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.     

Empirical pricing kernels

This paper investigates the empirical characteristics of investor risk aversion over equity return states by estimating a time-varying pricing kernel, which we call the empirical pricing kernel (EPK). We estimate the EPK on a monthly basis from 1991 to 1995, using S&P 500 index option data and a stochastic volatility model for the S&P 500 return process. We find that the EPK exhibits counter cyclical risk aversion over S&P 500 return states. We also find that hedging performance is significantly improved when we use hedge ratios based the EPK rather than a time-invariant pricing kernel.     

Evaluating absolute return managers

One traditional measure of investment performance, the information ratio (IR), is defined as the active return (alpha) divided by the tracking error (the standard deviation of the active return). Calculating an IR is straightforward when the benchmark for performance is a buy-and-hold standard like the S&P 500. For absolute return managers, however, the typical benchmark is zero, meaning that any excess return is classified as alpha and deemed to represent the return from active management or skill. In this paper, we argue that this standard approach confuses beta returns and alpha returns. The former can be earned by following generic strategies that are easily implemented and often replicated by ETFs, while the later are associated with more original or complex strategies that more genuinely reflect unique skills or expertise. We propose a new performance metric that strips out beta returns associated with investment-style factors. This approach leads to a new statistic, the alpha ratio, which can dramatically impact the relative performance rankings of managers and provide a clearer signal of manager skill.     

Stock price synchronicity and liquidity

We argue and provide evidence that stock price synchronicity affects stock liquidity. Under the relative synchronicity hypothesis, higher return co-movement (i.e., higher systematic volatility relative to total volatility) improves liquidity. Under the absolute synchronicity hypothesis, stocks with higher systematic volatility or beta are more liquid. Our results support both hypotheses. We find all three illiquidity measures (effective proportional bid-ask spread, price impact measure, and Amihud's illiquidity measure) are negatively related to stock return co-movement and systematic volatility. Our analysis also shows that larger industry-wide component in returns improves liquidity. We find that improvement in liquidity following additions to the S&P 500 Index is related to the stock's increase in return co-movement.     

Inferring volatility dynamics and risk premia from the S&P 500 and VIX markets

We estimate a flexible affine model using an unbalanced panel containing S&P 500 and VIX index returns and option prices and analyze the contribution of VIX options to the model’s in- and out-of-sample performance. We find that they contain valuable information on the risk-neutral conditional distributions of volatility at different time horizons, which is not spanned by the S&P 500 market. This information allows enhanced estimation of the variance risk premium. We gain new insights on the term structure of the variance risk premium, present a trading strategy exploiting these insights, and show how to improve S&P 500 return forecasts.     

Conditional risk–return relationship in a time-varying beta model

We investigate the asymmetric risk–return relationship in a time-varying beta CAPM. A state space model is established and estimated by the Adaptive Least Squares with Kalman foundations proposed by McCulloch. Using S&P 500 daily data from 1987:11–2003:12, we find a positive risk–return relationship in the up market (positive market excess returns) and a negative relationship in the down market (negative market excess returns). This supports the argument of Pettengill et al., who use a constant beta model. However, our model outperforms theirs by eliminating the unexplained returns and improving the accuracy of the estimated risk price.     

Exchange traded funds and asset return correlations

We provide novel evidence supporting the notion that arbitrageurs can contribute to return comovement via exchange trade funds (ETF) arbitrage. Using a large sample of US equity ETF holdings, we document the link between measures of ETF activity and return comovement at both the fund and the stock levels, after controlling for a host of variables and fixed effects and by exploiting the ‘discontinuity’ between stock indices. The effect is also stronger among small and illiquid stocks. An examination of ETF return autocorrelations and stock lagged beta provides evidence for price reversal, suggesting that some ETF‐driven return comovement may be excessive.     

Alternatives to the normal model of stock returns: Gaussian mixture, generalised logF and generalised hyperbolic models

Simple parametric models of the marginal distribution of stock returns are an essential building block in many areas of applied finance. Even though it is well known that the normal distribution fails to represent most of the “stylised” facts characterising return distributions, it still dominates much of the applied work in finance. Using monthly S&P 500 stock index returns (1871–2005) as well as daily returns (2001–2005), we investigate the viability of three alternative parametric families to represent both the stylised and empirical facts: the generalised hyperbolic distribution, the generalised logF distribution, and finite mixtures of Gaussians. For monthly return data, all three alternatives give reasonable fits for all sub-periods. However, the generalised hyperbolic distribution fails to describe some features of the marginal distributions in some sub-periods. The daily return data are much more symmetric and expose another problem for all three distributions: the parameters describing the behaviour of the tails also influence the scale so that simpler alternatives or restricted parameterisations are called for.      

Market co-movement between credit default swap curves and option volatility surfaces

We analyze the co-movement between the Credit Default Index (CDX) curve and the S&P 500 index's option volatility surface. We connect the reduced-form no-arbitrage model with the Nelson-Siegel (N-S) model on hazard rate implied from the CDX curve, and identify the levels, slopes, and curvatures from these two markets via the Unscented Kalman Filter (UKF). We find that the changes in the level, slope, and curvature in the CDX curve and those in the volatility surface are correlated due to the bridge of the S&P 500 index return. Finally, the co-movement between the CDX curve and S&P 500 index's volatility surface become stronger after the late 2000s global financial crisis.     

Modeling the leverage effect with copulas and realized volatility

In this paper, we propose the use of static and dynamic copulas to study the leverage effect in the S&P 500 index. Copula models can conveniently separate the leverage effect from the marginal distributions of the return and its volatility. Daily volatility is proxied by a measure of realized volatility, which is constructed from high-frequency data. We uncover a significant leverage effect in the S&P 500 index, and this leverage effect is found to be changing over time in a highly persistent manner. Moreover the dynamic copula models are shown to outperform the static counterparts.     

Does it matter who pays for bond ratings? Historical evidence

We test whether Standard and Poor's (S&P) assigns higher bond ratings after it switches from investor-pay to issuer-pay fees in 1974. Using Moody's rating for the same bond as a benchmark, we find that when S&P charges investors and Moody's charges issuers, S&P's ratings are lower than Moody's. Once S&P adopts issuer-pay, its ratings increase and no longer differ from Moody's. More importantly, S&P only assigns higher ratings for bonds that are subject to greater conflicts of interest, measured by higher expected rating fees or lower credit quality. These findings suggest that the issuer-pay model leads to higher ratings.     

The impact of deposit insurance on S&L shareholders' risk/return trade-offs

This article empirically examines how savings and loan associations' (S&Ls') stock returns respond to asset mix changes. When deposit insurance is underpriced, increases in financial leverage and the riskiness of the asset portfolio should lead to increases in expected return on common stock. In particular, changes in asset components which increase the volatility of an institution's portfolio should lead the stock market to upwardly revalue S&L equity. This hypothesis is examined using data for the July 1984–December 1989 period. Increases in commercial mortgage loans, acquisition and development loans, and investments in service corporations appear to cause higher return for shareholders of poorly capitalized, failing S&Ls. Similar increases appear to have little impact on the common stock returns of well-capitalized S&Ls.     

The comovement of option listed stocks

This study examines the changes in return comovement around the listing and delisting of stock option contracts. We show that newly option listed stocks experience an increase in comovement with a portfolio of option listed stocks and a decrease in comovement with the portfolio of non-optioned stocks. Similarly, stocks that undergo option delisting exhibit a decrease in comovement with option listed stocks and an increase in comovement with non-optioned stocks. We verify the reliability of our findings in several ways. A matched sample analysis suggests that our results are not driven by factors other than option listing and we find similar results using a calendar-time approach. Further analysis reveals that commonalities in option trading may induce the comovement in the option listed stocks. Overall, our evidence is consistent with the predictions of the category or habitat view of comovement.     

Does social network sentiment influence the relationship between the S&P 500 and gold returns?

This study explored the relationship between investor sentiment (extracted from the StockTwits social network), the S&P 500 Index and gold returns. We investigated bilateral causality between gold prices and S&P 500 prices, the power of investor sentiment and gold returns to predict S&P 500 returns, and the influence of gold returns on S&P 500 volatility. We also considered whether the influence of sentiment varies according to the user's degree of experience. We considered the sentiment of messages that mentioned the S&P 500 Index and that users posted between 2012 and 2016. Granger causality analysis, ARIMA models and GARCH models were used for predicting S&P 500 Index returns and S&P 500 volatility. We observed a causal relationship between gold price and the S&P 500 Index. Our results also suggest that sentiment and gold returns predict S&P 500 Index returns. Finally, we observed that gold returns influence S&P 500 volatility and that the sentiment of experienced users affects S&P 500 returns.     

Attention allocation and international stock return comovement: Evidence from the Bitcoin market

We employ extreme Bitcoin returns as exogenous shock events to investigate the impact of investor attention allocation on worldwide stock return comovement. We find that (1) these shock events decrease worldwide stock return comovement, (2) there is an asymmetric effect in which a crash shock event has a greater impact on return comovement than a jump shock event, and (3) the impact of these shock events on equity comovement is more pronounced in emerging markets. Our results suggest that identifying extreme Bitcoin returns will benefit portfolio construction. Our results may be of considerable interest to investors, as well as to academics interested in portfolio diversification, asset comovement, and cryptocurrencies.     

The dark side of global integration: Increasing tail dependence

We measure stock market coexceedances using the methodology of Cappiello, Gerard and Manganelli (2005, ECB Working Paper 501). This method enables us to measure comovement at each point of the return distribution. First, we construct annual coexceedance probabilities for both lower and upper tail return quantiles using daily data from 1974–2006. Next, we explain these probabilities in a panel gravity model framework. Results show that macroeconomic variables asymmetrically impact stock market comovement across the return distribution. Financial liberalization significantly increases left tail comovement, whereas trade integration significantly increases comovement across all quantiles. Decreasing exchange rate volatility results in increasing lower tail comovement. The introduction of the euro increases comovement across the entire return distribution, thereby significantly reducing the benefits of portfolio diversification within the euro area.     

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.     

Timescale-dependent stock market comovement: BRICs vs. developed markets

This paper examines the differences in the asset return comovement of the BRIC countries (Brazil, Russia, India and China), the other developed economies in their regions (Canada, Hong Kong and Australia) and the major industrialized economies (the U.K., Germany and Japan) with respect to the U.S. for different return periods. The novelty of the paper is that the stock return indices are decomposed to several timescales using wavelet analysis and that the results are further used as inputs for the dynamic conditional correlation (DCC) framework, which is used as a measure of comovement. The results propose that the level of stock market comovement depends on regional aspects, the level of development and especially on the timescale of returns. These factors should be carefully considered in designing internationally diversified portfolios. The BRICs provide some portfolio diversification benefits, but it is not justifiable to treat all BRICs as a homogeneous group of emerging economies in terms of stock market comovement.     

Unconditional return disturbances: A non-parametric simulation approach

Simulation methods are extensively used in Asset Pricing and Risk Management. The most popular of these simulation approaches, the Monte Carlo, requires model selection and parameter estimation. In addition, these approaches can be extremely computer intensive. Historical simulation has been proposed as a non-parametric alternative to Monte Carlo. This approach is limited to the historical data available.In this paper, we propose an alternative historical simulation approach. Given a historical set of data, we define a set of standardized disturbances and we generate alternative price paths by perturbing the first two moments of the original path or by reshuffling the disturbances. This approach is either totally non-parametric when constant volatility is assumed; or semi-parametric in presence of GARCH(1, 1) volatility. Without a loss in accuracy, it is shown to be much more powerful in terms of computer efficiency than the Monte Carlo approach. It is also extremely simple to implement and can be an effective tool for the valuation of financial assets.We apply this approach to simulate pay off values of options on the S&P 500 stock index for the period 1982–2003. To verify that this technique works, the common back-testing approach was used. The estimated values are insignificantly different from the actual S&P 500 options payoff values for the observed period.     

Structural holes and hedge fund return comovement: evidence from network-connected stock hedge funds in China

Using data from a new hedge fund database, we examine the impact of social networks on the return comovement of stock hedge funds in China. We use structural holes in the college alumni networks of managers to measure the managers’ social network positions. We perform an empirical analysis on a sample of 3,012 hedge fund products in China from 2010 to 2017. We find that greater structural holes are associated with higher return comovement. The positive impact of the structural holes on return comovement is not affected by market cycles, a manager's major in college, or his or her abilities.