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.     

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 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.     

Volatility dynamics for the S&P 500: Further evidence from non-affine,multi-factor jump diffusions

We apply Markov chain Monte Carlo methods to time series data on S&P 500 index returns, and to its option prices via a term structure of VIX indices, to estimate 18 different affine and non-affine stochastic volatility models with one or two variance factors, and where jumps are allowed in both the price and the instantaneous volatility. The in-sample fit to the VIX term structure shows that the second (stochastic long-term volatility) factor is required to fit the VIX term structure. Out-of-sample tests on the fit to individual option prices, as well as in-sample tests, show that the inclusion of jumps is less important than allowing for non-affine dynamics. The estimation and testing periods together cover more than 21 years of daily data.     

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.     

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.     

Hedging the black swan: Conditional heteroskedasticity and tail dependence in S&P500 and VIX

The recent financial crisis has accentuated the fact that extreme outcomes have been overlooked and not dealt with adequately. While extreme value theories have existed for a long time, the multivariate variant is difficult to handle in the financial markets due to the prevalent heteroskedasticity embedded in most financial time series, and the complex extremal dependence that cannot be conveniently captured by a single structure. Moreover, most of the existing approaches are based on a limiting argument in which all variables become large at the same rate. In this paper, we show how the conditional approach of Heffernan and Tawn (2004) can be implemented to model extremal dependence between financial time series. We use a hedging example based on VIX futures to demonstrate the flexibility and superiority of the conditional approach against the conventional OLS regression approach.     

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.     

A multi-horizon comparison of density forecasts for the S&P 500 using index returns and option prices

We compare density forecasts of the S&P 500 index from 1991 to 2004, obtained from option prices and daily and 5-min index returns. Risk-neutral densities are given by using option prices to estimate diffusion and jump-diffusion processes which incorporate stochastic volatility. Three transformations are then used to obtain real-world densities. These densities are compared with historical densities defined by ARCH models. For horizons of two and four weeks the best forecasts are obtained from risk-transformations of the risk-neutral densities, while the historical forecasts are superior for the one-day horizon; our ranking criterion is the out-of-sample likelihood of observed index levels. Mixtures of the real-world and historical densities have higher likelihoods than both components for short forecast horizons.     

Point and Figure charting: A computational methodology and trading rule performance in the S&P 500 futures market

This paper empirically contributes to the existing trading rule literature by providing a methodology for the calculation of Point and Figure charts using ultra-high-frequency data and tests trading rules using eight objective, pre-defined trading rules on S&P 500 futures contracts traded between 1990 and 1998. To assess the robustness of reported profits, a bootstrapping adjustment was conducted to determine the forecasting power of the PF trading rules. The results producing mixed statistical significance with some rules proving significant while many others were not.     

No-arbitrage conditions for storable commodities and the modeling of futures term structures

One distinguishable feature of storable commodities is that they relate to two markets: cash market and storage market. This paper proves that, if no arbitrage exists in the storage-cash dual markets, the commodity convenience yield has to be non-negative. However, classical reduced-form models for futures term structures could allow serious arbitrages due to the high volatility of the convenience yield. To avoid negative convenience yield, this paper proposes a semi-affine arbitrage-free model, which prices futures analytically and fits futures term structures reasonably well. Importantly, our model prices commodity-related contingent claims (such as calendar spread options) quite differently with classical models.     

Trend-following trading strategies in commodity futures: A re-examination

This paper examines the performance of trend-following trading strategies in commodity futures markets using a monthly dataset spanning 48 years and 28 markets. We find that all parameterizations of the dual moving average crossover and channel strategies that we implement yield positive mean excess returns net of transactions costs in at least 22 of the 28 markets. When we pool our results across markets, we show that all of the trading rules earn hugely significant positive returns that prevail over most subperiods of the data as well. These results are robust with respect to the set of commodities the trading rules are implemented with, distributional assumptions, data-mining adjustments and transactions costs, and help resolve divergent evidence in the extant literature regarding the performance of momentum and pure trend-following strategies that is otherwise difficult to explain.     

Volatilities implied by price changes in the S&P 500 options and futures contracts

We develop a new volatility measure: the volatility implied by price changes in option contracts and their underlying. We refer to this as price-change implied volatility. We compare moneyness and maturity effects of price-change and implied volatilities, and their performance in delta hedging. We find that delta hedges based on a price-change implied volatility surface outperform hedges based on the traditional implied volatility surface when applied to S&P 500 future options.     

DYNAMIC HEDGE FUND STYLE ANALYSIS WITH ERRORS‐IN‐VARIABLES

We revisit the traditional return‐based style analysis in the presence of time‐varying exposures and errors‐in‐variables (EIV). We apply a benchmark selection algorithm using the Kalman filter and compute the estimated EIV of the selected benchmarks. We adjust them by subtracting their EIV from the initial return series to obtain an estimate of the true uncontaminated benchmarks. Finally, we run the Kalman filter on these adjusted regressors. Analyzing EDHEC alternative index styles, we show that this technique improves the factor loadings and allows more precise identification of the return sources of the considered hedge fund strategy.     

Market uncertainty,expected volatility and the mispricing of S&P 500 index futures

An association between increased index futures mispricing and concurrent index volatility has been reported within several prior studies; in the present study, we argue that expected volatility over an arbitrage horizon also has an adverse effect on the ability and willingness of traders to engage in arbitrage, leading to greater and more persistent futures mispricing. Using the CBOE VIX and its innovation on the concurrent spot volatility as proxies for expected volatility, we present evidence of an increase in S&P 500 index futures mispricing with expected volatility. The impact of the VIX grows exponentially across the distribution of conditional mispricing levels, which suggests that the expectations of heightened future volatility become increasingly detrimental to arbitrage activities when the futures price deviations are enlarged; however, the influence of expected volatility is found to have been reduced during the global financial crisis period, a period during which concurrent volatility overwhelmingly dominated the magnitude of mispricing.     

Trading behavior in S&P 500 index futures

This article examines the determinants of trading decisions and the performance of trader types, in the context of the E-Mini S&;P 500 futures and S&;P 500 futures markets. Speculators and small traders tend to follow positive feedback strategies while hedgers dynamically adjust positions in response to market returns. Such strategies apparently reverse during the 2008–09 financial crisis. Investor sentiment and market volatility play an important role in determining the net trading position of traders across the sample period. While all trader types are better at foreseeing market upturns, an out-of-sample test suggests that speculators and small traders have some predictive ability for short-term market returns.     

Empirical performance of multifactor term structure models for pricing and hedging Eurodollar futures options

This article compares two one-factor, two two-factor, two three-factor models in the HJM class and Black's [Black, F. (1976). The pricing of commodity contracts. Journal of Financial Economics, 3, 167-179.] implied volatility function in terms of their pricing and hedging performance for Eurodollar futures options across strikes and maturities from 1 Jan 2000 to 31 Dec 2002. We find that three-factor models perform the best for 1-day and 1-week prediction, as well as for 5-day and 20-day hedging. The moneyness bias and the maturity bias appear for all models, but the three-factor models produce lower bias. Three-factor models also outperform other models in hedging, in particular for away-from-the-money and long-dated options. Making Black's volatility a square root or exponential function performs similar to one-factor HJM models in pricing, but not in hedging. Correctly specified and calibrated multifactor models are thus important and cannot be replaced by one-factor models in pricing or hedging interest rate contingent claims.     

Liquidity commonality in commodities

We examine liquidity commonality in commodity futures markets. Using data from 16 agricultural, energy, industrial metal, precious metal, and livestock commodities, we show there is a strong systematic liquidity factor in commodities. Liquidity commonality was present in 1997–2003 when commodity prices were relatively stable and during the recent boom. There is some support for both “supply-side” and “demand-side” explanations for this commonality. We find no evidence of a consistent link between stock and commodity liquidity in general. Energy commodities appear to provide a better hedge against equity market liquidity risk than the other commodity families.     

Corporate taxes,strategic default,and the cost of debt

The current US tax code’s loss carry provisions provide implicit tax subsidies to financially troubled firms. Since shareholders ultimately decide when to announce bankruptcy, such tax subsidies can incentivize them to strategically postpone default. Therefore, corporate taxation can influence corporate cost of debt. Using a large panel of corporate bonds, we find supporting evidence: credit spreads become smaller as tax loss carries grow larger. In contrast, tax shields such as depreciation, which limit loss carry gains, lead to wider spreads. Interestingly, when stockholders hold greater bargaining power – due to large managerial ownership – larger corporate tax shields lead to even narrower credit spreads.     

Overconfident individual day traders: Evidence from the Taiwan futures market

A specific day-trading policy in Taiwan futures market allows an investigation of the performance of day traders. Since October 2007, investors who characterize themselves as “day traders” by closing their day-trade positions on the same day enjoy a 50% reduction in the initial margin. Because we can identify day traders ex ante, we have a laboratory to explore trading behavior without the contamination of potential behavioral biases. Our results show that the 3470 individual day traders in the sample incur on average a significant loss of 61,500 (26,700) New Taiwan dollars after (before) transaction costs over October 2007–September 2008. This implies that day traders are not only overconfident about the accuracy of their information but also biased in their interpretations of information. We also find that excessive trading is hazardous only to the overconfident losers, but not to the winners. Last, we provide evidence that more experienced individual investors exhibit more aggressive day trading behavior, although they do not learn their types or gain superior trading skills that could mitigate their losses.