Using accounting data based indexing to create a low volatility portfolio of financial objects

• US 8,694,402 B2
• Filed: 08/23/2012
• Issued: 04/08/2014
• Est. Priority Date: 06/03/2002
• Status: Expired due to Term

• Current Assignee: Research Affiliates LLC (Research Affiliates Global Holdings LLC)
• Original Assignee: Research Affiliates LLC (Research Affiliates Global Holdings LLC)
• Inventors: Arnott, Robert D., Wood, Paul Christopher, Li, Feifei
• Primary Examiner(s): JOHNSON, GREGORY L
• Application Number:
  US13/593,415
• Publication Number:
  US 20130117199A1
• Time in Patent Office: 593 Days
• Field of Search: 705 35- 37
• US Class Current: 705/35
• CPC Class Codes: G06Q 40/04 Trading; Exchange, e.g. stocks, commodities, derivatives or currency exchange
• CPC Class Codes: G06Q 40/06 Asset management; Financial planning or analysis

Abstract

A system, method and computer program product creates an index based on accounting data, or a portfolio of financial objects based on the index where the portfolio is weighted according to accounting data. Indexes may be built with metrics other than market capitalization weighting, price weighting or equal weighting. Financial and non-financial metrics may be used to build indexes to create passive investment systems. A combination of financial non-market capitalization metrics may be used with non-financial metrics to create passive investment systems. Once built, the index may be used as a basis to purchase securities for a portfolio. Specifically excluded are widely-used capitalization-weighted and price-weighted indexes, in which price of a security contributes in a substantial way to calculation of weight of that security in the index or the portfolio, and equal weighting weighted indexes. The indexes may be constructed to minimize volatility.

Claims

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

selecting, by at least one processor, a geographic subset of a plurality of securities selected from a universe of securities wherein said geographic subset comprises;

selecting, by the at least one processor, at least one security having at least one low volatility measure from a plurality of securities ranked in order of said at least one low volatility measure from securities of each geography of said universe of securities;

weighting, by the at least one processor, said geographic subset of said plurality of securities using at least one measure of company size to make said geographic subset of securities at least one of;

country or region neutral, relative to weights of said starting universe to form a geographic portfolio (GP) strategy;

selecting, by the at least one processor, a sector subset of a plurality of securities selected from said universe of securities wherein said sector subset comprises;

selecting, by the at least one processor, at least one security having a low volatility measure from a plurality of securities ranked in order of said at least one low volatility measure from securities of each sector of said universe of securities;

weighting, by the at least one processor, said sector subset of securities based on at least one measure of company size to make the sector subset of securities sector neutral relative to the starting universe weight to form a sector portfolio (SP) strategy; and

mathematically combining, by the at least one processor, 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 1, 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 mathematically combining comprises:

averaging said strategies.

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

weighted averaging said strategies;

or

equally 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 at least one low volatility measure comprises at least one of:

a lower value of said beta;

a lower absolute value of said beta;

a lower positive value of said beta;

or

a lower 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 low volatility measure comprises:

a five (5) year daily data.

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

1 year daily,

1 year monthly,

2 year daily,

2 year monthly,

3 year monthly,

3 year daily,

4 year daily,

4 year monthly,

5 year monthly,

5 year daily, or

more.

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

a less than or equal to a five (5) year daily data 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 low volatility measure comprises at least one of:

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

or

wherein said low volatility measure 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 measure 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 measure 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 measure values.

31. The method according to claim 1, wherein the low volatility measure 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 said at least one low volatility measure of each said security, and further excluding any negative and/or zero value of said at least one low volatility measure.

38. The method according to claim 1, wherein said universe of said securities is divided into a plurality of groups according to at least valuation measure of said company.

39. The method according to claim 38, wherein said at least one valuation measure of said company comprises at least one of:

a price to earnings measure, or a price to market measure.

40. The method according to claim 38, wherein said plurality of groups are used to determine a selection of securities for the index.

41. The method according to claim 38, wherein said plurality of groups are used to determine a weight of securities in the index.

42. The method according to claim 41, wherein said plurality of groups comprises a lower valuation group, and a higher valuation group, and further comprising:

giving securities in said lower valuation group, greater weights; and

giving securities in said higher valuation group, lesser weights.

43. The method according to claim 1, wherein said low volatility measure is based on five (5) year daily data of a company.

44. The method according to claim 1, wherein said measure of company size comprises a price-based measure based on at least one of:

a historical price, a current price, or an expected price of a company.

45. The method according to claim 1, wherein said low volatility measure is modified by a regression.

46. The method according to claim 1, wherein said universe comprises a plurality of securities selected from another plurality of securities based on at least one valuation measure of said company.

47. The method according to claim 46, wherein said at least one valuation measure of said company comprises at least one of:

a price to earnings measure, a price to book measure, a dividend yield measure, or a price to market measure.

48. The method according to claim 46, wherein said universe comprises said plurality of securities selected based on having a valuation measure of value less than at least one historical average valuation measure of at least one of a geographic group, or a sector group, over a time period.

49. The method according to claim 1, wherein said weighting of said geographic subset and said sector subset is performed after at least one of said selecting of said geographic subset and said selecting of said sector subset.

50. A system of constructing a low volatility index comprising:

at least one processor; and

at least one memory coupled to said at least one processor;

wherein said at least one processor is configured to;

select a geographic subset of a plurality of securities selected from a universe of securities wherein said geographic subset comprises;

to select at least one security having at least one low volatility measure from a plurality of securities ranked in order of said at least one low volatility measure from securities of each geography of said universe of securities;

to weight said geographic subset of said plurality of securities using at least one measure of company size

to make said geographic subset of securities at least one of;

country or region neutral, relative to weights of said starting universe to form a geographic portfolio (GP) strategy;

to select a sector subset of a plurality of securities selected from said universe of securities wherein said sector subset comprises;

to select at least one security having a low volatility measure from a plurality of securities ranked in order of said at least one low volatility measure from securities of each sector of said universe of securities;

to weight said sector subset of securities based on at least one measure of company size to make the sector subset of securities sector neutral relative to the starting universe weight to form a sector portfolio (SP) strategy; and

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

51. A computer program product embodied on a nontransitory computer accessible medium, which when executed by at least one processor performs a method of constructing a low volatility index comprising:

selecting, by the at least one processor, a geographic subset of a plurality of securities selected from a universe of securities wherein said geographic subset comprises;

selecting, by the at least one processor, at least one security having at least one low volatility measure from a plurality of securities ranked in order of said at least one low volatility measure from securities of each geography of said universe of securities;

weighting, by the at least one processor, said geographic subset of said plurality of securities using at least one measure of company size

to make said geographic subset of securities at least one of;

country or region neutral, relative to weights of said starting universe to form a geographic portfolio (GP) strategy;

selecting, by the at least one processor, a sector subset of a plurality of securities selected from said universe of securities wherein said sector subset comprises;

selecting, by the at least one processor, at least one security having a low volatility measure from a plurality of securities ranked in order of said at least one low volatility measure from securities of each sector of said universe of securities;

weighting, by the at least one processor, said sector subset of securities based on at least one measure of company size to make the sector subset of securities sector neutral relative to the starting universe weight to form a sector portfolio (SP) strategy; and

mathematically combining, by the at least one processor, said geographic portfolio (GP) strategy and said sector portfolio (SP) strategy to obtain final low volatility index weights.