High frequency trading and end-of-day price dislocation : [Version 28 Oktober 2013]

We show that the presence of high frequency trading (HFT) has significantly mitigated the frequency and severity of end-of-day price dislocation, counter to recent concerns expressed in the media. The effect of HFT is more pronounced on days when end of day price dislocation is more likely to be the result of market manipulation on days of option expiry dates and end of month. Moreover, the effect of HFT is more pronounced than the role of trading rules, surveillance, enforcement and legal conditions in curtailing the frequency and severity of end-of-day price dislocation. We show our findings are robust to different proxies of the start of HFT by trade size, cancellation of orders, and co-location

Price limits are not always bad : a thesis presented in partial fulfilment of the requirements for the degree of Masters of Business Studies in Finance at Massey University, Albany, New Zealand, December 2006

Regulators impose price limits on daily price movements to protect investors from excessive volatility, but several empirical studies have cast serious doubt on the benefits of such mechanisms. Using a large cross-sectional sample combined with intraday data from the Tokyo Stock Exchange, this study finds evidence that partially supports conventional criticisms that price limits spread out volatility, delay price discovery, and interrupt trading activities. More importantly, the transaction data analysis reveals that price limits help to reduce order imbalance and improve information asymmetry, justifying the existence of price limits on the Tokyo Stock Exchange. JEL Classification: G10; G14 Keywords: Price limit; Order imbalance; Information asymmetry; Tokyo Stock Exchange

Are Chinese Stock Investors Watching Tokyo? An Analysis of Intraday High-Frequency Data from Two Chinese Stock Markets and the Tokyo Stock

Intraday minute-by-minute data from the Tokyo, Shanghai, and Shenzhen stock exchanges from January 7, 2008, to January 23, 2009, are analyzed to investigate the interaction between the Japanese and Chinese stock markets. We focus on two windows of time during which all three stock exchanges trade shares simultaneously, and specify appropriate lags in vector autoregression (VAR) estimations. Granger causality tests, variance decompositions, and impulse response functions show that, while Tokyo is impacted by Chinese stock price movements, China is relatively isolated. This implies that investors in Japan are more internationally oriented and alert to foreign markets than those in China.international linkage of stock prices, high frequency data, inefficiency, overreaction, China

The Evolution of Neural Network-Based Chart Patterns: A Preliminary Study

A neural network-based chart pattern represents adaptive parametric features, including non-linear transformations, and a template that can be applied in the feature space. The search of neural network-based chart patterns has been unexplored despite its potential expressiveness. In this paper, we formulate a general chart pattern search problem to enable cross-representational quantitative comparison of various search schemes. We suggest a HyperNEAT framework applying state-of-the-art deep neural network techniques to find attractive neural network-based chart patterns; These techniques enable a fast evaluation and search of robust patterns, as well as bringing a performance gain. The proposed framework successfully found attractive patterns on the Korean stock market. We compared newly found patterns with those found by different search schemes, showing the proposed approach has potential.Comment: 8 pages, In proceedings of Genetic and Evolutionary Computation Conference (GECCO 2017), Berlin, German