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on Market Microstructure |
| By: | Taiga Saito (Graduate School of Economics, University of Tokyo. Former research fellow at Financial Research Center in Financial Services Agency, Government of Japan.); Takanori Adachi (BKC Research Organization of Social Sciences, Ritsumeikan University); Teruo Nakatsuma (Department of Economics, Keio University); Akihiko Takahashi (Graduate School of Economics, University of Tokyo); Hiroshi Tsuda (Department 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 par- ticipants 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 open- ing 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 ndings 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 pro t in the price falling days and particularly, the aggressive servers in the server type make most of the pro t. 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:cfi:fseres:cf411&r=mst |
| By: | Federico Gonzalez; Mark Schervish |
| Abstract: | We propose a limit order book (LOB) model with dynamics that account for both the impact of the most recent order and the shape of the LOB. We present an empirical analysis showing that the type of the last order significantly alters the submission rate of immediate future orders, even after accounting for the state of the LOB. To model these effects jointly we introduce a discrete Markov chain model. Then on these improved LOB dynamics, we find the policy for optimal order choice and placement in the share purchasing problem by framing it as a Markov decision process. The optimal policy derived numerically uses limit orders, cancellations and market orders. It looks to exploit the state of the LOB summarized by the volume at the bid/ask and the type of the most recent order to obtain the best execution price, avoiding non-execution and adverse selection risk simultaneously. Market orders are used aggressively when the mid-price is expected to move adversely. Limit orders are placed under favorable LOB conditions and canceled when non-execution or adverse selection probability is high. Using ultra high-frequency data from the NASDAQ stock exchange we compare our optimal policy with other submission strategies that use a subset of all available order types and show that ours significantly outperforms them. |
| Date: | 2017–07 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:1707.01167&r=mst |
| By: | Biais, Bruno; Declerck, Fany; Moinas, Sophie |
| Abstract: | Who provides liquidity in modern, electronic limit order book, markets? While agency trading can be constrained by conflicts of interest and information asymmetry between customers and traders, prop traders are likely to be less constrained and thus better positioned to carry inventory risk. Moreover, while slow traders'limit orders may be exposed to severe adverse selection, fast trading technology can improve traders'ability to monitor the market and avoid being picked off. To shed light on these points, we rely on unique data from Euronext and the AMF enabling us to observe the connectivity of traders to the market, and whether they are proprietary traders. We find that proprietary traders, be they fast or slow, provide liquidity with contrarian marketable orders, thus helping the market absorb shocks, even during crisis, and earn profits doing so. Moreover, fast traders provide liquidity by leaving limit orders in the book. Yet, only prop traders can do so without making losses. This suggests that technology is not enough to overcome adverse selection, monitoring incentives are also needed. |
| Keywords: | Liquidity; high-frequency trading; proprietary trading; adverse selection; electronic limit order book; short-term momentum; contrarian. |
| JEL: | D82 G1 |
| Date: | 2017–06 |
| URL: | http://d.repec.org/n?u=RePEc:ide:wpaper:31762&r=mst |
| By: | Hollifield, Burton (Tepper School of Business Carnegie Mellon University); Sandås, Patrik (McIntire School of Commerce University of Virginia); Todd, Andrew (University of Virginia) |
| Abstract: | We measure the incidence of latency arbitrage for cross-listed stocks around the time of an exogenous shock that made the markets faster. Our sample is from NASDAQ Nordic and consists of Nordic blue chip firms listed and traded in multiple markets. We document a sharp decline in the incidence of cross-market arbitrage opportunities across the Nordic markets for cross-listed stocks from 2009 to 2010 and later. Over the five year sample period 77% of the observed cross-market arbitrage opportunities occurred in 2009 and 13% in 2010 and the remaining 10% spread over the last three years. The inside spread declines by, on average, 14.5 basis points or 53% from 2009 to 2013. Our results point to significant improvements in market efficiency and market quality as a result of the switch to a faster trading system. |
| Keywords: | Cross-market Arbitrage; Information Eciency; High Frequency Trading |
| JEL: | G10 G14 G15 |
| Date: | 2017–05–01 |
| URL: | http://d.repec.org/n?u=RePEc:hhs:rbnkwp:0338&r=mst |
| By: | Ripamonti, Alexandre |
| Abstract: | This paper tests the validity of the Corwin-Schultz bid-ask spread estimator in the Brazilian stock market. The Corwin-Schultz estimator arises as an easy way to compute asymmetric information throughout daily high and low stock prices for estimating overnight and non-negative adjusted spreads. The sample consisted of Ibovespa firms from 1986 to 2014 and was analysed with time series econometrics. The findings show that the measures of spread have stationarity properties, allowing for forecasting in a period of lagged variables, besides having the property of time-varying cointegration with market-to-book ratio, debt on equity, size and return and also presenting sensibility to different periods, industries and listing segments. Thus, the Corwin-Schultz bid-ask spread estimator seems to be a valid and reliable measure for forecasting aggregate-data variables through the weighted average of firm-level variables. |
| Keywords: | Corwin-Schultz bid-ask spread estimator; asymmetric information; market microstructure; time varying cointegration |
| JEL: | G11 G17 G39 |
| Date: | 2016 |
| URL: | http://d.repec.org/n?u=RePEc:pra:mprapa:79459&r=mst |
| By: | Carol Osler (Brandeis University); Alasdair Turnbull (Clarkson University) |
| Abstract: | This paper develops a model of dealer conduct – and misconduct – at the London 4 pm fix, a major currency market benchmark. The analysis clarifies the dealers’ incentives and strategies, helps explain why fix volatility remains high despite reforms, and provides insights relevant to benchmark design. Fix prices will be unusually volatile without collusion. Collusion is profitable because it shuts down a form of free-riding in which dealers front-run each other. The price trend accelerates more as the fix approaches under collusion than under independent trading. Statistical tests detect this shift around 2008, when major banks admit their dealers began colluding. |
| Date: | 2016–03 |
| URL: | http://d.repec.org/n?u=RePEc:brd:wpaper:101r&r=mst |