Intraday Dynamics of Volatility and Duration: Evidence from the Chinese Stock Market

We propose a new joint model of intraday returns and durations to study the dynamics of several Chinese stocks. We include IBM from the U.S. market for comparison purposes. Flexible innovation distributions are used for durations and returns, and the total variance of returns is decomposed into different volatility components associated with different transaction horizons. Our new model strongly dominates existing specifications in the literature. The conditional hazard functions are non-monotonic and there is strong evidence for different volatility components. Although diurnal patterns, volatility components, and market microstructure implications are similar across the markets, there are interesting differences. Durations for lightly traded Chinese stocks tend to carry more information than heavily traded stocks. Chinese investors usually have longer investment horizons, which may be explained by the specific trading rules in China.market microstructure, transaction horizon, high-frequency data, ACD, GARCH

Overnight momentum, informational shocks, and late informed trading in China

Based on high-frequency firm-level data, this paper uncovers new empirical patterns on intraday momentum in China. First, there exists a strong intraday momentum effect at the firm level. Second, the intraday predictability stems mainly from the overnight component rather than the opening half-hour component, which is consistent with the microstructure features of the Chinese market. Third, the intraday predictability attenuates (strengthens) following large positive (negative) informational shocks, implying a striking asymmetric reaction by market participants. Finally, we document that late-informed traders are relatively less experienced or skilful. Overall, the empirical results lend support to the model of late-informed trading

Order flow dynamics around extreme price changes on an emerging stock market

We study the dynamics of order flows around large intraday price changes using ultra-high-frequency data from the Shenzhen Stock Exchange. We find a significant reversal of price for both intraday price decreases and increases with a permanent price impact. The volatility, the volume of different types of orders, the bid-ask spread, and the volume imbalance increase before the extreme events and decay slowly as a power law, which forms a well-established peak. The volume of buy market orders increases faster and the corresponding peak appears earlier than for sell market orders around positive events, while the volume peak of sell market orders leads buy market orders in the magnitude and time around negative events. When orders are divided into four groups according to their aggressiveness, we find that the behaviors of order volume and order number are similar, except for buy limit orders and canceled orders that the peak of order number postpones two minutes later after the peak of order volume, implying that investors placing large orders are more informed and play a central role in large price fluctuations. We also study the relative rates of different types of orders and find differences in the dynamics of relative rates between buy orders and sell orders and between individual investors and institutional investors. There is evidence showing that institutions behave very differently from individuals and that they have more aggressive strategies. Combing these findings, we conclude that institutional investors are more informed and play a more influential role in driving large price fluctuations.Comment: 22 page

Cojumping: Evidence from the US Treasury Bond and Futures Markets

The basis between spot and future prices will be affected by jump behavior in each asset price, challenging intraday hedging strategies. Using a formal cojumping test this paper considers the cojumping behavior of spot and futures prices in high frequency US Treasury data. Cojumping occurs most frequently at shorter maturities and higher sampling frequencies. We find that the presence of an anticipated macroeconomic news announcement, and particularly non-farm payrolls, increases the probability of observing cojumps. However, a negative surprise in non-farm payrolls, also increases the probability of the cojumping tests being unable to determine whether jumps in spots and futures occur contemporaneously, or alternatively that one market follows the other. On these occasions the market does not clearly signal its short term pricing behavior.US Treasury markets, high frequency data, cojump test

Intraday rallies and crashes : spillovers of trading halts

This paper analyses a set of intraday rally and crash events at the firm level during the single stock circuit breaker (SSCB) program, and documents the cross-sectional spillover effects of such events on non-halted stocks. We test whether such major price jumps, and subsequent trading halts, affect related stocks through the destabilizing arbitrage channel. We find that extreme price movements that trigger the circuit breakers at the firm level are accompanied by a massive surge in volume, spread and short-term volatility, which gradually revert back to normal. Speculative strategies of arbitrageurs such as momentum and pairs trading cause cross-sectional spillovers in volume and volatility during the trading halt

The effect of macro news on volatility and jumps

This paper investigates the impact of the major US macroeconomic announcements on volatility and jumps of US financial markets. Results indicate significant volatility spillover effects on the following financial markets: exchange traded funds, exchange rates, equity index futures, Treasury bonds futures, volatility indices and equity spot indices. The expected component of changes of macro variables insignificantly affect volatility. The corresponding surprise component positively and significantly affect volatility. The exchange rate market is mostly affected by macro announcements. Moreover, news related jumps are higher in magnitude than non-news-related jumps. Most of the announcements cause significant increases in jump size. © 2015, Central University of Finance and Economics. All rights reserved

Liquidity of bitcoin – insights from Polish and global markets

Bitcoin can be exchanged for other cryptocurrencies as well as for fiat currencies on many different platforms. Nevertheless, its real convertibility may be limited by market liquidity. The main aim of this article is to characterize and compare big and small bitcoin markets in terms of liquidity. I examine four platforms with high trade volume: Kraken, Bitstamp, BitFlyer and BTCBOX, as well as small entities which enable bitcoin to be traded in Polish zloty: BitBay and BitMarket. I compare the number of trades and the time between trades on selected bitcoin markets, determine the volume distribution throughout the day and analyse the dynamics of Amihud’s illiquidity measure – ILLIQ. I find that an exchange which is among the global leaders in terms of trading bitcoin in a particular traditional currency can be considered a smaller market in terms of trade volume in another traditional currency. Moreover, the results imply that BitBay and BitMarket can be perceived as local markets. They are mainly used for trading in Polish zloty, and are illiquid in terms of trading in the remaining traditional currencies. Home bias, the fact that they offer a possibility of trading in a less popular currency (in comparison to the world reserve currencies), and that have their interface in Polish, may give these platforms a competitive advantage.Bitcoinem można obracać na wielu różnych platformach, wykorzystując do tego inne kryptowaluty, jak również waluty tradycyjne. Niemniej jego rzeczywista wymienialność może być ograniczona przez płynność rynku. Głównym celem artykułu jest scharakteryzowanie i porównanie wybranych giełd kryptowalut pod względem płynności. W tym celu przeanalizowano cztery platformy, które odznaczają się wysokim wolumenem obrotu: Kraken, Bitstamp, BitFlyer i BTCBOX, a także dwa małe podmioty umożliwiające handel w polskim złotym: BitBay i BitMarket. W artykule przedstawiono porównanie rynków pod względem liczby zawartych transakcji, średniego czasu pomiędzy kolejnymi transakcjami czy rozkładu wolumenu obrotu w ciągu dnia. Ponadto przeanalizowano zmiany w czasie miary płynności – ILLIQ. Wyniki pozwoliły stwierdzić, że platforma, która znajduje się wśród globalnych liderów w obrocie bitcoinem w danej walucie tradycyjnej, może być postrzegana jako podmiot mały, jeśli zostanie wzięty pod uwagę obrót w innej walucie tradycyjnej. Ponadto najbardziej popularne platformy umożliwiające wymianę bitcoina na polskiego złotego, czyli BitBay i BitMarket, mogą być uznane za rynki lokalne. Są one głównie wykorzystywane do handlu w złotym. W przypadku obrotu bitcoinem w innych walutach tradycyjnych cechuje je bardzo niska płynność. Czynniki takie jak home bias, możliwość handlu bitcoinem w mniej popularnej walucie tradycyjnej (w porównaniu ze światowymi walutami rezerwowymi) oraz interfejs użytkownika w języku polskim mogą dawać pewną przewagę konkurencyjną tym platformom

Volatility forecasting in the Chinese commodity futures market with intraday data

Given the unique institutional regulations in the Chinese commodity futures market as well as the characteristics of the data it generates, we utilize contracts with three months to delivery, the most liquid contract series, to systematically explore volatility forecasting for aluminum, copper, fuel oil, and sugar at the daily and three intraday sampling frequencies. We adopt popular volatility models in the literature and assess the forecasts obtained via these models against alternative proxies for the true volatility. Our results suggest that the long memory property is an essential feature in the commodity futures volatility dynamics and that the ARFIMA model consistently produces the best forecasts or forecasts not inferior to the best in statistical terms