Abhay Abhyankar

Uncovering Nonlinear Structure in Real-Time Stock-Market Indexes: The S&P 500, the DAX, the Nikkei 225, and the FTSE-100

This article tests for nonlinear dependence and chaos in real-time returns on the worlds four most important stock-market indexes. Both the Brock–Dechert–Scheinkman and the Lee, White, and Granger neural-network-based tests indicate persistent nonlinear structure in the series. Estimates of the Lyapunov exponents using the Nychka, Ellner, Gallant, and McCaffrey neural-net method and the Zeng, Pielke, and Eyckholt nearest-neighbor algorithm confirm the presence of nonlinear dependence in the returns on all indexes but provide no evidence of low-dimensional chaotic processes. Given the sensitivity of the results to the estimation parameters, we conclude that the data are dominated by a stochastic component.

Bid-ask Spreads, Trading Volume and Volatility: Intra-day Evidence from the London Stock Exchange

This paper examines intra-day variations in the bid-ask spread, volatility and volume for stocks traded on the London Stock Exchange. The data set used consists of quote and transactions data for a large sample of 835 stocks traded during the first quarter of 1991. The focus of the study is twofold; first, is to document a number of stylized facts regarding the intra-day behaviour of spread, trading volume, volatility etc. Second, the paper tests some predictions of two theoretical models of intra-day behaviour: the Admati and Pfleiderer and the Brock and Kleidon models. In addition, the paper also studies qualitatively the intra-day behaviour of several variables of interest including volume per transaction, transactions per fifteen-minute interval and spreads/trading volume for stocks of differing liquidity. The results suggest that the bid-ask spread is wide at the open, constant through the day and rises slightly at the close. Trading volume, in contrast is not highest at the open and the close. Volatility, based on the mid-point of the inside spread, shows a U-shaped pattern. Volume per transaction, in contrast, is fairly constant throughout the day. Further, the intra-day trading volume pattern differs for liquid and illiquid stocks. The results provide mixed support for current theoretical models of intra-day behaviour of spread, volume and volatility on the London Stock Exchange Copyright Blackwell Publishers Ltd 1997.

Trading-round-the clock: Return, volatility and volume spillovers in the Eurodollar futures markets☆

Abstract Using intra-daily data this paper investigates the inter-market transmission of returns, volatility and trading volume, between the Eurodollar (ED) futures markets of the CME and the SIMEX. The sample is unique in that the same contract is examined, in two markets with non-overlapping time zones, providing an unbiased test of inter-market transmission effects. The results suggest the existence of a lagged spillover effect in the mean return from the CME to the SIMEX but not vice-versa, though there are symmetric spillovers in lagged return volatility. We also find that the volume in the market that has earlier traded has a significant impact on the conditional volatility of the market that follows.

LIFFE cycles: intraday evidence from the FTSE-100 Stock Index futures market

We use a data set consisting of a complete history of all transactions and quotes to examine intraday patterns in trading volume, volatility and the quoted bid-ask spread in the market for FTSE-100 index futures. We document a number of regularities in the pattern of daily returns and volatility of the cash index. We also document intraday patterns in the basis, i.e. the contemporaneous difference between the futures price and the underlying cash index level. In general, we find returns vary over the day, reflecting in particular the influence of the US market openings in early afternoon London-time. We find that, while both volume and volatility exhibit a U-shaped pattern over the day, movements in the spread tend if anything to follow the opposite pattern. As far as consistency with microstructure models is concerned, our results are more supportive of the Brock and Kleidon model than the Admati and Pfleiderer model.

Moment condition failure in high frequency financial data: evidence from the S&P 500

Loretan-Phillips maximal moment exponent estimators are used to investigate the distribution of S&P 500 stock returns at a range of different frequencies. In all cases, the variance is found to be finite, but the existence of higher-order moments is in some doubt.

The Optimal Use of Return Predictability: An Empirical Study

In this paper we study the economic value and statistical significance of asset return predictability, based on a wide range of commonly used predictive variables. We assess the performance of dynamic, unconditionally efficient strategies, first studied by Hansen and Richard ( 1987 ) and Ferson and Siegel ( 2001 ), using a test that has both an intuitive economic interpretation and known statistical properties. We find that using the lagged term spread, credit spread, and inflation significantly improves the risk-return trade-off. Our strategies consistently outperform efficient buy-and-hold strategies, both in and out of sample, and they also incur lower transactions costs than traditional conditionally efficient strategies.

Does Conditioning Information Matter in Estimating Continuous Time Interest Rate Diffusions

We examine an important aspect of empirical estimation of term structure models; the role of conditioning information in dynamic term structure models. The use of both real world or simulated data implicitly incorporates conditioning information. We examine the bias created in estimating the drift by a specific form of conditioning, namely truncation. Using the theory of enlargement of nTtrations we provide estimates of the extent of this truncation bias for commonly used short rate models. We find that this truncation bias causes the drift of these models to have a nonlinear structure.

Uncovering Dividend Growth Predictability: New Evidence from the Post-WW II Period

We re-visit a puzzling result that in U.S. post-WW II data the dividend price ratio can predict aggregate returns but not dividend growth. We find that predictive regressions are sensitive to the method used to aggregate firm-level data. Using value weighted firm-level data we find strong evidence for dividend growth predictability in the post-WW II period. We explore the reasons behind the differences in predictability due to different weighting methods. We find that these differences in predictability are related to the fact, in the data, that it is not always the largest firms that pay the largest dollar dividends or earnings.

Macroeconomic Fundamentals, Expected Returns and the Pricing of Anomaly Portfolios

Recent research has identified more than three hundred factors that have statistically significant prices of risk in asset pricing tests. This evidence is disconcerting and more parsimonious factor pricing models are required. Our work contributes to the effort of reducing this “zoo of factors”. We propose a set of empirical factors that mimic macroeconomic sources of risk in the economy. Our three factor model does well in explaining the cross-section of a number of common benchmark portfolios and other ‘anomaly’ spreads relative to standard empirical factor models.

The Impact of Hedge Accounting Rules on Enterprise Risk Management Adoption Practices by Multinationals

We predict that adoption of Enterprise Risk Management (ERM) by multinational non-financial firms is inter-related with firm hedge accounting policies and GAAP quality. We hypothesize that sources of both market risk and idiosyncratic risk mitigate the ability of ERM-adopting firms to produce greater risk reduction. Therefore, we predict that sources of firm specific risk, such as pension risk, and hedge accounting policies, as well as GAAP quality, interact with ERM to affect incentives facing multinational firms to reduce their risk. Consistent with this hypothesis, we find that firms adopting ERM experience a reduction in stock return volatility but only for the period following implementation. Our results also find that income smoothing; GAAP choice and geographical complexity mitigate the effect of ERM adoption on risk and return volatility for ERM-adopting firms.