Our CEO presented a session about data intelligence for crypto-assets at the prestigious TradeTechFX conference that brings together some of the top FX trading firms in the world. The concept of the session was to highlight some unique insights that could be derived from using data science against crypto datasets.

1. Fascinating
Metrics About
Crypto Assets

2. Agenda
2
❖ Why crypto assets need a new type of analysis
❖ A data science-first approach to crypto asset analysis
❖ Some data insights that will shock you

3. Let’s start with
an obvious
statement...

4. Crypto is a new asset class
with new fundamentals

5. Every financial asset
class in history has
created new
analytical factors

6. Price, volume, information
correlations…
24x7 markets….
Supply-Demand balance…. Dividends, risk….

7. What makes crypto
assets different?

8. Some Things You’ve
Heard Before
8
“Crypto-Markets are irrational”
“Crypto is not directly correlated with other
asset classes”
“Crypto-assets are constantly vulnerable to
cyber attacks”

9. Some Things You’ve
Heard Before
9
“Crypto-Markets are irrational”
“Crypto is not directly correlated with
another asset classes”
“Crypto-assets are constantly vulnerable to
cyber attacks”

10. The Real Differentiators
10
Crypto Assets
record their
behavior in
public ledgers
Crypto Assets
power DApps

11. Crypto Assets are the richest
data asset class in history

12. And the first one that
reveals individual investor
behaviors….

13. But if crypto assets
are so different…
Why do we analyze
them using the same
old techniques?

15. Analyzing crypto assets with just price
and volume is being lazy and ignoring the
data-rich universe of this new asset class

16. INTRODUCING
Crypto Assets require a new
form of analysis…

18. Some fascinating analytics about crypto-
assets….

19. How many active traders are
making money in a crypto-
asset?

20. 2020
In/Out Money Analysis: Bitcoin

21. 2121
In/Out Money Analysis: Ethereum

22. How is This Helpful?
• Pragmatic levels of support and resistance
• Investor sentiment relative to price movements
• Potential trade counterparties

23. How about all time gains and
losses?

24. 2424
Global In/Out Money Analysis: Bitcoin Cash

25. 2525
Global In/Out Money Analysis: Ethereum

26. How is This Helpful?
• Accumulated volume
• Movements in inactive tokens
• Large token holder positions

27. How regularly crypto-assets
change hands?

28. 2828
UTXO Analysis: Bitcoin

29. 2929
UTXO Analysis: Litecoin

30. How is This Helpful?
• Accumulation trends
• Inactive coins movements
• Holding trend analysis

31. Are investors holding a given
crypto-asset for a long-time or
actively trading?

32. 3232
Ownership By Time Analysis: Ethereum

33. 3333
Ownership By Time Analysis: Dash

34. How is This Helpful?
• Momentum of new money coming into a crypto-asset
• Investor sentiment: long-term vs. short-term

35. How much concentration exists
in a given crypto asset?

36. 3636
Concentration Analysis: Bitcoin Cash

37. 3737
Concentration Analysis: Chainlink

38. How is This Helpful?
• Large investor accumulation patterns
• Mass selling risks
• Market manipulation vulnerabilities

39. Is money flowing in or out of
exchanges?

40. 4040
Exchange Classification: Bitcoin

41. 4141
Exchange Netflows Analysis: Bitcoin

42. 4242
Exchange Inventory Analysis: Binance

43. 4343
Exchange Inventory Analysis: Kraken

44. How is This Helpful?
• Monitor funds going in and out of exchanges
• Anticipate potential large positions in a given asset
• Quantify risks levels

45. How are crypto-asset traders
geographically distributed?

46. 4646
East-West Analysis: Ethereum

47. 4747
East-West Analysis: Litecoin

48. How is This Helpful?
• Geographic influence in a crypto-asset
• Risk exposure based on geographic trading patterns

49. Are exchange order books
realistic?

50. 5050
Exchange-On-Chain Analysis: Bitcoin

51. How is This Helpful?
• Quantifying exchange order book risk
• Identify potential fake volume scenarios

52. Fascinating Challenges
52
❖ Blockchain Deanonymization
❖ Derivative analytics
❖ Price Predictions
❖ Exchange fake volumes identification
❖We are working on it!

53. 53
❖ Crypto assets require a new form of
financial analysis
❖ Blockchain datasets reveal incredible
insights about the behavior of crypto
assets
❖ Data science can help simplify crypto
asset analysis for masses
Summary

54. INTRODUCING
Jesus Rodriguez
jr@intotheblock.io
medium.com/@jrodthoughts
intotheblock.com
Thank You!