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Agnostic Fundamental MBA Student Investment Management Fund November 30, 2018 1

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Page 1: Agnostic Fundamental1. Accounting information obtained from WRDS 2. Market Caps obtained from Bloomberg Terminals 3. Ran regressions using Python Two teams ran independent regressions

Agnostic FundamentalMBA Student Investment Management Fund

November 30, 2018

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Page 2: Agnostic Fundamental1. Accounting information obtained from WRDS 2. Market Caps obtained from Bloomberg Terminals 3. Ran regressions using Python Two teams ran independent regressions

MBA SIM Fund Members

Robert YapAashish SharmaAllison RicherMartin Mankus

Madeline Doherty Megan Dolle Spencer Elliott Yuejiang Fan

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Page 3: Agnostic Fundamental1. Accounting information obtained from WRDS 2. Market Caps obtained from Bloomberg Terminals 3. Ran regressions using Python Two teams ran independent regressions

Agnostic Fundamental

Agnostic Fundamental is a statistical approach to traditional fundamental analysis.It uses the statistician’s viewpoint to determine mispricings.

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Page 4: Agnostic Fundamental1. Accounting information obtained from WRDS 2. Market Caps obtained from Bloomberg Terminals 3. Ran regressions using Python Two teams ran independent regressions

Background Research

● The Original Paper by Söhnke M. Bartram and Mark Grinblattsought to “assess stock market informational efficiency with minimal data snooping.”

● By using Statistical Methods, they found companies’ peer-implied values, and ranked the divergences from the peer-implied values

● They found risk-adjusted returns of “up to 10% per year.”● Fundamental analysis using statistics.● More agnostic and less discretionary approach to fundamental-

based equity valuation.

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Page 5: Agnostic Fundamental1. Accounting information obtained from WRDS 2. Market Caps obtained from Bloomberg Terminals 3. Ran regressions using Python Two teams ran independent regressions

Regression Analysis

Y = β0 + β1x1 + β2x2 + … + βnxn

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Page 6: Agnostic Fundamental1. Accounting information obtained from WRDS 2. Market Caps obtained from Bloomberg Terminals 3. Ran regressions using Python Two teams ran independent regressions

Backtesting Returns

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Page 7: Agnostic Fundamental1. Accounting information obtained from WRDS 2. Market Caps obtained from Bloomberg Terminals 3. Ran regressions using Python Two teams ran independent regressions

Process

1. Accounting information obtained from WRDS2. Market Caps obtained from Bloomberg Terminals3. Ran regressions using Python

○ Two teams ran independent regressions to validate process4. Narrowed down universe using constraints in charter

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Page 8: Agnostic Fundamental1. Accounting information obtained from WRDS 2. Market Caps obtained from Bloomberg Terminals 3. Ran regressions using Python Two teams ran independent regressions

Constraints

● Long only, no shorting● 90% of firms must have a market capitalization greater

than $1B● Investment in each sector must be 25% or less● Investment in each firm must be 4% or less

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Page 9: Agnostic Fundamental1. Accounting information obtained from WRDS 2. Market Caps obtained from Bloomberg Terminals 3. Ran regressions using Python Two teams ran independent regressions

Investable Universe

3000

68

194

2961

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Page 10: Agnostic Fundamental1. Accounting information obtained from WRDS 2. Market Caps obtained from Bloomberg Terminals 3. Ran regressions using Python Two teams ran independent regressions

Constructing Our Portfolio

Achieving Sector Neutrality whilst conforming to our constraints.

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Page 11: Agnostic Fundamental1. Accounting information obtained from WRDS 2. Market Caps obtained from Bloomberg Terminals 3. Ran regressions using Python Two teams ran independent regressions

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Sector Neutrality

Page 12: Agnostic Fundamental1. Accounting information obtained from WRDS 2. Market Caps obtained from Bloomberg Terminals 3. Ran regressions using Python Two teams ran independent regressions

Composition of Our Portfolio

● 68 stocks

● each holding ≤ 4%

● all came from most underpriced decile

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Page 13: Agnostic Fundamental1. Accounting information obtained from WRDS 2. Market Caps obtained from Bloomberg Terminals 3. Ran regressions using Python Two teams ran independent regressions

Portfolio Returns

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Page 14: Agnostic Fundamental1. Accounting information obtained from WRDS 2. Market Caps obtained from Bloomberg Terminals 3. Ran regressions using Python Two teams ran independent regressions

Thank You!

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