Stock Exchange Index Research Articles

The impact of ESG strategies on growth in the logistics industry

The aim of the article is to analyse the relationship between company growth, measured as an increase in Earnings Per Share (EPS) in 3- and 5-year periods, and companies’ financial condition, measured using the Altman z-Score (AS) model. The study was carried out on the example of companies included in the WIG Index and Warsaw Stock Exchange Index (in Polish: Warszawski Indeks Giełdowy – WIG) Environmental, Social, and Governance (ESG) between 2013 and 2020. Furthermore, among the companies included in the WIG index, companies belonging to the logistics industry were distinguished. An analysis of linear and panel relationships was used to verify the nature of the relationships between the variables taken into account. The z-Altman index was found to have a positive effect on company growth in a 3-year period for companies from the transport and logistics industry and all companies included in the WIG ESG index. Regarding company growth over the longer 5-year period, the influence of the z-Altman index on growth was not observed. Therefore, the results for companies in the WIG index show that for company growth in both the 3- and 5-year periods, the financial and economic condition of a company, measured by the z-Altman index, has no impact on the size of this growth, which was also confirmed by panel models.

An Empirical Analysis of the Performance of Luxury Watch Portfolios among High-Net-Worth Individuals in India During the COVID-19 Pandemic

This study empirically evaluates luxury watches owned by high-net-worth individuals (HNIs) in India as unconventional alternative assets providing diversifying benefits. During the COVID-19 pandemic, the major stock exchanges in India, NSE and BSE, faced negative returns and high volatility, igniting numerous conservative investors to divest from traditional investments and retain alternative assets, such as luxury watches, due to their low correlation to financial markets. Owing to supply chain disruptions and demand forces, the overall secondary watch market prices surged throughout this period, creating high economic value for investors. Through hypothesis testing and attribution analysis, this paper evaluates the performance of watch portfolios owned by 57 HNIs, comprising of 464 watches, to investigate whether luxury watches are viable investments during economic downturns within the domain of alternative investments. Hence, this study employs suitable attribution tools such as Sharpe ratio, M2 Alpha, Treynor Measure and Jensen’s Alpha to understand the strength of their performance. Using academic literature, market data and primary data, this study found that luxury watches provided substantial portfolio diversification benefits and outperformed traditional assets like the NIFTY50 and gold in terms both nominal and risk adjusted returns during the pandemic. Brands such as Patek Philippe, Rolex, and Audemars Piguet achieved the highest performance, as Patek Philippe demonstrated superior risk-return trade-offs. Despite challenges such as valuation complexities and liquidity constraints, luxury watches provided remarkable upside potential, benefiting from a high retention rate due to their unique emotional features. Ultimately, the findings suggest that luxury watches can be viable alternative investments considering that 65% of these HNIs viewed their watch purchases as investment opportunities.

Is Dhaka Stock Exchange An Efficient Capital Market? - Evidence Of Weak-Form Efficient Market Hypothesis

This paper uses Random walk hypothesis to test the efficiency of Dhaka Stock Exchange Ltd (DSE), an emerging capital market of Bangladesh. In this paper, with Runs test, Dickey-Fuller Unit root test have been processed and analyzed to observed the behavior of daily return of Dhaka Stock Exchange indices during the study period. The sample includes the daily price indices of all securities listed on the DSE general, DSI (All Share), DSE-30, and Daily indices listed with DSE. As a proxy of movement of individual stock prices, daily closing prices of 30 companies operating in the Banking sector has been analyzed. The results provide evidence that DSE does not follow the random walk model and so DSE is not efficient even in weak form. To improve this capital market, the timely disclosure and dissemination of information to the shareholders and investors on the performance of the listed companies should be given emphasized.

Unraveling stock exchange connections: an empirical study of India, US, Hong Kong, Germany, France and Amsterdam

PurposeThe current study immerses itself in the realm of diversification prospects within a select group of preeminent global stock exchanges. Specifically, the study casts its discerning gaze upon the financial hubs of the United States, Hong Kong, Germany, France, Amsterdam and India. In this expansive vista of international financial markets, the present analytical study aims to unravel the multifaceted opportunities that lie therein for astute portfolio management and strategic investment decisions.Design/methodology/approachThe study encompasses daily time series data spanning from 2019 to 2022. To assess the interconnectedness among these stock indices, advanced statistical techniques, including Johansen cointegration methods and vector autoregressive (VAR) models, have been applied.FindingsThe research outcomes reveal both unidirectional and bidirectional relationships between the Indian, Hong Kong and US stock exchanges, encompassing both short-term and long-term time frames. Interestingly, the empirical findings indicate the presence of diversification opportunities between the Indian stock exchange and the stock exchanges of Germany, France and Amsterdam.Research limitations/implicationsThese insights hold significant value for both Indian and international investors, including foreign institutional investors (FIIs), domestic institutional investors (DIIs) and retail investors, as they can utilize this knowledge to construct more effective and diversified investment portfolios by understanding the intricate interconnections between these prominent global stock exchanges.Originality/valueThis research undertaking aspires to bring coherence to a landscape rife with divergent interpretations and methodological divergences. We are poised to offer a comprehensive analysis, a beacon of clarity amidst the murkiness, to shed light on the intricate web of interconnections that underpin the world's stock exchanges. In so doing, we seek to contribute a seminal piece of scholarship that transcends the existing ambiguities and thus empowers the field with a deeper understanding of the multifaceted dynamics governing international stock markets.

Monetary Policy and Stock Market Dynamics: An Empirical Perspective

This study examines the influence of monetary policy on stock market performance and activity in Bangladesh, focusing on the Dhaka Stock Exchange (DSEX) index, using monthly data from August 2012 to June 2024. The regression analyses incorporate key monetary variables: the 91-day treasury bill rate, broad money supply, and Consumer Price Index (CPI). The first model reveals that the current month's DSEX index is strongly dependent on the previous month's index level, with the 91-day treasury bill rate showing a significant negative correlation, the broad money supply exhibiting a positive relationship, and the CPI indicating a negative association with market performance. The second model demonstrates that both the 91-day treasury bill rate and CPI negatively impact market turnover, while broad money supply has a positive effect. These findings underscore the crucial role of monetary policy in shaping stock market dynamics in Bangladesh, providing valuable insights for policymakers and investors in emerging markets.

Cointegration and causality relationship of Indian stock market with selected world markets.

Background: The purpose of this study is to explore the trends and causes of established and emerging nations' stock market integration with India. The National Stock Exchange (NSE) indices act as a counterweight to international market indices. This study investigates the sustained interest of foreign investors in the Indian stock market in the wake of capital market reforms, as well as whether it moves in tandem with other markets in Asia and the United States. Methods: Our study examined the possibility of cross-country cointegration between the largest economies and indices around the world using multiple financial econometric models, such as Augmented Dickey-Fuller, Unit Root, Correlation, and Johansen Cointegration. Results: The findings of this study significantly support the notion that Indian and international financial markets are highly integrated. Vector error correction model indicates that the Indian market (NSE) is highly cointegrated with the US market (National Association of Securities Dealers Automated Quotations) and increased volatility signifies global contagion. Conclusion: A cursory examination of the data reveals distinct investment and portfolio diversification options for global investors. This could assist regulators in formulating more effective rules regarding price discovery processes.

Municipal bonds at Bucharest Stock Exchange: what the correlations are revealing?

"As highlighted by Pop & Georgescu (2024), the Romanian academic literature concerning municipal bonds is sparse, while the investigations regarding the factors that can influence the sub-sovereign bond trading at Bucharest Stock Exchange is quasi non-existent, to the best of authors’ knowledge. The present paper continues the work of Pop & Georgescu (2024) by trying to identify which of the public available information regarding various interest rates and Bucharest Stock Exchange (henceforth BVB) indices returns influence the trading activity of municipal bond market segment. The correlations presented within this paper imply that the modest profile of municipal bond segment at BVB is related to a relative small number of individual investors that dominate the transactions, using mostly observed data to decided when to trade and what to trade. The scarce correlations that appear in relation with the trading volume and trading value point toward the idea that only a small portion of the listed municipal bonds are owned by individual investors. Key words: municipal bond, Romania, correlations JEL Classification: G12"

Boom or bust? A Comparative Analysis of Monetary Policy and Stock Market Performance in India Across Economic Cycles

This study delves into the intricate relationship between monetary policy instruments and various sectors of the Indian stock market from 2011 to 2022. By Analyzing data encompassing significant policy shifts and economic events, including the Reserve Bank of India's (RBI) transition towards inflation targeting and flexible exchange rates, the study aims to uncover the nuanced impacts of monetary policy on sectoral indices. Utilizing a Vector Autoregression (VAR) model, the study examines the dynamic interplay between key monetary policy instruments—Cash Reserve Ratio (CRR), Marginal Standing Facility Rate (MSF), Repo Rate, Reverse Repo Rate, and Treasury Bills—and ten diverse sectors represented in the Bombay Stock Exchange (BSE) indices. The findings reveal intricate sectorspecific responses to monetary policy adjustments, reflecting the complex interplay of economic dynamics and policy measures. While some sectors exhibit positive correlations with certain monetary instruments, others display negative associations, underscoring the diverse impacts of monetary policy on sectoral performance. The study highlights the significance of understanding these nuanced relationships for policymakers, investors, and market participants in navigating India's evolving economic landscape.

Developing and developed Mediterranean stock exchanges: Interdependence in periods of crisis and stability

"This research aims to explore how the stock exchange indexes of developed and developing Mediterranean countries are interrelated, both during times of crisis and stability. Specifically, it examines the association between Macedonia's MBI10 index and the stock exchange indexes of Serbia (BELEX15), Italy (FTSE MIB), and Spain (IBEX35) from 2005 to 2022 using monthly data. To understand how crises impact the relationships between these markets, the study breaks down the timeframe into four distinct periods: before the Great Financial Crisis (pre-GFC), during the GFC, after the GFC (post-GFC), and during the Covid-19 pandemic and energy crisis. Through Pearson correlation and linear regression analyses, the findings show that the MBI10's correlation with the BELEX15, FTSE MIB, and IBEX35 indexes was strongest during the GFC. However, this correlation dropped significantly during the Covid-19 pandemic and energy crisis. Keywords: Mediterranean, stock exchange, Great Financial Crisis, interdependence, Covid-19, energy crisis JEL Classification: F02, F21, G15"

The Efficiency of Investment in Indian Stock Market using GRA Method

The Indian Stock Exchange, holds significant sway in the country's economy. They serve as pivotal platforms where a plethora of companies from diverse sectors converge, contributing to fastest growing in the world of one of the economies, a growth story. Growing up engaged in development stories for those interested, the Indian Stock Exchange offers many opportunities: government policies, economic indicators, Global market trends. It is affected by various factors like corporate earnings, all of which significantly impact stock prices. Indian stock market for the economic well-being of the country acts as a measure and reflecting global trends its dynamic shows character it is stocks, derivatives various financial like Includes tools. commodities, and currencies, with distinct sections, prominently represented by housing numerous listed companies across diverse sectors. Both domestic and international investors engage in the market, aiming for wealth creation while navigating associated risks according to their objectives. Over the years, spurred by economic reforms, technological advancements, and increased investor participation, India's stock market has experienced significant expansion and evolution. It has transitioned to electronic trading platforms, enhancing efficiency, transparency, and accessibility. Regulatory reforms have bolstered investor confidence and market integrity. Indian stock market for the economic well-being of the country acts as a measure and reflecting global trends its dynamic shows character it is stocks, derivatives various financial like Includes tools. commodities, and currencies, with distinct sections, prominently represented by housing numerous listed companies across diverse sectors. Both domestic and international investors engage in the market, aiming for wealth creation while navigating associated risks according to their objectives. Over the years, spurred by economic reforms, technological advancements, and increased investor participation, India's stock market has experienced significant expansion and evolution. The primary purpose of GRA is to elucidate the comparative ranking of alternatives based on their performance. In this method, known as Gray Relative Analysis, a super target sequence is established in accordance with specific scenarios. Subsequently, each alternative in the rows undergoes evaluation using the Carey correlation coefficient against the satisfying target collection. Finally, the gray correlation is computed by applying coefficients, revealing the correct target sequence and determining the size of gray contact for each variant sequence Infosys Limited, Reliance Industries Limited, HDFC Bank Limited, Tata Consultancy Services Limited and Housing Development Finance Corporation Limited. Earnings Per Share (EPS), Price-to-Earnings Ratio (P/E Ratio), Return on Equity (ROE), Debt-to-Equity Ratio (D/E Ratio) and Market Capitalization. The rank of GRA indicates the efficiency of investment in the Indian stock market. Housing Development Finance Corporation Limited has the highest GRG rank value, while HDFC Bank Limited has the lowest value.

Predicting the Direction of NEPSE Index Movement with News Headlines Using Machine Learning

Predicting stock market movement direction is a challenging task due to its fuzzy, chaotic, volatile, nonlinear, and complex nature. However, with advancements in artificial intelligence, abundant data availability, and improved computational capabilities, creating robust models capable of accurately predicting stock market movement is now feasible. This study aims to construct a predictive model using news headlines to predict stock market movement direction. It conducts a comparative analysis of five supervised classification machine learning algorithms—logistic regression (LR), support vector machine (SVM), random forest (RF), extreme gradient boosting (XGBoost), and artificial neural network (ANN)—to predict the next day’s movement direction of the close price of the Nepal Stock Exchange (NEPSE) index. Sentiment scores from news headlines are computed using the Valence Aware Dictionary for Sentiment Reasoning (VADER) and TextBlob sentiment analyzer. The models’ performance is evaluated based on sensitivity, specificity, accuracy, and the area under the receiver operating characteristic (ROC) curve (AUC). Experimental results reveal that all five models perform equally well when using sentiment scores from the TextBlob analyzer. Similarly, all models exhibit almost identical performance when using sentiment scores from the VADER analyzer, except for minor variations in AUC in SVM vs. LR and SVM vs. ANN. Moreover, models perform relatively better when using sentiment scores from the TextBlob analyzer compared to the VADER analyzer. These findings are further validated through statistical tests.

Macroeconomic factors and government bond yield in Indonesia

The issuance of bonds by the government attracts the interest of many investors, including foreigners. The government must understand the factors determining bond yields for managing government debt. This study aims to investigate the effect of domestic and global macroeconomic variables on government bond yields in Indonesia. The paper uses monthly data from November 2014 to December 2022. The research sample comprises government bonds with 5, 10, and 15-year tenor bonds. The GARCH (1,1) and GARCH-M (1,1) models are applied to estimate and analyze the determinants of government bond yields. Research findings reveal that Indonesian interest rates significantly affect the yield of 10- and 15-year tenor bonds. Inflation has no impact on bond yields across all tenors. The increase in foreign exchange reserves reduces bond yields in all tenors. The Indonesian stock exchange index is detrimental to long-term bond yields. The exchange rate has a positive impact on bond yields in all tenors. World oil prices significantly impact yields on 5- and 10-year tenor bonds. The Fed’s interest rate positively affects the yield on the 15-year tenor bond. The implication of these findings for the Indonesian government is the implementation of several aspects of economic and financial policies that can improve state debt management and financial market stability.

Impact of Visual Disturbances on the Trend Changes of COP Displacement Courses Using Stock Exchange Indices

This work aims to define a strategy for maintaining a vertical posture of the human body under conditions of conflicting sensory stimuli using a method of trend change analysis. The investigations involved 28 healthy individuals (13 females, 15 males, average age = 21, SD = 1.3 years). Measurements were conducted with eyes opened and closed and in the virtual environment with two sceneries oscillating at two frequencies. Values in the time domain were calculated—the mean center of pressure (COP) velocity and movement range in the AP direction—as well as values based on the moving average convergence divergence (MACD) computational algorithm—the trend change index (TCI), MACD_dT, MACD_dS, and MACD_dV. After dividing the analysis into distinct time periods, an increase in TCI values was identified in the oscillating scenery at 0.7 and 1.4 Hz during the 0.5–1 and 0.2–0.5 s time periods, respectively. Statistically significant differences were observed between measurements with an oscillation frequency of 0.7 Hz and those with an oscillation frequency of 1.4 Hz during the 0.2–0.5 s and 0.5–1 s periods. The use of stock exchange indices in the assessment of the ability to keep a stable body posture supplements and extends standard analyses in the time and frequency domains.

The travel behaviors before and after lockdown: Case study on Shanghai, 2022

From April 1 to May 31, 2022, Shanghai implemented a full lockdown in response to the rapid spread of COVID-19 to protect the vulnerable population. This paper aims to comprehensively assess the impact of this lockdown. Traffic data for March and June of 2022 were collected, including the vehicular traffic volumes from four typical intersections and metro ridership. Other important indicators, including COVID-19 cases, Baidu Index and Shanghai Stock Exchange Index, were also employed. The results show that: (1) In both March and June, except for the intersection near the major hospital, the ratios between the weekday and weekend traffic volumes were higher than those observed before the pandemic, which implies a significant drop in leisure trips during these periods. (2) The evolution of traffic volume in March was largely driven by some important COVID-19-related events, while the traffic volume in June showed a more spontaneous and stepwise recovery pattern. (3) The confirmed cases had a significant impact on the traffic volume in March, but the time lag of the confirmed cases was not found. The impact of confirmed cases on traffic volume in June was not significant. (4) The transfer from public transport to private ones could be observed during this period, but the recovery proportion of Shanghai metro ridership is higher than most other cities examined in this study, suggesting the importance of enhancing public confidence for public transport in the post-pandemic period. These findings can aid in refining potential pandemic measures for future scenarios.

Analysis of the Stability of the Banking Sector of Azerbaijan in Conditions of Economic Crisis Based on the Econometric Model

This article is devoted to the influence of a number of macroeconomic indexes on the amount of reserves for possible losses in the Azerbaijan banking sector.The purpose of research. The purpose of the research to analyze the stability of the banking sector to the impact of macroeconomic shocks in the economy, study what the concept of financial stability of the banking sector includes, and what methods are used in the process of its analysis and assessment, investigate the dependence of a number of variables characterizing the state of the banking sector on various macroeconomic shocks inherent in the economy, analyze how the Central Bank is involved in regulating and monitoring the financial stability of the banking sector, as well as through what measures it supports banks in times of crisis.Materials and мethodology. The practical stage of the work is to create a multiple regression model that will reveal the degree of impact of macroeconomic shocks on the position of the Azerbaijan banking sector. To carry out the analysis and construct regression equations, quarterly data for the period 2012-2023 were used. Information was taken from a number of sources: 1) Official website of the Central Bank of Azerbaijan; 2) Official website of Ministry of Finance; 3) Official website of Azerbaijan State Statistics Committee; 4) Reports on the development of the banking sector and banking supervision. To analyze and estimating the values of the dependent variables of provisions for possible losses and return on assets, values for the banking sector as a whole are taken from annual reports on the development of the banking sector and banking supervision.Since the source data in the work is quarterly, our model will be a time series estimated using the ordinary least squares (OLS) method. Lagged variables may be included in the time series. The lags in the explanatory variables take into account the degree of possible lag with which macroeconomic shocks affect banks. In other words, changes in the values of macroeconomic factors do not have an immediate impact on the position of banks, but appear after some time and are delayed [7]. Such lags need to be identified and taken into account in order to form a more accurate and complete picture of the impact of macroeconomic fluctuations on the banking sector.During preliminary diagnostics of the data, the presence of heteroscedasticity and first-order autocorrelation was revealed. To eliminate it, Newey-West corrections are applied, adjusting the variation-covariance matrix to obtain more consistent estimates of regression coefficients.Results. When selecting indexes to study the degree of impact of macroeconomic factors on the stability of the banking sector, we took into account the peculiarities of the economy of our country. The fact is that Azerbaijan is a raw materials country, the export of which consists of almost 70% of fuel and energy products [30]. This means that the size of export revenues, the financial position of companies and the stability of the economy are highly dependent on the price situation in the global energy market, namely the price of oil.In addition, Azerbaijan belongs to a number of countries with an emerging market, which is characterized by increased volatility of exchange rates and instability of financial markets and high interest rates and spreads. Therefore, our country is characterized by the risk of a sharp outflow of capital in the event of a crisis in the world, as investors seek to withdraw their funds from countries that are most vulnerable to the influence of macroeconomic shocks.GDP dynamics are one of the important indicators of the economic activity of the state. Its fall during the crisis negatively affects various spheres of economic and social life [8].The Baku stock exchange index reflects the state of the stock market of large companies, which are the most important for the country’s economy [9]. The collapse of the index means a deterioration in the position of companies, a decrease in the market value of their assets and shares, and increases problems with paying external debt and obtaining new loans to ensure the functioning of their activities. In addition, the collapse of quotes on the stock market leads to large losses as a result of their negative revaluation.Conclusion. When conducting a research of the sustainability of the banking sector in Azerbaijan based on an econometric model, it is necessary to take into account certain limitations. First, the availability and reliability of data is an important aspect that can affect the accuracy of the study results. Secondly, to fully understand the issues under study, it is necessary to take into account the context and specifics of the banking system of Azerbaijan. Finally, this study does not examine social and political factors that may also influence the sustainability of the banking system. Limitations of the study should be considered when interpreting the results and making recommendations.

A Study on Novice Investor Behavior in Indian Stock Exchange

Investing is not only a personal financial endeavor but also a critical driver of economic growth, shaping individual prosperity and national development. The research is significant because it emphasizes the critical role that financial literacy plays in influencing investment behavior. It also emphasizes the necessity of ongoing education and awareness campaigns to equip new investors with the information and abilities they need to make wise decisions on the Indian Stock Exchange. All things considered, the results provide insightful information that will help investors, financial institutions, and regulators develop policies to support a more knowledgeable, resilient, and inclusive investment environment in India. This study embarks on a journey to explore the intricate dynamics of investment in India, beginning with an exploration of its foundational role as the engine of economic progress. From influencing aggregate demand to shaping future productive capacity, investments yield significant influence over a nation's economic trajectory, fostering financial markets and enabling companies to raise capital for further growth. In addition, the research reveals that participants have a wide variety of investment objectives, with long-term wealth creation being the primary focus. Investment styles are characterized by a trade-off between risk and return, with moderate strategies being the most common, and considerable shares of aggressive and conservative methods. In emerging markets like India, where investor behaviors vary across a diverse spectrum, understanding the impact of different investor types becomes imperative. Delving into the distinct behaviors of individual, institutional, and foreign investors, this analysis sheds light on their contributions to the Indian stock market, unravelling their unique influences and dynamics.

Analysis of the Relationship Between Cross Capital Flows and Stock Exchange Index with Machine Learning

This paper investigates forecasting the BIST100 stock index using cross-capital flow analysis. It employs feature engineering and the Orthogonal Matching Pursuit (OMP) model to navigate the intricacies of financial time series prediction. The study meticulously selects features such as lagged values, moving averages, and volatility metrics, normalized to ensure unbiased model impact. The OMP model is carefully optimized to handle the dimensionality of financial data, avoiding overfitting through a sparsity constraint. This approach yields an R-squared score of 0.88, indicating a solid capability to capture index variance. Visual comparisons between actual and predicted values further validate the model's accuracy. The paper highlights the importance of methodological precision in developing models capable of discerning complex patterns, offering valuable insights for investment strategies. Implications of the study show that cross-capital movements and macroeconomic variables are a good fit with ML to predict the Stock Market despite the complexity of financial markets.

EXPLORING THE RELATIONSHIP OF MULTIPLE TIME DURATION RETURNS, AND ANNUAL VOLATILITY INTER SE FOR VARIOUS INDICES ON THE NATIONAL STOCK EXCHANGE

Stock exchanges are the epicenter of any capitalistic and free market model economy and the variety of indices maintained by them serve as the barometer. NSE, the largest stock exchange in India maintains and publishes prices changes data for 87 stock indices constituted based on different themes, strategy, and sectors including the benchmark NIFTY-50. The main objective of this study is to understand relationship for returns of 1 month, 3 months, 1 year, 3 years, 5 years and 1-year volatility inter se. The study interestingly reveals that there is impact of quarterly returns of the indices on annual returns. On the contrary it is unaffected by monthly returns. On the volatility front short term returns were seen affected by annual volatility while long term returns did not with exception of 5 year figures.

Extreme Connectedness Across Chinese Stock and Commodity Futures Markets

This study examines the price spillovers and connectedness among stock markets, the Shanghai Stock Exchange Composite (SSEC) index, Hang Seng index, Shenzhen Stock Exchange (SZSE) index, commodity futures markets, Aluminum (AL), Gold (AU), Copper (CU), Zinc, Steel Rebar, and Natural Rubber in bearish and bullish market situations. We use the quantile connectedness approach of Ando et al. (2022) to calculate hedge coverage ratios, optimal portfolio weights, and hedge coverage effectiveness. Our empirical analysis yields several important results. First, there is no difference in the results of the TVP-VAR-DY and TVP-VAR models in relation to the magnitude of return transmission during the sample period. Second, CU is the main transmitter and AU is the main receiver of shocks from the network. Third, under the QVAR method estimations, the CU (AU) is the major (minor) contributors to the network during the normal, bearish, and bullish market statuses. Fourth, the results of the hedge ratio strategy confirm that CU and AU are respectively the most and the least expensive assets for a long-term investment in the Chinese stock market in different market conditions.

Forecasting the Volatility of the Russian Stock Market in the Context of International Economic Sanctions

The article is devoted to the study of trends in the development of the Russian stock market in the context of international economic sanctions. The purpose of the study is to make forecasts of the volatility of the Russian stock market using a scenario approach. Statistical data of the Moscow Stock Exchange were used for calculations. The authors have made a forecast of the volatility of the stock exchange market of the Russian Federation. The basis of the forecast calculations is the dynamics of the Moscow Exchange Index (IMOEX), taken as a key indicator of the Russian organized securities market, for the period from June 2013 to July 2022. Based on the basic historical dynamics of the Moscow Stock Exchange Index, negative (international economic sanctions are being tightened) and positive (implies the easing and/or lifting of some sanctions) scenarios for the development of the stock market of the Russian Federation are compiled. The scientific novelty is the authors’ assessment of the convergence of the volatility forecast under negative and positive scenarios to a certain level of volatility in 2023. The results of the calculations showed that under different scenarios of the situation, volatility tends to the same value at different assumed values of the Moscow Exchange Index, which allowed us to draw a new and practically significant conclusion that over time the economy of the Russian Federation stabilizes regardless of the tightening or easing of international economic sanctions — this may be due to the implementation of the country has a policy of import substitution, the formation of national production in most areas of the economy and the development of the domestic market. The work carried out by the authors contributes to the development of theoretical and applied economics in terms of making forecasts for the development of the stock market and using the results of forecasting to make economically sound decisions.