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1. WO2007149378 - ALGORITHMIC TRADING SYSTEM AND METHOD

Note: Text based on automatic Optical Character Recognition processes. Please use the PDF version for legal matters

[ EN ]

WE CLAIM:
1. A method for constructing an order book for a tradable asset, said order book including hidden orders, said method comprising steps of:
measuring an effective spread of the tradable asset;
measuring a mid-quote volatility of the tradable asset;
measuring additions between best bid and ask of the tradable asset;
measuring additions less cancellations of the tradable asset;
calculating a probability of a hidden order for the tradable asset as a function of the effective spread, the mid-quote volatility, additions between best bid and ask, and additions less cancellations;
calculating a hidden order volume between the best bid and ask; and
calculating a hidden order price.

2. The method in accordance with claim 1 wherein the probability of a hidden order is also a function of the time of day.

3. A system for constructing an order book for a tradable asset, said order book including hidden orders, said system comprising:
means for measuring an effective spread of the tradable asset;
means for measuring a mid-quote volatility of the tradable asset;
means for measuring additions between best bid and ask of the tradable asset;
means for measuring additions less cancellations of the tradable asset;
means for calculating a probability of a hidden order for the tradable asset as a function of the effective spread, the mid-quote volatility, additions between best bid and ask, and additions less cancellations;
means for calculating a hidden order volume between the best bid and ask; and
means for calculating a hidden order price.

4. The system according to claim 3, further comprising means for merging the calculated hidden order volume and hidden order price with a displayed order book.

5. A computer-readable medium storing computer-executable instructions for constructing an order book for a tradable asset, said order book including hidden orders, by performing operations comprising:
measuring an effective spread of the tradable asset;
measuring a mid-quote volatility of the tradable asset;
measuring additions between best bid and ask of the tradable asset;
measuring additions less cancellations of the tradable asset;
calculating a probability of a hidden order for the tradable asset as a function of the effective spread, the mid-quote volatility, additions between best bid and ask, and additions less cancellations;
calculating a hidden order volume between the best bid and ask; and
calculating a hidden order price.

6. The method in accordance with claim 1 wherein the probability of a hidden order is also a function of the time of day.

7. A method for creating a model for calculating a probability and a characteristic of a hidden order for a tradable asset, said method comprising the steps of:
accessing a plurality of trading messages from a trading forum fora predefined period of time, each message including information about one or more orders for tradable assets or executed trades for tradable assets, said order information including identification of a tradable asset, a price, and a quantity;
identifying executed trades from said messages;
classifying a trade from the identified trades as displayed if the trade can be matched to orders in said messages;
classifying a trade as hidden where said trade cannot be matched to orders in said messages;
determining a side of each order corresponding to a trade classified as hidden;
calculating a hidden trade volume and a hidden trade location for tradable assets based upon said classifying steps and said determining step;

grouping each tradable asset in the plurality of tradable assets into one of a plurality of liquidity groups based upon said each tradable asset's median trade volume over a pre-determined liquidity period;
calculating for each tradable asset in the plurality of tradable assets at least one market condition; and
calculating for a liquidity group a coefficient associating the at least one market condition with at least one of said hidden trade volume and said hidden trade location.

8. The method according to claim 7 wherein the pre-determined liquidity period is a 21 -day period coinciding with a first 21-days of the plurality of trading messages.

9. The method according to claim 7, wherein the market condition comprises at least one of the an effective spread, a mid-quote volatility, additions between best bid and ask, average first level depth, order placements, order cancellations, and additions less cancellations over a pre-determined trading horizon

10. The method according to claim 7 wherein the number of liquidity groups is 11.

11. The method of claim 7 wherein the real-time trading messages are obtained from ARCA Comstock L1 and L2 feeds.

12. The method of claim 7 wherein the trading messages are obtained from a direct exchange l_2 feed.

13. The method of claim 7 wherein at least one coefficient x is standardized as Standard) by 'ts corresponding mean and standard deviation over a pre-determined prior standardization period.

14. The method of claim 13 wherein the pre-determined prior standardization period is the prior three months.

15. The method of claim 14, wherein the standardized coefficient Λf(staπdard) is

computed using the formula X,,anάaτΛ
— — where x is the mean over the precox)
determined prior standardization period and σ (x) is the standard deviation of x over the pre-determined prior standardization period.

16. The method of claim 7 further comprising a step of estimating a
McFadden's LRI to approximate a pseudo R2 for assessing the goodness of fit of a coefficient.