US Equity Research Articles

Why Do Equally Weighted Portfolios Beat Value-Weighted Ones?

Equal-weighted (EW) portfolios have outperformed their value-weighted (VW) counterparts over multiple decades in various investment universes. This article investigates the long-term evidence for the EW–VW return spread in a broad US equity universe across multiple factor models. Unsurprisingly, EW investing comes with a highly significant positive size factor exposure. Given its acyclic rebalancing character, EW investing is also found to benefit from short-term reversal effects while suffering from negative momentum exposure. The authors also document a pronounced seasonality effect in EW investing that would see outsized returns in January. They revisit these findings in the more investible universe of S&P 500 stocks and discuss how to best harvest the embedded factor premiums.

Assessing the Use of Gold as a Zero-Beta Asset in Empirical Asset Pricing: Application to the US Equity Market

This paper examines the use of the return on gold instead of treasury bills in empirical asset pricing models for the US equity market. It builds upon previous research on the safe-haven, hedging, and zero-beta characteristics of gold in developed markets and the close relationship between interest rates, stock, and gold returns. In particular, we extend this research by showing that using gold as a zero-beta asset helps to improve the time-series performance of asset pricing models when pricing US equities and industries between 1981 and 2015. The performance of gold zero-beta models is also compared with traditional empirical factor models using the 1-month Treasury bill rate as the risk-free rate. Our results indicate that using gold as a zero-beta asset leads to higher R-squared values, lower Sharpe ratios of alphas, and fewer significant pricing errors in the time-series analysis. Similarly, the pricing of small stock and industry portfolios is improved. In cross-section, we also find improved results, with fewer cross-sectional pricing errors and more economically meaningful pricing of risk factors. We also find that a zero-beta gold factor constructed to be orthogonal to the Carhart four factors is significant in cross-section and helps to improve factor model performance on momentum portfolios. Furthermore, the Fama–French three- and five-factor asset pricing models and the Carhart model are all improved by these means, particularly on test assets which have been poorly priced by the traditional versions. Our results have salient implications for policymakers, governments, central bank rate-setting decisions, and investors.

Multi-kernel property in high-frequency price dynamics under Hawkes model

Abstract This study investigates and uses multi-kernel Hawkes models to describe a high-frequency mid-price process. Each kernel represents a different responsive speed of market participants. Using the conditional Hessian, we examine whether the numerical optimizer effectively finds the global maximum of the log-likelihood function under complicated modeling. Empirical studies that use stock prices in the US equity market show the existence of multi-kernels classified as ultra-high-frequency (UHF), very-high-frequency (VHF), and high-frequency (HF). We estimate the conditional expectations of arrival times and the degree of contribution to the high-frequency activities for each kernel.

COVID-19 and information flow between cryptocurrencies, and conventional financial assets

In this paper, we analyze the impact of the ongoing COVID-19 pandemic on the information flow among the main cryptocurrencies (Bitcoin, Ethereum, Ripple, and Litecoin) and those of the fear index (VIX), Gold price, and the US equity market (S&P500). We use the transfer entropy measure to determine the information flow by allowing for nonlinear dynamics and extreme tail values in the series. Our results indicate that information flow and sharing have changed during the COVID-19 pandemic with the following main findings: i) cryptocurrencies show more correlation with VIX, Gold, and the US equity markets during the COVID-19 period; ii) Gold and VIX maintain their position as safe hedging tools against the pandemic; iii) during COVID-19, S&P500 is the dominant flow transmitter to the four cryptocurrencies, and iv) Ripple plays the dominant role of information flow to VIX, Gold, and S&P500.

Portfolio Allocation Optimization with US Equities

As a result of the worldwide pandemic, many industries are in need of growth stimuli, and the US equity markets, as the main growth engine, have intrigued investor interest. This article renders a performance analysis using the weights portfolio optimization given as a focal process that is skillfully implemented by financial practitioners. Each portfolio which includes Apple, IBM, Microsoft, Home Depot, Starbucks, NIKE, P&G, QUALCOMM, and JPM, gathers weekly return data from January 2017 to December 2020 and performs a Monte Carlo simulation. The amount of portfolio alternatives will be defined by the strategies being utilized, and it will choose ten stocks from a pool of 100 stocks to form a portfolio. Asset allocation strategies with Mean-Variance and Minimum Variance were constructed using the efficient frontier. Comparing a portfolio's asset allocation performances to that of the benchmark, the S&P 500 index, and an equally weighted strategy portfolio, with respect to asset allocation, the portfolio with the highest Sharpe ratio is the most optimal. The results in this study benefit investors and industry stakeholders in the post-covid era.

Hedge and safe haven role of commodities for the US and Chinese equity markets

AbstractWe examine the hedge and safe‐haven properties of four commodity classes (precious metals, energy, agriculture and livestock) for the overall and sectoral equity markets of the US and China. In doing so, we employ two quantiles‐based approaches, quantile regression and cross‐quantilogram, using daily data from 25 September 2014 to 06 July 2020. The hedging effectiveness (HE) and time‐varying conditional diversification benefits (CDB) are estimated. Our findings indicate that precious metals and agricultural commodities are weak safe havens for all equity sectors of China and the United States. In contrast, energy and livestock commodities are weak safe havens only for the information technology and healthcare sectors. Precious metals show better HE, whereas all commodities offer strong CDB. Our findings may be helpful for sectoral investors offsetting equity losses by investing in various commodity classes.

A News-Based Model for Pricing Equity Exchange-Traded Fund Holdings

A news-based model (NBM) in which stock prices are determined by three types of news is proposed. The first type is nondiversifiable macroeconomic and geopolitical news. Their impact on prices is accounted for using the total market return in the spirit of the capital asset pricing model. The second type is the equity sector/industry news whose impact on prices is modeled with returns of the relevant industry exchange-traded funds (ETFs). Finally, the company-specific news and its momentum are described using an optimized ARMA-GARCH model. It is found that, in some equity sectors, the industry impact on stock returns may exceed the total market impact. A comparison of the accuracy of NBM and the momentum-enhanced five-factor Fama–French model for a representative list of holdings of 10 major US equity sector ETFs demonstrates superiority of the former in most examples.

The Impact of ESG Risks on the Performance of Infrastructure Mutual Funds

Prior studies find mixed evidence on the impact of environmental, social, and governance (ESG) risk ratings on mutual fund performance. These studies implicitly assume that ESG risks are equally important for all sectors. In this article, we argue that ESG risk ratings are more likely to matter for securities related to a sector with a highly visible footprint. We provide complementary evidence to the existing literature by focusing on the performance of mutual funds investing in the infrastructure sector (IMFs). Using a sample of US equity IMFs, we find that lower ESG commitment is associated with higher performance (Carhart alpha) during normal periods, whereas it is associated with lower performance during recessions or bear market periods. Interestingly, our results also show that ESG risk scores do not affect the performance of comparable mutual funds not investing in the infrastructure sector (even in bear market periods).

Dynamic factor copula models with estimated cluster assignments

This paper proposes a dynamic multi-factor copula for use in high-dimensional time series applications. A novel feature of our model is that the assignment of individual variables to groups is estimated from the data, rather than being pre-assigned using SIC industry codes, market capitalization ranks, or other ad hoc methods. We adapt the k-means clustering algorithm for use in our application and show that it has excellent finite-sample properties. Applying the new model to returns on 110 US equities, we find around 20 clusters to be optimal. In out-of-sample forecasts, we find that a model with as few as five estimated clusters significantly outperforms an otherwise identical model with 21 clusters formed using two-digit SIC codes.

Spillovers and hedging between US equity sectors and gold, oil, islamic stocks and implied volatilities

We investigate the spillovers and hedging between US equity sector returns and oil, gold, Islamic stocks, and the implied volatilities of oil (OVX) and US stock market (VIX) based on spillover indexes and portfolio hedging methods. The spillover results indicate that the 30-day forward-looking market expectations of VIX most strongly influence all 10 US equity sectors’ returns. The healthcare and information technology (real estate and utilities) sectors are the most (least) affected by VIX. The US Islamic market index is the highest spillover transmitter (receiver) to (from) US sectoral returns compared to gold, oil, and OVX. The highest transmitters to and receivers of spillover from all other sectors are the industrial, consumer discretionary, and basic materials sectors. The real estate and utilities are mainly net spillover receiver sectors. Finally, the portfolio hedging results show that gold, oil, and US Islamic stocks most effectively hedge the risk of the real estate equity sector. Gold also emerges as the most effective hedge for the financial sector.

Investment sensitivity to market uncertainty in the travel and tourism sector

Raising capital is critical for the future expansion of travel and tourism businesses which have been adversely impacted by the COVID-19 pandemic. Investors sold their travel and tourism stocks below true value due to falling earnings during the pandemic. This study compares the sensitivity of stocks in different sectors to uncertainty when they are aggregated into different exchange-traded funds (ETFs). This reduces the extent of firm-specific peculiarities arising from market overreactions to news, mergers and acquisitions through time. Although previous studies have highlighted the effect of uncertainty on the financial decisions of travel and tourism firms, this study identifies a ‘fear-triggering point’ in the VIX index above which travel and tourism ETFs enter the state of uncertainty. This study has thus important implications for raising capital and financing tourism businesses in the US equity market, particularly during heightened uncertainty.

An Analysis of Gold and US Equity

This paper investigates the relations between gold and US equity by focusing on the period for the recent five years from 2017 to 2022, which is during and after the COVID-19 crisis, and derives the following findings. First, for the five years during and after the COVID-19 crisis, gold and US equity returns were little correlated. Second, during the five years, US equity returns were higher than gold returns. Third, during the five years, US equity volatilities were clearly higher than gold volatilities.

The US Equity Valuation Premium, Globalization, and Climate Change Risks

The US Equity Valuation Premium, Globalization, and Climate Change Risks

Responses of US Equity Market Sectors to the Silicon Valley Bank Implosion

Responses of US Equity Market Sectors to the Silicon Valley Bank Implosion

An empirical study of the contrarian strategy against US equities in the Japanese market

An empirical study of the contrarian strategy against US equities in the Japanese market

Co-Trading Networks for Modeling Dynamic Interdependency Structures and Estimating High-Dimensional Covariances in US Equity Markets

Co-Trading Networks for Modeling Dynamic Interdependency Structures and Estimating High-Dimensional Covariances in US Equity Markets

Frequency spillovers between green bonds, global factors and stock market before and during COVID-19 crisis

This paper examines frequency dynamic spillovers in return and volatility and the hedging ability of Green Bonds, gold, silver, oil, the US dollar index, and volatility index against downside US stock prices before and during the COVID-19 pandemic outbreak and for the short and long run. To do so, we use the Diebold and Yilmaz (2014), the TVP-VAR model, and the frequency spillover index by Baruník and Křehlík (2018). We show that the short-term volatility spillovers dominate their long-term counterparts. Green Bond is net transmitters of spillovers in the system at the short term and net receivers at the long term. S&P500 and silver (USDX and oil) are net transmitters (receivers) of short- and long-term spillovers. Gold and VIX are net receivers of short-term spillovers and net transmitters of long-term spillovers. COVID-19 crisis has more effects on the short-term spillover, which reaches its highest level early 2020. COVID-19 and time horizons lead the direction and the magnitude of spillovers. The Quantile-on-Quantile regression analysis shows significant nonlinear relationships between markets under study. More interestingly, we show that green bonds and gold are safe haven assets for US equity investors during COVID-19. On the other hand, a mixed portfolio offers higher diversification benefits. Finally, hedging effectiveness is dependent on COVID-19 and time horizon.

A study on equity home bias using vine copula approach

The study investigates if the mean-downside risk optimization technique for asset allocation can shed new light on the equity home bias puzzle. We propose a combined EGARCH-EVT-C-vine copula approach to properly capture the stylized properties of asset return series and estimate the downside risk appropriately by CVaR. Using weekly stock price data from 12 countries including seven G7 countries and five BRICS countries, we estimate international portfolio allocations based on mean-CVaR optimization model and compare the results to the mean–variance allocations. The study has been done from the perspective of US investors. The results of the study suggest that the US equity home bias is overestimated by the mean–variance approach. The mean-CVaR model helps to factor in the additional risk that investors face in international portfolio diversification and provides a plausible empirical explanation for the equity home bias phenomenon. The findings of the study have direct implications for portfolio managers and investors for taking better international investment decisions based on the knowledge of optimum portfolio.

Bitcoin unchained: Determinants of cryptocurrency exchange liquidity

We study bitcoin to US dollar (BTCUSD) liquidity and liquidity determinants using order book data from three large cryptocurrency exchanges. The BTCUSD market is more liquid than US equity markets with bid–ask spreads often below 1 basis point. We find that BTCUSD liquidity is largely explained by same-exchange past liquidity, past cryptocurrency market-wide liquidity and volatility, and fees charged on the blockchain for bitcoin transfers. Surprisingly, we find that BTCUSD liquidity is unrelated to broader financial markets and financial market liquidity. • Cryptocurrency liquidity is unrelated to broader financial markets. • Liquidity is related to activity on the Blockchain and cryptocurrency exchange specific conditions. • Bid–ask and effective spreads on cryptocurrency exchanges are significantly narrower than in equity or bond markets, and comparable to foreign exchange markets.

ETFs and information asymmetry of underlying securities: evidence on the volume-conditioned return autocorrelation

ABSTRACT This study investigates whether exchange-traded funds (ETFs) increase the information asymmetry of underlying securities by examining the relationship between the US equity ETF ownership or turnover and the volume-conditioned daily return autocorrelation proposed by. Specifically, we find that stocks with higher ETF ownership exhibit weaker return reversals. We confirm that the ETF ownership effect is robust in a variety of settings, such as various volume measures, within industry, and various regression frameworks. We also address the difference between the volume-conditioned autocorrelation and the unconditional autocorrelation. Moreover, we document that higher ETF turnover leads to weaker return reversals, independently of the ETF ownership effect. These findings suggest that higher ETF presence allows more informed traders to engage in trades or more liquidity traders to migrate to ETFs from underlying securities, resulting in higher information asymmetry for underlying securities.