نشریه اقتصاد و تجارت نوین
سال نوزدهم شماره 2 (پیاپی 63، تابستان 1403)

In recent years, the popularity of investing in cryptocurrencies has increased, and gradually, the cryptocurrency market has matured by attracting higher liquidity and developing online trading platforms. However, investing in this area can disrupt the balance between risk-adjusted returns due to sudden price fluctuations. To address this issue, selecting an optimal portfolio that simultaneously maximizes expected return while minimizing investment risk is crucial. Accordingly, this study aims to select an optimal portfolio of cryptocurrencies using the Conditional Value at Risk approach and the Markov Switching GARCH process. For this purpose, daily return data from six high-market-cap cryptocurrencies—Bitcoin, Ethereum, Litecoin, Ripple, Cardano, and Binance Coin—as well as the stablecoin Tether—were utilized from January 1, 2019, to December 1, 2023. The study results indicate that in a high-volatility regime, a larger portion of the investment portfolio is allocated to the stablecoin Tether and Bitcoin (which exhibit more stable price movements than other cryptocurrencies). Conversely, in a low-volatility regime, the optimal investment portfolio allocates a higher weight to altcoins, aiming to maximize expected returns.

Considering the two characteristics of real estate, including consumption and capital characteristics, the total demand of the housing sector can be divided into consumer and investment demand. Different policies can have different effects on each component of housing demand. In this study, using the iran's seasonal data of 1380-1400 and the stochastic dynamic general equilibrium approach, the effects of monetary and financial policy as well as the oil price shock on housing demand were investigated. The results show that investment demand can explain housing price fluctuations better than consumer demand. For example, while expansionary fiscal policy increases both types of consumption and investment demands; Contractionary financial policy causes a decrease in consumer demand and an increase in capital demand for housing. When the economy is booming, the housing market fluctuates. As the fluctuations in the housing market increase, the share of investment in housing increases, and this indicates that housing applicants tend to give more weight to the investment value than the value. Provide consumption that may cause the formation of a housing bubble. In the end, some reasonable policy proposals are presented in the field of price control.

Bushehr province is great importance in cross-border trade due to its proximity to the Persian Gulf. According to the goals set in the 7th development plan, one of the identified strategies is to strengthen the transit centered on the sea economy. Therefore, in the current research, with the benefit of Anderson & van Win coop 's multilateral attraction model and the exchange cost theory, the influencing factors on the amount of Bushehr province's exports to Iran's business partners during the years 2007 - 2021 have been investigated. The results obtained by the dynamic panel econometric method showed that the economic size and population of Bushehr province and the economic size of business partners have a positive effect on the province's exports. But the population of the target countries has a negative effect on the amount of exports of the province. Also, despite the fact that most of the exports and imports of goods from the province's customs is done the Persian Gulf countries, the infrastructure of the province's customs and trade costs do not have a significant effect on the province's exports, but the country's economic and political conditions have a negative and significant effect on Bushehr province's export.

Numerous studies have been conducted to explore the relationship between unemployment, inflation expectations, exchange rates, and inflation. However, the connection among these factors remains ambiguous, especially in the context of Iran's economy, where the macroeconomic structure and geopolitical situation significantly heighten its importance. In this research, the dynamics of the New Keynesian Phillips Curve, considering the exchange rate, are analyzed over the period from Q1 2000 to Q4 2022 on a seasonal frequency using a Multivariate Continuous Wavelet Transform (MCWT) model across different frequencies (short-term, medium-term, and long-term). According to the findings of this study, the structure of the Phillips Curve does not align with the realities of Iran's economy. Even during periods of economic recession and expansion, a significant relationship between inflation and unemployment is sometimes absent, even in the short term. However, inflation is primarily influenced by inflation expectations and, to a lesser extent, by the exchange rate in the medium and long term. This indicates that if expectations and exchange rates are not managed, they could lead to persistent long-term inflation. Furthermore, due to price stickiness, even with successful management of exchange rates and expectations, a significant reduction in prices may remain elusive.

The purpose of this research is to investigate the convergence of housing prices in the provinces of Iran using the Markov switching nonlinear unit root test along with the generalized Dickey - Fuller unit root test between 1993 and 2021. The results of the Dickey-Fuller test show that housing prices do not converge, while the Markov switching nonlinear unit root test confirms the validity of this theory in some periods of Iran's economy. According to the results obtained in the boom regime (housing price increase conditions), there is convergence in housing prices, but there is no convergence in the recession regime (housing price decrease conditions). The result obtained from the nonlinear test seems to be expected.This case could be considered as temporary due to inflationary conditions and high inflation expectations, the decrease in housing prices, and there is an expectation of a housing price increase in a short time, and therefore prices do not decrease rapidly. According to the results of the research, the use of policy tools specific to each region and province can provide better management in controlling the fluctuations of the country's housing market. The adoption of complementary policies to stabilize housing prices may also be appropriate

Financing is very important for businesses. Initial Coin Offering is a new way of financing businesses based on blockchain technology. It seems necessary to explain this method and calculate its success factors. Therefore, in this article, using the support vector machine (SVM) algorithm, we have investigated the factors affecting the success of initial coin offering campaigns among 307 projects from 2016 to the end of 2018. In this article, the effect of the characteristics of the project, campaign, social networks and the team in a cumulative process on the two target variables- the total amount raised in the ICO process, and the percentage of hard cap (maximum capital determined by the founders of the project) raised as success criteria- have been examined in two separate model series. By obtaining the optimal models based on their performance and prioritizing the features using the Lasso technique, this article shows the two features of "Token supply is fixed" and "availability of smart contract code" have the highest level of influence in the success of an Initial Coin offering According to the results of both optimal models.