FinTech Platform – Algorithmic Models and Trading Strategies
Dr. Hilton Chan
CEO Eniac FinTech Limited
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.
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
The changing financial landscape
Fintech – Quant Finance & Algo Models
Fintech – Quant Finance & Algo Models
Fintech – Quant Finance? Algo Trading?
Fintech – Quant Finance & Algo Trading
Growth in Algo Trading
Source: Aite Group
Source: https://en.wikipedia.org/wiki/Algorithmic_trading
Growth in Algo Trading
Gap Analysis
Source: The IBM Financial Markets Framework
Algo Model Development
Example,
1. Framing a research problem - “blackjack”
2. Statistical modela) house/banker’s advantage (~0.5% - 3%)
b) Law of large numbers
3. Order and Executiona) 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?
Algo development
1. Problem framing (opportunity identification)
2. Mathematical modela) Quantify the behaviours and factors (parameters)
b) Accuracy vs. Complexity vs. Efficiency
3. Statistical modela) Probability
4. Descriptive vs Predictive models
5. Other scientific approaches
6. Computer logics and algorithmsa) Data cleansing, mining, analytics, TS DBS
b) Calculation
c) Order & Execution
d) Risk Controls
Simple Algo Models (Technical Analysis)Before
data data visualization human + order & execution
Now
big data data analytics/human algo model/human computer + order & execution
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
More complicated Algo Models
Pair Trading/Statistical Arbitrage
- correlation
- order & execution
Borrowing from other science disciplines?
Signal Processing – Electrical & Computer Engineering
Borrowing from other science disciplines?
Quantum Physics
Borrowing from other science disciplines?
AI / Machine Learning – Computer Science
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
V-Algo Critical Success Factors
(Algo ICT Infrastructure / FinTech Innovation)
Big DataLow Latencyand Robust ICT Network
Real-Time Risk
Management
Time SeriesDatabase
SAFE
V-Algo
A new entrepreneur experience for the young talents
Building the FinTech race track for algo testing
Q & A