bai–Perron test is used to identify breakpoint dates for the Indian stock market index, and the Granger Causality test is employed to ascertain the direction of causality.

The F-bounds test reveals cointegration among the variables throughout the examined period. Specifically, the weighted average call money rate (WACR), inflation (WPI), currency exchange rate (EXE), and broad money supply (M3) exhibit statistical significance with precise signs. Furthermore, the study identifies the negative impact of the COVID-19 outbreak in March 2020 on the Indian stock market.

Although the study provides significant insights, it is not exempt from constraints. A significant limitation is selecting a relatively limited time period, specifically from April 2008 to September 2023. The limited time frame of this study may restrict the applicability of the results to more comprehensive economic settings, as dynamics between the monetary policy and the stock market can be influenced by multiple factors over varying time periods. Furthermore, the utilisation of the Weighted Average Call Money Rate (WACR) rather than policy rates such as the Repo rate presents an additional constraint as it may not comprehensively account for the impacts of particular policy initiatives, thereby disregarding essential complexities in the connection between monetary policy variables and financial markets.

The findings of the study suggest that investors and portfolio managers should consider economic issues while developing long-term investing plans. Reserve Bank of India should exercise prudence to prevent any discretionary measures that may lead to a rise in interest rates since this adversely affects the stock market. To mitigate risk, investors should closely monitor the adjustment of monetary policy variables.

The study has important social implications, especially regarding the lower levels of financial literacy among investors in India. Considering the complex nature of the study’s emphasis on monetary policy adjustments and their impact on the stock market. Investors face the risk of significant losses due to unexpected adjustments in monetary policy. Many individuals may need help understanding how policy changes impact their investments. Therefore, RBI must consider both price and financial stability when formulating monetary policies. Furthermore, market participants should consider the potential impact of fluctuating monetary policy variables when devising their long-term investment strategies. Given that adjustments in interest rates can markedly affect stock market dynamics, investors must carefully assess the implications of monetary policy decisions on their portfolios.

The study uses dummy variables in the ARDL model to represent structural breaks that emerged from the COVID-19 pandemic (as determined by the Bai–Perron multiple breakpoint test). The study also used the Perron unit root test to find out the stationary of the series in the presence of structural breaks. Additionally, the study also employed Bayesian inferences to affirm the robustness of the estimates.

The study examines the impact of real exchange rates and asymmetric real exchange rates on real stock prices in Malaysia, the Philippines, Singapore, Korea, Japan, the United Kingdom (UK), Germany, Hong Kong and Indonesia.

This study uses the asymmetric autoregressive distributed lag (ARDL) approach and non-linear autoregressive distributed lag (NARDL) approach.

The asymmetric ARDL approach shows more economic variables are found to be statistically significant than the ARDL approach. The asymmetric real exchange rate is mostly found to have a significant impact on the real stock price. Moreover, real output and real interest rates are found to have a significant impact on the real stock price. The Asian financial crisis (1997–1998) and the global financial crisis (2008–2009) are found to have a significant impact on the real stock price in some economies.

Economic variables are important in the determination of stock prices.

It is important to examine the impact of asymmetric real exchange rate on the real stock price as the depreciation of real exchange rate could have different impacts than the appreciation of real exchange rate on the real stock price. The previous studies in the literature mostly found the significant impact of nominal exchange rate on the nominal stock price.

The aim of this research is to re-examine the dynamic linkages between macroeconomic variables and the stock market indices in Malaysia following some transformational changes in the policies and the exchange rate regime.

Using monthly data points for all the economic variables and the stock market index (KLCI Index), the authors applied vector autoregression (VAR) model to examine the relationship. The authors also used impulse response function (IRF) in order to explore the effect of one-unit shock in “X” on “Y” under the VAR environment.

The authors' study finds a significant relationship between all the macroeconomic variables and the stock market index of Malaysia. The cointegration results indicate a long-term relationship, whereas the vector autoregressive-based impulse response analysis suggests that the Malaysian stock index (KLCI) responds negatively to the money supply, inflation and producer price index (PPI). However, the authors' results indicate a positive response from the stock index to the exchange rate.

The authors' study's results are based on selected macroeconomic variables and the VAR model. Researchers may find other variables and methods more useful and may provide findings accordingly.

Since the results are quite asymmetric, it would be interesting for the market players, policymakers and regulators to consider the findings and explore appropriate opportunities.

While the relationship between macroeconomic variables and stock market indices has been widely examined, a significant gap in the literature remains concerning the role of exchange rate variable on the stock market in an emerging economy context.

This paper aims to investigate the impact of geopolitical events of the Russia–Ukraine conflict on the stock market volatility of G20 countries. Furthermore, the paper also investigates the possible reasons for any similarities or differences in the results of the three sectors.

This paper measures the impact of the stock market sectoral index price (SIP) by using the daily closing price as a dependent variable. In addition, this study uses three independent variables: geopolitical risk (GPR), commodity price (CP) and foreign exchange rate (FER). Seventeen countries from the G20 are analyzed using a daily timeframe from September 2021 to August 2022 (before and during the Russian invasion).

The results revealed that FER, CP and GPR all affect SIP, but the level of significance and positive/negative signs vary in all three sectors. The positive FER affects SIP in all sectors, while the negative CP and GPR significantly impact SIP in the energy and transportation sectors.

This study’s research model is more suited for transportation and energy than consumer goods. Future researchers can enhance the research model for the consumer goods sector by incorporating additional variables to understand their relationship with SIP better.

This study explores the impact of the Russia–Ukraine conflict on the stock market in G20 countries, focusing on the top three most affected sectors.

This research aims to ascertain the extent to which the coronavirus disease 2019 (COVID-19) epidemic affected the relationship between inflation and real estate investment trusts (REITs) returns in South Africa.

This research used the Johansen cointegration test and effective test in establishing if there is a long-run cointegrating equation between the variables. To ascertain if COVID-19 resulted in a different relationship regime between inflation and REITs returns, the sequential Bai–Perron method was used.

Between December 2013 and July 2022, there was no evidence of a long-run relationship between inflation and REITs returns, and a restricted vector autoregressive (VAR) model with a period lag for each variable best describing the relationship. Using the sequential Bai–Perron method, for one break, the results show February 2020 as a structural break in the relationship. A cointegrating equation is also found for the period before the structural break and another after the break. Interestingly, the relationship is negative before the break and a new positive relationship (regime) is confirmed after the noted break.

This research helps REITs stakeholders to position themselves in light of any changes to macroeconomic activity within South Africa.

This is one of the first studies to test inflation relationship with REITs returns in South Africa and the effects of COVID-19 thereof. This research helps REITs stakeholders to position themselves in light of any changes to macroeconomic activity within South Africa.

This paper aims to examine the causation linking financial technology to economic growth in the East African Community states from 1997 to 2019.

Autoregressive distributed lag is used. Gross domestic product per capita proxies economic growth, automated teller machines, point of sale, debit card ownership and mobile banking measure financial technology.

The results unveil a significant relationship between financial technology and economic growth. The findings show bidirectional causality between automated teller machine and economic growth, with unidirectional causation from economic growth to point of sales and internet banking, mobile banking and government effectiveness to economic growth. The error correction term is negatively significant, demonstrating a long-term convergence between Fintech measures and economic growth.

The governments should effectively enact and implement policies that protect investments in financial technologies to boost economic growth in the East African Community countries. The government should reduce taxes on financial technology equipment and related services. The use of automated teller machine, debit card ownership and internet banking should be encouraged through cashless transactions. Financial institutions should adopt cashless operation policies to encourage the use of financial technologies.

Research results on the bond between financial technology and economic growth are not conclusive. These studies demonstrate that technological innovations are double edged-swords, with both positive and negative sides. The results are conflicting; some reveal positive relationships, while others show negative links. Hence, research is required to fill the lacuna.