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This study aims to investigate the diversification benefits attached to the crypto portfolios when combined with stocks, Forex instruments and commodity assets.

Markowitz diversification techniques have been used to analyze the risk-return tradeoffs of the individual portfolios. Daily prices on cryptocurrencies and the selected asset classes, cover the period before and during the pandemic COVID-19. The portfolio risk of the portfolios was calculated by identical techniques and analyzed with equal criteria.

The results with 270 trails indicate that stocks on average reduce the portfolio risk of crypto portfolios by 36% followed by fiat currency with 30.9% and commodities by 20.8%. Average daily returns stand in line with the standard portfolio theories where riskier portfolios offer higher returns and the other way around.

The authors contribute to the current literature by investigating the portfolio risk attached to the crypto portfolios when stocks, commodities and Forex instruments were added separately. To this end, results inform not only retail investors but also portfolio managers on the asset classes that generate better optimization for crypto portfolios.

This study aims to compare the diversification risk of the crypto portfolio with those of equity portfolios. For this purpose, the hypothetical index was constructed with 20 cryptocurrencies that hold the highest market capitalization in the Coin Market Cap database, named as the Crypto-Index 20.

The portfolio diversification techniques were used to identify risk linked with the six largest European equity indexes and compared with the Crypto-Index 20. Indexes were considered as an independent portfolio while analysis was completed separately for each of them. Data concerning stock prices and their trade volume were collected from the Thomson Reuters Eikon database while crypto prices and their trade volume from the Coin Market Cap database. The diversification risk of the stock indexes was measured separately for each portfolio with the same risk techniques and the same methodological process.

Research results indicate that Crypto-Index 20 on average was 76 times riskier than FTSE 100, 55 times riskier than FTSE MIB, 44 times riskier than IBEX 35, 10 times riskier than CAC 40 and 9 times riskier than DAX and MDAX. Crypto-Index 20 comprises a stronger positive correlation and is exposed to higher volatility than six selected European equity indexes.

This research provides practical implications for the investors on the diversification benefits and risks attached to the cryptocurrencies portfolio by comparing it with the traditional equity portfolios. From a policy perspective, regulators might obtain information on the risk properties involved into cryptocurrencies and the possibility of creating an optimal portfolio.

Since 2008, bitcoin has continued to attract investors due to its growing capitalization and opportunity for speculation. The purpose of this paper is to analyze the impact of bitcoin (BTC) on gold, the volatility index (VIX) and the dollar index (USDX).

The series used are weekly and cover the period from January 2016 to November 2022. To generate the results, the unrestricted vector autoregression (VAR), structural vector autoregression (SVAR) and wavelet coherence were performed.

The findings are mixed as not all tests show the exact effects of BTC in the three asset classes. However, common to all the tests is the significant influence that BTC maintains on gold and vice versa. The positive shock in BTC significantly increases the gold prices, confirmed in three different tests. The effects on the VIX and USDX are still being determined, where in some tests, it appears to be influential while in others not.

BTC’s diversification potential with equity stocks and USDX makes it a valuable security for portfolio managers. Furthermore, regulatory authorities should consider that BTC is not an isolated phenomenon and can significantly influence other asset classes such as gold.

The Russian invasion of Ukraine generated unprecedented panic in the European financial system. As expected, the European Union (EU) felt most of the negative effects of the war due to geographical proximity to Ukraine and energy dependence on Russia. This study aims to investigate the influence of Brent crude oil (BCO), Dutch Title Transfer Facility Natural Gas, and CBOE Volatility Index (VIX) on Deutscher Aktien Index (DAX), Austrian Traded Index (ATX) and Milano Indice di Borsa (FTSEMIB). The German, Austrian and Italian equity indexes were chosen due to the heavy dependence of these countries on Russian gas and oil.

The data cover the period from November 24, 2021, to June 24, 2022, including five months of the Russia–Ukraine war. To generate the intended results, vector autoregressive, structural vector autoregressive, vector error correction model, Johansen test and Granger causality test were used.

The results highlight that natural gas and the VIX carried negative effects on DAX, ATX and FTSEMIB. The BCO was expected to have influenced three selected equity indexes, while the results suggest that it was priced only in ATX.

This research provides modest evidence for the policymakers on the systemic risk that Russian gas has for the EU equity markets. From a managerial perspective, changes in oil and gas prices are a permanently integral part of portfolio risk analysis.

Paper aims to investigate the interdependencies and spillover effects that the Visegrad (V4 hereafter) Equity Markets hold on each other. The V4 group stands for the political alliance of four Central European countries: Poland, the Czech Republic, Hungary and Slovakia.

The study uses Wavelet coherence, dynamic conditional correlation GARCH (1, 1) and unrestricted vector autoregression (VAR) methodologies. Daily data series (covering the period from January 2, 2006, to February 2, 2023) are analyzed to assess coherence, time-varying conditional correlation and shock transmission among the V4 Equity Markets.

Wavelet analysis reveals that the Slovak equity market does not maintain coherence with three other equity markets. The time-varying conditional correlation documents for the high interdependence during the COVID-19 outbreak of the four indexes. The VAR estimates reveal that shocks in the Warsaw equity market are easily transmitted in Prague and Budapest exchanges but not in Bratislava. The results show that the Slovak equity market tends to be isolated from the influence of other three V4 exchanges. This isolation is attributed to its size, limited volume and adoption of the euro in 2009. The study emphasizes the Slovak financial system’s gravitation toward the Eurozone after euro adoption.

Notably, the findings provide important signals for local and international investors as the results cover four significant international shocks. The global meltdown of 2008/09, the Greek debt crisis of 2010/11, the COVID-19 pandemic and the Russia-Ukraine war.

The stability of exchange rates facilitates international trade, diminishes portfolio risk, and ensures that economic policies are effective. The war in Ukraine is showing that the European financial system is still fragile to external shocks. This paper examines the consequences of the Russian invasion of Ukraine on five Euro exchange rates. The final goal is to empirically test whether the ruble caused the euro to depreciate with the Russian invasion of Ukraine.

The exchange rates analyzed are Euro/Russian Ruble, Euro/US Dollar, Euro/Japanese Yen, Euro/British Pound, and Euro/Chinese Yuan. The data collected are daily and cover the period from November 1, 2021, to May 1, 2022. In this context, the changes in the FX rates reflect two months of the ongoing war in Ukraine. The FX rates used in the study contain 137 observations indicating five months of daily series.

The results from impulse response function, variance decomposition, SVAR, and VECM indicate that the EUR/RUB significantly influenced the Euro devaluation. On the other side, the FX rates used in our work altogether hold long-run cointegration. The situation is different in the short run, where only EUR/RUB, EUR/USD, and EUR/CNY possess significant relations with other parities.

The Ruble is not among hard currencies, but its position strengthened during this period due to the importance of Russian gas to the Eurozone. The results indicate that even weak currencies can be influential depending on the geopolitical and economic situation. To this end, diversification remains a valid concept not only in portfolio construction but also for the preservation of the national economy.

Insufficient internal financing capacities and challenges to accessing external finance are crucial to small and medium-sized enterprises (SMEs) investment and growth. This study aims to investigate how SME leverage of bank financing is related to the investment decision.

Using Heckman’s two-step econometric modelling to correct for sample selection bias, this study investigates the effect of entrepreneur characteristics, firm characteristics and performance on firms’ capital structure choices conditional on new investment decisions.

The main results reveal that larger firms with growth aspirations tend to make new investments. In the second stage equation, empirical results demonstrate that among SMEs who made a new investment, those SMEs with highly educated owner/managers, on average, use more external financing (i.e. banks loan) rather than internal funds – also, the smaller the company, the less bank leverage. Compared to the limited liability legal form, SMEs registered as individual businesses have less bank financial leverage. These results confirm that internal capacities for funding new investments are limited, and hence small firms must rely on external finance.

This study provides a unique empirical investigation and evidence based on a sample of SMEs in Kosovo. To the best of the authors’ knowledge, this study is the first attempt to empirically analyse investment behaviour in relation to capital structure for SMEs in Kosovo and one of the few, in general, to consider the sample selection bias issues underpinning the other studies in this field. The analysis corrects for sample selection bias, using growth aspiration as an instrumental variable.