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The purpose of the study is to analyze the hedging abilities of the cryptocurrencies vis-à-vis gold against macroeconomic shocks in four emerging economies, India, China, Brazil and Russia.

Using the monthly data from January 2013 to April 2023, the paper analyses the response of Cryptocurrencies vis-à-vis gold prices to three different macroeconomic shocks, namely, the economic policy uncertainty shock, the financial uncertainty shock and the inflation shock, within a VAR framework with the help of the Generalized Impulse Response Function.

Both gold and cryptocurrencies have limited hedging abilities against macroeconomic shocks across countries. In India, bitcoin has become the new digital gold, while in China, it is not bitcoin but rather gold that retains its hedging abilities. Neither bitcoin nor gold, Binance Coin or Cardano, are found to be the new digital gold in Brazil and Russia.

The paper compares the top nine cryptocurrencies with the traditional asset gold in terms of their hedging potential against macroeconomic shocks in emerging countries.

The purpose of this study is to explore the intricate relationship between oil prices, house prices in the UK and Norway, and the mediating role of gold and stock prices in both the short- and long-term, unraveling these complex linkages by employing an empirical approach.

This study benefits from a comprehensive set of econometric tools, including a multiequation vector autoregressive (VAR) system, Granger causality test, impulse response function, variance decomposition and a single-equation autoregressive distributed lag (ARDL) system. This rigorous approach enables to identify both short- and long-run dynamics to unravel the intricate linkages between Brent oil prices, housing prices, gold prices and stock prices in the UK and Norway over the period from 2005:Q1 to 2022:Q2.

The findings indicate that rising oil prices negatively impact house prices, whereas the positive influence of stock market performance on housing is more pronounced. A two-way causal relationship exists between stock market indices and house prices, whereas a one-way causal relationship exists from crude oil prices to house prices in both countries. The VAR model reveals that past housing prices, stock market indices in each country and Brent oil prices are the primary determinants of current housing prices. The single-equation ARDL results for housing prices demonstrate the existence of a long-run cointegrating relationship between real estate and stock prices. The variance decomposition analysis indicates that oil prices have a more pronounced impact on housing prices compared with stock prices. The findings reveal that shocks in stock markets have a greater influence on housing market prices than those in oil or gold prices. Consequently, house prices exhibit a stronger reaction to general financial market indicators than to commodity prices.

This study may have several limitations. First, the model does not include all relevant macroeconomic variables, such as interest rates, unemployment rates and gross domestic product growth. This omission may affect the accuracy of the model’s predictions and lead to inefficiencies in the real estate market. Second, this study does not consider alternative explanations for market inefficiencies, such as behavioral finance factors, information asymmetry or market microstructure effects. Third, the models have limitations in revealing how predictors react to positive and negative shocks. Therefore, the results of this study should be interpreted with caution.

These findings hold significant implications for formulating dynamic policies aimed at stabilizing the housing markets of these two oil-producing nations. The practical implications of this study extend to academics, investors and policymakers, particularly in light of the volatility characterizing both housing and commodity markets. The findings reveal that shocks in stock markets have a more profound impact on housing market prices compared with those in oil or gold prices. Consequently, house prices exhibit a stronger reaction to general financial market indicators than to commodity prices.

These findings could also serve as valuable insights for future research endeavors aimed at constructing models that link real estate market dynamics to macroeconomic indicators.

Using a variety of econometric approaches, this paper presents an innovative empirical analysis of the intricate relationship between euro property prices, stock prices, gold prices and oil prices in the UK and Norway from 2005:Q1 to 2022:Q2. Expanding upon the existing literature on housing market price determinants, this study delves into the role of gold and oil prices, considering their impact on industrial production and overall economic growth. This paper provides valuable policy insights for effectively managing the impact of oil price shocks on the housing market.

This paper aims to propose a new housing finance mechanism through gold price as an alternative to interest rate in Islamic home financing, especially on Bai’Bithaman Ajil (BBA) contract.

This study using simulation approach to calculate the monthly installments for home financing using gold price references. In simple terms, propose a financing formula in the BBA contract by converting the selling price of the house to the gold price, and then the monthly installments also follow the actual gold price. The authors provide an example by simulating this formula using historical data and cases of housing financing at Indonesian Islamic banks. The authors compare housing financing models based on gold prices and interest rates. Finally, The authors can compare the two housing financing models that are affordable for low-income people.

The results show that in the initial period, monthly installments of BBA based on gold price were lower than home financing based on interest rate. This result makes it possible for low-income people who cannot access financing based on interest rates to access financing based on gold price. However, the total installments of financing based on gold prices are higher than the financing model based on interest rates.

The paper confines one contract, namely, BBA, as it is claimed to be more Shariah-compliant than others.

These findings suggest an alternative model for Islamic banks and regulatory authorities in Indonesia to replace the interest rate reference with the gold price in BBA contract housing financing. This model can offer competitive advantages for Islamic banks, including lower initial installments and inflation-protected profits, serving as a means of differentiating them from conventional banks.

Gold price-based housing financing model in Islamic banks will increase the affordability of housing financing for low-income people.

This paper tries to solve two problems, namely, first, the problem of assuming that Islamic and conventional banks are the same, and second, the problem of housing finance affordability. This study needs to be explored.

The objective of this paper is to examine the determinants of the Greek house market during the period 2006–2022 using not only economic variables but also behavioral variables, taking advantage of available information on the volume of Google searches. In order to quantify the behavioral variables, we implement a Python code using the Pytrends 4.9.2 library.

In our study, we assert that models relying solely on economic variables, such as GDP growth, mortgage interest rates and inflation, may lack precision compared to those that integrate behavioral indicators. Recognizing the importance of behavioral insights, we incorporate Google Trends data as a key behavioral indicator, aiming to enhance our understanding of market dynamics by capturing online interest in Greek real estate through searches related to house prices, sales and related topics. To quantify our behavioral indicators, we utilize a Python code leveraging Pytrends, enabling us to extract relevant queries for global and local searches. We employ the EGARCH(1,1) model on the Greek house price index, testing several macroeconomic variables alongside our Google Trends indexes to explain housing returns.

Our findings show that in some cases the relationship between economic variables, such as inflation and mortgage rates, and house prices is not always consistent with the theory because we should highlight the special conditions of the examined country. The country of our sample, Greece, presents the special case of a country with severe sovereign debt issues, which at the same time has the privilege to have a strong currency and the support and the obligations of being an EU/EMU member.

The results suggest that Google Trends can be a valuable tool for academics and practitioners in order to understand what drives house prices. However, further research should be carried out on this topic, for example, causality relationships, to gain deeper insight into the possibilities and limitations of using such tools in analyzing housing market trends.

This is the first paper, to the best of our knowledge, that examines the benefits of Google Trends in studying the Greek house market.

The primary focus of this study is to examine the distributional consequences of the widespread increase in prices. The fundamental question the study aims to address is whether the dynamics of income distribution due to higher inflation differ in the short term compared to the long run.

The authors estimated a panel-data model (fixed effects) using inequality and inflation data available at a high frequency, i.e. on a quarterly basis for over 30 years, and found evidence that inflation causes rapid swings in income distribution.

The authors’ contribution to the literature lies in providing evidence that inflation rapidly causes swings in income distribution, even after controlling for the state of the economy. The authors also demonstrate that the magnitude and direction of the effect of inflation on income inequality depend on whether the initial inflation rate is below or above the Federal Reserve’s target of 2%.

To the best of the authors’ knowledge, the authors are the first to emphasize that the targets set by central banks can drive the strength and direction of the relationship between inflation and income inequality.

The purpose of this paper is to examine the degree of persistence in four precious metal prices (i.e. gold, palladium, platinum and silver) during the last four US recessions.

Using daily price data for gold, palladium, platinum and silver running from July 2, 1990, to March 21, 2022, and dating of business cycles in the USA provided by NBER (2022), the paper uses fractional integration to test the degree of persistence of precious metal prices.

The empirical analysis shows the unrelenting prominence of gold in relation to other precious metals (palladium, platinum and silver) as a hedge against market uncertainty in the post-pandemic new era.

Two are the main contributions of the paper. Firstly, the authors contribute to the commodity markets and finance literature on precious metal price modelling. Secondly, the authors also contribute to the literature on commodity markets and business cycles with a special focus on recessionary periods.

Market sentiment has shown to influence housing prices in the global north, but in emerging economies, the nexus is rare to chance on in the current state of science for policy direction. More importantly in the recent decade where policymakers are yet to conclude on the myriad of factors confronting the housing market in sub-Saharan Africa inhibiting affordability. This paper therefore examines the impact of market sentiment on house prices in South Africa.

The study used the Autoregressive Distributed Lag (ARDL) approach with quarterly data spanning from 2005Q1 to 2020Q4.

In all, it was established that market sentiment plays a minimal role in the property market in South Africa. But there was enough evidence of cointegration from the bound test between sentiment and house prices. Nevertheless, the lag values of sentiment pointed to a rise in house prices. Exchange rate volatilities and inflation had a statistically significant effect on prices in both the long and short term, respectively.

Policymakers could still monitor market sentiment in the housing market due to the strong chemistry between house prices and sentiment, as evidenced from the bound test, but focus on economic fundamentals as the main policy tool for house price reduction.

The findings and the creation of the sentiment index make an invaluable contribution to the paper and add to the paucity of literature on the study of market sentiment in the housing market.

The purpose of the study is to examine factors influencing cash holding of firms during periods of crisis. In recent times, the level of cash holdings in firms has seen a steady rise across industries for diverse reasons. However, the need to study cash holding becomes even more compelling during geopolitical instability as it causes firms to hold greater cash reserves for precautionary reasons.

This paper systematically reviews literature from 1984 to 2024 by organising the findings thematically based on the relationship between corporate cash holdings (CCH) and firm performance in times of war. The paper used 47 research articles from the Scopus database and Google Scholar. Literature connected to CCH, firm performance and war times was explored. The title and abstract analysis were conducted using VOSviewer software. As a result, the predetermined body of literature was visualised, and six theme-based clusters were identified.

This paper systematically reviews empirical studies, categorising them into six theme-based groups. These clusters encompass CCH and Determinants, Optimal Cash Holding Levels, Cash Holding Adjustment Speed and Theory, Cash Holding and Firm Value, Cash Holding and Firm Performance, Cash Holding in the Context of the Ukraine War and the adaptive financial strategies of firms in response to economic conditions by using cash holding as a hedging instrument. Inflation prompts adjustments in cash-holding strategies at a macro level. During crises, lower interest rates lead to increased cash holdings. Various motives influence firms’ cash-to-assets ratios. According to the pecking order theory, geopolitical risk negatively affects cash holdings. Exposure to pandemics prompts an increase in cash reserves. War shocks have a profound impact on economies, markets and stability; hence, geographic diversification can reduce the need for precautionary cash. In times of uncertainty, the financial stress of firms can get elevated, and therefore, having a well-diversified geographical portfolio of a firm’s investments can aid in meeting any financially distressing situation.

The literature on CCH has been phenomenal. This paper attempts to structure the issues surrounding cash holding and firm performance in wartime, like the Ukraine war, using the VOSviewer software. This study endeavours to highlight the reasons for cash holding during crises and understand how cash holding affects firm performance. Finally, this paper also tries to comprehend whether cash holding helps as a hedging instrument in times of war.

This study aims to conduct an empirical investigation to assess the hedge, diversifier and safe-haven properties of different environmental, social and governance (ESG) assets (i.e. green bonds and ESG equity index) vis-à-vis conventional investments (namely, equity index, gold and commodities).

The authors examine the sample period 2007–2021 using the bivariate cross-quantilogram (CQG) analysis and a dynamic conditional correlation (DCC) multivariate generalized autoregressive conditional heteroskedasticity (GARCH) experiment with several extensions.

The evidence shows that the analyzed ESG investments exhibit mainly diversifying features depending on the asset class taken as a reference, with some potential hedging/safe-haven qualities (for the green bond) in peculiar timespans. Therefore, the results suggest that investors might consider sustainable investing as a new measure of risk reduction, which has interesting implications for both portfolio allocation and policy design.

To the best of the authors’ knowledge, this study is the first that empirically investigates at once the dependence between different ESG investments (i.e. equity and green bond) with different conventional investments such as gold, equity and commodity market indices over a large sample period (2007–2021). Well-suited methodologies like the bivariate CQG and the DCC multivariate GARCH are used to capture the spillover effect and the hedging/diversifying nature, even in temporary contexts. Finally, a global perspective is used.

The purpose of this research is to primarily understand how crypto traders can use the Bitcoin as a hedge or safe haven asset to reduce their losses from crypto trading. The study also aims to provide insights to crypto investors (portfolio managers) who wish to maintain a crypto portfolio for the medium term and can use the Bitcoin to minimize their losses. The findings of this research can also be used by policymakers and regulators for accommodating the Bitcoin as a medium of exchange, considering its safe haven nature.

This study applies the cross-quantilogram (CQ) approach introduced by Han et al. (2016) to examine the safe-haven property of the Bitcoin against the other selected crypto assets. This method is robust for estimating bivariate volatility spillover between two markets given unusual distributions and extreme observations. The CQ method is capable of calculating the magnitude of the shock from one market to another under different quantiles. Additionally, this method is suitable for fat-tailed distributions. Finally, the method allows anticipating long lags to evaluate the strength of the relationship between two variables in terms of durations and directions simultaneously.

The Bitcoin acts as a weak safe haven asset for a majority of new crypto assets for the entire study period. These results hold even during greed and fear sentiments in the crypto market. The Bitcoin has the ability to protect crypto assets from sharp downturns in the crypto market and hence gives crypto traders some respite when trading in a highly volatile asset class.

This study is the first attempt to show how the Bitcoin can act as a true matriarch/patriarch for crypto assets and protect them during market turmoil. This study presents a clear and concise representation of this relationship via heatmaps constructed from CQ analysis, depicting the quantile dependence association between the Bitcoin and other crypto assets. The uniqueness of this study also lies in the fact that it assesses the protective properties of the Bitcoin not only for the entire sample period but also specifically during periods of greed and fear in the crypto market.