Trading Activity in Options and Stock Around Price-Sensitive News Announcements

This study investigates the trading activity in options and stock markets around informed events with extreme daily stock price movements. We find that informed agents are more likely to trade options prior to negative news and stocks ahead of positive news. We also show that optioned stocks overreact to the arrival of negative news, but react efficiently to positive news. However, the overreaction patterns are unique to the subsample of stocks with the lowest pre-event abnormal option/stock volume ratio (O/S). This finding suggests that the incremental benefit of option listing is related to the level of option trading activity, over and beyond the presence of an options market on the firm's stock. Finally, we find that the pre-event abnormal O/S is a better predictor of stock price patterns following a negative shock than is the pre-event O/S, implying that the former may contain more information about the future value of stocks than the latter.

What Moved Share Prices in the Nineteenth-Century London Stock Market?

Using a new weekly blue-chip index, this paper investigates the causes of stock price movements on the London market between 1823 and 1870. We find that economic fundamentals explain about 15 per cent of weekly and 34 per cent of monthly variation in share prices. Contemporary press reporting from the London Stock Exchange is used to ascertain what market participants thought were causing the largest movements on the market. The vast majority of large movements were attributed by the press to geopolitical, monetary, railway-sector, and financial-crisis news. Investigating the stock price changes on an independent list of events reaffirms these findings, suggesting that the most important specific events which moved markets were wars involving European powers.

Power-law behaviour, heterogeneity, and trend chasing

Long-range dependence in volatility is one of the most prominent examples in financial market research involving universal power laws. Its characterization has recently spurred attempts to provide some explanations of the underlying mechanism. This paper contributes to this recent line of research by analyzing a simple market fraction asset pricing model with two types of traders---fundamentalists who trade on the price deviation from estimated fundamental value and trend followers whose conditional mean and variance of the trend are updated through a geometric learning process. Our analysis shows that agent heterogeneity, risk-adjusted trend chasing through the geometric learning process, and the interplay of noisy fundamental and demand processes and the underlying deterministic dynamics can be the source of power-law distributed fluctuations. In particular, the noisy demand plays an important role in the generation of insignificant autocorrelations (ACs) on returns, while the significant decaying AC patterns of the absolute returns and squared returns are more influenced by the noisy fundamental process. A statistical analysis based on Monte Carlo simulations is conducted to characterize the decay rate. Realistic estimates of the power-law decay indices and the (FI)GARCH parameters are presented.

Long-term return reversals-Value and growth or tax? UK evidence

This paper examines (i) whether value-growth characteristics have more power than past performance in predicting return reversals; and (ii) whether typical rational behaviour such as incentives to delay paying capital gain taxes can better explain long-term reversals than past performance. We find that value-growth characteristics generally provide better explanations for long-term stock returns than past performance. The evidence also shows that winners identified by capital gains dominate past performance winners in predicting reversals in the cross-sectional comparison. However, in the time-series analysis, when returns on capital gain winners are adjusted by the Fama and French (1996) risk factors, the predictive power of capital gain winners disappears. Our results show that capital gain winners are heavily featured as growth stocks. Return reversals in capital gain winners potentially reflect market price corrections for growth stocks. We conclude that investors’ incentives to delay paying capital gain taxes cannot fully rationalise long-term reversals in the UK market. Our results also imply that the long-term return pattern potentially reflects a mixture of investor rational and irrational behaviour.

Do Low-Priced Stocks Drive Long-Term Contrarian Performance on the London Stock Exchange?

We investigate whether low-priced stocks drive long-term contrarian performance on the U.K. market. We find that contrarian performance at low, middle, and high price levels is positive. On the Fama-French risk adjusted basis, we find both low-priced and middle-priced losers have significantly positive returns. When we adjust returns by market and liquidity risk, only middle-priced losers maintain their positive returns. Our results reveal that low-priced stocks are not fully responsible for contrarian performance. Our empirical evidence is generally consistent with the overreaction hypothesis and behavioral models of value investing.

Predicting low velocity impact damage and Compression-After-Impact (CAI) behaviour of composite laminates

Low-velocity impact damage can drastically reduce the residual strength of a composite structure even when the damage is barely visible. The ability to computationally predict the extent of damage and compression-after-impact (CAI) strength of a composite structure can potentially lead to the exploration of a larger design space without incurring significant time and cost penalties. A high-fidelity three-dimensional composite damage model, to predict both low-velocity impact damage and CAI strength of composite laminates, has been developed and implemented as a user material subroutine in the commercial finite element package, ABAQUS/Explicit. The intralaminar damage model component accounts for physically-based tensile and compressive failure mechanisms, of the fibres and matrix, when subjected to a three-dimensional stress state. Cohesive behaviour was employed to model the interlaminar failure between plies with a bi-linear traction–separation law for capturing damage onset and subsequent damage evolution. The virtual tests, set up in ABAQUS/Explicit, were executed in three steps, one to capture the impact damage, the second to stabilize the specimen by imposing new boundary conditions required for compression testing, and the third to predict the CAI strength. The observed intralaminar damage features, delamination damage area as well as residual strength are discussed. It is shown that the predicted results for impact damage and CAI strength correlated well with experimental testing without the need of model calibration which is often required with other damage models.

Predicting the crushing behaviour of composite material using high-fidelity finite element modelling

The capability to numerically model the crushing behaviour of composite structures will enable the efficient design of structures with high specific energy absorption capacity. This is particularly relevant to the aerospace and automotive industries where cabin structures need to be shown to be crashworthy. In this paper, a three-dimensional damage model is presented, which accurately represents the behaviour of composite laminates under crush loading. Both intralaminar and interlaminar failure mechanisms are taken into account. The crush damage model was implemented in ABAQUS/Explicit as a VUMAT subroutine. Numerical predictions are shown to agree well with experimental results, accurately capturing the intralaminar and interlaminar damage for a range of stacking sequences, triggers and composite materials. The use of measured material parameters required by the numerical models, without the need to ‘calibrate’ this input data, demonstrates this computational tool's predictive capabilities