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on Market Microstructure |
| By: | Noss, Joseph (Bank of England); Pedace, Lucas (Bank of England); Tobek, Ondrej (University of Cambridge); Linton, Oliver (University of Cambridge); Crowley-Reidy, Liam (Bank of England) |
| Abstract: | This paper provides an in-depth analysis of the evolution of liquidity during the flash episode in sterling during the early hours of 7 October 2016. It examines a number of estimates both of the cost of trading, and the price impact of executed transactions. These include a variant of the ‘volatility over volume’ measure of liquidity based on transaction data, which provides a better proxy of illiquidity — as given by measures based on high-frequency limit order book data — than other summary measures of price impact. The paper also shows that the fall in the value of sterling during the initial part of the flash episode was consistent with the estimated impact on prices of a large number of individually small — but in aggregate large — volume of orders to sell sterling during a normally quiet period of the trading day. However, the subsequent change in price was larger than that consistent with the estimated impact on prices of observed orders to sell sterling. This might support the suggestion, which was included in the report on the episode provided by the Bank for International Settlements, that the move in sterling may have been amplified by the pause in trading on the CME futures exchange. |
| Keywords: | Flash crash; foreign exchange market; liquidity; price impact |
| JEL: | F33 F37 G01 G15 |
| Date: | 2017–10–27 |
| URL: | http://d.repec.org/n?u=RePEc:boe:boeewp:0687&r=mst |
| By: | Auld, T.; Linton, O. |
| Abstract: | We study the behaviour of the Betfair betting market and the sterling/dollar exchange rate (futures price) during 24 June 2016, the night of the EU referendum. We investigate how the two markets responded to the announcement of the voting results. We employ a Bayesian updating methodology to update prior opinion about the likelihood of the final outcome of the vote. We then relate the voting model to the real time evolution of the market determined prices. We find that although both markets appear to be inefficient in absorbing the new information contained in vote outcomes, the betting market is apparently less inefficient than the FX market. The different rates of convergence to fundamental value between the two markets leads to highly profitable arbitrage opportunities. |
| Keywords: | EU Referendum, Prediction Markets, Machine Learning, Efficient Markets Hypothesis, Pairs Trading, Cointegration, Bayesian Methods, Exchange Rates |
| Date: | 2017–11–07 |
| URL: | http://d.repec.org/n?u=RePEc:cam:camdae:1750&r=mst |
| By: | Martin Magris; Perttu Barholm; Juho Kanniainen |
| Abstract: | The main purpose of this work is to examine the behavior of the implied volatility smiles around jumps, contributing to the literature with a high-frequency analysis of the smile dynamics based on intra-day option data. From our high-frequency SPX S\&P500 index option dataset, we utilize the first three principal components to characterize the implied volatility smile and analyze its dynamics by the distribution of the scores' means and variances and other statistics for the first hour of the day, in scenarios where jumps are detected and not. Our analyses clearly suggest that changes in the volatility smiles have abnormal properties around jumps compared with the absence of jumps, regardless of maturity and type of the option. |
| Date: | 2017–11 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:1711.02925&r=mst |