Broad Market Index Research Articles

Hedging political risk in international portfolios

We show that internationally diversified portfolios carry sizeable political risk premia and expose investors to tail risk. We obtain political efficient frontiers with and without hedging political risk using a portfolio selection model for skewed distributions and develop a new asymptotic inference test to compare portfolio performance. Politically hedged portfolios outperform a broad market index and the equally weighted portfolio for US, Eurozone, and Japanese investors. Political risk hedging is not subsumed by currency hedging, and the diversification gains of politically hedged portfolios persist under currency hedging and transaction cost frictions. Hedging political risk induces equity home bias but does not fully explain the puzzle.

Impact of Board Members’ Social Capital on the Resilience of Public Companies to Exogenous Shocks

The objective of this study is to estimate the impact of board members’ social capital on firms’ market-based metrics of resilience to exogenous shocks. The social capital of directors was measured by their professional, political, and international connections. Firms’ resilience was evaluated based on their ability to resist and recover from the impact of shocks, as determined by stock market data. The data covers the period from 2007 to 2020 for over 200 Russian companies whose shares were included in the calculation of the Moscow Exchange Broad Market Index. During this period, three exogenous shocks occurred: the global financial crisis of 2008–2009, commodity price shock and sanctions in 2014–2015, and the COVID-19 pandemic in 2020. The system generalized method of moments is used to estimate the effect of directors’ connections on theability to mitigate shocks, while OLS with robust standard errors is used to reveal the influence of directors’ connections on firms’ ability to recover from shocks. The results indicate that professional connections moderated the negative impact on firms’ resistance to shocks and improved recovery speed during the global financial crisis. However, this type of connection reduced stock recovery speed after the COVID-19 crisis. Political and international connections have different effects on market-based metrics of firm resilience. It is possible that shocks of different nature require firms to leverage various forms of social capital from their directors in order to mitigate the negative effects of such shocks.

Implementation of deep learning models in predicting ESG index volatility

The consideration of environmental, social, and governance (ESG) aspects has become an integral part of investment decisions for individual and institutional investors. Most recently, corporate leaders recognized the core value of the ESG framework in fulfilling their environmental and social responsibility efforts. While stock market prediction is a complex and challenging task, several factors associated with developing an ESG framework further increase the complexity and volatility of ESG portfolios compared with broad market indices. To address this challenge, we propose an integrated computational framework to implement deep learning model architectures, specifically long short-term memory (LSTM), gated recurrent unit, and convolutional neural network, to predict the volatility of the ESG index in an identical environment. A comprehensive analysis was performed to identify a balanced combination of input features from fundamental data, technical indicators, and macroeconomic factors to delineate the cone of uncertainty in market volatility prediction. The performance of the constructed models was evaluated using standard assessment metrics. Rigorous hyperparameter tuning and model-selection strategies were implemented to identify the best model. Furthermore, a series of statistical analyses was conducted to validate the robustness and reliability of the model. Experimental results showed that a single-layer LSTM model with a relatively small number of neurons provides a superior fit with high prediction accuracy relative to more complex models.

Performance implications of hedging with industry ETFs

Extant research documents that hedge funds which bet on positive earnings surprises manage their sector risk by shorting industry exchange-traded funds (ETFs). We add to this literature by evaluating the performance of a hypothetical hedge fund that can anticipate positive earnings news. We construct return series for a naked strategy that only takes long stock positions and a hedged strategy that also holds short positions in industry ETFs around earnings announcements with positive content. Our main result is that hedging with industry ETFs improves fund performance based on various reward-to-risk ratios. This finding holds in various equity subsamples and both strategies tend to perform better among riskier stocks. Hedging with industry ETFs boosts fund performance compared to hedging with a broad market index.

The Multifractal Phenomenon of Stock Price Caused by “Tesla Rights Defense Event”

In this paper, we explore the periodicity of the multifractal phenomenon of stock price caused by public relations events using the multifractal detrended fluctuation analysis (MF-DFA) method. The Tesla stock closing price in the context of the Tesla rights defense event is used to obtain the generalized Hurst exponent and multifractal spectrum. We find that the stock price exhibits multifractal characteristics. Afterwards, we conduct a multifractal time-varying analysis using high-frequency data for 12 time periods before and after the Tesla rights defense event, which happened on 19 April 2021. We calculate the [Formula: see text] and [Formula: see text] before and after the rights defense event to measure the degree of multifractal of Tesla stock price. In addition, we also compute the difference between the two [Formula: see text] and two [Formula: see text], which are regarded as [Formula: see text] and [Formula: see text]. The results show that the Tesla stock market efficiency degree raised as the period time increases until the eighth period. And after the eighth period, both [Formula: see text] and [Formula: see text] tend to be stable, and the degree of market efficiency caused by the Tesla rights defense event remains almost unchanged. In addition, we use three broad market indices in the context of the Russia–Ukraine conflict to test the universality. The three broad market indices are Dow Jones Industrial Average (DJIA), Shanghai Stock Exchange Composite Index (SSEC) and Nikkei 225 ETF (N225). The results demonstrate that with the extending of time period, [Formula: see text] and [Formula: see text] gradually stabilize, indicating that public memorability will diminish and the market efficiency almost remains unchanged.

An Analysis of Volatility and Risk-Adjusted Returns of ESG Indices in Developed and Emerging Economies

The importance of Environmental, Social, and Governance (ESG) aspects in investment decisions has grown significantly in today’s volatile financial market. This study aims to answer the important question of whether investing in ESG-compliant companies is a better option for investors in both developed and emerging markets. This study assesses ESG investment performance in diverse regions, focusing on developed markets with high GDP, specifically the USA, Germany, and Japan, alongside emerging nations, India, Brazil, and China. We compare ESG indices against respective broad market indices, all comprising large and mid-cap stocks. This study employs a variety of risk-adjusted criteria to systematically compare the performance of ESG indices against broad market indices. The evaluation also delves into downside volatility, a crucial factor for portfolio growth. It also explores how news events impact ESG and market indices in developed and emerging economies using the EGARCH model. The findings show that, daily, there is no significant difference in returns between ESG and conventional indices. However, when assessing one-year rolling returns, ESG indices outperform the overall market indices in all countries except Brazil, exhibiting positive alpha and offering better risk-adjusted returns. ESG portfolios also provide more downside risk protection, with higher upside beta than downside beta in most countries (except the USA and India). Furthermore, negative news has a milder impact on the volatility of ESG indices in all of the studied countries except for Germany. This suggests that designing a portfolio based on ESG-compliant companies could be a prudent choice for investors, as it yields relatively better risk-adjusted returns compared to the respective market indices. Furthermore, there is insufficient evidence to definitively establish that the performance of ESG indices varies significantly between developed and emerging markets.

LGBT CEOs and stock returns: Diagnosing rainbow ceilings and cliffs

This study is the first to investigate the implications of lesbian, gay, bisexual, and transgender chief executive officers (LGBT CEOs) for stock performance, using an exhaustive sample of 26 LGBT publicly listed company CEOs since 2000. Firms with openly LGBT CEOs generate a statistically and economically significant monthly alpha of 0.69%− 1.08%, robust to portfolio weighting schemes, estimation frequency, multi-factor asset-pricing models, multicollinearity, sectoral allocation effects, and in subsamples in the United States and globally. The results imply that a “rainbow ceiling” exists with regards to LGBT executives, and that companies they lead are persistently undervalued due to discrimination by investors. LGBT CEOs on average represent small growth stocks with poor past performance, supporting the “rainbow cliff” hypothesis that the LGBT community is overrepresented in precarious leadership positions. Portfolios formed of stocks with LGBT CEOs robustly outperform broad market indices, evidencing attractiveness for ethical investment from both selfish and social perspectives.

Practical Applications of Catholic Values and Direct Indexing: No Performance Penance Needed

In <b><i>Catholic Values and Direct Indexing: No Performance Penance Needed</i></b>, from the Summer 2022 issue of <b><i>The Journal of Beta Investment Strategies</i></b>, authors <b>Rafika Shibly</b> (of <b>Citi Private Bank</b>) and <b>Andrew Subkoviak</b> and <b>Paul Bouchey</b> (both of <b>Parametric Portfolio Associates</b>) demonstrate that Catholic investors can own market-like portfolios that align with their values without sacrificing returns. Catholic values–based investing uses guidance from the Catholic Church to help invest in companies that promote human dignity and the common good, while divesting from companies that cause harm. Catholics can invest in existing Catholic values–based index funds or use direct indexing to create their own portfolios while deciding for themselves which companies to exclude. The authors demonstrate that two existing Catholic-values indexes have outperformed broad-market indexes like the S&amp;P 500 and have posted higher risk-adjusted returns. However, they exhibit significant tracking error relative to their benchmark indexes, meaning their returns deviate from the benchmarks year to year. The authors demonstrate that investors can improve their portfolios’ consistency with benchmarks by creating separately managed accounts (SMAs), then using direct indexing to create portfolios that mostly match benchmark indexes while screening out some companies, and then using portfolio optimization to reweight investments in ways that reduce tracking error.

Are capital markets turning efficient? Need for financial market efficiency index

Government, regulators, exchanges, banks, and institutions collaborate to develop rules and devote significant time and resources to improving the financial system, with the ultimate goal of creating a more effective market. The statistics on turnover and earnings only show the market’s Quantitative’ growth. The figures do not demonstrate how the market has improved in terms of Quality and Market Efficiency. A robust market structure and long-term growth in any market are only possible when development is based on both qualitative (market efficiency) and quantitative factors (Turnovers and Earnings). Historically, studies and research have laid great emphasis on determining the market’s level of efficiency. However, market efficiency was always checked using staggered time frames and efficiency tests. The need of the hour is a transparent and simple-to-understand tool that can continuously measure market efficiency and has universal applicability. This study proposes a tool for measuring efficiency called the Financial Market Efficiency Index — FMEI. The Index would derive its parameters from the broad market Index of any country to assess and compare market efficiency. The index would not only measure the qualitative growth (Market Efficiency) of any market, but it would also compare the market efficiency of all countries around the world. This would allow stakeholders to make the best decisions for their respective markets.

VOLATILITY SPILLOVER AND PANDEMIC – ANALYSIS OF SELECTED SECTORAL INDICES IN INDIA

The COVID-19 pandemic has impacted economies worldwide, and it has been reflected in their stock markets, as well. The effect was evident in the Indian stock markets, yet the nature and level of this impact are not very clear. This paper examines the short- and long-term spillover in the volatility between coronavirus cases on the broader market index, Nifty 50, and the indices of selected sectors: information technology, healthcare, and pharmaceuticals. Data for the period from January 2020 to July 2022 has been analyzed. The Dynamic Conditional Correlation GARCH model was used for analyzing the volatility spillover of coronavirus cases on Nifty 50, Nifty IT, Nifty Healthcare, and Nifty Pharma. The results show that there has been a significant long-term volatility spillover of infections on the broader market index, Nifty 50. However, there is no long-term persistence of COVID-19 on the sectoral indices. Only Pharma and Healthcare have exhibited significant short-term persistence. All the indices were negatively correlated with case numbers. Even though the sectoral indices did not exhibit significant long-term volatility spillover, they were positively correlated with the broader market index, Nifty 50, which in turn showed the significant long-term persistence of COVID-19. The results of the study are useful to policymakers and investors to understand the level of market impact due to the pandemic.

Sentimental Herding in Stock Market: Evidence from India

The present study examines herd behaviour in the Indian equity market using daily prices of 11 broad market indices, 12 sectoral indices, 16 strategic indices and 11 thematic indices from 1 January 2016 to 31 March 2022. For examining herd behaviour, daily returns, overnight returns, intraday spread, absolute market return and squared market return are calculated. Nifty 500 is used as a proxy index for the whole market. The regression models suggested by Christie and Huang (1995) and Chang et al. (2000) are used to calculate Cross-Sectional Standard Deviation (CSSD) and Cross-Sectional Absolute Deviation (CSAD) respectively, which measure the equity return dispersions. It is observed that herding exists in the Indian equity market when we calculate return dispersions using intraday spread. However, no herd presence is found when return dispersions are calculated through daily return, overnight return, absolute market return and squared market return. These results may be useful for investors, policy makers and regulatory bodies. Investors might design their investment strategy while making investment decision. Regulators might be able to formulate their policies to ensure market efficiency in the Indian equity market.

The impact of different sentiment in investment decisions: evidence from China’s stock markets IPOs

In this study, we used data on China’s initial public offerings (IPOs), market volatility and macro environment before and after two stock crashes during 2006–2016 to investigate how different investor sentiment affects IPO first-day flipping. The empirical results show that the expected returns of allocated investors are affected by sentiment, with allocated investors having higher psychological expectations of future returns during an optimistic bull market and their optimism discouraging first-day flipping, while higher risk-free interest rate levels and rising broad market indices also discourage first-day flipping and tend to sell in the future. The pessimistic bear market during which allocated investors have lower psychological expectations of future returns, their pessimism will promote first-day flipping, and the increase in the risk-free rate level will also promote first-day flipping, which is the opposite of the optimistic bull market, indicating that their risk aversion has increased and they tend to sell on the same day. We also found an anomaly that the greater the decline in the broad market index during a pessimistic bear market, the more inclined the allocated investors are to sell in the future when the broad market index rises in an attempt to gain higher returns. These findings help explain and understand the impact of market and macro index fluctuations on investor behavior under different investor sentiments.

The impact of influential shareholders on corporate dividend policy: evidence from Russia

PurposeThis study examines the impact of influential shareholders, namely, state and influential businessmen, on the dividend policies of firms. A special focus is made on the causal effect of exogenous changes: general and personal economic sanctions leading to toughened state policies concerning dividends.Design/methodology/approachRussian firms included into the Moscow Stock Exchange Broad Market Index were examined for a period from 2009 to 2019 using a generalized method of moments and a tobit model. The effect of personal sanctions was elucidated with the use of difference-in-differences method with multiple time periods.FindingsThe analysis showed that government or businessmen's ownership does not affect dividend payments. However, after 2014, state-owned companies began to increase their payments. At the same time, owing to a series of changes triggered by general economic sanctions, businessmen-owned companies decrease their dividends payout ratio. Personal sanctions imposed do not have long-term effect on Russian companies' dividends.Originality/valueThis study estimates the effect of ownership structure on dividend payouts after an exogenous change. The results show that there is heterogeneity in influential owners' decisions regarding dividends and changes strengthening it.

Revisiting the duration dependence in the US stock market cycles

ABSTRACT There is a big controversy among both investment professionals and academics regarding how the termination probability of a market state depends on its age. Using more than two centuries of data on the broad US stock market index, we revisit the duration dependence in bull and bear markets. Our results suggest that the duration dependence for both bull and bear markets is a nonlinear function of the state age. It appears that the duration dependence in bear markets is strictly positive. For 93% of the bull markets, the duration dependence is also positive. Only about 7% of the bull markets, those with the longest durations, do not exhibit positive duration dependence. We also compare a few selected theoretical distributions on their ability to describe the duration dependence in bull and bear markets. Our results advocate that the gamma distribution most often provides the best fit for both the survivor and hazard functions of bull and bear markets. However, our results reveal that none of the selected distributions accurately describes the right tail of the hazard functions.

Rule with an iron hand: powerful CEOs, influential shareholders and corporate performance in Russia

PurposeThis study examines whether CEO power influences the book-based and market-based performance of Russian companies when it is restricted by the presence of essential shareholders, namely, state and influential businessmen.Design/methodology/approachManagerial power is divided into structural, ownership, expert and prestige. The proposed power metrics include not only CEOs but also the board of directors' characteristics that may restrict or enhance CEO power. The empirical analysis is based on the sample of 90 large traded Russian firms, which shares are included in the Moscow Stock Exchange Broad Market Index (MICEX BMI), observed from 2012 to 2019.FindingsPanel data analysis suggests that higher board ownership and tenure may restrict CEO power, which in turn would be beneficial for corporate performance. the authors also see that in companies owned by influential businessmen, CEO power influence on M/B value is more negative, while state ownership does not moderate it. CEO power metrics, based on political experience and tenure, affect corporate performance differently in companies affiliated with extractive industries.Originality/valueFirst, the authors consider two channels through which a company in emerging markets may get additional resources: CEOs and influential owners. Second, the authors develop power metrics based on Finkelstein's managerial power classification (1992) and the idea of relative power proposed by Bebchuk et al. (2011). It allows identifying whether the board of directors' may constrain or enhance CEO power to raise corporate performance. Third, the authors analyze developing Russian markets that represent a good ground for testing the question, whereas empirical research on Russia is relatively scarce (Grosman and Leiponen, 2018). Fourth, the authors pay particular attention to the CEO power in the extractive industry, strategically important for the Russian economy.

Practical Applications of Is Tactical Allocation a Winning Strategy?

In <b><i>Is Tactical Allocation a Winning Strategy?</i></b>, from the Fall 2021 issue of <b><i>The Journal of Index Investing</i></b>, authors <b>Srinidhi Kanuri</b> (of the <b>University of Southern Mississippi</b>), <b>James Malm</b> (of the <b>College of Charleston</b>), and <b>D.K. Malhotra</b> (of <b>Thomas Jefferson University</b>) analyzed the performance of actively managed mutual funds that pursue tactical asset allocation (TAA) strategies. In such a fund, the manager frequently reallocates investments among different asset classes, based on performance predictions. The goals are to improve diversification, protect against short-term losses, and achieve positive alpha. The authors measured the performance of all tactical allocation funds from January 1994 to October 2016 and compared it to the performance of benchmarks consisting of broad-market indexes and static mixed portfolios that did not reallocate. They found that tactical allocation funds underperformed all the benchmarks and showed negative alpha—meaning that fund managers failed to predict which assets would outperform the market. While TAA funds did have some short-term risk reduction benefits, the authors nevertheless concluded that investors are better off investing in passive funds that follow indexes.

Testing the market efficiency in Indian stock market: evidence from Bombay Stock Exchange broad market indices

PurposeDespite volumes of research on the efficient market hypothesis (EMH) over the last six decades, the results are inconclusive as some studies supported the hypothesis, and some studies rejected it. The study aims to examine the market efficiency of the Indian stock market.Design/methodology/approachFor analysis, nine Bombay Stock Exchange (BSE) broad market indices were selected covering the study period from 01 January 2011 to 31 December 2020. The data collected for this study are daily open, high, low and closing prices of selected indices. The tools used in this study are: (1) unit root test to check the stationarity of time series, (2) descriptive statistics, (3) autocorrelation and (4) runs test.FindingsThe empirical findings of the study reveal that BSE broad market indices do not follow a random walk and Indian stock market is as weak-form inefficient.Research limitations/implicationsThe findings from this study provide several avenues for future research. One of the research implications is that anomalies in the statistical results by different academicians in the finance area need to be explained by future researchers.Practical implicationsInvestment companies need to understand that extraordinary skills are required to beat the market to make abnormal returns. In an inefficient market where securities do not reflect the complete available information, it is challenging for the investment brokers to convince the customers about the portfolios they recommend to the public that the rate of return would be more than expected.Social implicationsAs economic growth is related to the growth in the financial sector, developing countries like India depend on the accuracy of the information. In the presence of asymmetric information, the fluctuations in the stock market would have serious harmful consequences on the economy.Originality/valueAmid several controversies surrounding the EMH testing, this study is a modest attempt to provide evidence that the Indian stock market is in weak-form inefficient. However, it is essential to link investors' behaviour and trends observed in the financial sector to fully understand the implications of EMH.

Generalizing the Sharpe Ratio and Infinite Divisibility in Financial Markets

Investments with high Sharpe ratios tend to be fixed income investments, particularly short-term bonds. Such securities dominate income investment, but not growth investment. We generalize the Sharpe ratio to interpolate smoothly between risk-averse and risk-seeking behaviors, with the traditional Sharpe ratio as a special case. The generalized ratios may be used to optimize portfolios within a lifestyle strategy or a lifecycle strategy. We demonstrate that the Sharpe ratio has an interpretation connected to value at risk (VaR), if returns are normally distributed. We study broad market indices and indicators for US stocks, US corporate bonds, gold, and Japanese stocks. Using monthly data obtained from FRED, we show that these datasets are neither normal, nor log-normal, nor stable. We argue that none of these distributions is appropriate for market data. We argue instead for using infinitely divisible distributions, and fit Pearson distributions to the data.

A Comparative Analysis of the Nature of Stock Return Volatility in BRICS and G7 Markets

Through globalization and financial market liberalization, the opening up of markets has increased cross-border investments as investors search for higher risk-adjusted returns. This ability to invest internationally has raised the attention given to emerging markets that offer higher risk-adjusted returns relative to developed markets. However, despite the growing importance of emerging markets, the literature on the nature of volatility in global markets is typified by generalizations of findings from developed markets. To fill this gap, this study comparatively examined the nature of stock return volatility in developed G7 and emerging BRICS markets. Broad market index data and GARCH models over the period 2003:01–2020:08 were employed. The study found evidence of volatility persistence, asymmetry, mean reversion and weak evidence of a risk premium in both emerging and developed markets. There was also evidence of significant differences in the nature of volatility within the two sets of markets. These volatility patterns in both groups cast doubt on the assertion that developed markets are more informationally efficient than emerging markets. Thus, markets in the same group may not always have the same nature of volatility, especially in the wake of structural events such as the COVID-19 global pandemic.

Month-of-the-Year Effect: Empirical Evidence from Indian Stock Market

The present study aims to examine the existence of month-of-the-year effects in the Indian stock market. For analysis, we selected the BSE Ltd and NSE broad market cap indices, namely S&P BSE 500 and NIFTY 500, which are a comprehensive representation of the Indian stock market. The time selected for this study is from April 1, 2011, to March 31, 2021 (i.e., ten years). The study used secondary data collected from the 'monthly open, high, low and closing prices of broad market indices of the Indian stock market through the official websites (www.bseindia.com; and www.nseindia.com). The study's findings indicate that the ADF and PP test confirms the presence of unit root of the return series of S&P BSE 500 and NIFTY 500 Indices. The results from the KPSS test confirm the stationarity of the return series of both Indices. The regression coefficients for March were negative and significant for both indices. These results suggest that the month-the-of-the-year effect is the 'March effect.'