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The authors analyze the relationship between exchange rate fluctuations of a number of major currencies and its impact on US stock market returns, as proxied by the S&P 500. Many studies have explored this topic since the early 1970s with varied results and with no evidence that clearly explains the relationship between exchange rates and stock market returns. This study takes a different look at this hypothesis and investigates the pairwise relationship between various exchange rates and the United States stock market returns (S&P 500 INDEX) from January 2000 to December 2019.

The authors test the data for unit roots using Phillip-Perron method. They use Johansen cointegration model to determine whether returns on S&P 500 are integrated with S&P 500. They use the VAR/VECM analysis to test whether there are any interdependencies between exchange rates and stock market return. Finally, they use various GARCH models, including the EGARCH and TGARCH models, to determine whether there exist volatility spillovers from exchange rate fluctuations in various markets to the volatility in the US stock market.

Using GARCH modeling, the authors find volatility in Australian dollar, Canadian dollar and the euro impact market return, and the volatility of Australian dollars and euro spills over to the volatility of S&P 500. They also find that the spillover is asymmetric for Australian dollars.

One of the limitations could be that the authors use different bivariate GARCH models rather than the MV-GARCH models. For future project(s), they plan to do this analysis from the perspective of a European Union or a British investor and use returns in those markets to see the impact of exchange rates on those markets. It would be interesting to know how the relationship will change during periods of financial crises. This could be achieved by employing structural break methodology.

Many studies have explored the relation between stock market returns and exchange rates since the early 1970s with varied results and with no evidence that clearly explains the relationship between exchange rates and stock market returns. This paper contributes by adding to the existing literature on impact of exchange rate on stock returns and by providing a detailed and different empirical analysis to support the results.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

The purpose of this paper is to examine the relation between extreme return correlation and return volatility, in the context of US stock indexes, by detecting clusters of extreme returns using return and volatility thresholds based on an algorithm suggested in Laurini.

The daily returns and conditional volatilities estimated using GARCH (1, 1) serve as inputs to the two threshold algorithm that detects extreme return clusters. The analysis of the relation between correlation and volatility is then based on the extent of overlapping extreme return clusters across DJIA, S&P 500 and NASDAQ composite.

It is found that the correlation positive extreme returns within overlapping clusters significantly increases with volatility between DJIA and S&P 500. The authors did not find any significant change in the pair‐wise correlation between the positive extreme returns within overlapping clusters in each of these indexes with those of NASDAQ composite.

Prior researches examine extreme returns by using a return threshold and have found mixed results on the relation between correlation and volatility. This paper examines the relation between correlation and volatility between clusters of extreme returns and provides consistent results that are of vital interest to investors.

The purpose of this study is to examine and answer the following research questions: how does the US electronic industry perform from an intellectual capital (IC) perspective? What is the relationship between IC and company market value in the US electronic industry? This study investigated the relationship between IC and company market value in the US Standard & Poor's 500 (US S&P 500) publicly traded electronic companies from 1996 to 2005.

The Ohlson model theory was reviewed and to form the research models. Secondary data were retrieved from S&P's Compustat for quantitative analysis.

When applying multiple regression technique to the research hypotheses, there emerges a positive relationship between IC and market value of the company. Apparently, US electronic companies are knowledge intensive and utilize IC to create their market capitalization.

This is one of the first empirical researches that quantitatively examine the market value of US S&P's 500 electronic companies from IC perspective in the long‐term.

The Truncated Levy Flight (TLF) model has been successfully used to model the return distribution of stock markets in developed economies and a few developing economies such as India. Our primary purpose is to use the TLF to model the S&P 500 and the firms operating in the Ghana Stock Exchange (GSE).

We assess the predictive efficacy of the TLF model by comparing a simulation of the Standard and Poor's 500 (S&P 500) index and that of firms in the stock market in Ghana, using data from the same time period (June 2007–September 2013).

We find that the Levy models relatively accurately models the return distributions of the S&P 500 but does not accurately model the return distributions of firms in the Ghana stock market.

A major limitation is that we examined stock market data only from Ghana, while there are over 29 other African stock markets. We suggest that doctoral students and faculty can compare these stock markets either on the basis of age or the number of firms listed. For example, the oldest stock market was set up in 1883 in Egypt, while the more recent ones were set up in 2012 in the Seychelles and in Somalia.

Scholarly inquiry about the stock markets in Africa represents a rich area of research that we will encourage doctoral students and faculty to go into.

There has been little research done regarding the TLF model and African stock markets and this research has much utility and high level of originality.

Prior research on additions to the S & P 500 and the smaller MidCap 400 and SmallCap 600 indexes reach different conclusions regarding the key variables that explain the cross-section of announcement period abnormal returns. Most notable in this regard is that liquidity measures, long thought to be of importance, do not appear to explain abnormal returns of the S & P 500 when other factors are controlled for. By contrast, they do appear to matter for additions to the smaller stock indexes. To explore this difference, the purpose of this paper is to analyze the abnormal returns upon announcement that a stock will be added to the Nasdaq-100 Index in a cross-sectional manner, controlling for several possible alternative factors.

This paper analyzes abnormal returns upon announcement that a stock will be added to the Nasdaq-100 Index. The authors consider several possible sources of the positive price effects in a multivariate setting that controls simultaneously for measures of liquidity, arbitrage risk, operating performance and investor interest and awareness. The authors then analyze both trading volume and the bid-ask spreads. The authors finally examine analyst and investor interest, focussing on changes in analyst coverage.

The authors find that only liquidity variables are significant, but that factors representing feedback effects on the firm’s operations and level of managerial effort are not. The authors find that the average bid/ask spreads of stocks added to the Nasdaq-100 index are lower after the addition. The authors also find that the number of analysts following a stock increases significantly after addition, verifying increased analyst interest. Both forms of evidence are consistent with the hypothesis that the additions are associated with enhanced liquidity for the stocks.

The authors conclude that what does happen to a Nasdaq stock when it is announced that it will be added to the Nasdaq-100 Index is that more analysts are drawn to it, and its market liquidity is enhanced. The authors conclude that what does not happen is that there is no evidence of significant effects of enhanced managerial effort or operating performance associated with the inclusion. This difference is noteworthy because it suggests that a certification effect of additions to the S & P indexes associated with S & P’s selection process are unique to it and do not apply to the Nasdaq-100 Index additions based on market cap alone. The results provide indirect evidence on the existence and significance of the certification effect associated with additions to the S & P indexes.

The purpose of this paper is to investigate the interlinkages among four major stock markets in Latin America, i.e., those in Argentina, Brazil, Chile, and Mexico, as well as their associations with the US stock market, which influences financial markets globally.

Using the newly developed Hamilton filter methodology (Hamilton, 2018), the authors decompose each stock series to extract cyclical components.

Results indicate that the US S&P 500 is weakly contemporaneously correlated with stock market indices in Brazil, Mexico and Argentina, whereas it also leads the latter by three months. As such, sufficient time is available for policymakers and investors to enhance their forecasts of the latter.

Results indicate that the US S&P 500 is weakly contemporaneously correlated with stock market indices in Brazil, Mexico and Argentina, whereas it also leads the latter by three months. As such, sufficient time is available for policymakers and investors to enhance their forecasts of the latter.

This paper aims to analyze the impact of Covid-19 on the stock market volatility and uncertainty during the first and second waves.

This study has applied event study and autoregressive integrated moving average models using daily data of confirmed and death cases of Covid-19, US S&P 500, volatility index, economic policy uncertainty and S&P 500 of Bombay Stock Exchange to attain the purpose.

It is observed that, during the first wave, the confirmed cases and the fiscal measure have a significant impact, while the vaccination initiative and the abnormal hike of confirmed cases have a significant impact on the US stock returns during the second wave. It is further observed that the volatility of Indian and US stock markets spillovers during the sample period. Moreover, a perpetual correlation between the Covid-19 and the stock market variables has been noticed.

At present, the world is experiencing the third wave of Covid-19. This paper has considered the first and second waves.

It is expected that business leaders, stock market regulators and the policymakers will be highly benefitted from the research outcomes of this study.

This paper briefly highlights the drawbacks of existing policies and suggests appropriate guidelines to successfully implement the forthcoming initiatives to reduce the catastrophic impact of Covid-19 on the stock market volatility and uncertainty.