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on Market Microstructure |
| By: | Herrmann, Klaus; Teis, Stefan; Yu, Weijun |
| Abstract: | The adjusted measure of realized volatility suggested in [20] is applied to high- frequency orderbook and transaction data of DAX and BUND futures from EU- REX in order to identify the drivers of intraday volatility. Four components are identified to have predictive power: an auto-regressive pattern, a seasonal pattern, long-term memory and scheduled data releases. These components are analyzed in detail. Some evidence for two additional components, market microstrucuture events and unscheduled news, is given. Depending on the sampling frequency we estimate that between one and two thirds of the variation in realized volatility can be predicted by a simple linear model based on the components identified. It is shown how the predictive power of the different components depends on sampling frequencies. |
| Keywords: | volatility,realized variance,intraday seasonality,volatility prediction,high-frequency data,tick data,fractional integration,sampling frequency |
| Date: | 2014 |
| URL: | http://d.repec.org/n?u=RePEc:zbw:iwqwdp:152014&r=mst |
| By: | Gianbiagio Curato; Jim Gatheral; Fabrizio Lillo |
| Abstract: | We study the problem of the optimal execution of a large trade in the presence of nonlinear transient impact. We propose an approach based on homotopy analysis, whereby a well behaved initial strategy is continuously deformed to lower the expected execution cost. We find that the optimal solution is front loaded for concave impact and that its expected cost is significantly lower than that of conventional strategies. We then consider brute force numerical optimization of the cost functional; we find that the optimal solution for a buy program typically features a few short intense buying periods separated by long periods of weak selling. Indeed, in some cases we find negative expected cost. We show that this undesirable characteristic of the nonlinear transient impact model may be mitigated either by introducing a bid-ask spread cost or by imposing convexity of the instantaneous market impact function for large trading rates. |
| Date: | 2014–12 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:1412.4839&r=mst |
| By: | Xuefeng Gao; J. G. Dai; A. B. Dieker; S. J. Deng |
| Abstract: | Motivated by optimal trade execution, this paper studies the temporal evolution of the shape of a limit order book over a time horizon that is large compared with the length of time between order book events, with the aim of approximating the transient distribution of the shape. Relying on the stochastic order book model in Cont et al. (2010), we show that when the tick size approaches zero, a pair of measure-valued processes representing the "sell-side shape" and "buy-side shape" of an order book converges to a pair of deterministic measure-valued processes in a certain sense. Moreover, we describe the density profile of the limiting processes through ordinary differential equations which can be solved explicitly. We also perform experiments to test our limiting model against data. The empirical results suggest that the approximation is effective. |
| Date: | 2014–11 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:1411.7502&r=mst |
| By: | Li, Dan (Board of Governors of the Federal Reserve System (U.S.)); Schurhoff, Norman (Swiss Finance Institute) |
| Abstract: | Dealers in over-the-counter securities form networks to mitigate search frictions. The audit trail for municipal bonds shows the dealer network has a core-periphery structure. Central dealers are more efficient at matching buyers and sellers than peripheral dealers, which shortens intermediation chains and speeds up trading. Investors face a tradeoff between execution speed and cost. Central dealers provide immediacy by pre-arranging fewer trades and holding larger inventory. However, trading costs increase strongly with dealer centrality. Investors with strong liquidity need trade with central dealers and at times of market-wide illiquidity. Central dealers thus serve as liquidity providers of last resort. |
| Keywords: | Municipal bonds; over-the-counter financial market; network analysis; trading cost; liquidity; immediacy; transparency |
| JEL: | G12 G14 G24 |
| Date: | 2014–11–10 |
| URL: | http://d.repec.org/n?u=RePEc:fip:fedgfe:2014-95&r=mst |
| By: | Giovanni Cespa (Cass Business School, CEPR, and CSEF); Xavier Vives (IESE Business School) |
| Abstract: | Short-termism need not breed informational price inefficiency even when generating Beauty Contests. We demonstrate this claim in a two-period market with persistent liquidity trading and risk-averse, privately informed, short-term investors and find that prices reect average expectations about fundamentals and liquidity trading. Informed investors engage in "retrospective" learning to reassess inferences (about fundamentals) made during the trading game's early stages. This behavior introduces strategic complementarities in the use of information and can yield two stable equilibria that can be ranked in terms of liquidity, volatility, and informational efficiency. We derive implications that explain market anomalies as well as empirical regularities. |
| Keywords: | price speculation, multiple equilibria, average expectations, public information, momentum and reversal |
| JEL: | G10 G12 G14 |
| Date: | 2014–11–26 |
| URL: | http://d.repec.org/n?u=RePEc:sef:csefwp:383&r=mst |
| By: | Michael Bleaney (Department of Economics, Maastricht University); Spiros Bougheas (University of Nottingham, School of Economics); Zhiyong Li (University of Nottingham, School of Economics) |
| Abstract: | Research in both economics and psychology suggests that, when agents predict the next value of a random series, they frequently exhibit two types of biases, which are called the gambler’s fallacy (GF) and the hot hand fallacy (HHF). The gambler’s fallacy is to expect a negative correlation in a process which is in fact random. The hot hands fallacy is more or less the opposite of this – to believe that another heads is more likely after a run of heads. The evidence for these fallacies comes largely from situations where they are not punished (lotteries, casinos and laboratory experiments with random returns). In many real-world situations, such as in financial markets, succumbing to fallacies is costly, which gives an incentive to overcome them. The present study is based on high-frequency data from a market-maker in the foreign exchange market. Trading behaviour is only partly explained by the rational exploitation of past patterns in the data, but there is also evidence of the gambler’s fallacy: a tendency to sell the dollar after it has risen persistently or strongly. |
| Keywords: | Gambler’s Fallacy, Hot hand Fallacy, Foreign Exchange Market |
| URL: | http://d.repec.org/n?u=RePEc:not:notcdx:2014-17&r=mst |
| By: | Tim Bollerslev (Duke University, NBER and CREATES); Sophia Zhengzi Li (Michigan State University); Viktor Todorov (Northwestern University and CREATES) |
| Abstract: | Motivated by the implications from a stylized equilibrium pricing framework, we investigate empirically how individual equity prices respond to continuous, or \smooth," and jumpy, or \rough," market price moves, and how these different market price risks, or betas, are priced in the cross-section of expected returns. Based on a novel highfrequency dataset of almost one-thousand individual stocks over two decades, we find that the two rough betas associated with intraday discontinuous and overnight returns entail significant risk premiums, while the intraday continuous beta is not priced in the cross-section. An investment strategy that goes long stocks with high jump betas and short stocks with low jump betas produces significant average excess returns. These higher risk premiums for the discontinuous and overnight market betas remain significant after controlling for a long list of other firm characteristics and explanatory variables previously associated with the cross-section of expected stock returns. |
| Keywords: | Market price risks, jump betas, high-frequency data, cross-sectional return variation |
| JEL: | C13 C14 G11 G12 |
| Date: | 2014–12–04 |
| URL: | http://d.repec.org/n?u=RePEc:aah:create:2014-48&r=mst |