چکیده:
The importance of studying the efficiency of the Iranian capital market has led the present study to pursue the aim of empirical analysis of comparative market theory in the Iranian capital market. Therefore, in this research, an attempt has been made to explore this goal by analyzing irregular behaviors, inspired by the onion model of Sanders' research and focusing on transactions made in the market and index fluctuations. The present study is descriptive-analytical and applied from the perspective of the objective. In the research strategy layer, the archival and quantitative analysis strategy has been selected. The selection layer includes a quantitative single-method method. Finally, the central layer, techniques and procedures, includes the combination of a multilayer perceptron neural network with a water cycle algorithm for parameter optimization in Python software. The data included variables such as closing price, logarithmic return, moving averages, volatility, RSI, trading volume and calendar effects. The accuracy of the models was measured with the Rock curve and the significant differences in the results were evaluated with the Wilcoxon test. The findings show that the level of compliance of the Iranian capital market behavior with the adaptive market hypothesis is compared to the traditional efficient market hypothesis, because the tests of return independence (such as autocorrelation close to zero) support the efficient market hypothesis, but the performance of the MLP-WCA model with an accuracy of 78% and AUC=0.825, along with weak patterns in RSI and momentum, indicates a better explanation of the return behavior by the traditional market hypothesis. The results also indicate a significant impact of investor behavior on changes in stock value and returns. The results show that the buy and hold strategy with a cumulative return of 2.665 has performed better than the simple moving average rule with a return of 1.475 and the combined version of the moving average with volume with a return of 0.282.
خلاصه ماشینی:
The data collected from 112 listed companies over a 10-year period (from 1393 to 1403 SH) are structured as panel data and include variables such as stock prices, trading volume, logarithmic return, technical indicators (such as moving averages SMA and EMA, RSI, momentum, and volatility), and variables binary (such as the January and Monday effects) are.
This chapter examines the results obtained from accuracy assessment with the ROC curve and the Wilcoxon statistical test to answer the research questions: the superiority of the Adaptive Market Hypothesis (AMH) over the Efficient Market Hypothesis (EMH), the possibility of classifying stock return behavior, and the proposal of improved investment strategies.
The descriptive statistics provided for the data of 112 listed companies over the 10-year period provide a clear picture of the behavior of the Iranian capital market, which is consistent with the practical objective of the research (investigating changes in stock value and returns and the impact of investor behavior).
Table 3: Effects of annual and weekly lags Period Average Return Farvardin 0/000428 Other months 0/000502 Saturday Other days 0/000495 (Refer to the page image) Figure 2: Box plot of returns based on the first working day, Saturday (Refer to the page image) Figure 3: Box plot of returns based on Farvardin Table 4: Wilcoxon statistic Anomaly Wilcoxon statistic p-value Farvardin effect 154862848 0/337214643 First day effect (Saturday) The results presented in the table above and the Wilcoxon test in Table 4, along with charts (2 and 3), provide important information regarding calendar anomalies in the Iranian stock market, which are consistent with the main objective of the research (investigating the explanation of stock return behavior through the Adaptive Market Hypothesis) and the first question (the superiority of AMH over EMH).
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