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Data Analytics
Risk Mitigation in Financial Investments
Sumir Nagar - Chief Operating Officer
Agile FT LLC, Dubai, UAE
www.agile-ft.com
at
Shailesh J Mehta School of Management - IIT Powai
March 18, 2017
The opinions of the presenter are his individual opinions and/or advise, and are not to be construed as those of Agile FT LLC, Dubai, UAE.
Investments are subject to market risk and prudence is advised when investing in financial instruments.
Thanks to the School, Vinod, Aditya, and Shasti
House Rules & Etiquette
You can survive without your cellphones for a few minutes
I’m a big fan of interactive, let’s try and wait for logical breaks
before we debate, discuss, comment
So that we don’t talk over others, please indicate that you have
something to say
2
I’m Usually Unpopular
• Just a little about me
• This is a much larger topic & I will try to do justice in 60 minutes
• What I have to say can be construed to be CONTROVERSIAL
• What I have to say is NOT ROCKET SCIENCE
• Simply because Data Analytics is NOT ROCKET SCIENCE, (despite our best
efforts) to cast that impression
• I deal with
• Basics - (usually forgotten)
• Common Sense - (The Most Uncommon Thing)
• Prudence - (Whatever That Means)
3
Who Is The “Investor”
• Individual
• HNI
• Mid Income
• Low Income
4
Who Is The “Investor”
• Corporate
5
Who Is The “Investor”
• Financial Institution
• Bank
• Insurance
• Pension
6
Understanding Risk
7
Risk & Reward Are Closely Intertwined
8
You Cannot Hide From Risk
9
All You Can Do Is Manage Risk Down To
Manageable Levels
10
Risk Management Is A Simple Matter of
Assessing/Analysing Data Points
11
Risk Framework
• Needs Assessment - The Purpose
• Expected Outcome - The Result
• Horizon - Time Element
• Appetite to Loose & Absorb Shocks - Risk Appetite
• Ability to Manage Risk - Strategies
• Available Cash
12
Varying Objectives?
• Individuals
• Life Events: Education, Marriage, Housing, Retirement
• Corporate
• Manage surplus cash, even our cash flow cycles, growth, taxation
• Bank
• Manage cash flow mismatches between deposits, withdrawals,
lending, defaults, growth, taxation
• Insurance
• Risk Events, Cash flow mismatches, growth
13
Varying Needs
Analysis
• Regardless of the Investor Type the measures are identical
• What differs is the Analysis of the Need
• For Individual Investors the cycle begins with a Risk Assessment Questionnaire (Why, When, etc)
• For Corporates it depends on their Business Plans
• For Banks it depends on ALM
• For General Insurance Companies it depends on
• Risk Events
• Actuarial Calculations
• For Life & Pension Companies
• Risk Events (death, disability, medical conditions, retirement)
• Risk Assessments in case of Investment Backed or Unit Linked Plans
14
Individuals
15
Income
Group
Sources Horizon Appetite Avenues Returns % Share
Low Wages Short Low
Banks
Insurance
Fixed
Variable
60%
40%
Medium Wages Intermediate Medium
Banks
Insurance
MF’s
Fixed
Variable
Markets
40%
30%
30%
High
Wages
Business
Long High Varied
Fixed
Variable
Insurance
Markets
Hedges
PE
20%
20%
30%
20%
10%
Corporate
16
Size Surplus Horizon Appetite Avenues Returns % Share
Small Low Temporary Low Banks
Fixed
Variable
60%
40%
Medium Medium Intermediate Medium
Banks
MF’s
Treasuries
ICD’s
Family
Offices
Fixed
Variable
Markets
40%
30%
30%
Large High Long High All
Fixed
Variable
Markets
Hedges
20%
20%
30%
30%
Financial Institutions
17
Size Surplus Horizon Appetite Avenues Returns % Share
Small Low Temporary Low Banks
Fixed
Variable
60%
40%
Medium Medium Intermediate Medium
Banks
MF’s
Treasuries
Fixed
Variable
Markets
40%
30%
30%
Large High Long High All
Fixed
Variable
Markets
Hedges
20%
20%
30%
30%
Risk Types
• Market Risk
• Operational Risk
• Systemic Risk
18
Analytics
• Is largely dependent on various factors
• History - Hindsight is a great thing - (BUT The Bullet has been
fired)
• Future Prospects - Predictions have DEPENDENCIES (Variables)
• Guesswork - Probability (LACK of Certainty)
• Triggers - Events (we usually have little or no control)
• Availability - QUALITY Data (Sources, Cleanliness, Quantum)
• Methods, Techniques, Tools - Collection, Processing &
Interpretation
19
Risk Frameworks
• There are frameworks
• There are no global agreements
• If there are agreements, they are debated to
death in the event of failures
• We are only as good as our last predictions
20
Asset Classes & Their Nature
21
Equity Shares
• Usually Considered to be High Risk
• Investor Types
• Buy & Hold vs Dividend Stripping
• Market Investors - (Price Appreciation)
• Valuations - Driven by Market Perceptions
• Outstanding Shares
• Trading Volumes
• Follow herd mentality
• Informed sources close to the management
• Times EPS - (How Many Times)
• By what factor
• There is not a single yardstick
22
Interest Bearing
• Considered to be Low Risk
• Subject to Ratings
• Sanctity of Ratings
• Rating Agency Advisories are Conflicting
• Rating Agencies depend on Data Points
23
Contracts
• Derivatives & Futures
• Are actually SIMPLE to Understand
• They depend on an Underlying Instrument (or Basket)
• They were created as a means to safeguard physical deliveries of an underlying at
predetermined rates/prices
• However, they are Seldom held till expiry
• The complexities arise from
• End Use
• Lack of Standardised Pricing Models
• Traders usually have a pet Quant who works off complicated Excels
• And no Quant agrees with the other
24
Contracts
• Foreign Exchange
• Markets are driven by International Trade
Flows
• Subject to Government Intervention
• Easily swayed by unscrupulous Traders
25
Commodities
• Depend on Acts of God
• Discoveries
• Extraction Methods
26
Real Estate
• Considered one of the safe investment
avenues
• Subject to Infra
• Usually considered to be illiquid
27
Metals & Crude
• Gold
• Indian housewives hold 11% of the world's gold. That is more than the reserves of the USA,
the IMF, Switzerland, and Germany put together
• Earlier a country’s currency was valued in terms of its gold reserves
• The Gold Standard was abandoned
• This led to the advent of deficit financing
• Silver
• Platinum
• Copper
• Oil
• That can quickly change, as alternative energy technologies do exist, its just a matter of time
until Black Gold looses its lustre
28
Alternate Asset Classes
• MBS
• ABS
• Strips
• Exotics
• Digitals
• Structures
29
Invisible Cash Flows
• Arms
• Drugs
• Though illegal the income from these make it
into mainstream investing
30
Investment Scenarios
• Scenario Analysis - What If?
• Show Me The Money
• Money is like WATER
• It finds its own LEVEL
• It usually flows to where Money ALREADY exists
• Few take a Contrarian View
• The TREND is your FRIEND
• FOLLOW the TREND
31
Ever Heard of the 80:20 Rule?
32
Well here it is
33
80% of Investors have to LOOSE for the 20% to GAIN
34
This is called The SMART MONEY
35
They are SMART ‘cause they have what 80% DON’T
36
DATA
37
So Let’s Talk About DATA
ANALYTICS
• It deals with Histories
• It seeks to PREDICT basis the PAST
• History does’t always repeat itself
• It means throwing several variables into the MIX
• One of the biggest variables is The CYCLIC NATURE of market
movements
• It must predict when Cycles begin and End
• There are Macro Cycles and Micro Cycles (wheels within wheels)
• There are ALWAYS LEAD and LAG Indicators
38
Data Quality
• Data comes from various sources
• Its usually delayed
• To clean Data various interpolation techniques
have to be applied
• Log Linear
• Cubic Spline
39
Data Sources
• Data comes from various sources
• Markets - Prices
• Governments - Economic
• Agencies - Feeds
• Its usually delayed
• To clean Data various interpolation techniques have to be applied
• Log Linear
• Cubic Spline
40
Analytical Challenges
• Cross Referencing
• Feed Delays pose challenges
• Conflicting Data Sets need careful analysis
• Interpretation needs to be led by Humans
• Humans are usually subjective
• Algorithms are written by Humans
• Self Learning & AI are the new buzz words, BUT their accuracy will
take time to establish
• We will get it all wrong before we get it right
41
So Do We need Analytics
• Unequivocally - YES
• What we need is - Standardisation
• We need Global and Regional Models
• What works for the Advanced Economies
Doesn't necessarily work for the LDC’s
42
Decision Support
• Decision Support Systems are nothing but Algorithms
• Collect Data
• Clean Data
• Query Data
• Fetch Data
• Run Algorithm factoring in Variables we referenced earlier
• Publish on Screen or via Report
• Run various scenarios by changing around a few variables
• And Finally, in the face of a plethora of information taking a decision
43
Risk Mitigation
44
Technical Analysis
• Prices
• Volumes
• Trends
• Cycles
• Macro
• Micro
• Indicators
• Strategies
45
Strategies
• The Long & Short of It All
• Taking Long Positions
• Taking Short Positions
• Naked vs Covered
• Alternating Long & Short within Cycles
• Butterflies
• Long Butterfly
• Short Butterfly
• Straddles
• Strangles
• Combining Holdings & Derivatives
46
Tools
• MACD
• Day Moving Average
• Signal
• Crossover
• Japanese Candlesticks
• Fibonacci Numbers
• Finally its all about PATTERNS & CYCLES (My favourite is a Double Top Followed by a Double
Bottom)
• Thought to be PURE in terms of indication of market movements
• Markets are moved by Money Flows
• Money Flows are controlled by People
• So, someone makes the first move and the Markets follow
• That SOMEONE is the SMART MONEY (the 20%)
47
Fundamental Analysis
• Balance Sheet Analysis
• Key Financial Ratios
• Past Performance
• Future Prospects
• Sector Analysis
• Industry Analysis
• Competitor Analysis
• Technology Obsolescence & Ever-greening
• Distribution Framework
• Capital Adequacy
• Management Track Record
48
Hybrid Analysis
• Combine Fundamentals & Technicals
• Base macro decisions on Fundamentals
• Base Entry & Exit on Technicals
• Use the Snake in the Tunnel Technique
49
Tips & Tricks
• DON’T take a NAKED Short unless you have money to throw
• Market Tops & Bottoms are predicted by FOOLS or GENIUSES
• One Prediction does not a Guru Make
• Analyse, Analyse, Analyse
• Pick an Investment Strategy based on your Risk Appetite
• Stick with your Strategy, give it time
• If you’ve picked a good stock, don’t panic at the first downturn
• Cut Your Losses, Let your Profits Run
• Book Profits periodically, you’re bound to run afoul of the Trend at some time
• TRY (hard) not to average a loosing position
50
Manage Your
Portfolio
51
Models
• Build a Risk Based Model
• Models can be as Generic or Specific as You like
• Balance your Risk/Model
• Hedge your Bets
• Do Dry Runs BEFORE entering the Market
• Play out your Hypothesis
• Course Correct as You go
• Don’t let EGO get in the way of your Investment Decisions
• Finally, its about MAKING Money
• Prudence and Balance are your FRIENDS, NOT Greed
52
Questions?
Comments?
Suggestions?
Contact
sumirnagar.com
sumirnagar@yahoo.com
53

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Data Analytics: Risk Mitigation in Financial Investments v01

  • 1. Data Analytics Risk Mitigation in Financial Investments Sumir Nagar - Chief Operating Officer Agile FT LLC, Dubai, UAE www.agile-ft.com at Shailesh J Mehta School of Management - IIT Powai March 18, 2017 The opinions of the presenter are his individual opinions and/or advise, and are not to be construed as those of Agile FT LLC, Dubai, UAE. Investments are subject to market risk and prudence is advised when investing in financial instruments.
  • 2. Thanks to the School, Vinod, Aditya, and Shasti House Rules & Etiquette You can survive without your cellphones for a few minutes I’m a big fan of interactive, let’s try and wait for logical breaks before we debate, discuss, comment So that we don’t talk over others, please indicate that you have something to say 2
  • 3. I’m Usually Unpopular • Just a little about me • This is a much larger topic & I will try to do justice in 60 minutes • What I have to say can be construed to be CONTROVERSIAL • What I have to say is NOT ROCKET SCIENCE • Simply because Data Analytics is NOT ROCKET SCIENCE, (despite our best efforts) to cast that impression • I deal with • Basics - (usually forgotten) • Common Sense - (The Most Uncommon Thing) • Prudence - (Whatever That Means) 3
  • 4. Who Is The “Investor” • Individual • HNI • Mid Income • Low Income 4
  • 5. Who Is The “Investor” • Corporate 5
  • 6. Who Is The “Investor” • Financial Institution • Bank • Insurance • Pension 6
  • 8. Risk & Reward Are Closely Intertwined 8
  • 9. You Cannot Hide From Risk 9
  • 10. All You Can Do Is Manage Risk Down To Manageable Levels 10
  • 11. Risk Management Is A Simple Matter of Assessing/Analysing Data Points 11
  • 12. Risk Framework • Needs Assessment - The Purpose • Expected Outcome - The Result • Horizon - Time Element • Appetite to Loose & Absorb Shocks - Risk Appetite • Ability to Manage Risk - Strategies • Available Cash 12
  • 13. Varying Objectives? • Individuals • Life Events: Education, Marriage, Housing, Retirement • Corporate • Manage surplus cash, even our cash flow cycles, growth, taxation • Bank • Manage cash flow mismatches between deposits, withdrawals, lending, defaults, growth, taxation • Insurance • Risk Events, Cash flow mismatches, growth 13
  • 14. Varying Needs Analysis • Regardless of the Investor Type the measures are identical • What differs is the Analysis of the Need • For Individual Investors the cycle begins with a Risk Assessment Questionnaire (Why, When, etc) • For Corporates it depends on their Business Plans • For Banks it depends on ALM • For General Insurance Companies it depends on • Risk Events • Actuarial Calculations • For Life & Pension Companies • Risk Events (death, disability, medical conditions, retirement) • Risk Assessments in case of Investment Backed or Unit Linked Plans 14
  • 15. Individuals 15 Income Group Sources Horizon Appetite Avenues Returns % Share Low Wages Short Low Banks Insurance Fixed Variable 60% 40% Medium Wages Intermediate Medium Banks Insurance MF’s Fixed Variable Markets 40% 30% 30% High Wages Business Long High Varied Fixed Variable Insurance Markets Hedges PE 20% 20% 30% 20% 10%
  • 16. Corporate 16 Size Surplus Horizon Appetite Avenues Returns % Share Small Low Temporary Low Banks Fixed Variable 60% 40% Medium Medium Intermediate Medium Banks MF’s Treasuries ICD’s Family Offices Fixed Variable Markets 40% 30% 30% Large High Long High All Fixed Variable Markets Hedges 20% 20% 30% 30%
  • 17. Financial Institutions 17 Size Surplus Horizon Appetite Avenues Returns % Share Small Low Temporary Low Banks Fixed Variable 60% 40% Medium Medium Intermediate Medium Banks MF’s Treasuries Fixed Variable Markets 40% 30% 30% Large High Long High All Fixed Variable Markets Hedges 20% 20% 30% 30%
  • 18. Risk Types • Market Risk • Operational Risk • Systemic Risk 18
  • 19. Analytics • Is largely dependent on various factors • History - Hindsight is a great thing - (BUT The Bullet has been fired) • Future Prospects - Predictions have DEPENDENCIES (Variables) • Guesswork - Probability (LACK of Certainty) • Triggers - Events (we usually have little or no control) • Availability - QUALITY Data (Sources, Cleanliness, Quantum) • Methods, Techniques, Tools - Collection, Processing & Interpretation 19
  • 20. Risk Frameworks • There are frameworks • There are no global agreements • If there are agreements, they are debated to death in the event of failures • We are only as good as our last predictions 20
  • 21. Asset Classes & Their Nature 21
  • 22. Equity Shares • Usually Considered to be High Risk • Investor Types • Buy & Hold vs Dividend Stripping • Market Investors - (Price Appreciation) • Valuations - Driven by Market Perceptions • Outstanding Shares • Trading Volumes • Follow herd mentality • Informed sources close to the management • Times EPS - (How Many Times) • By what factor • There is not a single yardstick 22
  • 23. Interest Bearing • Considered to be Low Risk • Subject to Ratings • Sanctity of Ratings • Rating Agency Advisories are Conflicting • Rating Agencies depend on Data Points 23
  • 24. Contracts • Derivatives & Futures • Are actually SIMPLE to Understand • They depend on an Underlying Instrument (or Basket) • They were created as a means to safeguard physical deliveries of an underlying at predetermined rates/prices • However, they are Seldom held till expiry • The complexities arise from • End Use • Lack of Standardised Pricing Models • Traders usually have a pet Quant who works off complicated Excels • And no Quant agrees with the other 24
  • 25. Contracts • Foreign Exchange • Markets are driven by International Trade Flows • Subject to Government Intervention • Easily swayed by unscrupulous Traders 25
  • 26. Commodities • Depend on Acts of God • Discoveries • Extraction Methods 26
  • 27. Real Estate • Considered one of the safe investment avenues • Subject to Infra • Usually considered to be illiquid 27
  • 28. Metals & Crude • Gold • Indian housewives hold 11% of the world's gold. That is more than the reserves of the USA, the IMF, Switzerland, and Germany put together • Earlier a country’s currency was valued in terms of its gold reserves • The Gold Standard was abandoned • This led to the advent of deficit financing • Silver • Platinum • Copper • Oil • That can quickly change, as alternative energy technologies do exist, its just a matter of time until Black Gold looses its lustre 28
  • 29. Alternate Asset Classes • MBS • ABS • Strips • Exotics • Digitals • Structures 29
  • 30. Invisible Cash Flows • Arms • Drugs • Though illegal the income from these make it into mainstream investing 30
  • 31. Investment Scenarios • Scenario Analysis - What If? • Show Me The Money • Money is like WATER • It finds its own LEVEL • It usually flows to where Money ALREADY exists • Few take a Contrarian View • The TREND is your FRIEND • FOLLOW the TREND 31
  • 32. Ever Heard of the 80:20 Rule? 32
  • 33. Well here it is 33
  • 34. 80% of Investors have to LOOSE for the 20% to GAIN 34
  • 35. This is called The SMART MONEY 35
  • 36. They are SMART ‘cause they have what 80% DON’T 36
  • 38. So Let’s Talk About DATA ANALYTICS • It deals with Histories • It seeks to PREDICT basis the PAST • History does’t always repeat itself • It means throwing several variables into the MIX • One of the biggest variables is The CYCLIC NATURE of market movements • It must predict when Cycles begin and End • There are Macro Cycles and Micro Cycles (wheels within wheels) • There are ALWAYS LEAD and LAG Indicators 38
  • 39. Data Quality • Data comes from various sources • Its usually delayed • To clean Data various interpolation techniques have to be applied • Log Linear • Cubic Spline 39
  • 40. Data Sources • Data comes from various sources • Markets - Prices • Governments - Economic • Agencies - Feeds • Its usually delayed • To clean Data various interpolation techniques have to be applied • Log Linear • Cubic Spline 40
  • 41. Analytical Challenges • Cross Referencing • Feed Delays pose challenges • Conflicting Data Sets need careful analysis • Interpretation needs to be led by Humans • Humans are usually subjective • Algorithms are written by Humans • Self Learning & AI are the new buzz words, BUT their accuracy will take time to establish • We will get it all wrong before we get it right 41
  • 42. So Do We need Analytics • Unequivocally - YES • What we need is - Standardisation • We need Global and Regional Models • What works for the Advanced Economies Doesn't necessarily work for the LDC’s 42
  • 43. Decision Support • Decision Support Systems are nothing but Algorithms • Collect Data • Clean Data • Query Data • Fetch Data • Run Algorithm factoring in Variables we referenced earlier • Publish on Screen or via Report • Run various scenarios by changing around a few variables • And Finally, in the face of a plethora of information taking a decision 43
  • 45. Technical Analysis • Prices • Volumes • Trends • Cycles • Macro • Micro • Indicators • Strategies 45
  • 46. Strategies • The Long & Short of It All • Taking Long Positions • Taking Short Positions • Naked vs Covered • Alternating Long & Short within Cycles • Butterflies • Long Butterfly • Short Butterfly • Straddles • Strangles • Combining Holdings & Derivatives 46
  • 47. Tools • MACD • Day Moving Average • Signal • Crossover • Japanese Candlesticks • Fibonacci Numbers • Finally its all about PATTERNS & CYCLES (My favourite is a Double Top Followed by a Double Bottom) • Thought to be PURE in terms of indication of market movements • Markets are moved by Money Flows • Money Flows are controlled by People • So, someone makes the first move and the Markets follow • That SOMEONE is the SMART MONEY (the 20%) 47
  • 48. Fundamental Analysis • Balance Sheet Analysis • Key Financial Ratios • Past Performance • Future Prospects • Sector Analysis • Industry Analysis • Competitor Analysis • Technology Obsolescence & Ever-greening • Distribution Framework • Capital Adequacy • Management Track Record 48
  • 49. Hybrid Analysis • Combine Fundamentals & Technicals • Base macro decisions on Fundamentals • Base Entry & Exit on Technicals • Use the Snake in the Tunnel Technique 49
  • 50. Tips & Tricks • DON’T take a NAKED Short unless you have money to throw • Market Tops & Bottoms are predicted by FOOLS or GENIUSES • One Prediction does not a Guru Make • Analyse, Analyse, Analyse • Pick an Investment Strategy based on your Risk Appetite • Stick with your Strategy, give it time • If you’ve picked a good stock, don’t panic at the first downturn • Cut Your Losses, Let your Profits Run • Book Profits periodically, you’re bound to run afoul of the Trend at some time • TRY (hard) not to average a loosing position 50
  • 52. Models • Build a Risk Based Model • Models can be as Generic or Specific as You like • Balance your Risk/Model • Hedge your Bets • Do Dry Runs BEFORE entering the Market • Play out your Hypothesis • Course Correct as You go • Don’t let EGO get in the way of your Investment Decisions • Finally, its about MAKING Money • Prudence and Balance are your FRIENDS, NOT Greed 52