Equity Index Research Articles

Limitations in Faculty Advancement for Underrepresented Groups in Academic Otolaryngology.

Despite the increasing racial diversity of the United States, representation in academic medicine faculty does not reach concordance with the general population and worsens with higher rank. Few studies have examined this within academic Otolaryngology and surgical subspecialties. This project aims to compare rank equity in academic Otolaryngology on self-reported gender and race/ethnicity between the years 2000 and 2020. Publicly available data were obtained from the Association of American Medical Colleges under the "Data & Reports" section for the years 2000 and 2020. The report comprised of full-time faculty from all U.S. medical schools. To determine parity between faculty ranks across gender and race/ethnicity, rank equity index (REI) was calculated for associate/assistant, professor/associate, and professor/assistant professor comparisons. The percentage of women faculty in Otolaryngology has increased from 21% in 2000 to 37% in 2020; however, they did not achieve parity at all rank comparisons for both years. On the contrary, men were above parity at all rank comparisons. Improvements in rank equity occurred for Black/African American (Black) and Hispanic Latino/Spanish Origin (Latine) faculty between the years 2000 and 2020; however, when accounting for gender, benefits were concentrated among men. Advancement along the academic ladder is limited for women of all racial groups in academic Otolaryngology. While improved rank equity was seen for Black and Latine faculty, these improvements were largely among men. Future directions should aim to identify barriers to recruitment, retention, and promotion for women and underrepresented in medicine (URiM) academic otolaryngologists and create interventions that diversify Otolaryngology faculty at all ranks. NA Laryngoscope, 134:1625-1632, 2024.

Deciphering the cryptocurrency conundrum: Investigating speculative characteristics and volatility

This study employs Time-Varying Parameter Vector Autoregression (TVP-VAR) to analyze spillover effects among ten financial instruments spanning 395 weeks, encompassing significant events such as the 2016/17 cryptocurrency surge, the COVID-19 pandemic, and the Ukraine conflict. The research highlights Bitcoin's influence on equities and commodities, influenced by evolving factors, regulatory uncertainties, and market sentiment. Equity indices both transmit and absorb shocks, while commodities intensify market volatility. Overall, Bitcoin notably impacts speculative assets such as equity indices, with a moderated influence on less speculative assets, emphasizing its pivotal role in dynamic financial markets subject to changing regulations.

Assessing model risk in financial and energy markets using dynamic conditional VaRs

AbstractIt has been recognized that model risk has an important effect on any risk measurement procedures, particularly when dealing with complex markets and in the presence of a wide range of implemented models. We consider a normalized measure of model risk for the forecast of daily Value‐at‐Risk, combined with a model selection and an averaging procedure. This allows us to restrict the set of plausible models on a daily basis, making the initial choice of competing models less crucial and then yielding a more reliable assessment of model risk. Using AR‐GARCH‐type models with different distributions for the innovations, we assess the dynamics of model risk for different financial assets (a stock, an equity index, an exchange rate) and commodities (electricity, crude oil and natural gas) over 15 years.

Time-frequency return connectedness between Chinese coal futures and international stock indices

This paper explores the return connectedness between Chinese coal futures (thermal coal and coking coal) and 16 representative international equity indices from Asia, America, Australia, and Europe. We employ a time-frequency connectedness methodology to capture time-frequency features of the return connectedness between Chinese coal futures and stock indices. The empirical results suggest that return connectedness between Chinese coal futures and equity indices is time-varying and heterogeneous at different frequencies. The evidence also indicates that the short-term (high-frequency) return connectedness is stronger than long-term (low-frequency) during the sample period, implying that high-frequency return connectedness dominates total return connectedness. Meanwhile, Chinese thermal coal futures (TCF) and Chinese coking coal futures (CCT) serve as net receivers of return spillover in the coal-stock connectedness system, whether long-term or short-term. Finally, we detect that the return connectedness between Chinese coal futures and emerging equity markets exceeds developed equity markets. Summarily, the return connectedness between Chinese coal futures and the international stock indices varies depending on the development degree of the equity market, coal varieties, and time-frequency scales. These new findings offer implications for investors, policymakers, and market participants.

Practical Applications of Value for Equity Index Options: Expected—Not Realized—Volatility and the Distribution of Forecasts

Practical Applications of Value for Equity Index Options: Expected—Not Realized—Volatility and the Distribution of Forecasts

Efficient pricing and calibration of high-dimensional basket options

This paper studies equity basket options – i.e. multi-dimensional derivatives whose payoffs depend on the value of a weighted sum of the underlying stocks – and develops a new and innovative approach to ensure consistency between options on individual stocks and the index comprising them. Specifically, we show how to resolve a well-known problem that when individual constituent distributions of an equity index are inferred from the single-stock option markets and combined in a multi-dimensional local/stochastic volatility model, the resulting basket option prices will not generate a skew matching that of the options on the equity index corresponding to the basket.

Can Equity Market Risk be Diversified with the Help of ESG Investment and Commodities?

The present study examines the time–frequency relationship between conventional equity, environmental, social and governance (ESG) Index and commodities in the Indian context. The present study uses wavelet-based decomposition methodology, and wavelet coherence to examine the co-movement and coherence among these markets. In addition, wavelet analysis explored in-phase and out-phase time–frequency relationships among the variables. The findings of the study highlight the coherence between these markets in different time horizons. Our results show that the impact of the COVID pandemic persisted across the time scales in the case of ESG index, Nifty and Oil. There is strong co-movement between ESG index and Nifty, hence ESG index cannot be considered as a hedge during crisis periods. Whereas gold exhibits hedging attributes against the volatility of conventional equity. The empirical findings have several implications for understanding the hedging attributes of ESG indices and commodities against conventional equities.

Wheat as a hedge and safe haven for equity investors during the Russia–Ukraine war

This study assesses the safe haven and hedge profiles of wheat against equity markets during the Russia–Ukraine war using both DCC-GARCH and wavelet techniques. We found significant decrease in dynamic conditional correlations between wheat and the chosen indexes, suggesting that investors may reduce portfolio risks using wheat. Moreover, we demonstrate that wheat possesses weak safe-haven potential for equity indexes during the war, except for the FTSE/MIB while it provides hedging benefits for DAX30, S&P500 and FTSE100. These results are confirmed by our further analysis using wavelet coherency, which shows that wheat provides safe haven for these assets (except FTSE/MIB), especially for medium-term investors.

Assessing the Effect of the Magnitude of Spillovers on Global Supply Chains Using Quantile Vector Autoregressive and Wavelet Approaches

Overwhelmed by the negative impacts of the COVID-19 pandemic, global supply chains are being restructured and improved worldwide. It then becomes essential to accurately assess their vulnerabilities to external shocks and understand the relationships between key influential factors to obtain the desired results. This study provides a new conceptual econometric framework to examine the relationships between the purchasing managers’ index, service purchasing managers’ index, world equity index, unemployment rate, food and beverage historical prices, Baltic Dry Index, West Texas Intermediate Index, and carbon emissions. A quantile vector autoregressive (QVAR) model is used to assess the dynamic connectedness among Brazil, Russia, India, China, South Africa, and the United States based on such factors. A wavelet method is also utilized to assess the coherence between the time series. The results of the correlation and dynamic connectedness analyses for these countries reveal that the service purchasing managers’ index offers the highest spillover value toward the other factors.

An examination of green bonds as a hedge and safe haven for international equity markets

Green bonds are a type of fixed-income instrument that specifically designed to fund environmentally friendly projects. Investigating the performance of green bonds is essential to gain insights into the risk-return characteristics and dynamics within sustainable finance and their potential role in portfolio diversification. In this paper, we comprehensively examine the ability of green bonds to act as a hedge or a safe haven against nineteen international equity market movements (most of the G20 and Switzerland) over the 2014–2022 period. Using regression analysis, we find that green bonds had acted as a strong hedge for many countries but have lost such property for utmost after the COVID-19 outbreak, while they still provide safe haven benefit for many countries' equity indexes. By the use of a novel CAViaR-based TVP-VAR connectedness approach, we further examine the tail risk spillovers among green bond and international equities which extends the consideration in extreme loss (VaR) perspective. We show that the spillovers rapidly increased during the first wave of COVID-19 and has remained at relatively high level until recent days. In combination of all metrics, we argue that Saudi Arabia might be the only country that has received as good (or even better) protection from green bond in the post-pandemic era as (than) before. Overall, these should increase the attractiveness of green bonds as elements of a portfolio, enhancing the green transition.

Dynamic connectedness, spillover, and optimal hedging strategy among FinTech, Sukuk, and Islamic equity markets

The paper investigates the dynamic connectedness, spillover, and optimal hedging strategy of the FinTech, Sukuk, and Islamic equity markets. The CAViaR approach, TVP-VAR Frequency connectedness, and network connectedness approaches are used. We also apply the MVP, MCP, and MCoP approaches to construct portfolios based on the Fintech, Sukuk, and Islamic equity indices. We then compute hedge effectiveness, portfolio performance, and Sharpe ratios. We find that FinTech markets are predominantly intra-connected in the short and medium term; they are significantly interconnected in the long term. In terms of frequency decomposition, volatility transmission among the variables dominates in the short term in comparison with other examined durations. The Russian-Ukrainian War and COVID-19 pandemic both saw a considerable increase in the intensity of volatility transmission. There is higher information transmission from Islamic equity indices and less effective information transmission from Sukuk and Fintech indices. Our findings suggest that the dynamic portfolio weights for MCP and MCoP seem to be similar, but clearly differs from MVP approach. When delving into the existence of Fintech indices as a part of an international fixed-income Islamic investor's portfolio, our paper's findings – being robust to the portfolio construction method – establish that Fintech indices do have a notable role in fixed-income Islamic investment portfolios. Finally, we conclude by highlighting the fact that the benefits of diversifying a portfolio with FinTech and Islamic assets fluctuate with time and on a regular basis.

INVESTORS’ SENTIMENT AND EQUITY MARKETS DURING COVID-19 PERIOD: A QUANTILE REGRESSION APPROACH AND WAVELET ANALYSIS

The purpose of this study is to investigate the relationship between investor sentiment and leading equity market indices from the U.S., Europe, Asia, and globally between January 2020 and June 2022. The methodological approaches utilized are quantile regression and wavelet analysis. The results of quantile regression suggested that Google Search Volume (GSV) and Twitter-based Market Uncertainty Index (TMU) negatively influenced the equity indices at lower quantiles. The wavelet coherence analysis highlighted that, at lower frequency bands, GSV moves in sync with the S&P 500, NASDAQ Composite, Dow Jones Industrials, and FTSE 100 but not with the DAX, CAC 40, TOPIX, Nikkei 225, or MSCI. Nonetheless, when the TMU was used to measure investors’ sentiment, the results revealed that the whole series was out of phase.

Can diversification be improved by using cryptocurrencies? Evidence from Indian equity market

PurposeThis study aims to investigate the possibilities of cryptocurrencies as hedges and diversifiers in the Indian stock market before and during financial crisis due to the pandemic and the Russia–Ukraine war.Design/methodology/approachResearchers have used daily data on cryptocurrencies and Indian stock prices from March 10, 2015 to August 26, 2022. The researchers have used the dynamic conditional correlations (DCC)-GARCH model to determine the volatility spillover and dynamic correlation between stocks and digital currencies. Further, researchers have explored hedge ratio, portfolio weight and hedging effectiveness using the estimates of the DCC-GARCH model.FindingsThe findings indicate a negative conditional correlation between equities and cryptocurrencies before the crisis and a positive conditional correlation except for Tether during the crisis. Which implies that cryptocurrencies serve as a hedging asset in the stock market before a crisis but are not more than a diversifier during the crisis, except for Tether. Notably, Tether serves as a safe haven during times of crisis. Finally, the study suggests that Bitcoin, Ethereum, Binance Coin and Ripple are the most effective diversifiers for Indian stocks during the crisis.Originality/valueThis study makes several contributions to the existing literature. First, it compares the hedge and diversification roles of cryptocurrencies in the Indian stock market before and during crisis. Second, the study findings provide insights on risk hedging and can serve as a guide for investors. Third, it may help rational investors avoid underestimating risk while constructing portfolios, particularly in times of financial turmoil.

How do sectoral Islamic equity markets react to geopolitical risk, economic policy uncertainty, and oil price shocks?

This study explores the impact of three major risk and uncertainty indices (Geopolitical Risk (GPR), Economic Policy Uncertainty (EPU), and Oil Market Volatility (OVX)) on the Dow Jones Islamic Market (DJIM) World and the ten major sectoral Islamic equity indices. The investigation further evaluates whether the impact of these uncertainties varies between Islamic sectoral indices and the global benchmark. Our time-varying analysis shows that most Islamic equity indices are more resilient in hedging against GPR and EPU shocks compared to OVX shocks. Furthermore, the Quantile-on-Quantile results establish a positive correlation between DJIM World and most Islamic equity indices with GPR, demonstrating their robust capabilities to hedge against GPR shocks. These hedging abilities are more pronounced in the consumer goods, oil & gas, and financial sectors. The dependence structures between extreme EPU shocks and the DJIM world and consumer goods, financials, healthcare, and industrial sectors are positive only in bearish conditions, suggesting hedging benefits are predominantly limited to lower quantiles. Yet, the basic materials and oil & gas sectors can hedge EPU shocks better than the DJIM world and other sectors, depending on market states. Notably, no Islamic equity indices show resilience against OVX shocks. Our findings have prominent portfolio risk management and policy implications for investors and policymakers. These findings hold significant implications for portfolio risk management and policy strategies for investors and policymakers.

Diversity of functional edaphic macrofauna in Musa acuminata x Musa balbisiana (AAB) agroecosystems

Background: This study focused on evaluating the diversity and richness of the edaphic macrofauna in eight banana farms in the western zone of Nicaragua. Methods: The sampling design was random and descriptive, it was divided into two phases, the first was the collection of the sample, and the second was the classification, coding, and storage of the extracted macrofauna populations. Subsequently, the indices of diversity and species richness, relative abundance, by functional groups were estimated. Results: The results showed that the relative abundance of biodiversity was higher in the 0–20 cm soil depth stratum than in the branch and leaf biomass strata. The values ​​of the diversity indices of Dominion, Simpson, Shanon, Margalef, and Equity were in the normal range, with a tendency towards low diversity. Likewise, in the richness of species, the Dominant or most abundant genus were earthworms (Oligochaeta) and Hymenoptera (Solenopsis, Leptothorax, Camponotus, Pheidole), indicating the directly proportional relationship, that is to say, that the greater the number of earthworms the production increases and the greater the number of Hymenoptera it decreases, confirmed with the Pearson correlation coefficient with a reliability of 95%. Conclusions: It was concluded that based on the estimates of the diversity indicators, two detritivore genus (earthworms and Hymenoptera) were the ones with the greatest presence, being important in the production of the banana agrosystem due to the decomposition of organic matter and its nutritional contribution to the plant. We observed a direct correlation with earthworms and an indirect relationship with Hymenoptera.

Thematic Investing with Big Data: The Case of Private Equity

Using natural language processing, we score companies based on the frequency with which news articles contain both their names and terms private equity and leveraged buy-out. An index is then created and can be updated seamlessly at high frequency. The weights are set as a function of the relative exposure to this theme. We add liquidity constraints to ensure minimal transaction costs. Even though the algorithm does not optimize on either return or correlation, this listed private equity index is highly correlated to commonly used private equity fund market indices: nearly 90% correlation with Burgiss LBO fund index. In addition, our index has similar returns as non-tradable Leveraged Buy-Outs (LBO) fund indices. Our approach can be generalized to many other investment themes.

A further examination of equity indexed annuities

Equity indexed annuities (EIAs) are deferred annuities that credit interest according to a formula tied to the performance of an underlying equity index. This research expands previous research, particularly that of Reichenstein (2009, 2011), by examining the distribution of returns that could have been created on a rolling monthly basis since 1928 for 11 through 15-year investment horizons.Second, we examine investment alternatives that include the options imbedded in EIAs. Third, rather than assuming constant cap rates we allow cap rates to vary with interest rates. We find that for long time horizons the opportunity costs of investing in EIAs is high.

How smart is a momentum strategy? An empirical study of Indian equities

Smart Beta Investing has revolutionized investment management field with the ability to offer higher returns with lower costs. The momentum factor in the Smart Beta universe often outperforms other popular factors, besides being well documented in the literature, it is found to be pervasive across different geographies and asset classes. In this paper, we implement a long-only momentum based investment strategy for the Indian equity markets that delivers superior risk-adjusted performance, derived upon comparing multiple strategies across time frames. Based on these tests, we find that the lagged 6-months’ compounded returns indicator with quarterly rebalancing can be used to generate the highest risk-adjusted performance.The paper also tests a related phenomenon called the Accelerated Effect of momentum as documented by Ardila et. al. (2021) for the Indian equity market, and finds that the accelerated momentum effect underperforms the traditional momentum both on an absolute and risk-adjusted basis.

Momentum in Low Carbon and Fossil Fuel Free Equity Investing

The Conference of the Parties to the United Nations Framework Convention on Climate Change (COP27) reiterated that climate change remains a critical issue for humanity. Especially, it stressed on the need to encourage a clean energy mix, including renewable and low-emission energies, as part of the continuing transition toward a cleaner and sustainable energy. Using daily indices data covering the period 1st January 2017 to 28th February 2023, this paper studies the performance of 2 family classes among sustainability indices, namely, low carbon and fossil fuel free indices. Specifically, this study sheds further light by assessing the performance of trading strategies which are based on the momentum of low carbon and fossil-fuel free based indices. The performance is based on a thorough analysis of the Relative Strength Index (RSI) and is captured through the Sharpe and Sharpe per trade measures. We decompose the analysis into pre and post COVID-19 to provide some insights how these sustainable energy investments were impacted by the coronavirus pandemic. Findings support an adjusted overbought/oversold RSI 75(25) model resulted in less false signals than the traditional 70 (30) model. Relative to the post COVID-19 period, all selected equity indices performed poorly in the pre- COVID-19 period, with negative returns, except for the MSCI World Low Carbon Leaders and the SPDR MSCI Emerging Markets Fossil Fuel Free equity indices. Comparatively, in the post COVID-19 period, all indices witnessed superior return performance, with also increased risk levels. SPDR MSCI Emerging Markets Fossil Fuel Free index ranked first, even after adjusting for number of trades. Investments post COVID-19 early impact period performed better than a naive buy-and-hold strategy for greener investments like low carbon and fossil fuel free equity indices.

VOLATILITY SPILLOVERS BETWEEN BORSA ISTANBUL AND SELECTED COUNTRY STOCK MARKETS

Examining the international sentiment of the national stock market and the return and volatility spillovers in stock markets have been a hot topic in recent times. This study analyzes the return and volatility interaction between Borsa Istanbul (BIST) and the DJI (US), S&P500 (US), N225 (Japan) and SSE (China) equity indices. In this study, the daily returns of Borsa Istanbul (BIST), DJI, S&P500, N225 and SSE equity indices are taken into account and the interaction between return and volatility is analyzed with EGARCH and TGARCH models for the period between January 2012 and December 2022. In the study, Hafner & Herwatz variance causality test reveals volatility spillovers and causality from DJI, S&P500 and N225 indices to Borsa Istanbul at 1% significance level. According to the results obtained from EGARCH and TGARCH models, BIST is affected by the lagged returns of S&P500 and N225 indices by 0.31 and 0.16 at 1% significance level, respectively, and by the lagged returns of SSE index by 0.04 at 5% significance level. In this context, it is thought that the S&P500 index has a significant impact on the returns of Borsa Istanbul, and therefore, it is a matter that investors should take into account the lagged values of the N225 indices, especially the S&P500, when trading or investing in Borsa Istanbul.