پژوهش ها و چشم اندازهای اقتصادی

پژوهش ها و چشم اندازهای اقتصادی

تأثیرات پویای سیاست پولی بر بازدهی صنایع کوچک و بزرگ بورس اوراق بهادار تهران (تحلیل کوتاه­ مدت و بلندمدت)

نویسندگان
1 دانشجوی دکتری مالی، مهندسی مالی دانشکدگان فارابی، دانشگاه تهران، تهران، ایران
2 دانشیار گروه مالی و حسابداری دانشکدگان فارابی، دانشگاه تهران، تهران، ایران
چکیده
هدف از نگارش این مقاله، بررسی تأثیر سیاست پولی بر بازدهی صنایع کوچک و بزرگ در بورس اوراق بهادار تهران در افق زمانی بلندمدت و کوتاه مدت است. با توجه به تئوری‌های موجود، تأثیر سیاست‌های پولی با توجه به اندازه صنایع و نوع تأثیرپذیری آنها از این سیاست‌ها، متفاوت است. برای بررسی این موضوع، ابتدا صنایع به دو گروه صنایع کوچک (17 صنعت) و بزرگ (18 صنعت) تقسیم شدند. سپس با کاربرد روش تحلیل مؤلفه‌های اصلی (PCA) و با استفاده از نماگرهای حجم اعتبارات، نرخ ارز و خالص دارایی‌های خارجی بانک مرکزی، شاخص شرایط پولی به عنوان معیاری از سیاست پولی خاص اقتصاد ایران طراحی شد. در انتها با استفاده از مدل میانگین گروهی تلفیق شده (PMG)، تأثیر سیاست‌های پولی بر صنایع کوچک و بزرگ بورسی در بازه زمانی فروردین ماه 1389 تا اسفندماه 1402 به صورت ماهانه بررسی گردید. نتایج به دست آمده، نشان می‌دهد که در بلندمدت، سیاست پولی بر بازدهی صنایع کوچک، دارای تأثیر مثبت و معنی‌دار است؛ اما این سیاست، تأثیری بر صنایع بزرگ در دوره مورد بررسی ندارد. از طرفی، بین تأثیرات سیاست پولی بر بازدهی صنایع کوچک (بزرگ) در کوتاه‌مدت و بلندمدت، تفاوت وجود دارد. با توجه به نتایج به‌دست‌آمده، به سرمایه‌گذاران پیشنهاد می‌شود که با توجه به افق زمانی سرمایه‌گذاری، پرتفوی خویش را تعدیل نمایند.
کلیدواژه‌ها

موضوعات


عنوان مقاله English

The Dynamic Impacts of Monetary Policy on the Returns of Small and Large Industries in the Tehran Stock Exchange (A Short-Term and Long-Term Analysis)

نویسندگان English

Seyed Hassan Masoudi Alavi 1
Mohammad Nadiri 2
Alireza Saranj 2
1 Department of Financial management and Accounting, Farabi College, University of Tehran, Iran
2 Associate Professor, Department of Financial management and Accounting, Farabi College, University of Tehran, Iran
چکیده English

Aim and Introduction
Financial markets have become one of the most attractive environments for investment in the modern era. Through the efficient allocation of capital, these markets exert a significant influence across various domains, including trade, education, employment, technology, and the broader economy. Financial markets are categorized into specific industries and sectors based on the characteristics of the goods and services produced. These unique features and industry-specific conditions influence productivity, which in turn affects returns. 
Industry-level returns reflect a combination of financial and non-financial factors that shape stock market dynamics. Industry data offer critical insights into the sources of a country’s economic growth, particularly from an industrial standpoint. Furthermore, industries often act as a leading force in the stock market, as their performance is closely tied to macroeconomic fundamentals.
There are two primary approaches to investing in stocks and generating returns commensurate with risk: the fundamental approach and the technical approach. The fundamental approach is based on three key levels of analysis. The first is macroeconomic analysis, which considers variables such as gross domestic product, monetary policy, and the broader economic environment, along with their effects on the returns of various industries and sectors. The second is industry analysis, which evaluates the performance of companies within a specific industry based on the unique conditions and characteristics of that industry. The third is company analysis, which focuses on assessing a firm’s current operations and financial status to determine its intrinsic value and future potential. Therefore, industry-level analysis serves as a crucial component within the broader framework of fundamental investment analysis.
At the industry level, macroeconomic variables—especially government monetary policy—play a pivotal role. Monetary policy influences capital markets through four primary transmission channels: the exchange rate, interest rate, credit, and asset prices. 
Methodology
To examine the research hypotheses regarding the impact of monetary policy on the returns of small and large industries from April 2010 to March 2024, this study employs the Pooled Mean Group (PMG) estimator on monthly data. A key advantage of this method is its capacity to handle both stationary and non-stationary variables, thereby overcoming issues related to cointegration and the limited power of unit root tests in long-term estimations. 
The model used is a Panel Autoregressive Distributed Lag (ARDL) framework, which enables the simultaneous estimation of short-term and long-term coefficients. In this framework, a long-run relationship is assumed between Yt  and Xt , with fixed effects μi.
The error correction model is as follows:
∆yit=μi+∅iyi,t+βi'Xit+j=1p-1ωij*∆yi,t-j+j=0q-1δij*'∆Xi,t-j+…+εit          (1)   
The final equation is as follows: 
∆yit=μi+∅iyi,t-1-θi'Xit+j=1p-1ωij*∆yi,t-j+j=0q-1δij*'∆Xi,t-j+…+εit        (2) 
In this study, the dependent variable is the industry return (IR) for small and large industries, and the key independent variable is Monetary Policy (MP)—measured via the Monetary Conditions Index based on principal component analysis. Additional control variables include Liquidity Volume (LV), Oil Price (OP), and the Consumer Price Index (CPI).
Findings 
The results for long-term relationships reveal a positive and significant relationship between monetary policy and the return of small industries on the Tehran Stock Exchange, with an estimated coefficient of approximately 4.1%. However, no significant long-term relationship was found between monetary policy and the return of large industries. 
In the short term, the error correction terms are estimated at -0.78 and -0.70 for small and large industries, respectively. This indicates that roughly 78% and 70% of the disequilibrium between the independent and dependent variables is corrected each period, guiding the system toward long-run equilibrium. In the first model (small industries), monetary policy has no immediate impact on returns. Conversely, in the second model (large industries), monetary policy exerts a significant short-term effect at the 5% level.
Conclusion
Government policies exert a profound influence on financial markets, with monetary policy playing a distinct and varying role across industries. Despite its importance, this differentiation has received limited attention in Iran. This study contributes to the literature by analyzing the differential effects of monetary policy on small and large industries, using the PMG model to estimate both short-term and long-term impacts on a monthly basis from April 2010 to March 2024.
The findings reveal that, in the long run, monetary policy exerts a positive and significant impact on the returns of small industries, whereas this effect is absent in large industries. In the short run, with the significance of the error correction term confirming the adjustment toward long-term equilibrium, the dynamics between the independent and dependent variables become balanced over time. Furthermore, the analysis indicates that monetary policy has no significant effect on small industries in the short term but demonstrates a positive and significant impact in the long term. In contrast, for large industries, monetary policy has no discernible effect in the long run but exerts a positive and significant influence in the short term.
These results confirm both the main and sub-hypotheses of the study, which posit that the effects of monetary policy vary between small and large industries and differ across time horizons. Consequently, investors are advised to consider firm size, as reflected in market value, when constructing their portfolios. Specifically, they should align their investment strategies with their time horizons—favoring small industries for long-term investments and large industries for short-term opportunities.

کلیدواژه‌ها English

Keywords: Monetary Conditions Index (MCI)
Monetary policy
PMG model
Return of large industries
Return of small industries
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