Market Proxy Research Articles

Exploring information demand in the maritime industry: a Google Trends approach

ABSTRACT The fundamental impetus for this research is the documented wide use of Google and the ensuing applications of Google Trends in behavioural economics. Expanding the existing literature, we focus on addressing the question of whether information demand from individual investors can reflect a freight rates sentiment. This is achieved by analysing Google queries referring to investment in maritime stocks and other related markets. These searches comprise essentially a blend of information and intuition. More specifically, we examine whether the most frequently searched term and topic referred to Baltic Dry Index (BDI) can serve as a reliable and valid positive or negative sentiment market proxies. We find a negative impact on freight rates, capital markets, and the number of available dry bulk fleet, providing evidence aligned with the risk-averse investor theory. We unveil bidirectional interactions between our sentiment index and the two out of three examined maritime markets, supporting the rejection of the efficient market hypothesis. Our study also verifies the similar effects of information demand and media-produced sentiment indexes on the corresponding market. We succeed in confirming sentiment’s predictability out-of-sample for BDI. Beyond the academic value, our findings suggest a manner of enhancing the accuracy of freight rates predictions for practitioners.

Which Way Does the Wind Blow Between SPX Futures and VIX Futures?

ABSTRACTThe negative correlation between returns and volatility is well known. However, there is no consensus on whether returns cause changes in volatility or vice versa. In this paper, we investigate the contemporaneous relation between the VIX futures and E‐mini S&P 500 futures markets with the aim of shedding new light on the relation between market returns and implied volatility. We use the E‐mini S&P 500 futures (often referred to as SPX futures) as a proxy for stock market returns and VIX futures as a proxy for expectations of implied volatility. We consistently find that stock returns cause changes in expectations of implied volatility. To estimate the coefficients of interest, we use an identification through heteroskedasticity approach which takes advantage of predictable intraday shifts in volatility in the two futures markets.

Mediating impact of integrated reporting on audit quality and market reactions in Africa: evidence from South Africa

PurposeThe purpose of this study is to investigate the mediating impact of integrated reporting on the relationship between audit quality and market reactions in Africa using South Africa as a sample.Design/methodology/approachThe study sample size consists of 119 firms listed on the Johannesburg Stock Exchange. The study was carried out for the period 2011–2019. Market reactions were proxy by share price and adjusted market returns. The authors controlled for the effects of market reactions by using other firm specifics like operating income, assets, leverage and return on assets and thereafter carried out robustness checks included under additional analysis.FindingsResults from the study showed that integrated reporting partially mediates the relationship between audit quality and market reactions. Moreover, audit quality has a positive significant impact on market reactions in the form of the share price. The results were obtained in addition to a robustness check using adjusted market returns as a proxy for market reactions.Practical implicationsRegulators and standard setters in other countries should make integrated reporting mandatory. This study not only informs the public and investors about the organization’s business performance but also reveals auditor assurances that enchase market confidence in the company.Social implicationsExploring the mediating impact of integrated reporting on the relationship between audit quality and market reactions yields valuable insights. Integrated reporting, which combines financial and non-financial information, influences how investors perceive and react to audit quality. Understanding this interplay could shed light on the broader implications for corporate transparency and accountability.Originality/valueThe authors are the first to conduct such a study in an emerging economy. Hence, the authors used integrated reporting as a new variable in the study of audit quality and market reactions. Furthermore, the authors used adjusted market returns under robustness checks to check if audit quality has an impact on market reactions.

MSCI全球指数与韩国股指波动对韩国贸易的影响

This study aims to analyse the impact of the stock market on Korea’s import and export trade, mainly through the MSCI Global and KOSPI indices as stock market proxies, and Korea’s total imports, total exports, import price indices, economic sentiment indices, and business surveys indices as proxies for import and export trade. Using a time-varying vector autoregression (TVP-VAR) model, it was found that the MSCI Global and KOSPI indices have a short-term positive effect on Korea’s total imports and total exports, but the KOSPI has a negative effect on total exports. For price indices, the MSCI Global Index has a positive effect on the import price index, while the KOSPI has a negative effect at a 1-month lag. For the export price index, the MSCI Global Index has a negative impact at 1-month lag but a positive impact at 3-month lag. For the Economic Sentiment Index, both indices have a negative impact at the 1-month lag. For the business survey index, both have a positive impact. In addition, the study analyses data from three different points in time: the US subprime crisis in 2008, the European credit crisis in 2015 and the New Crown epidemic in 2020. The results show that in all three financial events, the MSCI Global Index had a positive impact on Korea’s total exports and imports in the short term, while the KOSPI had a positive impact on total imports and a negative impact on total exports. For the import price index, the MSCI Global Index has a short-term positive impact while the KOSPI has a negative impact. For the export price index, both indices have a negative impact during financial events. For the economic sentiment index, the MSCI Global Index has a negative impact in the first lag and turns to a positive impact in the second lag, while the opposite is true for the KOSPI. Finally, in all three financial events, both indices had a short-term positive impact on the business survey index.

Earnings management and corporate governance during COVID-19: Evidence from the European capital market

The objective of this paper is to analyse the impact of COVID-19 on the earnings manipulation of firms and whether corporate governance has a mitigating effect. The methodological approach consists of two steps: in the first stage, a pooled ordinary least squares (OLS) regression model has been implemented to compute the earnings management proxies, whereas in the second stage panel data regression analysis has been adopted to test the effects of corporate governance variables on the earnings management proxies themselves. Using data from STOXX Europe 600 as a proxy for the European capital market, it is found that the level of companies’ earnings manipulation increased during the pandemic. In particular, companies have engaged in more accounting and real earnings management (REM) practices. The findings show that a larger board helps to mitigate the positive relationship between COVID-19 and earnings manipulation, whereas no mitigating effect for board independence, board diversity and chief executive officer (CEO) duality has been found. In addition, an industry analysis has been developed both for robustness purposes and in order to check which sectors have been most and least affected by the pandemic. In particular, the findings show how the most affected industries reported a higher level of earnings management, resulting in a worse reporting quality. This paper provides additional evidence on the impact of COVID-19 on earnings management using a strong multi-country level governance setting. The results of this study provide useful suggestions for business practice, investors and policymakers.

An Empirical Study on the Linkage between S&P 500 Index and CSI 300 Index under COVID-19

Studying the linkage between US and Chinese stock markets under the context of COVID-19 outbreak in 2020 can help us to prevent related financial risks, regulate corresponding monetary policies, and avoid the herd effect of investors being blindly optimistic or pessimistic. Between January 1, 2020 and November 10, 2022, using the returns of the S&P 500 index as a proxy for the US stock market and the CSI 300 index as a proxy for the Chinese stock market, the VAR-GARCH-BEKK model was used to empirically analyze the relationship between the two. According to the findings, the rise and fall of the S&P 500 index has some favorable effects on the rise and fall of the CSI 300 index. Yet, the CSI 300 index's movement is largely determined by past data, suggesting that the S&P 500's volatility, which represents the US stock market, has little effect on the Chinese stock market, which is represented by the CSI 300.

Revisit the Use of Index Returns as the Proxy of Market Return in CAPM

This study compares the performance of the capital asset pricing model (CAPM), which uses a mean-variance optimal portfolio, and the Jakarta Composite Index (JCI) as the market return proxy. The data samples are monthly stock returns of Kompas 100, LQ45, and IDX30 index from September 2012-August 2022. The expected returns of assets are calculated using the CAPM with rolling regression methodology based on each index's 2-5 years period. The mean-squared errors for each sample group are calculated to determine the CAPM performance. Although the market indexes have a sub-optimal risk and return profile according to their position on the efficient frontier diagram, this study finds that the JCI as the market proxy results in better CAPM performance than the optimal portfolio. However, the beta results from using JCI as the market proxy are also consistently higher than those using an optimal portfolio, leading to the overestimation bias of the asset risk. Since most studies in CAPM testing use the market index as the market return proxy, particularly JCI in Indonesia, this study provides new insight into the challenges of using the optimal portfolio as the market return proxy.

Does Financial Development Enhance Economic Growth? The Case of Turkic Countries

In this study, we investigate whether financial development enhances economic growth in Turkic countries, namely, Azerbaijan, Kazakhstan, Kyrgyzstan, and Türkiye from 1995 to 2017. The financial development index is obtained from the International Monetary Fund to proxy for the level of financial development. The index shows the level of development of financial institutions and financial markets in terms of depth, access, and efficiency. The annual percentage growth rate of GDP per capita based on constant local currency is taken as an indicator of economic growth. The main result of the analysis shows that there is a positive relationship between financial development and economic growth. The result is robust using random effect regression, adding inflation, and including Banking Z Score. However, the main impact can be seen in the financial institution instead of the financial market proxy. The results support the supply-leading hypothesis for the economies of four Turkic countries.

Inclusion of debt claims in asset pricing models: Evidence from the CDS Index

Asset pricing theory suggests that the correct proxy for the market portfolio should contain both the debt and equity claims of the economy, whereas prevailing empirical studies fail to include the debt claim. Motived by the discrepancy between the theoretical and empirical models and the difficulty in constructing proxies, the study uses the Credit Default Swaps (CDS) market index as a proxy for the debt market and empirically tests its explanatory power in explaining stock return variations. Employing panel regression and Fama-MacBeth regression of all publicly traded U.S. companies from 2005 to 2020, the study finds a negative relationship between CDS index returns and stock returns. On average, a one standard deviation increase in CDS index return is associated with a 0.02% decrease in daily stock returns. Results of two-stage regressions show that the estimated systematic credit risk is positively priced in stock returns with similar economic magnitude as the well-documented beta risk. These results support asset pricing theories in the inclusion of debt claim and the risk-return tradeoff, while contradicting the credit risk puzzle documented in prior studies.

The impacts of CEO ownership and origin on firm performance: evidence from an emerging economy

This study aims to determine the effects of CEO ownership and CEO origin on the performance of non-financial firms listed on the Indonesia Stock Exchange from 2010–2018. The data used in this study were taken from annual reports of firms in non-financial sectors published by the Indonesia Stock Exchange from 2010–2018. This study utilized a purposive sampling technique to obtain 1,976 observations. The research model used is an unbalanced panel data analysis with a fixed-effect model approach. The results show that CEO ownership has a significant effect on firm performance when measured using Tobin’s Q as a market proxy. However, CEO origin does not have a significant effect on Tobin’s Q.

The Financial Performance of Newly Launched Chinese Infrastructure REITs

This paper explores the financial performance of the first group of nine infrastructure real estate investment trusts (REITs) that went public in mainland China in June 2021. Under the short-term event study framework, this research compares the abnormal returns and correlations of nine Chinese REITs with three groups of competitors (i.e., 49 quasi-REITs, 54 infrastructure asset-backed securities (ABSs), and 132 Wind utility firms). Three approaches are used to evaluate the performance of REITs: Risk-return indicators (e.g., Sharpe ratios and Jensen’s alphas) and raw returns measure the preliminary results, and panel data analyses capture the relative advantages of REITs over their competitors within the infrastructure industry. REITs are small-cap firms with the largest Sharpe ratios and greater diversification potential than the ABSs. Despite beating the market, they did not start to trade with a premium until the first month after their initial public offerings (IPOs). Post-event annualized abnormal returns are more than 15% against the ABSs and close to zero against Wind utility firms after controlling for key financial variables, and three mechanisms behind the REIT IPOs (i.e., asset type, taxation, and liquidity) are verified. Therefore, REITs outperform quasi-REITs and infrastructure ABSs as well as the market proxies, and their launch brought out favorable outcomes.

Government expenditure on key sectors of the economy and stock market performance in Nigeria

Purpose — This study examines the effect of Government Expenditure (GE) on key sectors of the economy and Stock Market Performance (SMP) in Nigeria.Method — Statistics Bulletin published by the Central Bank of Nigeria (CBN) was utilized as source for time series data between 1980 and 2021. SMP is proxied with MCAP and ASI while expenditure on agriculture, defense, education, and health formed components of government expenditure. The FM-OLS and ARDL methodology were adopted to determine the GE's short and long-term impact on SMP in Nigeria. ADF unit root testing, correlation analysis, Engle and Granger co-integration analysis, and preliminary descriptive statistics testing were all carried out.Result — The outcome indicates that all through the long and short term, GE on education, defense and agriculture have significant influence of SMP in the long run via MCAP channel. GE on defense and agriculture significantly affects SMP in the short run via ASI channel. Hence, this study concludes that GE components are key determinants in explaining the effect of government spending on SMP in Nigeria. The magnitude of this effect is a function of stock market proxy used.Contribution — This study provides empirical evidence on the impact of government spending on key sectors of the economy on stock market performance in Nigeria using two proxies (market capitalization and all share index) in short run and longrun.

Stock Market Proxy Testing in Beta Calculation in the COVID-19 Pandemic Period on the Indonesia Stock Exchange

This study was conducted to assess the stock price index on the Indonesia Stock Exchange (IDX) which can be used as a proxy for the stock market in Indonesia. The indexes used to search for stock market proxies in Indonesia are JCI, IDX30, LQ45, IDX BUMN20, Jakarta Islamic Index (JII), KOMPAS100, MNC36, SRI-KEHATI, and PEFINDO25. The period in this study is from June 2018 to October 2021 obtained through bloomberg.com. Based on the results of the Paired Sample t-Test, the JCI returns before and during the Covid-19 pandemic did not show a difference in stock beta. Then, the results of the Standard Error Estimate (SEE) test show that JCI returns have the smallest deviation rate in the period when Covid-19 occurred and in the entire period. The results showed that the JCI return can be used as a proxy for the stock market in Indonesia compared to the returns of other stock indexes.

Performance of the African stock market amid COVID-19 global health crisis: empirical analysis using four events

The study employs the market model and event study approach with four events to examine the performance of the African stock market amid COVID-19 global health crisis. We use daily stock market data from 14 African countries (as a proxy for the African market) spanning September 2019 to June 2021 and COVID-19 data to estimate average abnormal returns for Africa. The results show significant positive average abnormal returns in Africa when the WHO announced COVID-19 as a global health epidemic. The events of infections and deaths generated significant negative average abnormal returns while the event of vaccination did not generate any significant average abnormal returns in the market. In as much as pandemics are unpredictable, the African market quickly recovers as depicted by COVID-19; therefore, we recommend to investors, speculators, and portfolio managers not to quickly exit the continent during pandemics.

THE IMPACT OF INTEREST RATES ON THE SOUTH AFRICAN EQUITY MARKET

This paper investigates the effects of interest rate fluctuations on the South Africa's equity market. The Johannesburg Stock Exchange (JSE) - All Share Index (ALSI) was used as a proxy for the equity market, whilst treasury bill rates were used to represent interest rates. The Vector Auto Regression (VAR) model was applied to analyze the relationship between interest rates and the equity market. The Vector Error Correction Model (VECM) augmented the analysis by assessing the short and long-run dynamic relationship between the two variables. Monthly data was collected from Thomson Reuters and the South African Reserve Bank from 2002 to 2020. The results indicate that the relationship between interest rates and the equity market was significant but negative; that is, equity or share prices fall when the interest rates rise. A fall in share prices resembles poor or negative performance of the equity market; therefore, the market capitalization and share face value of listed companies is negatively affected. The outcomes of this study may assist the central bank in understanding the relationship between interest rates and equity prices, which can assist in the implementation of monetary policy tools that control interest rates volatility and reduce negative impact on the equity market. Policymakers and authorities could use the knowledge attained from this study to understand the relationship between interest rates and the equity market because an unnecessary increase in interest rates may negatively affect the equity market, leading to slow economic growth.

How Does the Fed Make Decisions: A Machine Learning Augmented Taylor Rule

The Federal funds rate is a cornerstone of asset pricing that has a significant impact on asset valuation and portfolio performance. However, estimating it reliably can be a challenging issue given that the FOMC makes monetary policy decisions based on complex economic conditions. The authors leveraged existing literatures’ findings on factors and combined those major factor categories into the new model, which includes inflation, labor markets, financial condition, and proxy of global market, and the authors selected the optimal data series to optimize the effectiveness of detecting Fed decisions through a classification factor selection process. Also, the authors improved the regression from fixed coefficients to gradient boosting nonlinear regression approach to reflect the dynamic interconnections among all the factors and their lags through different periods. Upon conducting out-of-sample forecasting, with these selected factors and machine learning gradient boosting regression, the out-of-sample RMSE improved by 77% from traditional Taylor rule model, which offered an alternative robust solution for forecasting the Federal fund rates that can be further applied to asset pricing and investing.

Exploring time and frequency linkages of green bond with renewable energy and crypto market.

This paper examines the dynamic linkages of green bond with the energy and crypto market. The S&P green bond index (RSPGB) is used as a proxy for the green bond market; S&P global clean energy index and ISE global wind energy (RIGW) are used as proxies for the renewable energy market, and; Bitcoin and Ethereum (RETHER) are used as the proxies of the crypto market. The daily prices of these constituent series are collected using Bloomberg from October 3, 2016 to February 23, 2021. We undertake an empirical analysis through the application of three key tests, namely: dynamic conditional correlation (DCC), Diebold and Yilmaz (Int J Forecast 28(1):57-66, 2012. 10.1016/j.ijforecast.2011.02.006), Baruník and Křehlík (J Financ Econom 16(2):271-296, 2018. 10.1093/jjfinec/nby001) model. The DCC reveals no dynamic linkages of volatility from the green bond to the energy and crypto market in the short run. Referring to Diebold and Yilmaz (2012), it dictates that the green bond (RSPGB) is a net receiver while the energy market (RIGW) and cryptocurrency (RETHER) are the largest and least contributors to the transmission of the volatility. Additionally, the Baruník and Křehlík (2018) model confirmed that the magnitude of the total spillover is high in more prolonged than shorter periods, suggesting reduced diversification opportunities. Overall, the present study exemplifies the significance of the green bond market as protection against risk.

Overconfidence bias in the Indian stock market in diverse market situations: an empirical study

Market situations affect investors’ sentiments. Sudden and sharp changes in the market may make investors adjust their beliefs and change their viewpoints. To quote, such sharp changes include the stock market crash of 2008 and the COVID-19 pandemic, which significantly impacted investors' emotions. In this direction, this study attempts to find investors’ overconfidence bias in different market situations, i.e., precrash period (2006–2008), crash period (2008–2010), and post-crash period (2010–2015, 2015–2020, 2020–2021). We have obtained secondary data for this study from the BSE 100 index (as a proxy of the Indian stock market). Econometric techniques used for data analysis include Vector Auto Regression (VAR), Granger causality VAR/Block Exogeneity Wald Test, and Impulse Response Function (IRF). The study finds that the investors were overconfident during pre-crash periods, i.e., before the global market crash of 2008 and the duration between 2015 and March 2020. In postcrash periods, i.e., during 2008–2010, 2010–2015, and 2020–2021, investors were not overconfident.

The power of investors’ optimism and pessimism in oil market forecasting

By modelling dynamism in the global oil market by three essential market-centric observables (viz., Market Expansion, Market Regime, and Market Liquidity), we study forecasting potential of the future oil markets within a memory-driven interdependence setting. We combine spot prices with our derived market proxies to produce representative global market proxies. The latter are used to quantify the extent of static and dynamic persistence within the system. Our extensive empirical investigation exploits the rich features of fractionally cointegrated vector autoregression, where the rate of disequilibrium error correction within the system is modelled to be slow, approximating real life system dynamics. An advantage is that it explains why we often experience a slow response of a policy intervention. We present robust evidence of both system-wide long-memory and a long-memory in the market-centric observables. We introduce a memory of memory estimation to discern the magnitude of the relative rate of acceleration/deceleration of shocks within each observable, which reflects on the overall stability of the system. Our results show significant degree of non-linear error dissipation and high degree of informational inefficiency. Rigorous out-of-sample forecasting exercise produces robust predictions and demonstrate superiority of our approach.

Do Sectoral Indices React Differently to Lockdowns Imposed Due to Covid-19? Lessons for Wealth Generation

This research paper is an attempt to study the impact of Covid-19 on the sectoral indices using Event Study Methodology (EVM) and regression models. It tries to analyze the differences in mean returns of one composite and ten sectoral indices on India’s premier National Stock Exchange during four periods-before lockdowns, during the lockdown, during unlocking and post unlock. The analysis is based on 15346 daily observations. Imposition of Lockdown is found to have a positive impact on the daily mean return of the eleven Nifty indices under study. The mean returns of sectoral indices are compared using non-parametric tests. The mean returns across four periods are compared using Friedman’s ANOVA and are found to be significantly different over the four periods. Post Hoc Analysis using Wilcoxon signed-rank test revealed that the daily mean returns during the lockdown were more than the daily mean returns during the period before lockdown, during unlock period or post unlock period. Kruskal Wallis test was used to investigate the equality of means of eleven indices found, mean returns of indices to be equal to each other during all the four alternate periods studied separately. GARCH (1,1) model is then used to estimate returns and variance of sectoral indices A significant portion of variances in sectoral index returns was explained by the variances in market proxy Nifty 50. The study highlights the emerging relevance of the Energy, FMCG, Healthcare, IT and Pharma sector during the lockdown as the abnormal positive returns have increased in these sectors. Infrastructure, Media and realty sectors have been severely affected due to the lockdown. The robustness of estimated parameters is checked by using a dummy variable regression model and it is found that stock markets were strengthening during the period of lockdown. The results of the dummy variable regression model are in line with the results of the Event Study Methodology (EVM) and GARCH (1,1). Overall, the imposition of lockdown as a policy initiative by the Government of India helped in mitigating the effect of Covid-19 on the stock market.