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on Market Microstructure |
By: | Kyungsub Lee; Byoung Ki Seo |
Abstract: | This study examine the theoretical and empirical perspectives of the symmetric Hawkes model of the price tick structure. Combined with the maximum likelihood estimation, the model provides a proper method of volatility estimation specialized in ultra-high-frequency analysis. Empirical studies based on the model using the ultra-high-frequency data of stocks in the S\&P 500 are performed. The performance of the volatility measure, intraday estimation, and the dynamics of the parameters are discussed. A new approach of diffusion analogy to the symmetric Hawkes model is proposed with the distributional properties very close to the Hawkes model. As a diffusion process, the model provides more analytical simplicity when computing the variance formula, incorporating skewness and examining the probabilistic property. An estimation of the diffusion model is performed using the simulated maximum likelihood method and shows similar patterns to the Hawkes model. |
Date: | 2019–08 |
URL: | http://d.repec.org/n?u=RePEc:arx:papers:1908.05089&r=all |
By: | Oleh Danyliv; Bruce Bland; Alexandre Argenson |
Abstract: | Despite the fact that an intraday market price distribution is not normal, the random walk model of price behaviour is as important for the understanding of basic principles of the market as the pendulum model is a starting point of many fundamental theories in physics. This model is a good zero order approximation for liquid fast moving markets where the queue position is less important than the price action. In this paper we present an exact solution for the cost of the static passive slice execution. It is shown, that if a price has a random walk behaviour, there is no optimal limit level for an order execution: all levels have the same execution cost as an immediate aggressive execution at the beginning of the slice. Additionally the estimations for the risk of a limit order as well as the probability of a limit order execution as functions of the slice time and standard deviation of the price are derived. |
Date: | 2019–08 |
URL: | http://d.repec.org/n?u=RePEc:arx:papers:1908.04333&r=all |
By: | Kondor, Péter; Pinter, Gabor |
Abstract: | We propose a new measure of private information in decentralised markets -- connections -- defined as the number of dealers with whom a client trades in a time period. Using proprietary data for the UK government bond market, we show that clients have systematically better performance when having more connections, and this effect is stronger during macroeconomic announcements. Time-variation in market-wide connections also helps explain yield dynamics. Given our novel measure, we present two applications suggesting that (i) dealers pass on information, acquired from their informed clients, to their subsidiaries, and (ii) informed clients better predict the order-flow intermediated by their dealers. |
Keywords: | Client-Dealer Connections; Government Bond Market; private information |
JEL: | G12 G14 G24 |
Date: | 2019–07 |
URL: | http://d.repec.org/n?u=RePEc:cpr:ceprdp:13880&r=all |
By: | Martin Stefan; Claudia Wellenreuther |
Abstract: | Futures for European carbon emission allowances resemble a relatively new class of financial assets that are currently traded on two exchanges: the ICE in London and the EEX in Leipzig. While the former features greater trading volumes, the latter hosts the majority of the primary auctions of ETS emission allowances. This letter, therefore, investigates which of these trading places dominates the carbon price discovery process. The results of various price discovery measures based on a vector error correction model indicate that the ICE leads the price discovery process of carbon futures. |
Keywords: | Carbon, Price Discovery, Information Leadership Share, EUA, Futures Markets, ETS |
Date: | 2019–08 |
URL: | http://d.repec.org/n?u=RePEc:cqe:wpaper:8719&r=all |
By: | Gustavo Fruet Dias (University of East Anglia); Marcelo Fernandes (Sao Paulo School of Economics); Cristina Mabel Scherrer (University of East Anglia) |
Abstract: | We formulate a continuous-time price discovery model and investigate how the standard price discovery measures vary with respect to the sampling interval. We ï¬ nd that the component share measure is invariant to the sampling interval, and hence, discrete-sampled prices suffice to identify the continuous-time component share. In contrast, information share estimates are not comparable across different sampling intervals because the contemporaneous correlation between markets increases in magnitude as the sampling interval grows. We show how to back out the continuous-time information share from discrete-sampled prices under cer-tain assumptions on the contemporaneous correlation. We assess our continuous-time model by comparing the estimates of the (continuous-time) component and information shares at different sampling intervals for 30 stocks in the US. We ï¬ nd that both price discovery measures are typ-ically stable across the different sampling intervals, suggesting that our continuous-time price discovery model ï¬ ts the data very well. |
Keywords: | high-frequency data, price discovery, continuous-time model, sampling interval |
JEL: | C13 C32 C51 G14 |
Date: | 2019–08–16 |
URL: | http://d.repec.org/n?u=RePEc:uea:ueaeco:2019_02&r=all |
By: | Kyungsub Lee; Byoung Ki Seo |
Abstract: | A simple Hawkes model have been developed for the price tick structure dynamics incorporating market microstructure noise and trade clustering. In this paper, the model is extended with random mark to deal with more realistic price tick structures of equities. We examine the impact of jump in price dynamics to the future movements and dependency between the jump sizes and ground intensities. We also derive the volatility formula based on stochastic and statistical methods and compare with realized volatility in simulation and empirical studies. The marked Hawkes model is useful to estimate the intraday volatility similarly in the case of simple Hawkes model. |
Date: | 2019–07 |
URL: | http://d.repec.org/n?u=RePEc:arx:papers:1907.12025&r=all |
By: | Martin, Ian; Papadimitriou, Dimitris |
Abstract: | We present a dynamic model featuring risk-averse investors with heterogeneous beliefs. Individual investors have stable beliefs and risk aversion, but agents who were correct in hindsight become relatively wealthy; their beliefs are overrepresented in market sentiment, so "the market" is bullish following good news and bearish following bad news. Extreme states are far more important than in a homogeneous economy. Investors understand that sentiment drives volatility up, and demand high risk premia in compensation. Moderate investors supply liquidity: they trade against market sentiment in the hope of capturing a variance risk premium created by the presence of extremists. |
Keywords: | Excess Volatility; heterogeneous beliefs; sentiment; Speculation; target prices |
JEL: | E44 G02 G11 G12 G13 |
Date: | 2019–07 |
URL: | http://d.repec.org/n?u=RePEc:cpr:ceprdp:13857&r=all |