جستجوی مقالات مرتبط با کلیدواژه « گام تصادفی » در نشریات گروه « علوم انسانی »

Fama (1970) showed that stock markets have weak efficiency and follow the random walk model, so investors cannot achieve abnormal returns by using historical data. It is very important, therefore, to know about the stock price process. The refining and petrochemical industry companies’ stocks are among the most popular ones in the Iranian stock market because they often distribute appropriate dividends to shareholders and sometimes even have good price returns. Also, petrochemical companies are known as the leaders of the stock market, with a great effect on the main stock market index in Iran (TEPIX). This article is to test the random walk hypothesis or weak efficiency of daily stock prices in six petrochemical and three refining Iranian companies.
 
To test the random walk hypothesis, in the first stage, augmented Dickey-Fuller (ADF) unit root tests were conducted using the approaches proposed by Dolado et al. (1990) and Hamilton (1994), along with the Zivot and Andrews (ZA) unit root test incorporating an endogenous structural break. According to the first stage, GARCH (1.1) and Exponential GARCH approaches were used in the second stage to control the fluctuations and leverage effects in evaluating weak efficiency. Daily stock price data (adjusted) were used to test the weak efficiency hypothesis.
 
The results of the augmented Dickey-Fuller (ADF) unit root test and the Zivot and Andrews endogenous structural break showed that Iranian companies of Nouri, Parsan, Pars, Tapico, Shepna and Shetran are pure random walk (weak efficiency). However, Fars, Shepdis, and Shabandar follow a random walk with drift, suggesting the absence of weak efficiency in these companies. In addition, the results of GARCH and exponential GARCH models showed that there is a positive relationship between risk and return for all seven companies. Also, volatility shocks in Fars, Nouri, Pars, and Tapico companies are completely permanent (weak performance). In addition, the shocks observed in Parsan, Shepdis, and Shatran companies are transient, with their effects dissipating over time, and the prices readjusted to the long-term mean, indicating the absence of weak efficiency. The evidence confirms that in these companies, the volatility caused by negative (adverse) news is more than the volatility caused by the same level of positive (favorable) news.
 
According to the findings of the two stages, Nouri, Pars, Tapico, and Shapna companies have weak efficiency which means that the stock price behavior of these companies cannot be predicted. On the other hand, Parsan, Shapedis, Shatran, Fars and Shabandar companies show weak efficiency which means that their stock price behavior is predictable. The results of this article have important implications for investors in the Iranian stock market. Market participants can engage in effective modeling for stocks that lack efficiency and exhibit predictable behavioral patterns to some extent. This allows them to gain insights into future prices and potentially earn profits.

The efficiency of the foreign exchange market is crucial because exchange rates play a vital role in balancing a nation's internal and external economies. Iran's foreign exchange market has undergone significant developments and fluctuations in recent years, impacting its efficiency. This is evident in the monthly time series data for the unofficial exchange rates of the dollar, euro, and yuan from 2001 to 2021. An interesting trend has emerged since 2017: the Chinese yuan appears to be gradually replacing the dollar and euro as the primary trading currency in Iran's international market. Statistical tests, including the Augmented Dickey-Fuller (ADF), Phillips-Peron (PP), and KPSS tests, indicate weak-form efficiency in the markets for all three currencies (dollar, euro, and yuan). This suggests that these markets remain vulnerable to speculative attacks. Furthermore, Johansen's cointegration and Granger's causality tests reveal an absence of semi-strong efficiency in all three markets. This implies that past price information alone is insufficient to predict future exchange rates. The research findings suggest that choosing the yuan as an alternative currency has had a somewhat positive impact on improving the efficiency of the Iranian currency market.

In the time series econometric literature, data generation and stationary are important issues in model selection and estimation method. Difference Stationary and Trend Stationary processes are data generation procedures. In Difference Stationary specification (integrated), the stochastic component follows a random walk process (unit root process) that it yields stationary by differencing, while in trend Stationary specification process, the stochastic component follows a stationary process. The variable variation pattern in the random walk model with trend (random) and the trend stationary model (deterministic trend) is very similar. The revealed facts show the upward trend of Iran's macroeconomic variables over the past few decades, which are very close to the variation pattern of trend and Difference Stationary models. In empirical work, the distinction between these two models is not simple, and misapplying of tests cause incorrect results in the research process. The purpose of this paper is to review again how to perform a unit root test and identify the nature of (deterministic or random) trends of macroeconomic time series of Iran. In the first step, the generalized Dickey Fuller root unit test (ADF) was performed using the Dolado et al. (1990) and Hamilton (1994) approach and then Perron's test (1989) was used to investigate structural break. The results show that 4 variables of 6 time series including nominal GDP, industrial value added, consumer prices and stock money follow the random walk process with positive drift (random trend), but real GDP and stock price index follow the trend stationary process (deterministic process).

Investors around the world are always looking for safe investments in the capital markets of countries or the stocks of their companies. Therefore, finding a practical and scientific way to identify the best investment opportunity will have a very positive impact on the choice of an investor. An efficient stock is a stock whose price information is reflected in the market and the use of past stock prices over a period of time to analyze future trends and fluctuations in stocks leads to correct and citationable results. In this study, assuming poor performance, a stock portfolio consisting of 11 shares accepted in the Iranian capital market has been examined. In the sense that through the stock price information from 95 to 99 years, the trend and intensity of fluctuations have been examined. Because the liquidity of stocks has increased and it will be safe to invest. The results of this research using multi-fractal method show more detailed details of the efficient stock ranking steps in a portfolio.

According to the efficient market hypothesis, market efficiency refers to the condition in which prices in the markets are adjusted immediately to the new information. The speed and quality of response to new information determine the level of market efficiency. The lower speed and quality will result in lower efficiency. The weak level of market efficiency is a condition in which the price of an asset is predictable with publicly available information. In another word, prices are following a predictable pattern and not moving based on the random walk hypothesis. This study compares and evaluates a weak level of efficiency in future and spot market of gold coins.

This study examines gold coin transactions and the efficiency of future contracts in various futures and cash markets. By using the daily return of gold coins from 2008 to 2018 and R software, the paper examines the weak form of efficiency through random walks and martingale difference sequence hypotheses.

Using 10 year period data from 2008 to 2018 demonstrates inefficiency in all markets. However, compared to the other markets, the cash coin market has a relatively higher level of market efficiency. We found that there is an indirect relationship between the term of the contract and its efficiency. The weak form efficiency of the contracts is lower in the future contracts with a longer term to maturity. The probability of rejecting the weak form of efficiency is higher in futures markets.

Considering a higher level of weak efficiency in the cash market (in comparison with the future markets) and the indirect relationship between the term of the contract and the level of efficiency, investors are encouraged to focus on the gold coin cash market. Price changes in the cash market are less predictable than in other markets. As a result, this market is recommended for passive investors who buy and hold the asset.

This study seeks to investigate the existence or absence of independence in return series in S&P index of the New York and 11 different indexes in Tehran Stock Exchange and their adherence to the random walk model in two Low volatility and high volatility regimes using the Markov switching model. Research sample included daily price information of 9 different industry indices of the bank, cement, oil products, machinery, chemicals, automobiles, sugar, food but sugar, metal minerals, index of 50 Top Companies and price index (TEPIX) in Tehran Stock Exchange Market for the period from 03/25/2011 to 03/19/2019. The results of the Markov Switching and Arima model showed that only in the high volatility regimes of the S&P index of the New York Stock Exchanges, with a durability of 32 percent, and the index of oil products in Tehran Stock Exchange with a 6 percent survival, the Arima model was not significant and in the rest The cases of the Arima model became significant.

The goal of this research is to empirical analyzing fractal dimensions on cash return and price indices of listed companies of Tehran Stock Exchange. To have access to this goal, cash return and price indices of Tehran Stock Exchange were studied. Statistical sample of research includes cash return and price indices during period 1382 to 1391. Using R/S analysis and Hurst exponent, this research surveys the cash return and price time series being stochastic. To study the stochastic time series and differentiating from time series are not stochastic, R/S analysis is used as an efficient nonlinear method. Distribution type disrelation is the most important advantage of R/S analysis. Results of research show that, cash return and price indices time series are not stochastic and have a long-memory.

Financial Scientists have always been eager to distinguish between whether the price series could be random walk (unit root) or mean reversion processes. Random walk means that accruing shocks to the stock price have permanent impacts and prices dont revert to their previous trend path. In efficient market, the stock return couldnt be predicted using previous price variation. However, efficient market hypothesis is under question because the researchers have provided evidences that reveal some anomalies in stock markets. Mean reversion stock price is one of these anomalies. The purpose of this research is the study of mean reversion in the period 1380-1389. In line with this research, using unit root test (Dickey Fuller generalized), the phenomenon of mean reversion in the total stock price index, stock price and cash returns index, and the index's top fifty companies were examined. The results of the study indicate that continuous changes in the total stock price index and the index of the top fifty companies follow a random walk process or more words that are not eligible for mean reversion. But the price and cash returns index index the result shows that only 1% error level was confirmed that the mean reversion. Error levels of 5% and 10% of the rest of the process did not follow a random walk and mean reversion confirmed. In general, the performance of the Tehran Stock Exchange Index and fifty top companies indicate But the price and returns index results in poor performance suggests a lack of cash.

Predictability of stock prices in Tehran stock exchange index (TEPIX) is investigated. Five econometric models including Random Walk, Autoregressive, GARCH(1,1), TGARCH and EGARCH performed to eliminate linear structures form series and five statistical tests employed to examine the nonlinearity in residuals of that econometrical models. Results from econometric models rejected the random walk hypothesis, this shows that we can accept the possibility of prediction with historical data. From results of nonlinearity tests we can accept existence of nonlinear structures in the residuals of models. This is another evidence to accept the predictability in TEPIX.

Financial Scientists have always been eager to distinguish between whether the price series could be random walk (unit root) or mean reverting processes.By a random walk we mean that accruing shocks to the system have permanent impacts and prices do not revert to their previous trend path, in addition, regarding to random walk processes the price series volatility could increase with out any limit or restrictions. In this survey, using the time series of price and utilizing Augmented Dickey-Fuller Test we have attempted to investigate a sample of selected firms, listed in Tehran stock exchange. To start we have developed a simple definition of mean reversion and tested the presence of such a qualification in price series of the sample.