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1 – 10 of over 31000Jocelyn Grira, Sana Guizani and Ines Kahloul
The purpose of this paper is to analyze the hedging capacity of Bitcoin in relation to the S&P 500 index during the COVID-19 pandemic.
Abstract
Purpose
The purpose of this paper is to analyze the hedging capacity of Bitcoin in relation to the S&P 500 index during the COVID-19 pandemic.
Design/methodology/approach
In order to investigate the hedging features of Bitcoin in relation to the S&P 500 index during the COVID-19 pandemic, the authors use the Granger causality applied on a daily sample of observations ranging from January 1st, 2019 to December 31st, 2020. As robustness checks, the authors use autoregressive models to test the validity of the findings.
Findings
Using time series of daily data from 1st January 2019 to 31st December 2020, the results show that Bitcoin is not considered as a safe haven because it moves at the same pace as the S&P 500. As a robustness check, the authors use the exponential GARCH model and confirm our previous findings. Overall, the study contributes to the debate on both COVID-19's impact on financial systems and the hypothesis of Bitcoin being a safe haven during extreme global crises.
Originality/value
The study contributes to the debate on both COVID-19's impact on financial systems and the hypothesis of Bitcoin being a safe haven during extreme global crises.
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Eric Belasco, Michael Finke and David Nanigian
The purpose of this paper is to explore the impact of S&P 500 index fund money flow on the valuations of companies that are constituents of the index and those that are not.
Abstract
Purpose
The purpose of this paper is to explore the impact of S&P 500 index fund money flow on the valuations of companies that are constituents of the index and those that are not.
Design/methodology/approach
To examine the impact of passive investing on corporate valuations, the authors run panel regressions of price‐to‐earnings ratio on aggregate money flow into S&P 500 index funds and control for various accounting variables that impact price‐to‐earnings ratio. These regressions involve two samples of stocks. The first sample consists of S&P 500 constituents. The second consists of large‐cap stocks that are not constituents of the S&P 500. The authors also run a set of separate regressions with price‐to‐book ratio rather than price‐to‐earnings ratio as the dependent variable.
Findings
It is found that the valuations of S&P 500 constituents increased by 139 to 167 basis points relative to nonconstituents, depending on valuation metric, due to S&P 500 index fund money flow when evaluated at mean values of money flow and valuation metrics. The valuations of firms within the S&P 500 index respond positively to changes in S&P 500 index fund money flow while the valuations of firms outside the index do not. Additionally, the impact of money flow on valuations persists the month after the flow occurs, suggesting that the impact does not dissipate over time.
Practical implications
Mispricings among individual stocks arising from index fund investing may reduce the allocative efficiency of the stock market and distort investors' performance evaluations of actively managed funds.
Originality/value
The paper is the first to explore the long‐run relationship between S&P 500 index fund money flow and corporate valuations.
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Allen Michel, Jacob Oded and Israel Shaked
The cornerstone of Modern Portfolio Theory with implications for many aspects of corporate finance is that reduced correlation among assets and reduced standard deviation are key…
Abstract
Purpose
The cornerstone of Modern Portfolio Theory with implications for many aspects of corporate finance is that reduced correlation among assets and reduced standard deviation are key elements in portfolio risk reduction. The purpose of this paper is to analyze the conditional correlation and standard deviation of a broad set of indices with the S & P 500 conditioned on market performance.
Design/methodology/approach
The authors examined volatility and correlation for a set of indices for a 19-year period based on weekly data from July 2, 1993 to June 30, 2012. These included the NASDAQ, MSCI EAFE, Russell 1000, Russell 2000, Russell 3000, Russell 1000 Growth, Russell 1000 Value, Gold, MSCI EM and Dow Jones UBS Commodity. The data for the Wilshire US REIT, Barclays Multiverse, Multiverse 1-3, Multiverse 3-5 and Multiverse 10+ became available starting July 2, 2002. For these indices the authors used weekly data from July 1, 2002 through June 30, 2012. For the iBarclays TIPS, the authors used weekly data from the time of availability, namely, for the period December 12, 2003 through June 29, 2012.
Findings
The findings demonstrate that both the conditional correlations and standard deviations vary as a function of market performance. Moreover, the authors obtain a U-shape distribution of correlations conditioned on market performance for equity indices, such as NASDAQ, as well as for the Wilshire REIT. Namely, correlations tend to be high when market returns are at low or high extremes. For more typical market performance, correlations tend to be low. A modified U-shape is found for bond indices and the Dow Jones UBS Commodity Index. Interestingly, the correlation between gold and the S & P 500 is unrelated to the return on the S & P.
Originality/value
While it has been observed that asset classes move together, this paper is the first to systematically analyze the nature of these asset class correlations.
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The purpose of this paper is to propose two hybrid forecasting models which integrate available ones. A hybrid contaminated normal distribution (CND) model accurately reflects the…
Abstract
Purpose
The purpose of this paper is to propose two hybrid forecasting models which integrate available ones. A hybrid contaminated normal distribution (CND) model accurately reflects the non‐normal features of monthly S&P 500 index returns, and a hybrid GARCH model captures a serial correlation with respect to volatility. The hybrid GARCH model potentially enables financial institutions to evaluate long‐term investment risks in the S&P 500 index more accurately than current models.
Design/methodology/approach
The probability distribution of an expected investment outcome is generated with a Monte Carlo simulation. A taller peak and fatter tails (kurtosis), which the probability distribution of monthly S&P 500 index returns contains, is produced by integrating a CND model and a bootstrapping model. The serial correlation of volatilities is simulated by applying a GARCH model.
Findings
The hybrid CND model can simulate the non‐normality of monthly S&P 500 index returns, while avoiding the influence of discrete observations. The hybrid GARCH model, by contrast, can simulate the serial correlation of S&P 500 index volatilities, while generating fatter tails. Long‐term investment risks in the S&P 500 index are affected by the serial correlation of volatilities, not the non‐normality of returns.
Research limitations/implications
The hybrid models are applied only to the S&P 500 index. Cross‐sectional correlations among different asset groups are not examined.
Originality/value
The proposed hybrid models are unique because they combine available ones with a decision tree algorithm. In addition, the paper clearly explains the strengths and weaknesses of existing forecasting models.
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Many papers have argued that there are long‐run downward‐sloping demand curves (LRDDC) for stocks. The purpose of this paper is to analyze this hypothesis using a new, unique, and…
Abstract
Purpose
Many papers have argued that there are long‐run downward‐sloping demand curves (LRDDC) for stocks. The purpose of this paper is to analyze this hypothesis using a new, unique, and ostensibly information‐free event: the re‐weighting of the Standard & Poor (S&P) 500 index from market based to free‐float based, which involves a significant shift in supply that, under the LRDDC, should result in significant and permanent price movements.
Design/methodology/approach
Event study methodology is used to examine abnormal returns and trading activity around the free‐float weight implementation dates for S&P 500 firms with various investable weight factors.
Findings
As a result of S&P 500 index re‐weighting, affected stocks experience statistically significant excess returns of −1.54 percent during the event week. This return is reversed during the following 30 days as trading volume returns to normal levels. These results are contrary to previous studies that analyze ostensibly informational events and/or different exchanges.
Research limitations/implications
Results of this study indicate that arbitrage appears to be effective in eliminating a long‐term mispricing, which challenges the validity of the LRDDC hypothesis.
Originality/value
This study contributes to the body of literature on the S&P 500 index firms by providing supporting evidence for the price‐pressure hypothesis.
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Ernest N. Biktimirov and Yuanbin Xu
The purpose of this study is to compare market reactions to the change in the demand by index funds between large and small company stocks by examining the transition of the S&P…
Abstract
Purpose
The purpose of this study is to compare market reactions to the change in the demand by index funds between large and small company stocks by examining the transition of the S&P 500, S&P 400 MidCap and S&P 600 SmallCap indexes from market capitalization to free-float weighting. This unique information-free event allows not only avoiding confounding information signaling and investor awareness effects but also comparing the effect of the decrease in demand on stocks of different sizes.
Design/methodology/approach
This study uses the event study methodology to calculate abnormal returns and trading volume around the full-float adjustment day. It also tests for significant changes in institutional ownership and liquidity. Multivariate regressions are used to examine the relation of liquidity changes and price elasticity of demand to the cumulative abnormal returns around the full-float adjustment day.
Findings
This study finds significant decreases in stock price accompanied with significant increases in trading volume on the full-float adjustment day, and significant gains in quasi-indexer institutional ownership and liquidity. The main finding is that cumulative abnormal returns around the event period are related to changes in the number of quasi-indexer and transient institutional shareholders, not to changes in liquidity or price elasticity of demand.
Originality/value
This study provides the first comprehensive comparison analysis of stock market reactions to the decline in demand between large and small company stocks. As an important implication for future studies of the index effect, changes in institutional ownership should be considered in the analysis.
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Rashiqa Kamal, Edward R. Lawrence, George McCabe and Arun J. Prakash
There is empirical evidence that a firm's addition to S&P 500 results in significant abnormal returns and an increase in a stock's liquidity. The purpose of this paper is to argue…
Abstract
Purpose
There is empirical evidence that a firm's addition to S&P 500 results in significant abnormal returns and an increase in a stock's liquidity. The purpose of this paper is to argue that changes in the information environment after the year 2000 due to the implementation of Regulation Fair Disclosure (FD), decimalization and Sarbanes Oxley Act, should result in reduced abnormal returns in the post‐2000 period.
Design/methodology/approach
The authors compare the abnormal returns and liquidity changes around the announcement day of firm's addition to S&P 500 in the pre‐ and post‐2000 periods. Univariate and multivariate tests are used to control for factors that research shows affect the abnormal returns around additions to S&P 500.
Findings
It is found that the reduction in informational asymmetry in the post‐2000 period has resulted in a significant decrease in the abnormal return on the announcement day of additions to S&P 500 index and changes in the stock's liquidity in the post announcement period are now marginal.
Originality/value
Existing literature related to changes in the abnormal returns around additions to S&P 500 does not account for changes in the information environment in the two sub periods, pre‐ and post‐2000. The results may have implications for studies related to additions to S&P 500 where the sample period spans over the two sub periods.
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The purpose of this paper is to investigate the initial public offerings (IPOs) of the firms that are eventually included in one of the S&P 400, the S&P 500, or the S&P 600…
Abstract
Purpose
The purpose of this paper is to investigate the initial public offerings (IPOs) of the firms that are eventually included in one of the S&P 400, the S&P 500, or the S&P 600 Indices. Do these firms have very different IPO features than the rest of the IPOs?
Design/methodology/approach
The control sample is formed of IPOs that are not included in the corresponding index, and the IPOs that end up in each S&P index are compared to this control sample. Logistic regressions are utilized to estimate the odds of inclusion into one of these indices.
Findings
The author finds that the IPO features, such as underpricing, offer price, underwriter's reputation, venture capital presence, and so on, are found to be substantially different for the index samples. The index firms are found to be “superstars” that deliver extremely high long‐run returns between their IPO date and their index inclusion date. The above results suggest that the quality of index firms has a persistent component to it that can be detected even during the IPO process. After estimating the determinants of the index inclusion, the author discovers that factors implying lower asymmetric information about firm's business (such as, the firm being a spinoff, or being certified by a venture capitalist or a prestigious underwriter, etc.) increase its odds of inclusion.
Originality/value
The paper proposes and tests two new hypotheses related to inclusion into an S&P index. Discoveries made in this paper can help someone recognize which IPOs could become “superstars” that end up in an S&P index.
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John M. Geppert, Stoyu I. Ivanov and Gordon V. Karels
The purpose of this paper is to examine the shocks to firm's beta around the event of addition or deletion from the S&P 500 index.
Abstract
Purpose
The purpose of this paper is to examine the shocks to firm's beta around the event of addition or deletion from the S&P 500 index.
Design/methodology/approach
The total derivative of beta and Campbell and Vuolteenaho decomposition of beta methodologies are used, on monthly and daily basis, to examine the behavior of beta around the event.
Findings
Results show a significant increase in correlations of the event firms' returns and the market proxy returns and cash‐flow betas, and decrease in discount‐rate betas for added firms and the opposite effects for deleted firms. Robustness tests indicate that the total derivative changes effects are typical for the event firms industry but that the cash‐flow correlation changes are specific to the firm. These findings suggest that addition or deletion from the S&P 500 index is not an information free event.
Research limitations/implications
The Campbell and Vuolteenaho methodology has limitations – it is conditional on the selection of state variables. In future research it would be beneficial to use different state variables in the beta decomposition framework. Another relevant question for a future research is: what are the effects of the event on the Fama‐French factor model loadings?
Originality/value
The paper's findings contribute to the ongoing debate in the literature of the information hypothesis for addition or deletion from the S&P 500 index.
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The purpose of this paper is to directly examine the information hypothesis of S&P 500 index inclusion announcements by investigating the degree to which information beyond…
Abstract
Purpose
The purpose of this paper is to directly examine the information hypothesis of S&P 500 index inclusion announcements by investigating the degree to which information beyond Standard & Poor's eight stated criteria enters the inclusion decision.
Design/methodology/approach
Isolating a sample of S&P 500 additions and their eligible candidates during 1987‐2004, this paper employs logistic analysis that identifies factors ex post beyond the stated criteria that help distinguish the type of information that influences the final selection decision and that is arguably priced at the inclusion announcements.
Findings
The evidence indicates that, when choosing among new S&P 500 candidates, the S&P's committee relies primarily on publicly available information related to enterprise risk and historical performance. Material, private insight into future value‐relevant information plays at most a small part in the selection.
Research limitations/implications
The results suggest that index additions convey limited new information about added firms. Studies analysing index additions should start with the presumption that index inclusion announcements are information‐free events, and focus on the consequences of index inclusions such as liquidity, awareness or arbitrage risk, in their relation to index premia.
Originality/value
The results indicate that the previous evidence supporting the information hypothesis using the S&P 500 inclusions is not compelling.
Details