Introduction: Liquidity is an important issue for securities traded in financial markets. A certain level of liquidity is necessary for securities to be traded in the quantites required in a timely fashion whithout any price discount. The goal of this paper is to examine the relationship between different liquidity proxies and STOCKS’ TRADING CHARACTERISTICS for listed companies in Tehran Stock Exchange. In this paper, five different liquidity proxies are introduced. The proxies are stock turnover, the illiquidity ratio, zero return measure, proportional bid-ask spread and turnover adjusted number of zero daily volumes. STOCKS’ TRADING CHARACTERISTICS include stock price, TRADING volume, return volatility, absolute return, and Beedles’ thin TRADING measure ….

Objective: The efficient market hypothesis (EMH) states that stock prices reflect all available information and price changes (or return) should be unpredictable. But the lead-lag effect is a phenomenon that provides the predictability of return in the stock market. Examining the lead-lag relationship between stocks, in addition to evaluating market efficiency, provides investors with useful TRADING strategies. Methods: This study has investigated the lead-lag effect between stocks within 20 industries of the Tehran Stock Exchange (which cover 75% of the market capital) from 2015 to 2020 using the vector autoregression (VAR) model. Results: From 20 industries in our sample, 13 industries show the lead-lag effect. In 10 industries, the return of small stocks leads to the return of big stocks within the same industry. Whereas, in the other 3 industries, the return of big stocks leads to the return of small stocks within the same industry. In addition, a stronger leadlag effect has been observed in the computer, transportation, and metal products industries (which are relatively small industries). Conclusion: These observed lead-lag relationships (or predictable returns) between stocks intra-industry show a systemic inefficiency in the Tehran Stock Exchange market. Also, the results show that in some industries of the Tehran Stock Exchange, there are potentially profitable TRADING strategies.

Due to the volatility and uncertainty inherent in the stock market, devising an optimal TRADING strategy is a complex endeavor. Given the non-repetitive nature of TRADING circumstances, learning through interactions becomes imperative. Reinforcement learning emerges as an interactive learning approach capable of adjusting system parameters based solely on a scalar efficiency signal. This paper introduces a methodology wherein the states of the system are defined by the time step, the total number of shares purchased thus far, the standard deviation of stock prices from the beginning to the current step, and the difference between the current price and the price at the previous step. By defining a suitable reinforcement signal, the paper employs one of the most popular reinforcement learning algorithms, Q-learning, to approximate state-action value functions. The stock market is simulated using a set of equations, and the proposed method is applied. Performance evaluation is conducted by comparing the proposed model against mean reversion TRADING strategy across 5000 simulated markets. The experimental results demonstrate that the TRADING strategy derived from the Q-model not only yields lower average cost but also exhibits greater reliability compared to mean reversion strategy.

Geographical, morphological and taxonomic status of Pistacia khinjuk Stocks ex Stocks in Iran was revised. A total of 181 accessions (herbarium materials or specifically collected for this study) were examined geographically and morphologically. The chromosome number of 2n=24, revealed among 15 accessions studied, was taken as evidence to lump the variability observed in P. khinjuk as one taxonomic species. However the states of the leaflet number, i.e. 1 (rarely 3) and 3-7 were taken as the key character in order to subdivide the P. khinjuk material in Iran into two varieties: khinjuk (the autonym variety) with 3-7 and populifolia Boiss. with 1 (rarely 3) leaflet in number. The relative illustrations are prepared and presented. Some nomenclatural corrections are also included.

Policymakers often express concern that behavioral finance such as herding by financial market participants destabilizes markets and increases the fragility of the financial system. This paper provides an empirical research on herding behavior of investors whit employing technique of Lakonishok, Shleifer, and Vishny, 1992, (LSV) herding measure by using a data-set consisting of all their daily transactions of 59 corporations in Tehran stock exchange corporations and during 24 months (from Dec.2007 until Dec.2009), and explores the factors that can explain such behavior. In this study demonstrates that herding is affected by four features specific to the stocks, such as their size, systematic risk, idiosyncratic risk, and P/E. Size, systematic risk and idiosyncratic risk tend to positively affect herding but this effect is significantly higher for size. This context also reveals that P/E influences herding negatively. In general most of the results are consistent with the theory that herding is information based, and also when market conditions are favorable.

Improving participation in voluntary activities in Iran is important because increasing productivity among young people, given the country's young population, contributes to community sustainability. Therefore, a better understanding of volunteer motivation in Iranian youth is needed. The Volunteer Functions Inventory (VFI) for assessing volunteer motivations has good psychometric properties and is adapted to several languages, but no validated Iranian translation yet exists. The purpose of this study was to investigate the psychometric CHARACTERISTICS of voluntary functions inventory in members of Iranian Red Crescent Society. Sample size was 595 members of Youth Organization of Iranian Red Crescent Society from 31 provinces and 175 cities of Iran that were selected by multi-stage cluster sampling method and responded to voluntary functions inventory. Data were collected using a demographic sample and voluntary functions inventory (VFI). Confirmatory factor analysis using principal components method was used for data analysis. The results of the present study showed that the voluntary functions inventory had validity and reliability. Also, the factor structure showed that 29 items and 6 factors well assess people's attitudes to volunteering, and the structure of this inventory was well-fitted and confirmed all goodness of fit models. The present study provides the use of the Iranian translation of the Voluntary Functions Inventory (6 scales and 29 items) to assess volunteer motivation among young Iranian volunteers.

One of the major functions of exchange is to enhance stock liquidation. If stock market is not cash and liquid, it will not encourage investment. On the other hand, stock market has intensely been affected by the development of advanced computer technologies, which has caused a large volume of trades to conduct online.The present research analyzes the trades conducted in Tehran Stock Exchange from the viewpoint of high-frequent TRADING (HFT). It also discusses the effect of such trades on market liquidation.Based on this, it studies five major and influential factors on liquidation power, including number of trades, number of buyers, number of the traded stocks, number of TRADING days and value of the stocks traded in Tehran Stock Exchange between 21 Mars 2011 and 22 September 2012. Correlations between these factors and the variable of the HFTs were tested through multivariate regression and SPSS.According to the results, there is a positive and significant relationship among the HFTs with 3 variables including number of trades, number of buyers and number of TRADING days at confidence level of 95%. Therefore, HFTs are effective in liquidation power.

In this paper, a model has been provided for selection of the right portfolio in stock exchange. Financial industries ranking and companies ranking have been applied for selection of the right stock in this model. These rankings have been done through the PROMETHEE decision making method. Technical Analysis has been done for determining the right time to buy and sell the superior stocks. A survey has been done for determining the effective criteria over industry and company evaluation. The developed model has been applied in Tehran Stock Exchange (TSE) as a real case and a real problem has been solved. It is concluded that by using both Fundamental and Technical Analysis, an investor can get higher return on stocks instead of using just one individual analysis. In other words, while Fundamental Analysis distinguishes which stocks to buy, Technical Analysis shows when to buy the superior stocks.

In recent decades, a number of efforts have been done at the national and international level to control and regulate the emission of greenhouse gases. Compliance with limits imposed by regulations on emitting gases requires adaptation in existing facilities, making new investments and incurring other costs which are unbearable to many companies especially old ones. As the total reduction of emissions are intended for the sake of environment, certain mechanisms should be designed to allow pollutants to buy the credit of other companies instead of reducing their own emissions. The sale and purchase of credit obtained as a result of reduction in emissions is called "emission TRADING". In this paper, we first provide a brief history and concept of emissions TRADING. Then, emission TRADING at the international level will be discussed based on Kyoto Protocol and regional emission TRADING with reference to the European Union emission TRADING program. Finally the legal framework of emission TRADING and its basic elements will be discussed.