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on Market Microstructure |
| By: | Taiga Saito (Faculty of Economics, The University of Tokyo); Takanori Adachi (BKC Research Organization of Social Sciences, Ritsumeikan University); Teruo Nakatsuma (Department of Economics, Keio University); Akihiko Takahashi (Faculty of Economics, The University of Tokyo); Hiroshi Tsuda (epartment of Mathematical Sciences, Doshisha University.); Naoyuki Yoshino (Financial Services Agency, Government of Japan. ADBI Institute) |
| Abstract: | In this study, we investigate ordering patterns of different types of market participants in Tokyo Stock Exchange (TSE) by examining order records of the listed stocks. Firstly, we categorize the virtual servers in the trading system of TSE, each of which is linked to a single trading participant, by the ratio of cancellation and execution in the order placement as well as the number of executions at the opening of the afternoon session. Then, we analyze ordering patterns of the servers in the categories in short intervals for the top 10 highest trading volume stocks. By classifying the intervals into four cases by returns, we observe how different types of market participants submit or execute orders in the market situations. Moreover, we investigate the shares of the executed volumes for the different types of servers in the swings and roundabouts of the Nikkei 225 index, which were observed in July, August, and September in 2015. The main findings of this study are as follows: Server type A, which supposedly includes non-market making proprietary traders with high-speed algorithmic strategies, executes and places orders along with the direction of the market. The shares of the execution and order volumes along with the market direction increase when the stock price moves sharply. Server type B, which presumably includes servers employing a market making strategy with high cancellation and low execution ratio, shifts its market making price ranges in the rapid price movements. We observe that passive servers in Server type B have a large share and buy at low levels in the price falls. Also, Server type B, as well as Server type A, makes profit in the price falling days and particularly, the aggressive servers in the server type make most of the profit. Server type C, which is assumed to include servers receiving orders from small investors, constantly has a large share of execution and order volume. |
| Date: | 2017–06 |
| URL: | http://d.repec.org/n?u=RePEc:tky:fseres:2017cf1052&r=mst |
| By: | Tobias Braun; Jonas A. Fiegen; Daniel C. Wagner; Sebastian M. Krause; Thomas Guhr |
| Abstract: | In an Ultrafast Extreme Event (or Mini Flash Crash), the price of a traded stock increases or decreases strongly within milliseconds. We present a detailed study of Ultrafast Extreme Events in stock market data. In contrast to popular belief, our analysis suggests that most of the Ultrafast Extreme Events are not primarily due to High Frequency Trading. In at least 60 percent of the observed Ultrafast Extreme Events, the main cause for the events are large market orders. In times of financial crisis, large market orders are more likely which can be linked to the significant increase of Ultrafast Extreme Events occurrences. Furthermore, we analyze the 100 trades following each Ultrafast Extreme Events. While we observe a tendency of the prices to partially recover, less than 40 percent recover completely. On the other hand we find 25 percent of the Ultrafast Extreme Events to be almost recovered after only one trade which differs from the usually found price impact of market orders. |
| Date: | 2017–07 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:1707.05580&r=mst |
| By: | Baranova, Yuliya (Bank of England); Liu, Zijun (Bank of England); Shakir, Tamarah (Bank of England) |
| Abstract: | We develop a model of dealer intermediation in bond markets that takes account of how changing regulatory requirements for banks since the financial crisis, in particular, the introduction of minimum leverage ratio requirements, affect the cost and ability of dealer banks to provide intermediation services. The framework considers two distinct dealer functions: that of provider of repo financing (to prospective bond market participants) and that of market-maker. The cost and ability of dealers to provide these services under different regulatory constraints determines the price impact of a given trade on the market — or the level of ‘market liquidity premia’. In the model the impact on market liquidity varies for different levels of market volatility or ‘stress’. We find that under normal market conditions estimates of corporate bond liquidity risk premia are higher under the new regulations, but also that corporate bond market liquidity is more resilient due to better-capitalised dealers continuing to intermediate markets under higher levels of market stress than pre-crisis. Mapping these changes in liquidity premia to GDP, via their impact on the cost of borrowing for corporates in the real economy, the results of the model suggest that under normal market conditions there may be a greater cost of regulation via corporate bond markets than incorporated in earlier studies. However, once offset against the benefits of greater dealer resilience, including the benefits to market functioning, there remain net benefits to new regulations. |
| Keywords: | Regulation; market liquidity; dealer intermediation; corporate bonds; cost-benefit analysis |
| JEL: | G12 G23 G24 G29 |
| Date: | 2017–07–14 |
| URL: | http://d.repec.org/n?u=RePEc:boe:boeewp:0665&r=mst |