Granted Patent B2

US 8,620,789 · App. 13/593,415 · Granted Dec 31, 2013

Inventors: Robert D. Arnott (Newport Beach, CA); Paul Christopher Wood (Waltham, GB); Feifei Li (Irvine, CA)

Assignee: Research Affiliates, LLC

Abstract

Claims (168)

1. A method of constructing a low volatility index comprising:

selecting a geographic subset of a plurality of securities selected from a universe of securities wherein said geographic subset comprises selecting at least one security having a lowest beta from a plurality of securities ranked in order of beta from securities of each geography of said universe;

weighting said geographic subset of securities using a low volatility factor, comprising:

weighting by computing a multiplicative product of a weight of the given geography's security and said low volatility factor, and

reweighting or normalizing said weights of said geographic subset of said plurality of securities to make the geographic subset of securities at least one of: country or region neutral, relative to the weights of said starting universe to form a geographic portfolio (GP) strategy;

selecting a sector subset of a plurality of securities selected from said universe of securities wherein said sector subset comprises selecting at least one security having a lowest beta from a plurality of securities ranked in order of beta from each sector of said universe securities;

weighting said sector subset of securities using a low volatility, comprising:

weighting by computing a multiplicative product of an weight of the given sector security and said low volatility factor, and

reweighting or normalizing said weight of said sector subset of securities to make the sector subset of securities sector neutral relative to the starting universe weight to form a sector portfolio (SP) strategy; and

averaging said geographic portfolio (GP) strategy and said sector portfolio (SP) strategy to obtain final low volatility index weights.

2. The method according to claim 1 , wherein said geographic subset comprises at least one of a country subset for a large country, or a regional subset for a plurality of small countries.

3. The method according to claim 2 , wherein said large country comprises at least one of:

United States;

Japan;

United Kingdom;

France;

Germany;

Canada;

Switzerland;

Netherlands;

Australia;

Italy;

Spain;

any Europe, Middle East, Africa (EMEA)country;

Austria;

Belgium;

Denmark;

Finland;

Greece;

Ireland;

Norway;

Portugal;

Sweden;

Luxembourg;

any Asia Pacific (APAC) country;

Hong Kong;

Singapore; or

New Zealand.

4. The method according claim 1 , wherein each said geographic subset comprises at least one of:

north america,

south america,

europe,

middle east,

africa,

asia,

oceania,

continents,

at least one geographic region, or

at least one economic community.

5. The method according to claim 1 , wherein said geographic subset comprises countries of a given geographic region, less the top ten largest countries comprising at least one of:

South Korea;

Taiwan;

Brazil;

China;

Russian Federation;

South Africa;

India;

any country from AMERICAS;

Argentina;

Chile;

Colombia;

Peru;

Mexico;

any country from Europe, Middle East, Africa (EMEA);

Czech Republic;

Egypt;

Hungary;

Morocco;

Poland;

Turkey;

Israel;

any country from Asia Pacific (APAC);

Indonesia;

Malaysia;

Philippines;

Thailand; or

Pakistan.

6. The method according to claim 1 , wherein said geographic subset comprise countries of a given geographic region, excluding the largest countries and focus on regions of small countries.

7. The method according to claim 1 , wherein said geographic subset comprise countries from at least one of:

Americas;

Europe, Middle East Africa (EMEA); or

Asia Pacific (APAC).

8. The method according to claim 1 , further comprising:

applying a maximum cap on the final low volatility index weights.

9. The method according to claim 8 , wherein said maximum cap comprises 5% of said index.

10. The method according to claim 8 , further comprising:

rebalancing at least one of: annually, quarterly, semi-annually, monthly, or periodically, said final low volatility index weights.

11. The method according to claim 1 , further comprising:

rebalancing annually said final low volatility index weights.

12. The method according to claim 1 , wherein said selecting said geographic subset of securities comprises selecting at least one of:

a number of said plurality of securities;

a percentage of said plurality of securities;

a portion of said plurality of securities;

30% of said plurality of securities;

a single security of said plurality of securities; or

a pair of securities of said plurality of securities.

13. The method according to claim 1 , wherein said universe comprises comprises a non-price accounting data based index (ADBI),

wherein said ADBI comprises an index of securities selected based upon at least one non-price metric, and weighted based upon at least one non-price metric.

14. The method according to claim 13 , wherein said non-price ADBI comprises said index of securities selected based upon said at least one non-price metric, and weighted based upon said at least one non-price metric, wherein said at least one non-price metric comprises at least one of:

revenues of an entity associated with each given security;

sales of the entity associated with said each given security;

cashflow of the entity associated with said each given security;

book value of the entity associated with said each given security;

dividends of the entity associated with said each given security;

earnings of the entity associated with said each given security; or

profit of the entity associated with said each given security.

15. The method according to claim 1 , further comprising:

normalizing weightings for any security to make the subset weight consistent with the weight of the subset of the universe.

16. The method according to claim 1 , wherein said averaging comprises:

equally averaging said strategies.

17. The method according to claim 1 , wherein said averaging comprises:

weighted averaging said strategies.

18. The method according to claim 1 , further comprising:

applying signal diversification enhancement on said final weights.

19. The method according to claim 1 , further comprising:

avoiding over-concentrated allocations.

20. The method according to claim 1 , further comprising:

minimizing tracking error.

21. The method according to claim 1 , further comprising:

removing outliers.

22. The method according to claim 1 , further comprising wherein said lowest beta comprises at least one of:

a lowest value of said beta;

a lowest absolute value of said beta;

a lowest positive value of said beta; or

a lowest negative value of said beta.

23. The method according to claim 1 , wherein said universe is used to ensure sufficient liquidity of said securities.

24. The method according to claim 1 , wherein said beta comprises:

a five (5) year daily beta.

25. The method according to claim 1 , wherein said beta comprises at least one of:

1 yr daily,

1 yr monthly,

2 yr daily,

2 yr monthly,

3 yr monthly,

3 yr daily,

4 yr daily,

4 yr monthly,

5 year monthly,

5 year daily, or

more.

26. The method according to claim 1 , wherein said beta comprises at least one of:

a less than or equal to a five (5) year daily beta to decrease turnover; or

between two year daily data and 5 year daily data, inclusive, to decrease turnover.

27. The method according to claim 1 , wherein said beta comprises at least one of:

removing or truncating observations of a security that is beyond 3 std deviations or below 3 negative std deviations of a 5 year daily data; or

wherein said beta comes from an ordinary least squares regression after the removal or truncation of outliers.

28. The method according to claim 1 , wherein said low volatility factor comprises:

k-beta, where k is at least one of:

k greater than zero;

k is between 1 and 2 inclusively, or

k is between 0.5 and 3 inclusively.

29. The method according to claim 1 , wherein said low volatility factor comprises at least one of:

k-Beta,

1.5-Beta,

1.2-Beta, or

1-Beta of a given geography's security.

30. The method according to claim 1 , wherein the method further comprises:

excluding negative and zero low volatility factor values.

31. The method according to claim 1 , wherein the factor (K-Beta) of a security of a given geography is greater than zero (0).

32. The method according to claim 1 , wherein the method is used to keep a return characteristic of the index, while decreasing a risk characteristic of the index while maintaining diversified geographic and sector variation.

33. The method according to claim 1 , wherein the method comprises:

determining days that a security does not trade and removing data from such non-trading days.

34. The method according to claim 33 , wherein said determining comprises:

determining days when a security has a zero return in consecutive days, concluding a security was not liquid, and removing the security.

35. The method according to claim 33 , wherein said determining comprises:

determining a day when a large proportion of securities in a given market have a zero return, concluding the given market is closed for said day, and removing data of all securities of that market for that day.

36. The method according to claim 1 , wherein any said weighting comprises a positive, negative, or zero weighting.

37. The method according to claim 1 , wherein any weight of a security may be divided by Beta of each said security, and further excluding any negative and/or zero beta.

Assignments (3)

Continuity (14)