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on Market Microstructure |
| By: | Cebiroglu, Gökhan; Hautsch, Nikolaus; Horst, Ulrich |
| Abstract: | We develop a model of an order-driven exchange competing for order flow with off-exchange trading mechanisms. Liquidity suppliers face a trade-off between benefits and costs of order exposure. If they display trading intentions, they attract additional trade demand. We show, in equilibrium, hiding trade intentions can induce mis-coordination between liquidity supply and demand, generate excess price fluctuations and harm price efficiency. Econometric high-frequency analysis based on unique data on hidden orders from NASDAQ reveals strong empirical support for these predictions: We find abnormal reactions in prices and order flow after periods of high excess-supply of hidden liquidity. |
| Keywords: | liquidity externalities,order flow,trade signaling,limit order book |
| JEL: | G02 G10 G23 |
| Date: | 2014 |
| URL: | http://d.repec.org/n?u=RePEc:zbw:cfswop:468&r=mst |
| By: | Songzi Du; Haoxiang Zhu |
| Abstract: | This paper studies the welfare consequence of increasing trading speed in financial markets. We build and solve a dynamic trading model, in which traders receive private information of asset value over time and trade strategically with demand schedules in a sequence of double auctions. A stationary linear equilibrium and its efficiency properties are characterized explicitly in closed form. Slow trading (few double auctions per unit of time) serves as a commitment device that induces aggressive demand schedules, but fast trading allows more immediate reaction to new information. If all traders have the same speed, the socially optimal trading frequency tends to be low for scheduled arrivals of information but high for stochastic arrivals of information. If traders have heterogeneous trading speeds, fast traders prefer the highest feasible trading frequency, whereas slow traders tend to prefer a strictly lower frequency. |
| JEL: | D44 D82 G14 |
| Date: | 2014–10 |
| URL: | http://d.repec.org/n?u=RePEc:nbr:nberwo:20588&r=mst |
| By: | Wensheng Kang; Ronald A. Ratti; Kyung Hwan Yoon |
| Abstract: | This paper examines the impact of structural oil price shocks on the covariance of U.S. stock market return and stock market volatility. We construct from daily data on return and volatility the covariance of return and volatility at monthly frequency. The measures of daily volatility are realized-volatility at high frequency (normalized squared return), conditional-volatility recovered from a stochastic volatility model, and implied-volatility deduced from options prices. Positive shocks to aggregate demand and to oil-market specific demand are associated with negative effects on the covariance of return and volatility. Oil supply disruptions are associated with positive effects on the covariance of return and volatility. The spillover index between the structural oil price shocks and covariance of stock return and volatility is large and highly statistically significant. |
| Keywords: | Stock return and volatility, oil price shocks, stock volatility, structural VAR |
| JEL: | E44 G10 Q41 Q43 |
| Date: | 2014–11 |
| URL: | http://d.repec.org/n?u=RePEc:een:camaaa:2014-71&r=mst |
| By: | Starr, Ross M. |
| Keywords: | Social and Behavioral Sciences |
| Date: | 2014–11–12 |
| URL: | http://d.repec.org/n?u=RePEc:cdl:ucsdec:qt1vk1k4fm&r=mst |
| By: | Guglielmo Maria Caporale; Luis Gil-Alana; Alex Plastun |
| Abstract: | This paper examines short-term price reactions after one-day abnormal price changes and whether they create exploitable profit opportunities in various financial markets. A t-test confirms the presence of overreactions and also suggests that there is an «inertia anomaly», i.e. after an overreaction day prices tend to move in the same direction for some time. A trading robot approach is then used to test two trading strategies aimed at exploiting the detected anomalies to make abnormal profits. The results suggest that a strategy based on counter-movements after overreactions does not generate profits in the FOREX and the commodity markets, but it is profitable in the case of the US stock market. By contrast, a strategy exploiting the «inertia anomaly» produces profits in the case of the FOREX and the commodity markets, but not in the case of the US stock market. |
| Keywords: | Efficient Market Hypothesis, anomaly, overreaction hypothesis, abnormal returns, contrarian strategy, trading strategy, trading robot, t-test |
| JEL: | G12 G17 C63 |
| Date: | 2014 |
| URL: | http://d.repec.org/n?u=RePEc:diw:diwwpp:dp1423&r=mst |
| By: | Simone Cirillo; Stefan Lloyd; Peter Nordin |
| Abstract: | We propose a Genetic Programming architecture for the generation of foreign exchange trading strategies. The system's principal features are the evolution of free-form strategies which do not rely on any prior models and the utilization of price series from multiple instruments as input data. This latter feature constitutes an innovation with respect to previous works documented in literature. In this article we utilize Open, High, Low, Close bar data at a 5 minutes frequency for the AUD.USD, EUR.USD, GBP.USD and USD.JPY currency pairs. We will test the implementation analyzing the in-sample and out-of-sample performance of strategies for trading the USD.JPY obtained across multiple algorithm runs. We will also evaluate the differences between strategies selected according to two different criteria: one relies on the fitness obtained on the training set only, the second one makes use of an additional validation dataset. Strategy activity and trade accuracy are remarkably stable between in and out of sample results. From a profitability aspect, the two criteria both result in strategies successful on out-of-sample data but exhibiting different characteristics. The overall best performing out-of-sample strategy achieves a yearly return of 19%. |
| Date: | 2014–11 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:1411.2153&r=mst |
| By: | Baruník, Jozef; Vácha, Lukáš |
| Abstract: | We introduce wavelet-based methodology for estimation of realized variance allowing its measurement in the time-frequency domain. Using smooth wavelets and Maximum Overlap Discrete Wavelet Transform, we allow for the decomposition of the realized variance into several investment horizons and jumps. Basing our estimator in the two-scale realized variance framework, we are able to utilize all available data and get feasible estimator in the presence of microstructure noise as well. The estimator is tested in a large numerical study of the finite sample performance and is compared to other popular realized variation estimators. We use different simulation settings with changing noise as well as jump level in different price processes including long memory fractional stochastic volatility model. The results reveal that our wavelet-based estimator is able to estimate and forecast the realized measures with the greatest precision. Our timefrequency estimators not only produce feasible estimates, but also decompose the realized variation into arbitrarily chosen investment horizons. We apply it to study the volatility of forex futures during the recent crisis at several investment horizons and obtain the results which provide us with better understanding of the volatility dynamics. |
| Keywords: | quadratic variation,realized variance,jumps,market microstructure noise,wavelets |
| Date: | 2014 |
| URL: | http://d.repec.org/n?u=RePEc:zbw:fmpwps:16&r=mst |