Ambition:
Become a quant trader active in high frequency trading
Internal Origin
(attributes of the system)
Helpful to achieving the objective
Strengths
- Broad Business Know How
- Financial Sector Know How
- Trading Specialist
- Already apt in low and medium frequency trading
External Origin
(attributes of the environment)
Helpful to achieving the objective
Opportunities
- Trading has become fully algorithmic
- Great volatility to be used for profit
- Crypto adds a new dimension to trading
Internal Origin
(attributes of the system)
Hamper achieving the objective
Weaknesses/Areas for further development
- Weak machine learning skills
- Average in python programming
- Need to strengthen stats and math know how
External Origin
(attributes of the system)
Helpful to achieving the objective
Threats
- Trading works against retail
- Volatility can go both way
- Trading strategies change over time
Action Plan Template
| What do I want/need to learn? | What do I have to do to achieve this? | What resources or support will I need? | How will I measure success? | Target dates for review and completion |
|---|---|---|---|---|
| Provide a specific description of the desired changes (e.g. skills to gain, knowledge to acquire, topics/themes/content to cover) | Some examples, a new/ongoing course, conference, self-development (like wider research or reading), coaching/mentoring, job shadowing | Some examples, teaching staff support, library support, student advisor support, line manager, etc. | Some examples, appraisals, course assessments, team feedback, tutor feedback | Note that these need to be realistic/achievable |
| Python | Spend time in programming (3 hours per week at least) | Generate more time | Able to generate more code | 31/12/2022 |
| Machine learning | Spend time in programming (3 hours per week at least) | Generate more time | Able to generate more code | 31/12/2022 |
| Stats and maths | Spend time in programming (3 hours per week at least) | Generate more time | Easier applications of stats model to my trading strategies | 31/12/2022 |
| Improve on Greenblat’s trading strategy | Backtest more | Review quantinsti institiute training material | ROI of 20% p/a | 31/12/2022 |
Progress Update