SLIDE 1 FinTech Platform – Algorithmic Models and Trading Strategies
CEO Eniac FinTech Limited
SLIDE 2 Who are we?
- Eniac is a FinTech company providing consultancy,
design and development related to quantitative finance and algorithmic model building for financial institutes and private investors.
- Our V-Algo FinTech platform provides a rendezvous for
big data, algo developers, algo entrepreneurs and professional investors to enhance financial success, risk assessment and investment experience in the global financial markets.
SLIDE 3 Agenda
- 1. The Changing Financial Landscape (paradigm
shift)
- 2. Algo Model Development and Innovation
- 3. FinTech Platform and Innovation
- 4. Enhancing financial success, risk assessment
and investment experience
SLIDE 4
The changing financial landscape
SLIDE 5
Fintech – Quant Finance & Algo Models
SLIDE 6
Fintech – Quant Finance & Algo Models
SLIDE 7
Fintech – Quant Finance? Algo Trading?
SLIDE 8
Fintech – Quant Finance & Algo Trading
SLIDE 9 Growth in Algo Trading
Source: Aite Group
SLIDE 10 Source: https://en.wikipedia.org/wiki/Algorithmic_trading
Growth in Algo Trading
SLIDE 11 Gap Analysis
Source: The IBM Financial Markets Framework
SLIDE 12
Algo Model Development
SLIDE 13 Example,
1. Framing a research problem - “blackjack” 2. Statistical model
a) house/banker’s advantage (~0.5% - 3%) b) Law of large numbers
3. Order and Execution
a) Data cleansing (random card generator) b) High frequency transactions/trading c) Risk controls
- stand on 17 or more
- minimal bet
- table limit
Algo model for the banker? player?
SLIDE 14
SLIDE 15 Algo development
- 1. Problem framing (opportunity identification)
- 2. Mathematical model
a) Quantify the behaviours and factors (parameters) b) Accuracy vs. Complexity vs. Efficiency
a) Probability
- 4. Descriptive vs Predictive models
- 5. Other scientific approaches
- 6. Computer logics and algorithms
a) Data cleansing, mining, analytics, TS DBS b) Calculation c) Order & Execution d) Risk Controls
SLIDE 16
Simple Algo Models (Technical Analysis)
Before data data visualization human + order & execution Now big data data analytics/human algo model/human computer + order & execution
SLIDE 17 Big Data (interdisciplinary; innovative)
Skirt length theory (Hemline theory) HKEx (data volume/day)
Every day (day-data) – 1M bytes Every minute (minute-data) – 1G bytes Every tick (tick-data) – 60G bytes
SLIDE 18 More complicated Algo Models
Pair Trading/Statistical Arbitrage
- correlation
- order & execution
SLIDE 19
Borrowing from other science disciplines?
Signal Processing – Electrical & Computer Engineering
SLIDE 20
Borrowing from other science disciplines?
Quantum Physics
SLIDE 21
Borrowing from other science disciplines?
AI / Machine Learning – Computer Science
SLIDE 22 Algorithmic Models and Trading?
Market volatility
- 1. Identify market opportunities, i.e.
inefficiency, discrepancy, trends, pattern, etc
- 2. Observe and “predict/describe” the market
- data modeling, data analytics, data mining
- intelligence analysis (telecom, AML, weather
forecast, etc.)
- 3. Risk controls (discipline)
- 4. Reduce human fallacies
SLIDE 23 V-Algo Critical Success Factors (Algo ICT Infrastructure / FinTech Innovation)
Big Data
Low Latency and Robust ICT Network Real-Time Risk Management Time Series Database
SAFE
SLIDE 24
V-Algo A new entrepreneur experience for the young talents
SLIDE 25
Building the FinTech race track for algo testing
SLIDE 26
Q & A
