|
on Market Microstructure |
| By: | Masayuki Susai (Nagasaki University); Yushi Yoshida (Faculty of Economics, Kyushu Sangyo University) |
| Abstract: | We investigate the intra-day effect of interventions in both the post- global crisis and pre-crisis periods by the Bank of Japan (BOJ) in foreign exchange markets using limit order data at intra-day high frequency. First, we find that the relationship between order flow and market return in dollar/yen exchange markets breaks down following unexpected and very high volumes of offer/sell orders by BOJ interventions. Then, a simple methodology of using large recursive residual is proposed to detect the exact timing of interventions. Second, the dataset allows measuring how long an individual limit order stays in the market. With the measured lifetime of limit orders, we find interventions, detected by the proposed methodology, significantly reduce the life-time of limit order in the market. By applying the same methodology on non-intervention days, we find no such evidence on the life-time of limit orders although large recursive residuals are also pervasive in non-intervention days. |
| Keywords: | the Bank of Japan; Central bank interventions; Foreign exchange market; Life time of limit order; Order flow. |
| JEL: | F31 G12 G14 G15 E58 |
| Date: | 2012–07 |
| URL: | http://d.repec.org/n?u=RePEc:kyu:dpaper:56&r=mst |
| By: | Martin Scholtus (Erasmus University Rotterdam); Dick van Dijk (Erasmus University Rotterdam) |
| Abstract: | This paper investigates the importance of speed for technical trading rule performance for three highly liquid ETFs listed on NASDAQ over the period January 6, 2009 up to September 30, 2009. In addition we examine the characteristics of market activity over the day and within subperiods corresponding to hours, minutes, and seconds. Speed has a clear impact on the return of technical trading rules. For strategies that yield a positive return when they experience no delay, a delay of 200 milliseconds is enough to lower performance significantly. On low volatility days this is already the case for delays larger than 50 milliseconds. In addition, the importance of speed for trading rule performance increases over time. Market activity follows a U-shape over the day with a spike at 10:00AM due to macroeconomic announcements and is characterized by periodic activity within the day, hour, minute, and second. |
| Keywords: | Technical Trading; High-Frequency Trading; Latency Costs; Trading Speed; Market Activity |
| JEL: | G10 G14 G20 |
| Date: | 2012–03–01 |
| URL: | http://d.repec.org/n?u=RePEc:dgr:uvatin:20120018&r=mst |
| By: | Gyarmati, Ákos; Lublóy, Ágnes; Váradi, Kata |
| Abstract: | During the 2007/2008 global economic crisis, market liquidity became an important issue both on the field of theoretical finance and in practice. In theory market liquidity is usually being modeled with price impact functions. In this study we show how the price impact function can be estimated from order book data. Our estimation is based on the Budapest Liquidity Measure (BLM) which is a liquidity measure that captures the transaction cost nature of liquidity. The main outcome of this paper is a method with which market participants can easily estimate price impact functions. This is of major importance, as the price impact function can be a useful tool during a dynamic portfolio optimization process. The price impact functions can help investors in their trading decisions. |
| Keywords: | market liquidity; price impact function; liquidity measure |
| JEL: | G14 G11 |
| Date: | 2012 |
| URL: | http://d.repec.org/n?u=RePEc:pra:mprapa:40339&r=mst |
| By: | Pablo Su\'arez-Garc\'ia; David G\'omez-Ullate |
| Abstract: | In this paper we perform a statistical analysis of the high-frequency returns of the IBEX35 Madrid stock exchange index. We find that its probability distribution seems to be stable over different time scales, a stylized fact observed in many different financial time series. However, an in-depth analysis of the data using maximum likelihood estimation and different goodness-of-fit tests rejects the L\'evy-stable law as a plausible underlying probabilistic model. The analysis shows that the Normal Inverse Gaussian distribution provides an overall fit for the data better than any of the other subclasses of the family of the Generalized Hyperbolic distributions and certainly much better than the L\'evy-stable laws. Furthermore, the right (resp. left) tail of the distribution seems to follow a power-law with exponent \alpha=4.60 (resp. \alpha =4.28). Finally, we present evidence that the observed stability is due to temporal correlations or non-stationarities of the data. |
| Date: | 2012–08 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:1208.0317&r=mst |
| By: | Kirill Vaninsky; Stepan Myzuchka; Alexander Lukov |
| Abstract: | We introduce and treat rigorously a new multi-agent model of the limit order book. Our model is designed to explain a behavior of the market when new information a?ecting the market arrives. Our model has two major features. First, it constitutes a nonlinear Markov process. Second, it has two additional parameters which we call slow parameters. These parameters measure mood of two groups of investors, namely, bulls and bears. We explain the intuition behind the equations and present numerical simulations which show that behavior of the model is similar to the behavior of the real market. |
| Date: | 2012–08 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:1208.3083&r=mst |