Dynamics of Trade-By-Trade Price Movements: Decomposition and Models

By Tina Hviid Rydberg, N. Shephard. 2003

291 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/eac0b40f9b7abed7996b72315dd796a0a6a6ff7a

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In Economics and Econometrics

Citations in the corpus

Direct Estimation of Equity Market Impact (2005, background): “Rydberg and Shephard (2003) develop a rich econometric framework for describing price motions; Dufour and Engle (2000) investigate the key role of waiting time between successive trades.”
Integer-valued Lévy processes and low latency financial econometrics (2012, methodology): “This component view of high-frequency data echoes earlier work by, for example, Engle (2000), Rydberg and Shephard (2003), Barndorff-Nielsen et al. (2009) and Russell and Engle (2010).”
Predicting Bid–Ask Spreads Using Long‐Memory Autoregressive Conditional Poisson Models (2011, unknown): “Since bid-ask spreads are strictly positive but the Poisson distributions (and extensions thereof) are defined on N ∪ {0}, we follow Rydberg and Shephard (2003) and shift the spread distributions without loss of generality by one tick to the left.”
Capturing the Zero: A New Class of Zero-Augmented Distributions and Multiplicative Error Processes (2010, unknown): “(30) This type of transformation was suggested in a similar setting by Rydberg and Shephard (2003) and accounts for the multicollinearity between the lags of yt and It.”
A Discrete-State Continuous-Time Model of Financial Transactions Prices and Times (2005, unknown): “Rydberg and Shephard (2000, 2003) have proposed an alternative model for discrete price movements, Bauwens and Giot (2003) have proposed an alternative competing risk model, and Prigent, Renault, and Scaillet (2001) have applied the two-state ACM model suggested here in an option pricing setting.”
Forecasting the direction of the US stock market with dynamic binary probit models (2011, methodology): “…qualitative models such as traditional static logit and probit models were considerd by Leung, Daouk, and Chen (2000) whereas Hong and Chung (2003), Rydberg and Shephard (2003), and Anatolyev and Gospodinov (2007) used the so-called autologistic model to predict the return direction.”
Leverage and Volatility Feedback Effects in High-Frequency Data (2006, methodology): “The one-factor affine stochastic volatility model, first studied in the context of option pricing by Scott (1987) and later analyzed more formally by Heston (1993), is arguably the most widely used continuous-time stochastic volatility model in finance.”
A General Framework for Observation Driven Time-Varying Parameter Models (2008, unknown): “In addition to the GARCH and MEM classes of models, the GAS framework also encompasses the time-varying binomial models of Cox (1958) and Rydberg and Shephard (2003), the ACM model of Russell and Engle (2005), and some of the Poisson models in Davis et al. (2003).”
A Reduced Form Framework for Modeling Volatility of Speculative Prices Based on Realized Variation Measures (2007, background): “3 The idea of modeling the jump process in terms of the occurrence and the size of the jumps has a natural precedent in the bin model for tick-by-tick transaction prices proposed by Rydberg and Shephard (2003) .”
Realistic Statistical Modelling of Financial Data (2000, methodology): “Forecasts can be calculated on the basis on both the model developed in Russell and Engle (1998) and Rydberg and Shephard (1998a).”
Semantic Frames to Predict Stock Price Movement (2013, methodology): “In contrast to the ADS model, our approach does not calculate the conditional probability of each factor.”