What do we know about the price spillover between green bonds and Islamic stocks and stock market indices?

This paper investigates the risk transmission, linkages, and directional predictability between green bonds, Islamic stocks, and other asset classes. Using daily data from November 2008 to August 2020, we use the Standard & Poor's (S&P) Green Bond Index to represent the green bond market and the Dow Jones Islamic World Index and the S&P Global Shariah Indices to represent Islamic stocks. The other asset classes considered include the S&P 500 Stock Composite, S&P 500 Bond, and S&P 500 Energy indices. This paper uses the novel quantile cross-spectral (coherency), the windowed scalogram difference (WSD), and the cross-quantilogram (CQ) correlation approaches. The results from the quantile coherency analysis reveal a negative spillover effect from green bond price returns to Islamic stocks in the long run, which indicates that the green bond market poses a long-run systemic risk to Islamic stocks. From the WSD analysis, the results show that the integration between green bonds and Islamic stocks, the S&P 500 Stock Composite, and the S&P 500 Bond index is weaker during volatile market conditions. The CQ correlation suggests that the dependency between green bonds and other asset returns is concentrated in the lower quantiles and that this dependency is weaker at longer lags. Our results underscore the significance of green bonds in investor portfolios as a new investment asset class.     

Efficiency with costly information: a reinterpretation of evidence from managed portfolios

We investigate the informational efficiency of mutual fund performancefor the period 1965-84. Results are shown to be sensitive tothe measurement of performance chosen. We find that returnson S&P stocks, returns on non-S&P stocks, and returnson bonds are significant factors in performance assessment.Once we correct for the impact of non-S&P assets on mutualfund returns, we find that mutual funds do not earn returnsthat justify their information acquisition costs. This is consistentwith results for prior periods.     

An analysis of the importance of S&;P 500 discretionary constituent changes

The main purpose of this paper is to investigate the impact of the S&P 500 index committee’s decisions to change the constituent firms in the index on benchmark risk measures. The index is managed and changed discretionally by the index committee to make it as representative of the market condition as possible. In addition, the index constantly changes due to important corporate events such as bankruptcies, mergers and acquisitions, and spin-offs. We reconstruct market portfolios by retaining all discretionally deleted firms in a 3 and 5 year periods. We estimate betas at every deletion date in terms of reconstructed market portfolios; we found that these estimate betas are significantly different from the betas obtained from the constantly updated S&P 500 portfolio. We also found that such portfolios are less representative of the business cycle than the actual S&P 500 portfolio. Finally, we found that the portfolio returns obtained by retaining all discretionally deleted firms deviate significantly from the returns of the actual S&P 500 index over the studied period, October 1989 to December 2007.     

The S&P500 index effect reconsidered: Evidence from overnight and intraday stock price performance and volume

This study focuses on S&P500 inclusions and deletions, examining the impact of potential overnight price adjustment after the announcement of an S&P500 index change. We find evidence of a significant overnight price change that diminishes the returns available to speculators although there are still profits available from the first day after announcement until a few days after the actual event. More importantly, observing the tick-by-tick stock price performance and volume effects on the key days during the event window for the first time, we find evidence of consistent trading patterns during trading hours. A separate analysis of NASDAQ and NYSE listed stocks allows for a detailed examination of the price and volume effect at an intra-day level. We find that index funds appear to cluster their rebalancing activities near to and after the close on the event date, suggesting that they are more concerned with tracking error than profit.     

FILTER RULE TESTS OF THE ECONOMIC SIGNIFICANCE OF SERIAL DEPENDENCIES IN DAILY STOCK RETURNS

In this paper we examine the ability of filter rules to predict variation in expected daily returns for a sample of 120 Dow Jones and S&P 100 stocks from 1963 through 1989. Equally weighted portfolios of filter-rule-traded stocks consistently outperform a buy-and-hold portfolio of the same stocks before accounting for transaction costs. The difference in returns between filter rule and buy-and-hold portfolios is eliminated by one-way transaction costs of 12 basis points. The economic significance of daily stock return autocorrelations is estimated. A marginal 1 percent increase in a first-order autocorrelation increases filter rule returns by an estimated 3.84 percent.     

Prediction of stock price movement based on daily high prices

Prediction of stock close price movements has attracted a lot of research interest. Using machine learning techniques, especially statistical classifiers, for day ahead forecasting of the movement of daily close prices of a broad range of several hundreds of liquid stocks is generally not very successful. We suspect that one of the reasons for failure is the relatively high volatility of prices in the last minutes before the market closes. There have been some attempts to use less volatile daily high prices instead, but the studies concentrated only on a specific non-statistical machine learning approach on a small number of specific securities. We show that incorporating statistical classifiers for day ahead daily high price movement predictions in to some simple portfolio management techniques significantly increases their performance. Tests performed on S&P 500 stocks show that such a strategy is robust, i.e. the difference in reliability for different stocks does not vary significantly, and that such a strategy greatly outperforms the S&P 500 index and several other benchmarks while increasing the risk only by a small amount.     

Order Imbalances and Stock Price Movements on October 19 and 20, 1987

On October 19, 1987, NYSE stocks in the S&P index declined seven percentage points more than NYSE stocks not in this index. In the first hour of trading on October 20, the S&P stocks virtually recovered to the level of the non-S&P stocks. There is a strong relation between order imbalances and stock price movements, both in analyses of time series and cross-sections. Thus, in addition to the breakdown in the linkage between future prices and the spot index on these two days, there were also breakdowns in the linkage among NYSE stocks.     

Asymmetric Correlation and Volatility Dynamics among Stock, Bond, and Securitized Real Estate Markets

We apply a multivariate asymmetric generalized dynamic conditional correlation GARCH model to daily index returns of S&P500, US corporate bonds, and their real estate counterparts (REITs and CMBS) from 1999 to 2008. We document, for the first time, evidence for asymmetric volatilities and correlations in CMBS and REITs. Due to their high levels of leverage, REIT returns exhibit stronger asymmetric volatilities. Also, both REIT and stock returns show strong evidence of asymmetries in their conditional correlation, suggesting reduced hedging potential of REITs against the stock market downturn during the sample period. There is also evidence that corporate bonds and CMBS may provide diversification benefits for stocks and REITs. Furthermore, we demonstrate that default spread and stock market volatility play a significant role in driving dynamics of these conditional correlations and that there is a significant structural break in the correlations caused by the recent financial crisis.     

S&P 500 Cash Stock Price Volatilities

S&P 500 stock return volatilities are compared to the volatilities of a matched set of stocks, after controlling for cross-sectional differences in firm attributes known to affect volatility. No significant difference in volatility is observed between 1975 and 1983—before the start of trade in index futures and index options. Since then, S&P 500 stocks have been relatively more volatile. The difference is statistically, but not economically, significant. The relative increase occurs primarily in daily returns and only to a lesser extent in longer interval returns. Other factors besides the start of derivative trade could be responsible for the small increase in volatility.     

Lack of consumer confidence and stock returns

This paper investigates the link between the lack of consumer confidence and stock returns during market fluctuations. Using a Markov-switching framework, we first focus on whether the shock to consumer confidence has asymmetric effects on stock returns. We also examine whether the decreased confidence pushes the stock market into bear territory. Empirical evidence using monthly returns on Standard & Poor's S&P 500 price index suggests that market pessimism has larger impacts on stock returns during bear markets. Moreover, the lack of consumer confidence leads to a higher probability of switching to a bear market regime.     

EXCESS RETURNS OF INDEX REPLACEMENT STOCKS: EVIDENCE OF LIQUIDITY AND SUBSTITUTABILITY

Excess returns of S&P index replacement stocks are attributed to price pressures and imperfect substitutes in previous research. However, parameter estimates are biased by the use of pre-announcement returns; replacements are characterized by rising stock prices. Using a future estimation period to avoid this bias, we find excess returns do not reverse. Further, we find no relation between excess returns and the amount of stock closely held or the size of index funds. The evidence supports efficient market assumptions: the stock market is liquid and stocks are close substitutes.     

Index tracking and beta arbitrage effects in comovement

This paper develops a stylised model for S&P 500 index changes with two beta-based styles: index trackers and beta arbitrageurs who trade in both high and low beta event stocks to exploit mean reversion towards one. Arbitrageurs engage in common or contrarian trading patterns relative to index funds depending on whether historical betas are below or above one. Thus, the overall comovement effect has two distinct components. After index additions, pre-event low beta stocks drive the overall beta increases due to common demand – albeit for different reasons - from indexers and arbitrageurs. By contrast, arbitrageur shorting of high beta additions diminishes or sometimes reverses the beta increases for these stocks driven by indexers. Analogous results hold for index deletions.     

Can we forecast the implied volatility surface dynamics of equity options? Predictability and economic value tests

We examine whether the dynamics of the implied volatility surface of individual equity options contains exploitable predictability patterns. Predictability in implied volatilities is expected due to the learning behavior of agents in option markets. In particular, we explore the possibility that the dynamics of the implied volatility surface of individual stocks may be associated with movements in the volatility surface of S&P 500 index options. We present evidence of strong predictable features in the cross-section of equity options and of dynamic linkages between the volatility surfaces of equity and S&P 500 index options. Moreover, time-variation in stock option volatility surfaces is best predicted by incorporating information from the dynamics in the surface of S&P 500 options. We analyze the economic value of such dynamic patterns using strategies that trade straddle and delta-hedged portfolios, and find that before transaction costs such strategies produce abnormal risk-adjusted returns.     

Do Demand Curves for Small Stocks Slope Down?

Stocks added to the S&P 500 generally experience positive abnormal returns following the announcement. Several competing explanations exist for this reaction, but small sample sizes and other issues make it difficult to distinguish among them. We examine this subject using the small‐cap Russell 2000 index, which has several advantages over the S&P 500 in this context. Our primary finding is that stocks added to or deleted from the Russell 2000 experience significant changes in stock price and trading volume, but the effect is transitory. The results support the price pressure hypothesis.     

Overreaction of country ETFs to US market returns: Intraday vs. daily horizons and the role of synchronized trading

In this paper we study the intraday price formation process of country Exchange Traded Funds (ETFs). We identify specific parts of the US trading day during which Net Asset Values (NAVs), currency rates, premiums and discounts, and the S&P 500 index have special effects on ETF prices, and characterize a special intraday and overnight updating structure between these variables and country ETF prices. Our findings suggest a structural difference between synchronized and non-synchronized trading hours. While during synchronized trading hours ETF prices are mostly driven by their NAV returns, during non-synchronized trading hours the S&P 500 index has a dominant effect. This effect also exceeds the one that the S&P 500 index has on the underlying foreign indices and suggests an overreaction to US market returns when foreign markets are closed.     

Oil and stock market activity when prices go up and down: the case of the oil and gas industry

We examine the asymmetric effects of daily oil price changes on equity returns, market betas, oil betas, return variances, and trading volumes for the US oil and gas industry. The responses of stock returns associated with negative changes in oil prices are higher than that associated with positive changes in oil prices. Stock risk measured by market beta is influenced more due to oil price decreases than due to oil price increases. On the other hand, oil risk exposures (oil betas) and return variances are more influenced by oil price increases than oil price decreases. The results of our study indicate that oil and gas firm returns, market betas, oil betas, return variances respond asymmetrically to oil price changes. We also find that relative changes in oil prices along with firm-specific factors such as firm size, ROA, leverage, market-to-book ratio (MBR) are important in determining the effects of oil price changes on oil and gas firms’ returns, risks, and trading volumes.     

Index-futures arbitrage and the behavior of stock index futures prices

This article examines intraday transaction data for S&P500 stock index futures prices and the intraday quotes for theunderlying index. The data indicate that the futures price changesare uncorrelated and that the variability of these price changesexceeds the variability of price changes in the S&P 500index. This excess variability of the futures over the indexremains even after controlling for the nonsynchronous pricesin the index quotes, which induces auto-correlation in the indexchanges. We advance and examine empirically two hypotheses regardingthe difference between the futures price and its theoreticalvalue: that this 'mispricing' increases on average with maturity,and that it is path-dependent. Evidence supporting these hypothesesis presented.     

The market price of risk of the variance term structure

In this paper I examine the market price of risk of the variance term structure. To this end, the S&P 500 option implied variance term structure is used as a proxy for aggregate variance risk. Principal component analysis shows that time variation in the variance term structure over the 1996–2012 period can be explained mainly by two factors which capture changes in the level and slope. The market price of risk of each factor is estimated in the cross-section of stock returns. The slope of the variance term structure is the most significant factor in the cross-section of stocks returns and carries a negative risk premium. The slope factor has also some predictive ability over long horizon equity returns.     

Comovement

Building on Vijh (Rev. Financial Stud. 7 (1994)), we use additions to the S&P 500 to distinguish two views of return comovement: the traditional view, which attributes it to comovement in news about fundamental value, and an alternative view, in which frictions or sentiment delink it from fundamentals. After inclusion, a stock's beta with the S&P goes up. In bivariate regressions which control for the return of non-S&P stocks, the increase in S&P beta is even larger. These results are generally stronger in more recent data. Our findings cannot easily be explained by the fundamentals-based view and provide new evidence in support of the alternative friction- or sentiment-based view.     

A new weighting-scheme for equity indexes

This paper proposes a novel methodology for computing a cross capitalization-weighted index, coined CCWI, that characterizes the most influential stocks that drive the index. The methodology, based on the factor analysis approach combined with the Equi-correlation model of Engle and Kelly (2012), encapsulates all the main information to replicate any given large equity stock index. We build a proxy that tracks accurately the S&P 500 while reducing the cost of duplication for large equity indexes with the methodology combining the PCA approach and the DECO model. We provide an application to the S&P 500 by constructing an aggregate stock index composed of the most influential stocks. The analysis reveals that the CCWI is useful for asset and risk management. Robustness checks expand the equity index universe to MIB, TSX, CAC, DAX, FTSE, NIKKEI, HSI and DJIA, both during full- and sub-periods.