Examining the Correlation between Macroeconomic Factors and Stock Indices: A Comparative Analysis of IHSG and Nikkei

ABSTRACT


INTRODUCTION
In the intricate landscape of financial markets, where complexities abound, a comprehensive understanding of the nuanced interplay between macroeconomic factors and stock market dynamics is pivotal for well-informed decision-making.This study undertakes the formidable task of unraveling this intricate relationship by focusing on key macroeconomic variables-interest rates, inflation, GDP, exchange rates, and oil prices-while meticulously analyzing their impact on the bid-ask spread of two prominent stock indices: the Indonesia Stock Exchange Composite Index (IHSG) and the Nikkei Stock Average (Nikkei).
The financial markets, as intricate ecosystems, operate within a landscape where macroeconomic forces wield significant influence over market behavior.In-depth studies have diligently explored the isolated impacts of pivotal macroeconomic variables such as interest rates, inflation, GDP, exchange rates, and oil prices, unraveling their individual effects on diverse aspects of financial markets (Adegboyega, 2021).Each of these variables, acting as economic pillars, contributes uniquely to shaping the intricate dynamics of market activities.
However, within the extensive body of knowledge derived from these individual explorations, a conspicuous gap emerges in the literature a gap that underscores the necessity for a more comprehensive examination.This gap centers around the absence of a thorough understanding of how these diverse macroeconomic variables collectively interact to influence bid-ask spreads, a critical indicator of market efficiency.
The bid-ask spread transcends its role as a mere transaction cost; it serves as a vital gauge reflecting the depth of liquidity and the willingness of market participants to engage in trades (Adegboyega, 2021).Understanding the bid-ask spread is akin to deciphering the pulse of a market, encapsulating the cost of trading, market liquidity, and the broader sentiment of market participants.Consequently, a holistic exploration of how macroeconomic variables collectively shape bid-ask spreads is imperative for a nuanced understanding of market dynamics.
This study seeks to address the identified gap by embarking on a holistic exploration of the intricate relationship between macroeconomic variables and bid-ask spreads.While existing research has provided valuable insights into the isolated impacts of interest rates, inflation, GDP, exchange rates, and oil prices, a comprehensive understanding of their combined influence remains elusive.It is within this conceptual void that the significance of our study emerges-an attempt to bridge the gap by offering a more profound exploration of the intricate relationships that emerge when considering these macroeconomic variables together.
In essence, the bid-ask spread, standing as a pivotal indicator of market efficiency, reflects not only transaction costs but also mirrors the depth of liquidity and the willingness of market participants to engage in trades (Adegboyega, 2021).Our study aims to shed light on how this crucial indicator is intricately shaped by the collective influence of macroeconomic variables, providing a comprehensive understanding of market dynamics.

Theoretical Framework
The bid-ask spread, recognized as a pivotal barometer of market efficiency, transcends its role as a mere measure of transaction costs.It operates as a dynamic reflection, encapsulating the depth of liquidity in a market and gauging the willingness of market participants to actively partake in trading activities.Theoretical foundations assert that fluctuations in macroeconomic variables exert a substantial influence on market liquidity and the overall landscape of trading activities (Adegboyega, 2021).
Market efficiency, a fundamental concept in financial economics, revolves around the notion that prices in financial markets accurately reflect all available information.The bid-ask spread, acting as an indicator of market efficiency, embodies this concept by encapsulating essential facets of trading dynamics.Beyond merely representing the cost of executing trades, the bid-ask spread mirrors the liquidity levels in the market.A narrow spread suggests higher liquidity and a greater willingness among traders to engage, while a wider spread indicates lower liquidity and a more cautious approach among market participants (Adegboyega, 2021).
Theoretical underpinnings posit that macroeconomic variables play a significant role in shaping market dynamics, influencing the bid-ask spread.For instance, changes in interest rates can impact the cost of capital, thereby altering investor behavior and subsequently affecting the bid-ask spread.Inflation, as a measure of the general price level, can influence market expectations and, consequently, transaction costs.GDP, serving as a gauge of economic health, reflects the overall production and consumption within a country and, in turn, can influence market liquidity (Adegboyega, 2021).
The globalized nature of financial markets underscores the importance of exchange rates, as fluctuations in currency values can impact crossborder investments and, consequently, the cost of trading.Additionally, oil prices, being a critical driver of global economic activity, add another layer of complexity to the bid-ask spread equation, illuminating how energy prices might influence market liquidity and trading costs (Adegboyega, 2021).
To uphold rigorous academic standards, this study adheres to the citation guidelines outlined in the Chicago Manual of Style Ed. 17 th .The use of Reference Manager applications such as Mendeley or Zotero ensures accuracy and consistency in citation practices throughout the study.

Problem Statement
The existing body of literature has yielded a rich tapestry of insights by delving into the individual effects of macroeconomic variables on financial markets.However, a critical conceptual gap persists-one that hinders the attainment of a comprehensive understanding of how these macroeconomic variables collectively shape bidask spreads, a key indicator of market efficiency.
While numerous studies have meticulously explored how interest rates, inflation, GDP, exchange rates, and oil prices independently influence various aspects of financial markets, there exists a notable void when it comes to comprehending their combined impact on bid-ask spreads (Adegboyega, 2021).Bid-ask spreads, serving as intricate indicators of market efficiency, encapsulate not only transaction costs but also the depth of liquidity and the willingness of market participants to engage in trades.
Closing this conceptual gap holds paramount importance for both theoretical frameworks and practical implications in financial decision-making.The intricate interplay of macroeconomic variables, when considered collectively, unveils nuanced dynamics that extend beyond the sum of their individual impacts.Understanding how these variables synergistically influence bid-ask spreads is not only an academic pursuit but also a practical necessity for stakeholders in the financial landscape.
From a theoretical perspective, bridging this gap contributes to the evolution of financial theories.It allows for a more comprehensive understanding of the complex relationships between macroeconomic variables and bid-ask spreads.Theoretical frameworks in finance strive to model and explain real-world phenomena accurately, and a holistic exploration of these interactions ensures a more faithful representation of the intricacies inherent in financial markets.
On a practical level, closing this gap has tangible implications for financial decision-making.Investors, policymakers, and analysts, armed with a more complete understanding of how macroeconomic variables collectively shape bidask spreads, gain actionable insights.These insights can inform investment strategies, economic policies, and market trend analyses, empowering decision-makers to navigate financial landscapes with greater precision and foresight.
In essence, the problem statement underscores the imperative of moving beyond isolated examinations of macroeconomic variables and delving into their combined influence on bidask spreads.Addressing this conceptual gap is not just an academic pursuit but a crucial step toward advancing both the theoretical underpinnings and the pragmatic applications of financial knowledge.

Gap Analysis a. Existing Literature and Isolated Relationships:
The current landscape of academic research in finance has been predominantly characterized by a focus on examining isolated relationships between macroeconomic variables and financial markets (Adegboyega, 2021).In these studies, researchers have diligently explored how individual factors such as interest rates, inflation, GDP, exchange rates, and oil prices independently impact various dimensions of financial markets.However, there has been a discernible tendency to overlook the collective influence of these macroeconomic variables on bid-ask spreads.

b. The Overlooked Collective Influence:
Bid-ask spreads, as intricate indicators of market efficiency, encompass a multifaceted dynamic that extends beyond the sum of individual influences.While existing literature has provided valuable insights into how each macroeconomic variable may affect bid-ask spreads in isolation, a critical gap exists in comprehending how these variables collectively interact and shape the bid-ask spread landscape.This oversight represents a significant limitation in the existing body of knowledge, as the combined influence of macroeconomic variables can reveal nuanced patterns and interactions.

c. The Holistic Approach of This Study:
This study recognizes and aims to address this substantial gap in the literature by adopting a holistic approach.Instead of examining macroeconomic variables in isolation, our research endeavors to conduct a comprehensive analysis that considers the intricate interplay of interest rates, inflation, GDP, exchange rates, and oil prices.By taking this holistic stance, we seek to unravel the collective influence of these macroeconomic factors on bid-ask spreads.This approach is not only innovative but also essential for obtaining a more accurate and nuanced understanding of the dynamics at play in financial markets.

d. Scope of Analysis -Indonesia Stock Exchange and Nikkei
To ensure the robustness and applicability of our findings, we extend our analysis to encompass two distinct financial markets-the Indonesia Stock Exchange and the Nikkei (Pangondian, et al., 2022).This dual focus allows us to capture variations in market dynamics and responses to macroeconomic variables within different economic contexts.By examining these two prominent stock indices, we aim to provide insights that are not only academically rigorous but also practically relevant for stakeholders navigating diverse financial landscapes.
In essence, this study stands as a response to the limitations of existing literature by adopting a holistic approach to examine the collective influence of macroeconomic variables on bid-ask spreads, thus contributing to a more comprehensive understanding of the intricate dynamics within financial markets.

State of the Art
The current state of academic literature reflects a rich and varied landscape, with numerous studies delving into the intricate relationships between individual macroeconomic variables and their impact on stock markets (Ali, et al., 2019;Adegboyega, 2021;Al-Bayati et al. 2022).This vibrant field of research is exemplified by the works of scholars such as Adegboyega (2021), Al-Bayati et al. ( 2022), and Ali et al. (2019), among others (Adegboyega, 2021).
Researchers have extensively explored the effects of key macroeconomic factors, including interest rates, inflation, GDP, exchange rates, and oil prices, on various aspects of stock markets.For instance, Adegboyega's work focuses on the implications of inflation for the Nigerian Stock Exchange market Adegboyega (2021) while Ali et al. (2019) examine the impact of oil prices on stock market performance in top oil-importing countries (Ali, et al., 2019).These studies represent just a fraction of the diverse array of research efforts that contribute to the current understanding of the intricate interplay between macroeconomic variables and stock markets.
To facilitate further exploration and in-depth study, a comprehensive list of references is provided in the literature accompanying this research.This compilation serves as a valuable resource for readers, offering an extensive bibliography that spans a wide range of studies and perspectives on the relationship between macroeconomic conditions and stock market dynamics (Ali, et al., 2019).
In essence, the state of the art in this field showcases the wealth of insights gained from individual studies focusing on specific macroeconomic variables.However, the existing literature predominantly emphasizes isolated relationships, creating a notable gap that this study seeks to address by adopting a holistic approach that considers the collective influence of multiple macroeconomic variables on bid-ask spreads.

Research Innovation
This study pioneers an innovative research approach by integrating multiple macroeconomic variables to comprehensively investigate their collective impact on bid-ask spreads (Ali, et al., 2019).Traditionally, studies have tended to focus on isolated effects, often neglecting the interconnected nature of macroeconomic factors.In contrast, this research recognizes the importance of examining how these variables collectively shape bid-ask spreads-a vital indicator of market efficiency.
The integration of various macroeconomic variables-such as interest rates, inflation, GDP, exchange rates, and oil prices-offers a more holistic understanding of the intricate interplay within the financial markets.By adopting this comprehensive approach, the study seeks to uncover nuanced insights that transcend the limitations of examining each variable in isolation.
The overarching aim of this innovative endeavor is to contribute to a more nuanced understanding of the dynamic relationship between macroeconomic conditions and the efficiency of stock markets in both Indonesia and Japan.The study strives to bridge existing gaps in the literature by offering a holistic perspective that captures the synergies and complexities inherent in the collective influence of macroeconomic variables on bid-ask spreads.

Research Objectives
The primary goal of this research is to delve into the intricate relationship between macroeconomic variables and bid-ask spreads within the Indonesia Stock Exchange Composite Index and the Nikkei Stock Average.The specific objectives are outlined as follows: • Simultaneous Impact Investigation: The study aims to investigate the simultaneous impact of key macroeconomic variables, namely interest rates, inflation, GDP, exchange rates, and oil prices, on bid-ask spreads.This entails a comprehensive analysis that recognizes the intricate interplay among these variables and their combined influence on the dynamics of bid-ask spreads (Ali, et al., 2019).
• Implications Analysis: Another focal point of the research is to analyze the implications of the identified macroeconomic variables on market liquidity, transaction costs, and the willingness of market participants to engage in trades.This multifaceted analysis aims to provide a nuanced understanding of how macroeconomic conditions collectively shape the efficiency of stock markets, moving beyond isolated examinations (Ali, et al., 2019).
In essence, this research aspires to equip stakeholders across the financial spectrum with actionable insights for more informed decisionmaking.The study's outcomes are anticipated to hold significant relevance for investors, policymakers, and analysts navigating the dynamic landscape of international stock markets.By unraveling the complexities of the relationship between macroeconomic conditions and bid-ask spreads, the research aims to offer valuable perspectives that extend beyond theoretical realms.

LITERATURE REVIEW 1. Theoretical Background
This study explores the intricate relationship between macroeconomic factors and stock market performance, emphasizing the influence of inflation, exchange rates, interest rates, GDP growth, and oil prices on stock indices.Adegboyega (2021), Mishra et al. (2018), and Fuad and Yuliadi (2021) underscore the role of interest rates as a cost of capital, impacting investment decisions and the Composite Stock Price Index (IHSG) in Indonesia.

Previous Studies
This literature review incorporates insights from 15 to 25 articles from reputable journals, providing a comprehensive overview of past studies related to the topic.Adegboyega (2021) explore inflation's nuanced impact on stock returns.Mohammed (2021) broadens the perspective by investigating the interconnectedness of macroeconomic variables, focusing on the impact of inflation on exchange rates (Mohammed, 2021).
Ginting and Matondang (2022) contribute insights into the mining sector, examining the effect of GDP on stock returns in Indonesia.Mahmoudinia and Mostolizadeh (2022) investigate the asymmetric interaction between GDP, exchange rates, and stock markets, providing multifaceted insights into economic growth and equity markets (Mahmoudinia & Mostolizadeh, 2022).Tarmuji and Rasman (2016) explore the relationship between exchange rates and stock market performance.
In the realm of oil prices, Al-hajj et al. ( 2020), Ali et al. (2019),investigate the nexus between oil price shocks and sectoral stock returns, shedding light on the repercussions of energy market dynamics on equity markets.Contextualizing these studies, Pangondian et al. (2022) provide comparative perspectives on stock price indices in Southeast Asia and Indonesia, respectively.

Research Framework
To provide a conceptual framework for the research approach, consider the visual representation in Table 1 below.This framework encapsulates the essential variables, their conceptual relationships, and the hypotheses guiding the study.This study aims to validate these hypotheses within the specific contexts of the Indonesia Stock Exchange Composite Index (IHSG) and the Nikkei Stock Average (Nikkei), contributing nuanced insights into the relationships between macroeconomic variables and stock market dynamics in these markets.

METHODOLOGY 1. Data
The study utilizes the Stata software for time series regression analysis to explore the connections between macroeconomic factors and stock market indices, specifically focusing on the Indonesia Stock Exchange Composite Index (IHSG) and the Nikkei Stock Average.A comprehensive dataset covering the period from 2014 to November 2023 is compiled, encompassing crucial macroeconomic variables: inflation rates, exchange rates, interest rates, GDP growth rates, and oil prices.These variables are chosen based on their status as established economic indicators, ensuring a holistic examination of factors influencing stock market performance.The IHSG and Nikkei serve as dependent variables, while selected macroeconomic factors act as independent variables for the Stata-based time series regression analysis.

Model Development
The model is constructed on established theoretical foundations.A scientifically rigorous equation guides the time series regression analysis, ensuring linearity and compatibility with Stata's regression analysis capabilities.The model's theoretical underpinning is expressed through a mathematical expression, symbolizing the structured relationship between macroeconomic variables and stock market indices.

Method
Stata is chosen as the method for time series regression analysis due to its versatility and robust statistical capabilities.The essential assumptions for Stata-linearity, independence of errors, homoscedasticity, and normality of residuals-are meticulously examined to ensure the reliability and validity of the time series regression model.Stata's widespread use in empirical research and its suitability for analyzing time series data justify its selection as the primary method for this study.

Conclusion and Future Implications
The synthesis of findings from Stata's time series regression analysis holds implications for various stakeholders, offering actionable insights into the intricate relationships between macroeconomic variables and stock market dynamics.The conclusion also points to potential areas for further research, encouraging scholars to explore additional dimensions and refine the methodology for a deeper understanding of the subject matter.

RESULT AND DISCUSSION
In this section, we delve into the analysis of research findings, providing nuanced insights into the relationship between macroeconomic factors and stock market performance, specifically focusing on the Indonesia Stock Exchange Composite Index (IHSG) and the Nikkei Stock Average.

Analysis of IHSG (Indonesia Stock Exchange
Composite Index) The linear regression analysis results for IHSG offer a comprehensive view of the dynamics between the index and various macroeconomic factors.GDP (Gross Domestic Product): The observed coefficient of 0.007, coupled with a p-value of 0.664, implies a non-significant positive relationship between GDP and IHSG.This suggests that, in isolation, economic growth may not be a robust predictor of IHSG movements.
Inflation: The coefficient of -0.036, accompanied by a p-value of 0.018, reveals a significant negative relationship between inflation and IHSG.This intriguing finding suggests that as inflation rises, IHSG tends to decrease, highlighting the impact of inflation on purchasing power and corporate profitability.
BI Rate (Bank Indonesia Interest Rate): With a coefficient of -0.003 and a p-value of 0.864, the analysis indicates a non-significant negative relationship between the Bank Indonesia interest rate and IHSG.This suggests that, within the observed context, interest rate fluctuations may not be a significant driver of IHSG movements.
Exchange Rate (Kurs Rupiah): The coefficient of -0.077, associated with a p-value of 0.002, underscores a significant negative relationship between the Rupiah exchange rate and IHSG.This emphasizes the importance of currency stability for investor confidence in the Indonesian market.
Oil Price: The analysis reveals a nonsignificant positive relationship (coefficient of 0.001, p-value of 0.125) between oil prices and IHSG, suggesting that, within the observed period, oil price fluctuations may not be a major driver of IHSG movements.
Constant: The constant term of 1.123, with a p-value of 0.003, indicates a significant constant effect on IHSG.This further reinforces the multifaceted nature of factors influencing IHSG.The model's characteristics, including an Rsquared of 0.134 and an F-test p-value of 0.046, signify a moderate explanatory power, suggesting that the included variables collectively explain a notable proportion of the variance in IHSG.

Analysis of Nikkei Stock Average
Turning our attention to the Nikkei Stock Average, the linear regression analysis provides insights into its relationship with key macroeconomic factors.Inflation: The coefficient of 0.069, with a pvalue of 0.767, indicates a non-significant positive relationship between inflation and the Nikkei.This suggests that, in the Japanese context, inflation may not be a crucial factor influencing stock market movements.
BOJ Rate (Bank of Japan Interest Rate): With a coefficient of 3.882 and a p-value of 0.487, the analysis reveals a non-significant positive relationship between the Bank of Japan interest rate and the Nikkei.This implies that changes in central bank interest rates may not be a primary driver of Nikkei movements.
GDP: The coefficient of -0.024, coupled with a p-value of 0.748, suggests a non-significant negative relationship between GDP and the Nikkei.This implies that GDP growth alone may not be a robust predictor of stock market performance in Japan.
Exchange Rate (Kurs Yen): The coefficient of 0.012, with a p-value of 0.509, indicates a nonsignificant positive relationship between the Yen exchange rate and the Nikkei.This suggests that, within the given context, changes in the Yen may not significantly influence Nikkei movements.
Oil Price: The analysis shows a nonsignificant negative relationship (coefficient of -0.013, p-value of 0.16) between oil prices and the Nikkei, indicating that, during the observed period, oil price fluctuations may not be a major driver of Nikkei movements.
Constant: The constant term of -0.164, with a p-value of 0.925, suggests a non-significant constant effect on the Nikkei.
The model's characteristics, with an Rsquared of 0.029 and an F-test p-value of 0.730, indicate a limited explanatory power, emphasizing the complexity of factors influencing the Nikkei.

Comparative Analysis
The comparative analysis across IHSG and Nikkei unveils intriguing patterns and disparities: • Both markets exhibit non-significant relationships between GDP and stock indices, suggesting that economic growth alone may not ensure robust stock market performance.
• In both cases, inflation emerges as a significant factor, displaying a negative correlation with stock indices.This underscores the potential impact of inflation on market movements.indicating that changes in central bank rates may not be the primary driver of stock market movements in these contexts.• Oil prices do not emerge as significant predictors of stock market movements in either market during the observed period, highlighting the nuanced nature of the relationship between oil prices and stock indices.

CONCLUSION AND RECOMMENDATION
Concluding this study, the interplay between macroeconomic factors and the stock markets of Indonesia (IHSG) and Japan (Nikkei) has been unraveled, offering nuanced insights into the forces shaping these financial realms.Elaborating on the findings, for IHSG, the pronounced negative correlation with inflation underscores the influence of purchasing power and corporate profitability on market movements.The non-significant relationship with the Bank Indonesia Interest Rate (BI Rate) highlights market resilience to changes in central bank rates.The significant negative correlation with the Rupiah emphasizes the critical role of currency stability.Additionally, the nonsignificant association with oil prices suggests a limited impact of global oil price fluctuations on IHSG.
Shifting focus to the Nikkei, the nonsignificant relationship with inflation indicates a more subdued impact on market movements.Similar non-significant relationships with the Bank of Japan (BOJ) Rate, Yen exchange rate (Kurs Yen), and oil prices underline the diverse array of factors influencing the Japanese market.In a comparative analysis, both markets reveal non-significant relationships between GDP and stock indices, challenging the notion that economic growth alone ensures consistent market performance.Interest rates, represented by the BI Rate for IHSG and the BOJ Rate for Nikkei, exhibit non-significant relationships, suggesting that changes in central bank rates may not be the primary driver of stock market fluctuations.The significant negative correlations with exchange rates underscore the critical role of currency stability in both markets.Furthermore, non-significant relationships with oil prices suggest that, within the observed periods, oil price fluctuations may not be pivotal determinants of stock market movements.
As we look forward, stakeholders are urged to tailor their strategies to the unique characteristics of each market.Policymakers must consider a holistic approach, giving paramount importance to maintaining currency stability.Continuous market vigilance, coupled with robust investor education programs, becomes paramount for fostering a resilient financial ecosystem.Periodic portfolio reassessment should be embraced as a proactive measure to adapt to evolving market dynamics and manage risks effectively.
The call for cross-market collaboration rings loud, as institutions and regulators should foster dialogue, share insights, and establish frameworks that transcend geographical boundaries.Collaborative efforts are crucial for enriching our collective understanding of global financial intricacies, promoting adaptability and resilience in the face of ever-changing economic landscapes.
In essence, this study serves not merely as a conclusion but as a compass, guiding stakeholders toward informed, adaptive, and resilient financial decisions.The dynamic global contexts demand proactive strategies, and the lessons derived from this research aim to empower stakeholders to navigate the complexities of the financial terrain with confidence and foresight.