System and method for behavioral finance

• US 20060036542A1
• Filed: 07/08/2005
• Published: 02/16/2006
• Est. Priority Date: 07/09/2004
• Status: Abandoned Application

• Current Assignee: Douglas S. McNair
• Original Assignee: Douglas S. McNair
• Inventors: McNair, Douglas S.
• Application Number:
  US11/176,940
• Publication Number:
  US 20060036542A1
• Time in Patent Office: Days
• US Class Current: 705/39
• CPC Class Codes: G06Q 20/10 specially adapted for electronic funds transfer [EFT] systems; specially adapted for home banking systems
• CPC Class Codes: G06Q 40/04 Trading; Exchange, e.g. stocks, commodities, derivatives or currency exchange

Abstract

A system suitable for an automated investment share price pattern search includes a computer, a historical information database accessible by the computer having historical information for a plurality of investments stored thereon, a connection to a supply of real-time or historical timeseries data, the data comprising real-time or historical data relating to a plurality of investments. Software executing on the computer generates an investment classification for the investment to be examined based upon the historical information and the real-time data relating to the investment or investments to be examined. The process gathers price and volume data of listed firms from arbitrarily many stock markets. The invention uses the statistics of asymmetric stochastic volatility (ASV) to classify and associate the recent fluctuations in share price with a recommended action: sell, buy, or hold.

Claims

1. A method for generating markup for annotating a chart of timeseries data, wherein a volatility feature set of technical event data related to the timeseries data is stored in a database, the method comprising:

(a) receiving, from a client, a request for markup information related to an event;

(b) performing pattern recognition on the timeseries data based on an asymmetric stochastic volatility characterizing the timeseries data to characterize and classify features in the timeseries data;

(c) determining markup tags in accordance with the features which are characterized and classified in step (b);

(d) assembling the markup tags determined in step (c), in accordance with a markup format, to generate a markup annotation for the event, the markup annotation containing the markup information requested in step (a); and

(e) sending the markup annotation to the client.

2. The method of claim 1, further including, at the client, displaying the timeseries as a chart, and annotating the chart in accordance with the markup information.

3. The method of claim 2, further including analyzing and manipulating the markup information at the client.

4. The method of claim 1, wherein the request specifies a desired format for the markup information.

5. The method of claim 4, wherein the desired format is XML.

6. The method of claim 1, wherein the features are selected in accordance with the request.

7. An automated stock timeseries pattern search system comprising:

a computer;

a historical information database accessible by said computer, said historical information database having historical information for a plurality of investments stored thereon;

a connection to a supply of real-time data, said real-time data comprising real-time data relating to said plurality of investments;

chart-generating software executing on said computer for generating an investment chart for the stock or stocks to be examined based upon the historical information and the real-time data relating to the stock or stocks to be examined;

pattern-recognition software executing on said computer for performing pattern recognition on the historical information and the real-time data based on an asymmetric stochastic volatility characterizing the historical information and the real-time data to characterize and classify features in the historical information and the real-time data; and

markup software executing on said computer for retrieving asymmetric stochastic volatility markup annotations and for displaying the investment chart with annotations to determine if a pattern exists in the historical information and the real-time data.

8. The system of claim 7, further comprising pre-screening software executing on said computer for pre-screening the historical information and the real-time data relating to an investment to be examined to determine whether the investment to be examined meets a threshold value for liquidity, and wherein said pattern-recognition software executing on said computer performs the asymmetric stochastic volatility analysis if the investment to be examined meets the threshold value for liquidity.

9. The system of claim 8, wherein the investment to be examined is determined to meet the threshold value for the asymmetric stochastic volatility analysis.

10. The system of claim 8, further comprising software executing on said computer for examining a last point of the stock timeseries to determine whether the fundamental event is favorable or unfavorable, and whether the associated technical event in the share price will be a breakup or breakdown (“

gap-up”

or “

gap-down”

).