Do commodities make effective hedges for equity investors?

The purpose of this paper is to evaluate whether commodities are effective hedges for equity holders. We employ three different methodologies to calculate time varying hedge ratios. First, we examine time-varying hedge ratios and how much portfolio risk can be reduced relative to a long position in the S&P 500. We calculate hedge ratios from realized variances and covariances; second, we estimate a recursive multivariate GARCH (BEKK) model and calculate the hedge ratios from the estimated covariances; and thirdly, we calculate the hedge ratios by estimating recursive OLS regressions. The results of our paper are very clear. First, commodities are not effective hedges for the S&P 500. Equity market investors and asset managers looking for a way to manage and reduce portfolio risk will be well advised to search for alternative hedges for the S&P 500 than commodities. Second, our results do not support the claim that commodities were a good hedge for the equity market during the financial crisis.     

Sovereign rating actions and the implied volatility of stock index options

This paper examines the interaction between the equity index option market and sovereign credit ratings. S&P and Moody's signals exhibit strong impact on option-implied volatility while Fitch's influence is less significant. Moody's downgrades reduce the market uncertainty over the rated countries' equity markets. Strong causal relationships are found between movements in the option-implied volatility and all credit signals released by S&P and Fitch, but only actual rating changes by Moody's, implying differences in rating agencies' policies. The presence of additional ratings tends to reduce market uncertainty. The findings highlight the importance of rating information in the price discovery process and offer policy implications.     

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.     

Speculative bubbles in the S&P 500: Was the tech bubble confined to the tech sector?

This study tests for the presence of periodically, partially collapsing speculative bubbles in the sector indices of the S&P 500 using a regime-switching approach. We also employ an augmented model that includes trading volume as a technical indicator to improve the ability of the model to time bubble collapses and to better capture the temporal variations in returns. We find that well over half of the S&P 500 index by market capitalization and seven of its ten sector component indices exhibited at least some bubble-like behavior over our sample period. Thus the speculative bubble that grew in the 1990s and subsequently collapsed was surprisingly pervasive in the US equity market and it affected numerous sectors including financials and general industrials, rather than being confined to information technology, telecommunications and the media. In addition, we develop a joint model for cross-sectional contagion of bubbles across the sectors and we examine whether there is evidence for bubble spillovers.     

Correlation dynamics in equity markets: evidence from India

This study is aimed at understanding the correlation dynamics of the equity markets from a developing country perspective using daily data from July 1997 to August 2006. A simple unconditional correlation estimate and dynamic time varying correlation estimate from a DCC-MVGARCH of Engle and Sheppard (2001) are derived for S&P CNX Nifty and other 10 world indices that includes four developed and six Asian country indices. The results show low correlation across S&P CNX Nifty with both Asian and developed nations. In addition a Logistic Smooth Transition Regression (LSTR) model is implemented and finds that the S&P CNX Nifty index is moving towards a better integration with other world markets but not at a very noteworthy phase. The low correlation provides space for the global funds to diversify risk in Indian markets.     

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.     

International order flows: Explaining equity and exchange rate returns

Macroeconomic models of equity and exchange rate returns perform poorly at high frequencies. The proportion of daily returns that these models explain is essentially zero. Instead of relying on macroeconomic determinants, we model equity price and exchange rate behavior based on a concept from microstructure–order flow. The international order flows are derived from belief changes of different investor groups in a two-country setting. We obtain a structural relationship between equity returns, exchange rate returns and their relationship to home and foreign equity market order flow. To test the model we construct daily aggregate order flow data from 800 million equity trades in the U.S. and France from 1999 to 2003. Almost 60% of the daily returns in the S&P100 index are explained jointly by exchange rate returns and aggregate order flows in both markets. As predicted by the model, daily exchange rate returns and order flow into the French market have significant incremental explanatory power for the daily S&P returns. The model implications are also validated for intraday returns.     

Spillover effects of the 2008 global financial crisis on the volatility of the Indian equity markets: Coupling or uncoupling? A study on sector-based data

This paper focuses on the following question: has the global financial stress in the US markets during the subprime crisis induced a persistent volatility of Indian equity stocks? We answer this question using sector-based data and we propose a simple stochastic volatility model augmented with exogenous inputs (financial stress indicators in the US market). We derive analytically the autocorrelation of the squared returns using cross-moments and estimate the impact of several variables such as the CDS spreads, the ABCP spreads, market liquidity, the volatility of the S&P 500 using a Kalman filter approach with the impact captured through Almon polynomials. We find a strong evidence of persistent volatility irrespective of the sector and interpret this finding as the result of two factors: the lower liquidity of the Indian equity markets during the subprime crisis and a wake-up call effect.     

A new approach to measuring riskiness in the equity market: Implications for the risk premium

We introduce a new approach to measuring riskiness in the equity market. We propose option implied and physical measures of riskiness and investigate their performance in predicting future market returns. The predictive regressions indicate a positive and significant relation between time-varying riskiness and expected market returns. The significantly positive link between aggregate riskiness and market risk premium remains intact after controlling for the S&P 500 index option implied volatility (VIX), aggregate idiosyncratic volatility, and a large set of macroeconomic variables. We also provide alternative explanations for the positive relation by showing that aggregate riskiness is higher during economic downturns characterized by high aggregate risk aversion and high expected returns.     

The influence of oil prices on the banking sector in oil-exporting economies: Is there a psychological barrier?

This paper examines the relationship between crude oil prices and banking sector market indices in the oil-exporting economies of the Gulf Cooperation Council (GCC), using daily frequency data over 2010–2017. Controlling for global banking impacts (S&P500 Banking Index) and interest rates (T-bills), dynamic ordinary least squared (DOLS) and fully modified ordinary least squared (FM-OLS) analysis indicates that oil prices positively affect bank indices until the $95 per barrel mark, after which the impact becomes negative, close to the psychological barrier found in the US equity market. The S&P500 Banking Index positively affects the GCC banking sector, whereas the interest rate affects it negatively. The validity of an inverse U-shaped relationship between crude oil price and banking sector indices is demonstrated. Causality analysis reveals the existence of bidirectional causalities between the prices of crude oil, GCC banking sectors, and the US banking sector. This paper demonstrates a vital non-linear relationship for oil-banking portfolio management and hedging strategies with oil price risk.     

International capital asset pricing: Evidence from options

We study the risk dynamics and pricing in international economies through a joint analysis of the time-series returns and option prices on three equity indexes underlying three economies: the S&P 500 Index of the United States, the FTSE 100 Index of the United Kingdom, and the Nikkei-225 Stock Average of Japan. We develop an international capital asset pricing model, under which the return on each equity index is decomposed into two orthogonal jump-diffusion components: a global component and a country-specific component. We apply separate stochastic time changes to the two components so that stochastic volatility can come from both global and country-specific risks. For each economy, we assign separate market prices for the two return risk components and the two volatility risk components. Under this specification, we obtain tractable option pricing solutions. Model estimation reveals several interesting insights. First, global and country-specific return and volatility risks show different dynamics. Global return movements contain a larger discontinuous component, and global return volatility is more persistent than the country-specific counterparts. Second, investors charge positive prices for global return risk and negative prices for volatility risk, suggesting that investors are willing to pay positive premiums to hedge against downside global return movements and upside volatility movements. Third, the three economies contain different risk profiles and also price risks differently. Japan contains the largest idiosyncratic risk component and smallest global risk component. Investors in the Japanese market also price more heavily against future volatility increases than against future market downfalls.     

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.     

Recovering the real-world density and liquidity premia from option data

In this paper, we develop a methodology for simultaneous recovery of the real-world probability density and liquidity premia from observed S&P 500 index option prices. Assuming the existence of a numéraire portfolio for the US equity market, fair prices of derivatives under the benchmark approach can be obtained directly under the real-world measure. Under this modelling framework, there exists a direct link between observed call option prices on the index and the real-world density for the underlying index. We use a novel method for the estimation of option-implied volatility surfaces of high quality, which enables the subsequent analysis. We show that the real-world density that we recover is consistent with the observed realized dynamics of the underlying index. This admits the identification of liquidity premia embedded in option price data. We identify and estimate two separate liquidity premia embedded in S&P 500 index options that are consistent with previous findings in the literature.     

Intraday volatility responses to monetary policy events

This paper explores the effects of US monetary policy events on intraday volatility in the US equity markets. We examine Federal Open Market Committee (FOMC) announcements as well as real-time changes in market expectations about future policy announcements and their impact on the intraday volatility dynamics of the S&P 500 index. The analysis shows elevated intraday volatility following FOMC announcements through the market close, with a spike at the time of the announcement. We then differentiate the volatility spike by modeling an asymmetric response based on the direction of the actual target rate change. Our results suggest that the size of the volatility spike is dependent on the direction of the rate change, with expansionary monetary policy actions having a larger spike than contractionary policy actions. The duration of these volatility spikes is relatively short-lived, with the spike dampening out within 15 minutes. A more lasting impact is, however, documented for real-time changes in market expectations where the volatility spike tends to persist for at least one hour.     

A Web Of Shocks: Crises Across Asian Real Estate Markets

The behaviour of real estate markets during the 1997–98 Financial crisis in Asian economies has received little attention despite the extensive research on other asset markets over this time. This paper examines the transmission of shocks across national real estate markets prior to and during the Asian crisis using a multivariate latent factor framework. The results reveal that diversification opportunities prior to the crisis are much reduced during the crisis. A comparison with regional equity markets shows that the transmission of shocks differs across the real estate and equity markets, providing evidence that investment in multiple asset classes provides some protection from large market downturns.     

亚洲汇率波动及政策挑战

自东亚危机以来,亚洲各国采取了一系列的措施降低货币危机的风险,包括执行保守的汇率政策,实现经常账户盈余,积累外汇储备,减少外部债务,谨慎开放资本市场和展开地区金融合作,这些改革使亚洲在全球金融危机期间的表现远胜于其他新兴市场经济。但亚洲货币依然受到了严重冲击,而且出现了非常大的差异性。这既是亚洲的开放经济所决定的,同时也在三个方面对下一步的亚洲汇率政策提出了挑战:第一,汇率体系究竟应该浮动还是管制?第二,到底多少外汇储备才是最佳规模?第三,地区金融合作能否增强亚洲汇率的稳定性?     

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.     

A profitable trading and risk management strategy despite transaction costs

We present a new profitable trading and risk management strategy with transaction cost for an adaptive equally weighted portfolio. Moreover, we implement a rule-based expert system for the daily financial decision-making process using the power of spectral analysis. We use several key components such as principal component analysis, partitioning, memory in stock markets, percentile for relative standing, the first four normalized central moments, learning algorithm, and switching among several investment positions consisting of short stock market, long stock market and money market with real risk-free rates. We find that it is possible to beat the proxy for the equity market without short selling for 168 S&P 500-listed stocks during the 1998–2008 period and 213 Russell 2000-listed stocks during the 1995–2007 period. Our Monte Carlo simulation for both the various set of stocks and the interval of time confirms our findings.     

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.     

Foreign exchange market reactions to sovereign credit news

We analyse the reaction of the foreign exchange spot market to sovereign credit signals by Fitch, Moody’s and S&P during 1994–2010. We find that positive and negative credit news affects both the own-country exchange rate and other countries’ exchange rates. We provide evidence on unequal responses to the three agencies’ signals. Fitch signals induce the most timely market responses, and the market also reacts strongly to S&P negative outlook signals. Credit outlook and watch actions and multiple notch rating changes have more impact than one-notch rating changes. Considerable differences in the market reactions to sovereign credit events are highlighted in emerging versus developed economies, and in various geographical regions.