Considering the increasing development of the stock exchange market and its potential for creating economic growth and development of the country, it is very important to study the factors affecting this market and this issue is very important for all users of this market. The main purpose of this study is to investigate the effect of the manufacturing Purchasing Managers Index (PMI) on the stock price index in Iran. Therefore, the present study has used the monthly data from 2018: 10 to 2022: 11 and using the Granger causality method and Johansen co-integration to investigate the relationship between Purchasing Managers Index and total stock price index and manufacturing stock price index. The results indicate that there is a one-way causality from the growth of the manufacturing purchasing managers index to the growth of the total stock price index and the growth of the manufacturing stock price index. Also, based on Johansen's cointegration test, there is a long-term positive relationship between the growth of manufacturing purchasing managers index and the growth of total stock price index, and also between the growth of manufacturing purchasing managers index and the growth of manufacturing stock price index. Given that the increase in PMI indicates economic prosperity in the manufacturing sector, this positive relationship shows that, as expected, stock price indices react positively to improvement signals in the manufacturing sector and negatively to negative signals.

In order to estimate the price index model of petro-chemical industry, we have used the monthly time series data and the Auto Regressive Distributed Lags (ARDL) model. The results indicate that a long-run relationship exists between oil price, currency rate and inflation and the price index of petro-chemical industry. Coefficient of Error Correction Term (ECT) is obtained about -0. 06. That is, any shock in a period, only 6 percent of the variation will be adjusted to the next period. Thus, next equilibrium is very slow. Among Macroeconomic variables, inflation, oilprice and currency rate have significant and positive effects on the petrochemical stock price index, respectively.

In this paper we examine the effect of the oil volatility, Consumer Price Index (CPI) and Industrial Production on the Stock Market return in Tehran Stock Exchange (TSE). We used seasonal data in period 1378-1390 and Auto Regressive Distributed Method (ARDL) for the short-term and long-term relationship between the variables. As results of research indicate, we find that there is positive short-term relationship between oil volatility and industrial production with stock market return and no long-term relationship between these variables.

Selecting effective criteria on prices and consequently on investor’ s decision making is one of the most debating topics in portfolio optimization debate. Both of market and industry price changing and the information releasement by companies can affect stock prices. As a result, the goal of this study is surveying the role of market and industry price changing on stock prices and its effect on portfolio optimization. So we use stock price synchronicity. Stock price synchronicity measures the degree to which the market change can explain stock price movement. So by collecting price changing data from 130 sample companies during 10 years and with solving regression equations we computed stock price synchronicity. Then by collecting financial and nonfinancial data from the samples and analyzing these data and using data envelopment analysis (DEA) technique we made several portfolio to compare them by sharp ratio. The result shows that stock price synchronicity is about 59% in the sample and it is in conformity with international surveys like Jin and Myers (2006). Also the result shows that if stock price synchronicity affection be considered in portfolio selection then portfolios will have better return. In this research we use data envelopment analysis to choose portfolios and use Fuzzy Delphi to choose effective criteria on stock price changing.

AbstractObjectiveThe dynamic relationship between stock prices and housing prices has been an important topic of discussion in the academic and professional literature. The impact of stock prices on housing prices can be examined through two substitution effects and the wealth effect. Real estate and stocks are both assets and can also be considered investment options. The connection between these two assets, housing and stocks, can be interpreted as a substitution effect. This implies that a high return on investment in the stock market may lead investors to divest from the housing market, resulting in a decrease in demand and housing prices. In this case, stock prices will harm housing prices. When housing is considered as a consumer good, the effect of wealth is more pronounced. An increase in income and wealth, including financial assets due to the increase in stock prices, has a positive effect on the total consumption expenditure, including housing costs. More specifically, because homeowners receive windfalls from stocks, the wealth effect of these windfalls increases the purchase of houses as a consumer good. In other words, the wealth effect establishes a positive correlation between stock prices and housing. This is because high returns in the stock market augment the overall wealth of homeowners, enhancing their capacity to invest in additional real estate. Therefore, the stock market index can have a positive or negative effect on housing prices. It is necessary to examine this relationship for each country in detail and based on statistical evidence. Accordingly, in the present study, the effect of the stock market index on housing prices in Iran is investigated. MethodsTo reach the research goals, data spanning from 1971 to 2020 is utilized. To test the research hypotheses, the NARDL method was used to identify possible asymmetries effect of positive and negative shocks of the stock price index on the housing price index. ResultsFindings show that in the short run, positive and negative shocks in the stock market index have no significant effect on the housing price index, but in the long term, positive shocks in the stock market index have a positive effect on the housing price index, while the effect of negative shocks on the housing price index is insignificant. ConclusionAccording to the obtained results, due to the substantial impact of stock market fluctuations on housing prices in Iran, it is recommended that policymakers take the following into account when formulating stock market policies. First, in the policymaking process for the housing sector, where the anticipation of housing price trends is crucial, careful attention should be given to potential shifts in the stock market index. Next, a long-term boom in the stock market correlates with an increase in housing prices, while the impact of a stock market downturn on housing price increases is deemed insignificant. Consequently, policies promoting a stock market boom can be considered as a contributing factor to the rise in housing prices.

One of the most important market in each economy in financial markets that is strongly affected by other economic variables such as oil price shocks. One of the most important problems in oil export in country is the volatility and Instability of oil price. For this reason in this Thesis we are intendent to evaluate effect of oil price shocks on the stock market in iran. Fot this reasen we have used One of the most famous time series model, that is SVAR to analysis this shoks. The result of this research shows that the relative importants of oil price shoks in comparation to other variable of the model is not so high.