My presentation to SQA Fuzzy Day

1. Intelligence in the Data Channel
An Unusual Approach to Global Information
Manish Aurora
Rational Investing LLC
www.InfoSuez.com
212 466 1119
manish.aurora@rationalinvesting.com

2. The Beta Not Taken
 Fama French (1993) => Factor Race; knowing the literature is table stakes
 Traditional Investors estimate cash flows; ergo, to outperform, systems need
to apply risk thinking at that level
 Globally,
 the macro environment,
 flow of corporate events,
 pace and quality of data availability
all vary
 Assembly of information on a global basis is underwhelming
 Separation of risk vs. data intelligence is an institutional flaw
 Poor quality of Information is holding the science back
 Given the expenses of the business, few outperform consistently 2

3. Suez Canal vs. Cape of Good
Hope
 Quant input data has holes, lags several days; sell side analysis lags weeks
 Needed: Finished real time information -> a reduction in noise and uncertainty
 The greatest source of alpha: normalized trend lines of recurring cash
revenues and costs
 Even with intelligent interpolation, maybe 50% of material information in
company filings can be absorbed in an automated fashion
 Highly specific human intervention limited to what is most relevant ->
productivity rises 10x i.e. an analyst can cover 150 companies instead of 15
 A team of 24 financial engineers maintains DCF models for 3,000 stocks
 Focused on standardizing corporate finance rather than statistical relationships
3

4. Legacy Flow
4
Optimizer
Factor Model
Vendor + Mathematical Scrubbing
Accounting Data

5. Intelligent Flow
5
Risk Adjusted Position
Analyst + A.I. -> Business Cycle -> DCF w / Factor Spread
Analyst + A. I. -> Economic Data -> Recurring Line Items
Accounting Data

6. Where Angels Fear to Tread
 Growth Response
to Macro Conditions
 Cyclical + Leverage
Normalization
 Data Standardization and Scrubbing
6
 Corporate Events and Volatility Dampening
 Interpolation and Terminal Cost Structure
 CAPM Discounts Cash Flow Projection => NPV

7. Examples of Economic Data and
Scrubbing
7
• Non Recurring costs – litigation settlements, SAP
implementation, merger redundancy
• Rollups’ impact on CapEx projection,
maintenance masquerading as acquisitions
• Unfunded pensions, regulatory costs
• Potential Energy/Mineral Reserves, Patent Expiry
• FX Exposures, commodity hedges

8. Artificial Intelligence is Interpreter +
Interpolator
8
• Estimate real, risk adjusted, recurring targets for:
• Maintenance CapEx
• SG&A
• Cyclically adjusted forward Revenues
• Terminal Operating Costs
• Result:
• Sustainable Free Cash Flow Valuation
• Strong evidence for intuitive ideas e.g.
leverage is risk, margins impact returns

9. 9
Artificial Intelligence, and the Other Kind
• Immense feedback loop between model and scrubbing,
volatility and growth amortization tuned with experience
• A.I. = Logical decision trees integrate fundamentals
• Mathematics extrapolates cash flow through business cycle
• Inject -> Risk Adjusted DCF Standard Across Sectors
• Systems scale labor: Analysts review for errors, footnotes
+ events applying limited corrections

10. 10
● Why is Machine Learning still a Challenge?
- Economic relationships are non-linear; list of contingencies a mile long
● Every business cycle is different in
- Drivers of growth on the way up
- Assets which become stranded on the way down
● The system parses a large set of distributed decision trees, needs human tuning for
- Dampening cost shifts and events
- Checks for reconciliation with balance sheet and statement of financial condition
• Do not foresee A.I. blending this into alpha without pre-set parameters
Pattern Recognition for Corporate Finance
Harnesses Data to Standardize DCF

11. US Feed Market Neutral 8 years
11
Average Annual Return 10.14%
SD Annualized 4.46%
Sharpe Ratio 2.25
0
5
10
15
20
25
30
-2
-1.5
-1
-0.5
0
0.5
1
1.5
2
2.5
3
3.5
4
More
Frequency
Monthly Returns (%)
Track Record
0
5
10
15
20
25
-2
-1.5
-1
-0.5
0
0.5
1
1.5
2
2.5
3
3.5
4
More
Frequency
Monthly Returns (%)
S&P 500

12. Biography
Manish Aurora, Managing Principal - Methodology and Product Architecture
• Co-founded Rational Investing LLC and built its first valuations starting in 1998.
The firm is now 20 professionals modeling the G7 and MSCI World markets
• Designed and developed the FX trading platform of FXCM www.fxcm.com, at peak
the world’s largest non-bank online FX dealer
• Converted Merrill’s European FX derivatives exposure at NYC, London, Singapore
offices to the Euro
• Reprogrammed JP Morgan’s global swaps pricing and counterparty credit risk
calculation using Massively Parallel Supercomputing technology
• Designed the Value at Risk calculator for the merger of Chase and Chemical, then
the biggest bank merger ever, under a tight deadline from the Federal Reserve
• Designed and constructed the first CMBS and Corporate Bond credit risk models
at BlackRock
• Sell-side analyst at Nomura Securities covering real estate equity, debt, CMBS
• Built the first commercial paper direct issuance and investment management and
reporting system for GE Capital, ITT, Ford at Financial Sciences
• MBA from University of Chicago; BS in computer science, University of Scranton
12

13. 13
Pieter Hellquist Principal, Fundamental and Valuation Research 2009 - present
● Leads reviews of Standard DCF valuations produced quarterly by the firm
● Guides supporting fundamental research by offshore team
● Head of International Operations for Velocity, a provider of electronic trading systems
● Global Product Manager for Citibank’s cross border equities data and trading systems
● Senior Manager for the Citi's e-commerce in Europe and its FX trading systems out of
Australia
● Marketing Manager in London for Information Products for Reuters - Northern Europe;
Marketing Director Japan built a US$ 100+ million practically from scratch
● MBA from INSEAD, M.Engg at Lund University, Sweden; year at Ecole Centrale de Paris
Biography
Harbhajan Aurora Founding Principal, Technology and Research Management, Bombay
● Recruits and trains the analyst and software engineering teams in corporate finance
● Co-founded Rational Investing LLC and, since 1999, oversees the senior analysts.
Instrumental in creating the valuation and data normalization review processes
● Coordinated development of the FXCM trading platform and oversaw its test team
● Principal of a textile manufacturing and trading business for 20 years in Bombay and Surat
● Head of Chicago Pneumatic’s North Indian marketing and sales, managed 30 professionals
selling machinery for large-scale infrastructure projects of national importance
● BSE from the University of Punjab. State record for mathematics proficiency

14. US Long Only Feed and Simulation
14
Average Annual Return 24.2%
SD Annualized 16.3%
Sharpe Ratio 1.47
Average Annual Return 22.7%
SD Annualized 14.4%
Sharpe Ratio 1.57

15. 8 Years US Market Neutral Simulation
15
Average Annual Return 10.97%
SD Annualized 3.29%
Sharpe Ratio 2.77
Excluding financials and utilities. Exposure is aggregate of individual buy/sell decisions by Rational Investing model,
5% per sector net limit, 7.5% stop loss, monthly rebalancing, 25% mis-pricing threshold for investment, 10% for
exit .
0
5
10
15
20
25
30
-2
-1.5
-1
-0.5
0
0.5
1
1.5
2
2.5
3
3.5
4
More
Frequency
Monthly Returns (%)
Track Record
0
5
10
15
20
25
-2
-1.5
-1
-0.5
0
0.5
1
1.5
2
2.5
3
3.5
4
More
Frequency
Monthly Returns (%)
S&P 500

16. Appendix
Japan Simulation 5 Years
16
Average Annual Return 8.23%
SD Annualized 4.12%
Sharpe Ratio 1.99
0
2
4
6
8
10
12
14
-2
-1.5
-1
-0.5
0
0.5
1
1.5
2
2.5
3
3.5
4
More
Frequency
Monthly Returns (%)
Track Record
0
3
6
9
12
15
18
-2
-1.5
-1
-0.5
0
0.5
1
1.5
2
2.5
3
3.5
4
More
Frequency
Monthly Returns (%)
Nikkei 225

17. Appendix
Japan Feed Record 5 Years
17
Average Annual Return 8.24%
SD Annualized 4.96%
Sharpe Ratio 1.65
0
2
4
6
8
10
12
14
16
-2
-1.5
-1
-0.5
0
0.5
1
1.5
2
2.5
3
3.5
4
More
Frequency
Monthly Returns (%)
Track Record
0
3
6
9
12
15
18
-2
-1.5
-1
-0.5
0
0.5
1
1.5
2
2.5
3
3.5
4
More
Frequency
Monthly Returns (%)
Nikkei 225

18. Appendix
UK Simulation 8 years
18
Average Annual Return 9.9%
SD Annualized 5.0%
Sharpe Ratio 1.95
0
5
10
15
20
25
-2
-1.5
-1
-0.5
0
0.5
1
1.5
2
2.5
3
3.5
4
More
Frequency
Monthly Returns (%)
Rational Investing
0
5
10
15
20
25
30
-2
-1.5
-1
-0.5
0
0.5
1
1.5
2
2.5
3
3.5
4
More
Frequency
Monthly Returns (%)
FTSE 100

19. Appendix
UK Feed Record 4 years
19
Average Annual Return 4.1%
SD Annualized 3.1%
Sharpe Ratio 1.18
0
3
6
9
12
15
-2
-1.5
-1
-0.5
0
0.5
1
1.5
2
2.5
3
3.5
4
More
Frequency
Monthly Returns (%)
Track Record
0
3
6
9
12
15
-2
-1.5
-1
-0.5
0
0.5
1
1.5
2
2.5
3
3.5
4
More
Frequency
Monthly Returns (%)
FTSE 100