S&P 500 Index Additions and Earnings Expectations

Stock price increases associated with addition to the S&P 500 Index have been interpreted as evidence that demand curves for stocks slope downward. A key premise underlying this interpretation is that Index inclusion provides no new information about companies' future prospects. We examine this premise by analyzing analysts' earnings per share (eps) forecasts around Index inclusion and by comparing postinclusion realized earnings to preinclusion forecasts. Relative to benchmark companies, companies newly added to the Index experience significant increases in eps forecasts and significant improvements in realized earnings. These results indicate that S&P Index inclusion is not an information‐free event.     

Trade Imbalances and Inventory Effects in Long-term S&P 500 Index Options

This article investigates how trade imbalances affect prices in the S&P 500 Long‐term Equity Anticipation Securities (LEAPS) market. From 1994 to 1996, put volume was 30 times higher than call volume, and public purchases of puts vastly outnumbered sales. We find that LEAPS put quotes are revised following trade imbalances by more than can be explained by information effects, suggesting that put prices are subject to price pressure or inventory effects. The results suggest market frictions are important in the pricing of options, at least in settings in which arbitrage is particularly costly and public demand leans toward one type of order.     

Pinning in the S&P 500 futures

We show that Standard & Poor's (S&P) 500 futures are pulled toward the at-the-money strike price on days when serial options on the S&P 500 futures expire (pinning) and are pushed away from the cost-of-carry adjusted at-the-money strike price right before the expiration of options on the S&P 500 index (anti-cross-pinning). These effects are driven by the interplay of market makers' rebalancing of delta hedges due to the time decay of those hedges as well as in response to reselling (and early exercise) of in-the-money options by individual investors. The associated shift in notional futures value is at least $115 million per expiration day.     

Option pricing under stock market cycles with jump risks: evidence from the S&P 500 index

Review of Quantitative Finance and Accounting - This study incorporates the Markov switching model with return jumps to depict the behavior of stock returns. Based on the daily Standard &...     

A comprehensive long-term analysis of S&P 500 index additions and deletions

We investigate the long-term effects of S&P 500 index additions and deletions on a sample of stocks from 1962 to 2003 and find a significant long-term price increase for both added and deleted stocks, with deleted stocks outperforming added stocks. The long-term price increase for added stocks can be attributed to increases in institutional ownership, liquidity, and analyst coverage, and a decrease in the shadow cost in the long-term. However, while deletion has no significant effect on analyst coverage and shadow cost, we find a rebound in the institutional ownership and liquidity of deleted stocks. The difference in the long-term price increase of added and deleted stocks can be explained by analyst coverage and operating performance.     

An Examination of Option-Implied S&P 500 Futures Price Distributions

Expected S&P 500 futures price distributions are derived using no-arbitrage option pricing models. These distributions are parameterized both as the lognormal and as a less restrictive three-parameter Burr-XII distribution. The resulting option-based probability assessments display some evidence of miscalibration very near to expiration and far from expiration, but are accurate over intermediate time ranges. The means of the implied price distributions correspond closely to the contemporaneous futures prices for both distributions, although marginally better with the Burr-XII. The Burr-XII distribution also performs better than the lognormal based on calibration statistics, and hence, is used to recalibrate estimated distributions.     

Bounds for VIX futures given S&P 500 smiles

We derive sharp bounds for the prices of VIX futures using the full information of S&P 500 smiles. To that end, we formulate the model-free sub/superreplication of the VIX by trading in the S&P 500 and its vanilla options as well as the forward-starting log-contracts. A dual problem of minimizing/maximizing certain risk-neutral expectations is introduced and shown to yield the same value.The classical bounds for VIX futures given the smiles only use a calendar spread of log-contracts on the S&P 500. We analyze for which smiles the classical bounds are sharp and how they can be improved when they are not. In particular, we introduce a family of functionally generated portfolios which often improves the classical bounds while still being tractable; more precisely, they are determined by a single concave/convex function on the line. Numerical experiments on market data and SABR smiles show that the classical lower bound can be improved dramatically, whereas the upper bound is often close to optimal.     

Changes in cash holdings around the S&P 500 additions

We analyze the changes in cash holding policies of S&P 500 firms from before to after their inclusion in the index. One year after inclusion, their mean industry-adjusted cash holdings decline by nearly 32% from the year before inclusion. Several factors explain this decline. The precautionary motive for cash subsides due to these firms becoming more visible, less uncertain, and less constrained to raise cheap external capital. Corporate governance deteriorates after inclusion due to increased managerial entrenchment, which leads to a reduction in cash as suggested by the free cash flow hypothesis. Most index firms face diminishing investment opportunities and decreasing capital expenditures, which implies a lesser need for cash holdings related to the transaction motive.     

Analysis of DJIA,S&P 500, S&P 400, NASDAQ 100 and Russell 2000 ETFs and their influence on price discovery

This study examines the temporal behavior of price discovery in the spot, ETF and futures markets of the DJIA, S&P 500, S&P 400, NASDAQ 100 and Russell 2000. We document an increasing trend in the price discovery metrics of exchange traded funds for all indexes but the DJIA. Contrary to past studies, our findings show that the spot market rather than the futures market leads the price discovery. The arbitrage process that links exchange traded funds to spot prices, and not the futures prices might explain the results. This daily arbitrage that ensures exchange traded funds prices equal net asset values appear to promote spot market price discovery especially with the popularity of exchange traded funds in more recent years. We additionally document that the temporal behavior of the exchange traded funds price discovery metric affects differently price discovery in the spot and futures markets across indexes.     

SV mixture models with application to S&P 500 index returns

Understanding both the dynamics of volatility and the shape of the distribution of returns conditional on the volatility state is important for many financial applications. A simple single-factor stochastic volatility model appears to be sufficient to capture most of the dynamics. It is the shape of the conditional distribution that is the problem. This paper examines the idea of modeling this distribution as a discrete mixture of normals. The flexibility of this class of distributions provides a transparent look into the tails of the returns distribution. Model diagnostics suggest that the model, SV-mix, does a good job of capturing the salient features of the data. In a direct comparison against several affine-jump models, SV-mix is strongly preferred by Akaike and Schwarz information criteria.     

Decision trees unearth return sign predictability in the S&P 500

Technical trading rules and linear regression models are often used by practitioners to find trends in asset returns. However, these models typically neglect interaction terms between the lagged daily directional movements. We propose a decision tree forecasting model that has the flexibility to capture arbitrary interaction patterns. To study the importance of interaction terms, we construct a binary Markov process with a deterministic component that cannot be predicted without interaction terms between the lagged directional movements. We show that some tree based strategies achieve trading performance significant at the 99% confidence level on the S&P 500 over the past 20 years, after adjusting for multiple testing. The best strategy breaks even with the buy-and-hold strategy at 21 bps in transaction costs per round trip. A four-factor regression analysis shows significant intercept, and correlation with the market. The directional predictability is strongest during the bursts of the dotcom bubble, financial crisis, and European debt crisis. The return sign predictability during these periods confirms the necessity of interaction terms to model daily returns.     

The jump component of S&P 500 volatility and the VIX index

Much research has investigated the differences between option implied volatilities and econometric model-based forecasts. Implied volatility is a market determined forecast, in contrast to model-based forecasts that employ some degree of smoothing of past volatility to generate forecasts. Implied volatility has the potential to reflect information that a model-based forecast could not. This paper considers two issues relating to the informational content of the S&P 500 VIX implied volatility index. First, whether it subsumes information on how historical jump activity contributed to the price volatility, followed by whether the VIX reflects any incremental information pertaining to future jump activity relative to model-based forecasts. It is found that the VIX index both subsumes information relating to past jump contributions to total volatility and reflects incremental information pertaining to future jump activity. This issue has not been examined previously and expands our understanding of how option markets form their volatility forecasts.     

Returns and option activity over the option-expiration week for S&P 100 stocks

For S&P 100 stocks, we find that the weekly returns over option-expiration (OE) weeks (a month’s third-Friday week) tend to be high, relative to: (1) the third-Friday weekly returns of other stocks with less option activity, (2) the own stock’s other weekly returns, (3) the risk, based on asset-pricing alphas. For these same stocks, a month’s fourth-Friday weekly returns underperform modestly. We suggest the following two avenues are likely partial contributors towards understanding these return patterns: (1) delta-hedge rebalancing by option market makers, with a reduction in short-stock hedge positions over the OE week, and (2) declining risk perceptions over the OE week, as measured by option-derived implied volatilities. Our findings suggest option activity can induce reliable patterns in the weekly returns of option-active large-cap stocks.     

The Price Response to S&P 500 Index Additions and Deletions: Evidence of Asymmetry and a New Explanation

We study the price effects of changes to the S&P 500 index and document an asymmetric price response: There is a permanent increase in the price of added firms but no permanent decline for deleted firms. These results are at odds with extant explanations of the effects of index changes that imply a symmetric price response to additions and deletions. A possible explanation for asymmetric price effects arises from the changes in investor awareness. Results from our empirical tests support the thesis that changes in investor awareness contribute to the asymmetric price effects of S&P 500 index additions and deletions.     

Founding-Family Ownership and Firm Performance: Evidence from the S&P 500

We investigate the relation between founding‐family ownership and firm performance. We find that family ownership is both prevalent and substantial; families are present in one‐third of the S&P 500 and account for 18 percent of outstanding equity. Contrary to our conjecture, we find family firms perform better than nonfamily firms. Additional analysis reveals that the relation between family holdings and firm performance is nonlinear and that when family members serve as CEO, performance is better than with outside CEOs. Overall, our results are inconsistent with the hypothesis that minority shareholders are adversely affected by family ownership, suggesting that family ownership is an effective organizational structure.     

CONDITIONAL HETEROSKEDASTICITY AND THE WEEKEND EFFECT IN S&P 500 INDEX FUTURES

Conflicting results have been reported regarding the existence of a weekend effect in S&P 500 index futures. Given the numerous evidence in recent research that asset returns are affected by conditional heteroskedasticity and have fat-tailed distributions, this paper re-examines the existence of a weekend effect in S&P 500 index futures by using a GARCH model. The results generated by the new methodology support the conclusion of Cornell (1985) that there is no weekend effect in S&P 500 index futures.     

Non-linearities in financial bubbles: Theory and Bayesian evidence from S&P500

The modeling process of bubbles, using advanced mathematical and econometric techniques, is a young field of research. In this context, significant model misspecification could result from ignoring potential non-linearities. More precisely, the present paper attempts to detect and date non-linear bubble episodes. To do so, we use Neural Networks to capture the neglected non-linearities. Also, we provide a recursive dating procedure for bubble episodes. When using data on stock price-dividend ratio S&P500 (1871.1–2014.6), employing Bayesian techniques, the proposed approach identifies more episodes than other bubble tests in the literature, while the common episodes are, in general, found to have a longer duration, which is evidence of an early warning mechanism (EWM) that could have important policy implications.     

Accounting for decarbonisation and reducing capital at risk in the S&P500

This article accounts for carbon emissions in the S&P 500 and explores the extent to which capital is at risk from decarbonising value chains. At a global level it is proving difficult to decouple carbon emissions from GDP growth. Top-down legal and regulatory arrangements envisaged by the Kyoto Protocol are practically redundant given inconsistent political commitment to mitigating global climate change and promoting sustainability. The United Nations Environment Programme (UNEP) and European Commission (EC) are promoting the role of financial markets and financial institutions as drivers of behavioural change mobilising capital allocations to decarbonise corporate activity.     

Idiosyncratic volatility and cash flow volatility: New evidence from S&P 500

Employing firm-level data of S&P 500 constituent companies from 1990 to 2016, we offer new evidence on the strong time series and cross-sectional relationships between Idiosyncratic stock return volatility (Ivol) and cash flow volatility even after controlling for illiquidity and firm size, which also vary by period of economic condition. Our results show that Ivol is well explained by the volatility of the three components of DuPont ROE. Aggregate asset turnover volatility alone explains 81.8% of the time series variation of aggregate Ivol, and all independent variables explain 94.7% of the aggregate Ivol. While profit margin volatility and asset turnover volatility have significant relationships with Ivol during the sample period, the volatility of equity multiplier shows significance during the two recession periods in early and late 2000s.