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on Market Microstructure |
| By: | Mila Getmansky; Ravi Jagannathan; Loriana Pelizzon; Ernst Schaumburg; Darya Yuferova |
| Abstract: | We study two fast crashes using orders/cancellations/trades data with trader identities for a stock trading in the spot and single stock futures markets on the National Stock Exchange of India during April-June/2006 when there was no algorithmic trading. Spot (futures) prices fell by 6.1% (4.6%) and 11.1% (12.3%) within 15 minutes during crashes. Buying by capital constrained short-term-traders who were the primary intraday liquidity providers was not sufficient to halt price decline. Domestic mutual funds, slow to move in, bought sufficient quantities leading to price recovery. Crashes and recoveries began in the spot market though volume was higher in futures. |
| JEL: | G00 G1 G12 G14 G18 G2 |
| Date: | 2017–12 |
| URL: | http://d.repec.org/n?u=RePEc:nbr:nberwo:24098&r=mst |
| By: | Valerii Salov |
| Abstract: | Whether you trade futures for yourself or a hedge fund, your strategy is counted. Long and short position limits make the number of unique strategies finite. Formulas of the numbers of strategies, transactions, do nothing actions are derived. A discrete distribution of actions, corresponding probability mass, cumulative distribution and characteristic functions, moments, extreme values are presented. Strategies time slice distributions are determined. Vector properties of trading strategies are studied. Algebraic not associative, commutative, initial magmas with invertible elements control trading positions and strategies. Maximum profit strategies, MPS, and optimal trading elements can define trading patterns. Dynkin introduced the term interpreted in English as "Markov time" in 1963. Neftci applied it for the formalization of Technical Analysis in 1991. |
| Date: | 2017–12 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:1712.07649&r=mst |