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<Article>
<Journal>
				<PublisherName>Shiraz University</PublisherName>
				<JournalTitle>Iranian Journal of Economic Studies</JournalTitle>
				<Issn>2322-1402</Issn>
				<Volume>15</Volume>
				<Issue>1</Issue>
				<PubDate PubStatus="epublish">
					<Year>2026</Year>
					<Month>06</Month>
					<Day>01</Day>
				</PubDate>
			</Journal>
<ArticleTitle>Stacked Intelligence: A Robust Ensemble Approach to Forecasting Big Tech Stock Prices in Turbulent Markets (2020–2025)</ArticleTitle>
<VernacularTitle></VernacularTitle>
			<FirstPage>7</FirstPage>
			<LastPage>34</LastPage>
			<ELocationID EIdType="pii">8589</ELocationID>
			
<ELocationID EIdType="doi">10.22099/ijes.2026.55448.2097</ELocationID>
			
			<Language>EN</Language>
<AuthorList>
<Author>
					<FirstName>Younes</FirstName>
					<LastName>Nademi</LastName>
<Affiliation>Department of Economics, Ayatollah Boroujerdi University, Boroujerd, Iran.</Affiliation>

</Author>
<Author>
					<FirstName>Majid</FirstName>
					<LastName>Ebtia</LastName>
<Affiliation>Zagros Data Sciences Research Group, Ayatollah Boroujerdi University, Boroujerd, Iran.</Affiliation>

</Author>
<Author>
					<FirstName>Ramin</FirstName>
					<LastName>Khochiany</LastName>
<Affiliation>Department of Economics, Ayatollah Boroujerdi University, Boroujerd, Iran.</Affiliation>

</Author>
<Author>
					<FirstName>Sayyed Mohammad</FirstName>
					<LastName>Hoseini</LastName>
<Affiliation>Gahar Artificial Intelligence Research Group, Ayatollah Boroujerdi University, Boroujerd, Iran</Affiliation>

</Author>
</AuthorList>
				<PublicationType>Journal Article</PublicationType>
			<History>
				<PubDate PubStatus="received">
					<Year>2026</Year>
					<Month>01</Month>
					<Day>05</Day>
				</PubDate>
			</History>
		<Abstract>Accurate forecasts of the mega-cap technology stocks—Apple, Amazon, Alphabet, Meta and Microsoft—are vital for risk management and asset allocation. This study proposes a stacking ensemble that fuses Support Vector Regression (SVR), Random Forests (RF) and Extreme Gradient Boosting (XGBoost) as base learners, with a parsimonious linear meta-learner. We use daily OHLC data from 2 January 2020 to 11 March 2025, a span capturing the volatility of the COVID-19 shock and its aftermath. After differencing to ensure stationarity, the target variable becomes the daily change in closing price (Δ&quot;Close&quot; ). Models are trained on an expanding 80% window and tested on the final 20% of observations. Performance is assessed on strictly out-of-sample predictions using RMSE, MAE, MSE, and R^2. Across all five firms, the ensemble achieves the highest explanatory power (R^2≈0.80&quot;-&quot; 0.83) for predicting daily price changes and lowers RMSE by 8–15% relative to the best individual model. Friedman tests show these improvements are significant at the 1% level for Microsoft, Meta and Alphabet, and at 5% for Amazon; Apple shows no significant difference. The results indicate that combining heterogeneous learners curbs overfitting and exploits complementary nonlinear and temporal signals, producing stable forecasts during extreme market stress. The framework provides investors and policymakers with a validated AI tool for improving risk-return profiles in tech-heavy portfolios and offers methodological guidance for future financial-forecasting research.</Abstract>
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			<Object Type="keyword">
			<Param Name="value">Stock price forecasting</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">artificial intelligence</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">Stacking Ensemble</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">Big Tech equities</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">Machine learning</Param>
			</Object>
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</Article>

<Article>
<Journal>
				<PublisherName>Shiraz University</PublisherName>
				<JournalTitle>Iranian Journal of Economic Studies</JournalTitle>
				<Issn>2322-1402</Issn>
				<Volume>15</Volume>
				<Issue>1</Issue>
				<PubDate PubStatus="epublish">
					<Year>2026</Year>
					<Month>06</Month>
					<Day>01</Day>
				</PubDate>
			</Journal>
<ArticleTitle>Suppressed Inflation and Exchange Rate Pass-through: Evidence from Iran</ArticleTitle>
<VernacularTitle></VernacularTitle>
			<FirstPage>35</FirstPage>
			<LastPage>50</LastPage>
			<ELocationID EIdType="pii">8628</ELocationID>
			
<ELocationID EIdType="doi">10.22099/ijes.2026.52964.2030</ELocationID>
			
			<Language>EN</Language>
<AuthorList>
<Author>
					<FirstName>Mohsen</FirstName>
					<LastName>Behzadi Soufiani</LastName>
<Affiliation>Faculty of Economics, University of Tehran, Tehran, Iran.</Affiliation>

</Author>
</AuthorList>
				<PublicationType>Journal Article</PublicationType>
			<History>
				<PubDate PubStatus="received">
					<Year>2025</Year>
					<Month>04</Month>
					<Day>17</Day>
				</PubDate>
			</History>
		<Abstract>Based on empirical evidence backed by quantity theory of money, there is a proportionate reaction of the price level to an exogenous increase in the nominal money stock and it can cause a persistent inflation. However, governments control the relation between liquidity growth and inflation in the short run by managing exchange rate. Inflation control through government intervention using exchange rate in Iran, as an oil exporting country took place in last decades. Bearing sanctions in mind, exchange rate had significant overshoots causing two states in Iranian monetary environment. To capture the dynamics, this study using TAR estimation for liquidity, exchange rate and price levels over the period 2001-2025, detected exchange rate growth as the threshold variable at the value of 11% dividing economy into two states. In the low exchange rate regime, exchange rate changes have no statistically significant effect on inflation, while liquidity growth emerges as the primary driver and inflation persistence remains strong through significant lagged effects. In contrast, once the threshold is exceeded, exchange rate depreciation becomes a key and highly significant determinant of inflation, indicating intensified pass-through effects under higher volatility. Although liquidity continues to exert a positive and stronger influence, inflation persistence weakens, suggesting a shift from backward-looking dynamics toward contemporaneous shocks and potentially forward-looking expectations. Liquidity with a larger coefficient than in the lower regime, suggesting that monetary expansion has an even stronger inflationary impact under high exchange rate volatility which could not be suppressed.</Abstract>
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			<Object Type="keyword">
			<Param Name="value">Inflation</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">Exchange rate</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">Time Series Analysis</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">Monetary</Param>
			</Object>
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<ArchiveCopySource DocType="pdf">https://ijes.shirazu.ac.ir/article_8628_91eeee2a4dbfaf3591897b71951d9766.pdf</ArchiveCopySource>
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<Article>
<Journal>
				<PublisherName>Shiraz University</PublisherName>
				<JournalTitle>Iranian Journal of Economic Studies</JournalTitle>
				<Issn>2322-1402</Issn>
				<Volume>15</Volume>
				<Issue>1</Issue>
				<PubDate PubStatus="epublish">
					<Year>2026</Year>
					<Month>06</Month>
					<Day>01</Day>
				</PubDate>
			</Journal>
<ArticleTitle>Investigating Multidimensional Spatial Patterns of the Relationship between Financial Stress and Financial Market Growth: A Hybrid MSPAHM Model Approach</ArticleTitle>
<VernacularTitle></VernacularTitle>
			<FirstPage>51</FirstPage>
			<LastPage>84</LastPage>
			<ELocationID EIdType="pii">8632</ELocationID>
			
<ELocationID EIdType="doi">10.22099/ijes.2026.55255.2090</ELocationID>
			
			<Language>EN</Language>
<AuthorList>
<Author>
					<FirstName>Mahshid</FirstName>
					<LastName>Jahangiri</LastName>
<Affiliation>Department of Economics, Shi. C., Islamic Azad University, Shiraz, Iran.</Affiliation>

</Author>
<Author>
					<FirstName>Hashem</FirstName>
					<LastName>Zare</LastName>
<Affiliation>Department of Economics, Shi. C., Islamic Azad University, Shiraz, Iran.</Affiliation>

</Author>
<Author>
					<FirstName>Jalil</FirstName>
					<LastName>Khodaparast Shirazi</LastName>
<Affiliation>Department of Economics, Shi. C., Islamic Azad University, Shiraz, Iran.</Affiliation>

</Author>
</AuthorList>
				<PublicationType>Journal Article</PublicationType>
			<History>
				<PubDate PubStatus="received">
					<Year>2025</Year>
					<Month>12</Month>
					<Day>20</Day>
				</PubDate>
			</History>
		<Abstract>This study investigates the multidimensional spatial patterns characterizing the relationship between financial stress and financial market growth among companies listed on the Tehran Stock Exchange. The research incorporates three critical dimensions: spatial interdependencies, network structures, and inter-sectoral interactions. The analytical framework employs the innovative Multidimensional Spatial Panel Autoregressive Hybrid Model (MSPAHM), which facilitates simultaneous examination of temporal dynamics, spatial dependencies, and sectoral heterogeneity across the economic landscape. The empirical analysis encompasses a comprehensive dataset of Tehran Stock Exchange-listed companies spanning 2010 to 2024, capturing multiple economic cycles and policy regimes. The findings reveal that financial stress exerts a significant negative impact on firms&#039; financial growth, with effects propagating through spatial spillover mechanisms to interconnected companies within the broader economic network. This transmission occurs across both direct and indirect channels, creating cascading effects throughout the market structure. Notably, the analysis identifies substantial sectoral variation in vulnerability patterns. Capital-intensive and import-dependent industries demonstrate heightened susceptibility to financial stress shocks, with effect magnitudes intensifying markedly during periods of economic sanctions and maximum pressure policies. These results underscore the dynamic and networked nature of financial stress, emphasizing its dependence on sectoral characteristics and temporal contexts. The study concludes that effective policy intervention requires adopting a systemic approach grounded in comprehensive network analysis, enabling policymakers to anticipate spillover effects and design targeted interventions that account for the interconnected nature of firm-level financial distress within the broader economic ecosystem.</Abstract>
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			<Object Type="keyword">
			<Param Name="value">Financial Stress</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">Financial Market Growth</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">Spatial Panel Model</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">Spatial Spillover</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">Sectoral Heterogeneity</Param>
			</Object>
		</ObjectList>
<ArchiveCopySource DocType="pdf">https://ijes.shirazu.ac.ir/article_8632_c46121dc919a130a41fec8281553c271.pdf</ArchiveCopySource>
</Article>

<Article>
<Journal>
				<PublisherName>Shiraz University</PublisherName>
				<JournalTitle>Iranian Journal of Economic Studies</JournalTitle>
				<Issn>2322-1402</Issn>
				<Volume>15</Volume>
				<Issue>1</Issue>
				<PubDate PubStatus="epublish">
					<Year>2026</Year>
					<Month>06</Month>
					<Day>01</Day>
				</PubDate>
			</Journal>
<ArticleTitle>The Asymmetric Impact of Market Risk and Turbulence on Financial Reporting Conservatism: The Moderating Role of Macroeconomic Fluctuations in an Emerging Economy</ArticleTitle>
<VernacularTitle></VernacularTitle>
			<FirstPage>85</FirstPage>
			<LastPage>117</LastPage>
			<ELocationID EIdType="pii">8640</ELocationID>
			
<ELocationID EIdType="doi">10.22099/ijes.2026.55683.2105</ELocationID>
			
			<Language>EN</Language>
<AuthorList>
<Author>
					<FirstName>Mostafa</FirstName>
					<LastName>Shamsoddini</LastName>
<Affiliation>Department of Accounting and Economics, University of Hormozgan, Bandar Abbas, Iran.</Affiliation>

</Author>
<Author>
					<FirstName>Narges</FirstName>
					<LastName>Salari Kangi</LastName>
<Affiliation>Department of Business Administration, University of Hormozgan, Bandar Abbas, Iran.</Affiliation>

</Author>
</AuthorList>
				<PublicationType>Journal Article</PublicationType>
			<History>
				<PubDate PubStatus="received">
					<Year>2026</Year>
					<Month>02</Month>
					<Day>16</Day>
				</PubDate>
			</History>
		<Abstract>This study identifies a theoretical puzzle: while agency theory predicts that all forms of uncertainty increase accounting conservatism as a precautionary buffer, we find that market turbulence reduces it. This paradoxical reversal cannot be explained by standard risk-aversion frameworks. Using a balanced panel of 154 firms listed on the Tehran Stock Exchange over 2015-2024 (1,540 firm-year observations), we employ FGLS as our primary estimator, complemented by System GMM to address endogeneity. Our findings reveal a fundamental asymmetry consistent with our proposed Conditional Dominance Framework: market risk has a positive and significant effect on conservatism, supporting the agency-theoretic view of conservatism as a rational response to mitigate agency costs. Conversely, market turbulence exerts a negative and significant impact, consistent with Prospect Theory&#039;s prediction that under ambiguity and loss-domain conditions, managers become risk-seeking and abandon prudent reporting. Critically, this behavioral reversal is not constant but is activated and amplified by adverse macroeconomic conditions—inflation and exchange rate depreciation—which act as cognitive regime-switches. Economic growth and higher real interest rates weaken these relationships. The primary contribution is demonstrating that financial reporting conservatism is not merely a strategic response but a fragile defense mechanism that systematically collapses under extreme macro-volatility, challenging the implicit assumption that conservatism always increases with uncertainty. Our findings offer critical insights for managers, investors, and policymakers navigating volatile emerging economies.&lt;br /&gt; </Abstract>
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			<Object Type="keyword">
			<Param Name="value">Financial Reporting Conservatism</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">Market Risk</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">Market Turbulence</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">Macroeconomic Fluctuations</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">Emerging Markets</Param>
			</Object>
		</ObjectList>
<ArchiveCopySource DocType="pdf">https://ijes.shirazu.ac.ir/article_8640_1116cdf9a88dc62b86e94301107bb1ca.pdf</ArchiveCopySource>
</Article>

<Article>
<Journal>
				<PublisherName>Shiraz University</PublisherName>
				<JournalTitle>Iranian Journal of Economic Studies</JournalTitle>
				<Issn>2322-1402</Issn>
				<Volume>15</Volume>
				<Issue>1</Issue>
				<PubDate PubStatus="epublish">
					<Year>2026</Year>
					<Month>06</Month>
					<Day>01</Day>
				</PubDate>
			</Journal>
<ArticleTitle>Endogenous Liquidity Creation in Bank Centric Economies: A DSGE Analysis of Iran, Azerbaijan, and Armenia</ArticleTitle>
<VernacularTitle></VernacularTitle>
			<FirstPage>119</FirstPage>
			<LastPage>167</LastPage>
			<ELocationID EIdType="pii">8649</ELocationID>
			
<ELocationID EIdType="doi">10.22099/ijes.2026.55887.2112</ELocationID>
			
			<Language>EN</Language>
<AuthorList>
<Author>
					<FirstName>Zahra</FirstName>
					<LastName>Mohammadi</LastName>
<Affiliation>Department of Economics, University of Isfahan, Isfahan, Iran</Affiliation>

</Author>
<Author>
					<FirstName>Rasoul</FirstName>
					<LastName>Bakhshi</LastName>
<Affiliation>Department of Economics, University of Isfahan, Isfahan, Iran</Affiliation>

</Author>
<Author>
					<FirstName>Mohammad</FirstName>
					<LastName>Vaez Barzani</LastName>
<Affiliation>Department of Economics, University of Isfahan, Isfahan, Iran</Affiliation>

</Author>
</AuthorList>
				<PublicationType>Journal Article</PublicationType>
			<History>
				<PubDate PubStatus="received">
					<Year>2026</Year>
					<Month>04</Month>
					<Day>02</Day>
				</PubDate>
			</History>
		<Abstract>This study employs a calibrated Dynamic Stochastic General Equilibrium (DSGE) model to compare endogenous liquidity creation and its allocation in Iran, Armenia, and Azerbaijan over 2005–2024. It significantly contributes by introducing a structural Liquidity Distribution Indicator (LDI), measuring the share of bank-created liquidity allocated to firm lending. Countries are selected based on similar Liquidity Creation Intensity (LCI), defined as the ratio of central bank borrowing to total deposits. The model features a representative household and bank with financial frictions to analyze how balance sheet liquidity allocation affects the transmission of a –1% lending rate shock, interpreted as a relaxation of credit conditions before and after COVID-19. Calibrated to country-specific financial structures and solved using a fully nonlinear routine, the model generates impulse responses from nonlinear transition dynamics. Results show that before COVID-19, banks in Iran and Armenia allocated a relatively small share of liquidity to firm lending, with Azerbaijan displaying a similar pattern driven by state-dominated intermediation. Although post-COVID liquidity support temporarily increased lending shares, structural banking features continued to constrain effective monetary transmission. Overall, interest rate policy alone appears insufficient to mitigate risks from concentrated liquidity allocation; strengthening credit allocation mechanisms and banking intermediation is essential for macro-financial stability.</Abstract>
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			<Param Name="value">Endogenous Liquidity Creation</Param>
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			<Object Type="keyword">
			<Param Name="value">Liquidity Distribution (Bank Balance Sheet Based)</Param>
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			<Object Type="keyword">
			<Param Name="value">DSGE Model</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">Banks</Param>
			</Object>
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<ArchiveCopySource DocType="pdf">https://ijes.shirazu.ac.ir/article_8649_af97b63cbfaff5b235c409f1118d98df.pdf</ArchiveCopySource>
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