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on Market Microstructure |
| By: | Sandrine Jacob Leal; Mauro Napoletano; Andrea Roventini; Giorgio Fagiolo |
| Abstract: | We build an agent-based model to study how the interplay between low- and high- frequency trading affects asset price dynamics. Our main goal is to investigate whether high-frequency trading exacerbates market volatility and generates ash crashes. In the model, low-frequency agents adopt trading rules based on chrono- logical time and can switch between fundamentalist and chartist strategies. On the contrary, high-frequency traders activation is event-driven and depends on price fluctuations. High-frequency traders use directional strategies to exploit market in- formation produced by low-frequency traders. Monte-Carlo simulations reveal that the model replicates the main stylized facts of financial markets. Furthermore, we find that the presence of high-frequency trading increases market volatility and plays a fundamental role in the generation of flash crashes. The emergence of flash crashes is explained by two salient characteristics of high-frequency traders, i.e., their ability to i) generate high bid-ask spreads and ii) synchronize on the sell side of the limit order book. Finally, we find that higher rates of order cancellation by high-frequency traders increase the incidence of flash crashes but reduce their duration. |
| Date: | 2014–01–31 |
| URL: | http://d.repec.org/n?u=RePEc:thk:rnotes:37&r=mst |
| By: | Bing-Yi Jing; Cui-Xia Li; Zhi Liu |
| Abstract: | In this paper, we consider the estimation of covariation of two asset prices which contain jumps and microstructure noise, based on high frequency data. We propose a realized covariance estimator, which combines pre-averaging method to remove the microstructure noise and the threshold method to reduce the jumps effect. The asymptotic properties, such as consistency and asymptotic normality, are investigated. The estimator allows very general structure of jumps, for example, binfinity activity or even infinity variation. Simulation is also included to illustrate the performance of the proposed procedure. |
| Keywords: | Ito semi-martingale; High frequency data; Microstructure noise; Covolatility; Jumps; Central limit theorem. |
| Date: | 2013–10–14 |
| URL: | http://d.repec.org/n?u=RePEc:wyi:journl:002161&r=mst |
| By: | Kent Wang; Junwei Liu; Zhi Liu |
| Abstract: | We propose a new thresholdæ™re-averaging realized estimator for the integrated co-volatility of two assets using non-synchronous observations with the simultaneous presence of microstructure noise and jumps. We derive a noise-robust Hayashi朰oshida estimator that allows for very general structure of jumps in the underlying process. Based on the new estimator, different aspects and components of co-volatility are compared to examine the effect of jumps on systematic risk using tick-by-tick data from the Chinese stock market during 2009?011. We find controlling for jumps contributes significantly to the beta estimation and common jumps mostly dominate the jump抯 effect, but there is also evidence that idiosyncratic jumps may lead to significant deviation. We also find that not controlling for noise and jumps in previous realized beta estimations tend to considerably underestimate the systematic risk. |
| Keywords: | Ito semi-martingale, High-frequency finance, Co-volatility, Non-synchronous trading, Idiosyncratic jumps, Co-jump, Microstructure noise |
| JEL: | C13 C14 G10 G12 |
| Date: | 2013–10–14 |
| URL: | http://d.repec.org/n?u=RePEc:wyi:journl:002184&r=mst |
| By: | Gao-Feng Gu (ECUST); Xiong Xiong (TJU); Yong-Jie Zhang (TJU); Wei Chen (SZSE); Wei Zhang (TJU); Wei-Xing Zhou (ECUST) |
| Abstract: | Price gap, defined as the logarithmic price difference between the first two occupied price levels on the same side of a limit order book (LOB), is a key determinant of market depth, which is one of the dimensions of liquidity. However, the properties of price gaps have not been thoroughly studied due to the less availability of ultrahigh frequency data. In the paper, we rebuild the LOB dynamics based on the order flow data of 26 A-share stocks traded on the Shenzhen Stock Exchange in 2003. Three key empirical statistical properties of price gaps are investigated. We find that the distribution of price gaps has a power-law tail for all stocks with an average tail exponent close to 3.2. Applying modern statistical methods, we confirm that the gap time series are long-range correlated and possess multifractal nature. These three features vary from stock to stock and are not universal. Furthermore, we also unveil buy-sell asymmetry phenomena in the properties of price gaps on the buy and sell sides of the LOBs for individual stocks. These findings deepen our understanding of the dynamics of liquidity of common stocks and can be used to calibrate agent-based computational financial models. |
| Date: | 2014–05 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:1405.1247&r=mst |
| By: | M. Alessandra Crisafi; Andrea Macrina |
| Abstract: | We consider an optimal execution problem over a finite period of time during which an investor has access to both a standard exchange and a dark pool. We take the exchange to be an order-driven market and propose a continuous-time setup for the best bid and best ask prices, both modelled by arbitrary functions of incoming market and limit orders. We consider a random drift so to include the impact of market orders, and we describe the arrival of limit orders and of order cancellations by means of Poisson random measures. In the situation where the trades take place only in the exchange, we find that the optimal execution strategy depends significantly on the resilience of the limit order book. We assume that the trading price in the dark pool is the mid-price and that no fees are due for posting orders. We allow for partial trade executions in the dark pool, and we find the optimal order-size placement in both venues. Since the mid-price is taken from the exchange, the resilience of the limit order book also affects the optimal allocation of shares in the dark pool. We propose a general objective function and we show that, subject to suitable technical conditions, the value function can be characterised by the unique continuous viscosity solution to the associated system of partial integro differential equations. We present a numerical example of which model parameters are analysed in detail. |
| Date: | 2014–05 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:1405.2023&r=mst |
| By: | Yi-Fang Liu (College of Management and Economics - Tianjin University, China Center for Social Computing and Analytics - Tianjin University, CES - Centre d'économie de la Sorbonne - CNRS : UMR8174 - Université Paris 1 - Panthéon-Sorbonne); Wei Zhang (College of Management and Economics - Tianjin University, China Center for Social Computing and Analytics - Tianjin University); Chao Xu (College of Management and Economics - Tianjin University, China Center for Social Computing and Analytics - Tianjin University); Jørgen Vitting Andersen (CES - Centre d'économie de la Sorbonne - CNRS : UMR8174 - Université Paris 1 - Panthéon-Sorbonne); Hai-Chuan Xu (College of Management and Economics - Tianjin University, China Center for Social Computing and Analytics - Tianjin University) |
| Abstract: | This paper studies the switching of trading strategies and its effect on the market volatility in a continuous double auction market. We describe the behavior when some uninformed agents, who we call switchers, decide whether or not to pay for information before they trade. By paying for the information they behave as informed traders. First, we verify that our model is able to reproduce some of the stylized facts in real financial markets. Next we consider the relationship between switching and the market volatility under different structures of investors. We find that there exists a positive relationship between the market volatility and the percentage of switchers. We therefore conclude that the switchers are a destabilizing factor in the market. However, for a given fixed percentage of switchers, the proportion of switchers that decide to buy information at a given moment of time is negatively related to the current market volatility. In other words, if more agents pay for information to know the fundamental value at some time, the market volatility will be lower. This is because the market price is closer to the fundamental value due to information diffusion between switchers. |
| Keywords: | Agent-based model; heterogeneity; switching behavior; market volatility |
| Date: | 2014–04 |
| URL: | http://d.repec.org/n?u=RePEc:hal:cesptp:halshs-00983051&r=mst |
| By: | Biao Guo; Qian Han; Doojin Ryu; Robert I. Webb |
| Abstract: | This study examines the short-term relationship between stock market returns and implied volatility using� high frequency data . This is the first study to analyze� high frequency data on the VKOPSIa newly introduced volatility index implied by the KOSPI200 options.� KOSPI 200 optioins� are the� most actively traded derivative contracts in the world and trading is dominate by �individuals. We find a strong asymmetric and negative return-volatility relationship both at the daily and intraday frequency, which cannot be explained by the standardhypotheses on the asymmetric volatility effect. Our results also show that the relationship is more pronounced in the presence of� extremely negative stock market returns. |
| Keywords: | Asymmetric volatility, Implied volatility, VKOSPI, KOSPI200 options |
| Date: | 2013–10–14 |
| URL: | http://d.repec.org/n?u=RePEc:wyi:wpaper:002046&r=mst |
| By: | Qinghua Li |
| Abstract: | This paper studies four trading algorithms of a professional trader at a multilateral trading facility, observing a realistic two-sided limit order book whose dynamics are driven by the order book events. The identity of the trader can be either internalizing or regular, either a hedge fund or a brokery agency. The speed and cost of trading can be balanced by properly choosing active strategies on the displayed orders in the book and passive strategies on the hidden orders within the spread. We shall show that the price switching algorithms provide lower and upper bounds of the mixed trading algorithms. Especially, when the internalization premium is zero, an internalizing trader's optimal mixed trading strategy can be achieved among the set of price switching strategies. For both an internalizing trader and a regular trader, the optimal price switching strategy exists and is expressed in terms of the value function. A parallelizable algorithm to numerically compute the value function and optimal price switching strategy for the discretized state process is provided. |
| Date: | 2014–04 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:1404.7320&r=mst |
| By: | Yan He; Hai Lin; Chunchi Wu; Uric B. Dufrene |
| Abstract: | We investigate the information cost of stock trading during the 2000 presidential election. We find that the uncertainty of the election induces information asymmetry of politically sensitive firms under the Bush/Gore platforms. The unusual delay in election results in a significant increase in the adverse selection component of trading cost of politically sensitive stocks. Cross-sectional variations in bid-ask spreads are significantly and positively related to changes in information cost, controlling for the effects of liquidity cost and stock characteristics. This empirical evidence is robust to different estimation methods. |
| Keywords: | Presidential election; information asymmetry; transaction costs; bid-ask spreads; adverse selection cost |
| JEL: | G0 G14 |
| Date: | 2013–10–14 |
| URL: | http://d.repec.org/n?u=RePEc:wyi:wpaper:001975&r=mst |
| By: | Yan He; Hai Lin; Chunchi Wu; Uric B. Dufrene |
| Abstract: | We investigate the information cost of stock trading during the 2000 presidential election. We find that the uncertainty of the election induces information asymmetry of politically sensitive firms under the Bush/Gore platforms. The unusual delay in election results creates a significant increase in the adverse selection component of the trading cost of politically sensitive stocks. Cross-sectional variations in bid-ask spreads are significantly and positively related to changes in information cost, controlling for the effects of liquidity cost and stock characteristics. This empirical evidence is robust to different estimation methods. |
| Keywords: | Presidential election; Information asymmetry; Transaction costs; Bid-ask spreads; Adverse selection cost |
| Date: | 2013–10–14 |
| URL: | http://d.repec.org/n?u=RePEc:wyi:journl:002085&r=mst |
| By: | Biao Guo; Qian Han; Maonan Liu; Doojin Ryu |
| Abstract: | This is the first study to examine the intraday price discovery and volatility transmission processes between the Singapore Exchange and the China Financial Futures Exchange. Using one- and five-minute high-frequency data from May to November 2011, we find that China’s CSI 300 index futures dominate Singapore’s A50 index futures in both intraday price discovery and intraday volatility transmission processes. However, A50 futures contracts also make a substantial contribution (26%-37%) in the price discovery process. These results have important implications for both traders and policymakers. |
| Keywords: | Price Discovery, Volatility Transmission, Futures Market, CSI 300, A50, Information Share. |
| Date: | 2013–10–14 |
| URL: | http://d.repec.org/n?u=RePEc:wyi:journl:002180&r=mst |
| By: | Haiqiang Chen; Paul Moon Sub Choi |
| Abstract: | We document differential private information in cross-border asset pricing using the probability of informed trading (PIN) for Canadian shares traded on both sides of Niagara Falls. Relative to the New York Stock Exchange (NYSE), the Toronto Stock Exchange (TSX) hasmore informed trades and a larger information share. This cross-border information imbalance is associated with small but positive price premiums in New York as predicted by a model. The dynamics of these premiums depends on trade informativeness. Lastly, the PIN for TSX trading typically rises upon cross-listing on the NYSE, which is consistent with the negative event-study response. |
| Keywords: | Cross-listing, Probability of informed trading, Information share, Price discovery, Convergence speed, Bid–ask spread |
| JEL: | G15 G14 D82 |
| Date: | 2013–10–14 |
| URL: | http://d.repec.org/n?u=RePEc:wyi:journl:002166&r=mst |
| By: | Christiane Baumeister; Pierre Guérin; Lutz Kilian |
| Abstract: | The substantial variation in the real price of oil since 2003 has renewed interest in the question of how to forecast monthly and quarterly oil prices. There also has been increased interest in the link between financial markets and oil markets, including the question of whether financial market information helps forecast the real price of oil in physical markets. An obvious advantage of financial and energy market data in forecasting oil prices is their availability in real time on a daily or weekly basis. We investigate whether mixed-frequency models can be used to take advantage of these rich data sets. We show that, among a range of alternative high-frequency predictors, changes in U.S. crude oil inventories produce substantial and statistically significant real-time improvements in forecast accuracy. The preferred mixed-data sampling (MIDAS) model reduces the mean-squared prediction error by as much as 16 percent compared with the no-change forecast and has statistically significant directional accuracy as high as 80 percent. This MIDAS forecast also is more accurate than a mixed-frequency real-time vector autoregressive forecast, but not systematically more accurate than the corresponding forecast based on monthly inventories. We conclude that typically not much is lost by ignoring high-frequency financial data in forecasting the monthly real price of oil. |
| Keywords: | Econometric and statistical methods, International topics |
| JEL: | C53 G14 Q43 |
| Date: | 2014 |
| URL: | http://d.repec.org/n?u=RePEc:bca:bocawp:14-11&r=mst |
| By: | Haiqiang Chen; Paul Moon Sub Choi; Yongmiao Hong |
| Abstract: | The adjustment to parity can be nonlinear for a cross-listed pair: Convergence may be quicker when the price deviation is sufficiently profitable. We propose a� threshold� error� correction� model� (ECM)� to� gauge� the� market-respective information shares of Canadian listings traded on the Toronto Stock Exchange (TSX)� and� the� New� York� Stock� Exchange� (NYSE).� Since� dynamics may alternatively� be� gradual,� we� further� generalize� the� threshold� framework to� a smooth� transition� ECM.� The� empirical� implications� are� as� follows:� First,� the TSX�� and�� the�� NYSE�� appear�� to�� have� �integrated�� over�� time.�� Second, parity-convergence� accelerates� upon� discounts� on� the� cross-listings� on� the NYSE.� Third,� we� find� a� larger� feedback� from� the� NYSE� if� the� price� gap exceeds the threshold (required arbitrage return). Fourth, informed traders tend to cluster on the NYSE upon discounts on the cross-listings. Fifth, information share and threshold are affected by the relative degree of privateinformation, market�� friction�� and�� liquidity�� measures,�� firm-level�� characteristics,�� and aggregate risks. |
| Keywords: | Price discovery; Information share; Threshold error correction model; Smooth transition error correction model |
| JEL: | C32 G15 G14 |
| Date: | 2013–10–14 |
| URL: | http://d.repec.org/n?u=RePEc:wyi:journl:002160&r=mst |
| By: | Bing-Yi Jing; Xin-Bing Kong; Zhi Liu; Per Mykland |
| Abstract: | Empirical evidence of asset price discontinuities or “jumps†in financial markets has been well documented in the literature. Recently, Ait-Sahalia and Jacod (2009b) defined a general “jump activity index†to describe the degree of jump activities for asset price semimartingales, and provided a consistent estimator when the underlying process contains both a continuous and a jump component. However, only large increments were used in their estimator so that the effective sample size is very small even for large sample sizes. In this paper, we explore ways to improve the Ait-Sahalia and Jacod’s estimator by making use of all increments, large and small. The improvement is verified through simulations. A real example is also given. |
| Keywords: | Semimartingale, Power variation, High frequency, Jump activity index, Stable convergence. |
| Date: | 2013–10–14 |
| URL: | http://d.repec.org/n?u=RePEc:wyi:journl:002150&r=mst |
| By: | Lubnau, Thorben |
| Abstract: | This article explores whether common technical trading strategies used in equity markets can be employed profitably in the markets for WTI and Brent crude oil. The strategies tested are Bollinger Bands, based on a mean-reverting hedge portfolio of WTI and Brent. The trading systems are tested with historical data from 1992 to 2013, representing 22 years of data and for various specifications. The hedge ratio for the crude oil portfolio is derived by using the Johansen procedure and a dynamic linear model with Kalman filtering. The significance of the results is evaluated with a bootstrap test in which randomly generated orders are employed. Results show that some setups of the system are able to be profitable over every five-year period tested. Furthermore they generate profits and Sharpe ratios that are significantly higher than those of randomly generated orders of approximately the same holding time. The best results with some Sharpe ratios in excess of three, are obtained when a dynamic linear model with Kalman filtering and maximum likelihood estimates of the unknown variance of the state equation is employed to constantly update the hedge ratio of the portfolio. The results indicate that the crude oil market may not be weak-form efficient. -- |
| Keywords: | Oil Prices,Commodities,Technical trading,Market efficiency,Future returns,Kalman Filtering |
| Date: | 2014 |
| URL: | http://d.repec.org/n?u=RePEc:zbw:euvwdp:353&r=mst |
| By: | Hongquan Li; Yongmiao Hong |
| Abstract: | The classical volatility models, such as GARCH, are return-based models, which are constructed with the data of closing prices. It might neglect the important intraday information of the price movement, and will lead to loss of information and efficiency. This study introduces and extends the range-based autoregressive volatility model to make up for these weaknesses. The empirical results consistently show that the new model successfully captures the dynamics of the volatility and gains good performance relative to GARCH model. |
| Keywords: | Volatility modeling; Price range; Forecasting performance; Intraday information;�GARCH |
| JEL: | G32 C01 C53 |
| Date: | 2013–10–14 |
| URL: | http://d.repec.org/n?u=RePEc:wyi:journl:002128&r=mst |
| By: | Eleonora Iachini (Banca d'Italia); Stefano Nobili (Banca d'Italia) |
| Abstract: | This paper introduces a coincident indicator of systemic liquidity risk in the Italian financial markets. In order to take account of the systemic dimension of liquidity stress, standard portfolio theory is used. Three sub-indices, that reflect liquidity stress in specific market segments, are aggregated in the systemic liquidity risk indicator in the same way as individual risks are aggregated in order to quantify overall portfolio risk. The aggregation takes account of the time-varying cross-correlations between the sub-indices, using a multivariate GARCH approach. This is able to capture abrupt changes in the correlations and makes it possible for the indicator to identify systemic liquidity events precisely. We evaluate the indicator on its ability to match the results of a survey conducted among financial market experts to determine the most liquidity stressful events for the Italian financial markets. The results show that the systemic liquidity risk indicator accurately identifies events characterized by high systemic risk, while not exaggerating the level of stress during calm periods. |
| Keywords: | financial crisis, liquidity risk, systemic risk, stress index, multivariate GARCH |
| JEL: | G01 G10 G20 |
| Date: | 2014–04 |
| URL: | http://d.repec.org/n?u=RePEc:bdi:opques:qef_217_14&r=mst |