Bin Models for Trade-by-trade Data. Modelling the Numberof Trades in a Xed Interval of Time

@inproceedings{Rydberg1999BinMF,
  title={Bin Models for Trade-by-trade Data. Modelling the Numberof Trades in a Xed Interval of Time},
  author={Tina Hviid Rydberg},
  year={1999}
}
In this paper we propose a simple time series model of the number of transactions made in intervals of length seconds. We call this model the BIN model. The properties of the BIN model are evaluated while we explore connections between this model and Cox processes | that is Poisson processes with random intensities. We apply the modelling framework to data on trades in IBM shares. Some keywords Aggregation, BIN model, Compound processes, Cox process, Trade-by-trade data. All of the papers on… CONTINUE READING

References

Publications referenced by this paper.
Showing 1-10 of 40 references

The statistical analysis of dependencies in point processes

D. R. Cox
P. A. P. Lewis (Ed.), Symposium on Point Processes, pp. 55{66. New York: Wiley and Sons. • 1972
View 5 Excerpts
Highly Influenced

Non{Gaussian OU based models and some of their uses in nancial economics

O. E. Barndor -Nielsen, N. Shephard
Unpublished discussion paper: Nu eld College, Oxford. • 1999
View 10 Excerpts
Highly Influenced

Dynamics of trade-by-trade price movements : decomposition and models

BNP Paribas, Harewood Avenue
1998
View 6 Excerpts
Highly Influenced

Autoregressive conditional heteroskedasticity with estimates of the variance of the United Kingdom in ation

R. F. Engle
Econometrica 50, 987{1007. • 1982
View 8 Excerpts
Highly Influenced

Forecasting transaction rates: the autoregressive conditional duration model

R. F. Engle, J. R. Russell
Econometrica 66, 1127{1162. • 1998
View 3 Excerpts
Highly Influenced

Modelling high frequency data in continuous time

N. Meddahi, E. Renault, B. Werker
Unpublished paper: CIRANO, CRDE, Montreal University. • 1998
View 1 Excerpt
Highly Influenced

Nonlinear ltering techniques for estimation and risk management in partially observed stochastic volatility models

R. Frey, W. Runggaldier
Unpublished paper: Mathematics Department, EZH. • 1998
View 3 Excerpts
Highly Influenced

Stochastic Volatility Duration Models

View 1 Excerpt
Highly Influenced

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