This is an example of how data analytics computed over high-frequency data can be used for estimating trading costs (e.g. in a pre-trade market-impact analysis). This demo is illustrative only, please read the fine print below for the disclaimer.
Parameters for an institutional trade:



The example is based on objective market data for a quantitative analysis only. We base our results on estimations provided in the literature for US equities. The inputs to the model are calculated using Ticksmith's data platform.

Among the many things that could be wrong in these results: the model could be wrong, the model might not generalize beyond the 2008-2012, the model might only be applicable to US equities and hence not be used for Canadian equities as is done above, the model could assume that the various inputs are calculated differently than the way I decided to do it (in particular, there exists many ways for calculating price volatility when using high-frequency data), etc. Finally, we have added to the model the cost associated with the trading direction. We have also interpolated the estimated values in order to allow for a range of participation rates. For all these reasons, the above estimates should be taken as illustrative only.

This demo is provided for general information purposes only. In particular, it does not constitute investment research, advice, or any form of recommendation relating to financial transactions.