1st lesson belanja
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John
- Rate RM321
- Response 17h
-
Students6
Number of students accompanied by John since their arrival at Superprof
Number of students accompanied by John since their arrival at Superprof
RM321/h
Contact
1st lesson belanja
- Economics
- Macroeconomics
- Finance
- Econometrics
Quantitative trader/developer with a MSc in Finance teaches Financial Markets, Macroeconomics, Investing principles, AI applied to Finance and How to build your own Investment/Trading Algorithms
- Economics
- Macroeconomics
- Finance
- Econometrics
Lesson location
About John
About Me — Professional, reliable, and results-oriented I’m John, a Swiss quantitative trader-developer with an MSc in Finance (HEC Lausanne). I design and run 30+ systematic strategies across equities, FX, and crypto, supported by professional infrastructure (IBKR via FIX/IB Gateway, MT5, SQL, Docker). My teaching is grounded in risk management, evidence, and real-world execution—no hype, just methods you can trust and reuse. Why you can trust my teaching Proven practice: live, production-style workflows (clean data, realistic costs/slippage, post-trade analytics). Risk-first mindset: volatility targeting, drawdown controls, and disciplined validation (out-of-sample, walk-forward). Regulatory awareness: I’m building a Swiss SA and a US LLC and pursue a fully compliant path (education only; no investment advice). Clear structure: each lesson has objectives, a hands-on build, and a concise written recap with next steps. Professional standards: punctuality, respectful communication, confidentiality, and transparent expectations at all times. What students can expect Clarity and rigor: complex ideas explained simply, backed by examples and templates you keep. Personalization: pace and depth adapted to your background—coding experience is optional. Practical outcomes: from finance basics to AI-for-finance and algorithm design, you leave with usable skills and artifacts (notebooks, checklists, starter code). Bilingual: English and French. I take your learning seriously and measure success by your confidence and independence. My goal is to make you competent, careful, and capable—whether you’re a motivated beginner, a student, a career switcher, or an active investor seeking discipline and structure.
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About the lesson
- Primary
- Secondary
- SPM
- +5
levels :
Primary
Secondary
SPM
Form 6
STPM
Adult education
Masters
Doctorate
- English
All languages in which the lesson is available :
English
About my approach I’m John, a quantitative trader-developer (MSc Finance, HEC Lausanne). I teach with a risk-first, project-based method that blends market intuition with rigorous, production-style workflows (clean data, realistic costs/slippage, robust evaluation). Everything we do is hands-on and tied to real-world use. Teaching method & techniques Project-based learning: short concept → guided build → mini-deliverable (notebook, dashboard, backtest, or TradingView/MT5 script). Risk discipline baked in: volatility targeting, drawdown rules, pre-trade checks, and post-trade analytics. Evidence over hype: out-of-sample tests, walk-forward, data leakage checks, and practical error traps. Clear building blocks: data → features → model/rules → execution → monitoring. Tooling you’ll reuse: Python (pandas, numpy), yfinance/Polygon, SQL basics, TradingView Pine/MT5, and simple NLP for news/sentiment. A typical 60–90 minute lesson Warm-up (5–10 min): quick review of last outcome and today’s goal. Core concept (10–15 min): targeted explanation with one clean example. Hands-on build (25–40 min): we implement—e.g., a factor screen, a macro dashboard, or a strategy backtest with realistic costs. Validation (10–15 min): we stress-test (OOS split, walk-forward, regime check), discuss risk/position sizing. Wrap-up (5–10 min): key takeaways, short homework or template to extend, and next-step plan. What sets me apart Live, production mindset: I teach from real execution practices (IBKR Gateway/FIX workflows, SQL pipelines)—not just slides. Risk & realism: transaction costs, slippage, and regime awareness are included from day one. Clear templates: you leave with reusable code/notebooks, checklists, and playbooks. Bilingual & structured: English/French, with concise summaries and action items each session. Ethical & regulated path: I frame methods within sound compliance thinking (education only, no investment advice). Who these lessons are for Motivated beginners to advanced learners in: finance, economics, data/AI, or trading. Students (HS/Undergrad/Master’s) needing clarity, structure, or a capstone-style project. Career switchers & junior quants looking for practical, portfolio-ready builds and interview-level rigor. Active investors & founders who want a disciplined approach to markets, macro, and systematic strategies. Coding background: helpful but not required—I adapt pace and provide starter templates. Topics you can choose (mix & match) Financial Markets Basics: microstructure, ETFs, order types, price drivers. Macroeconomics for Investors: cycles, yield curves, gold/Treasuries hedging, policy shocks. Investing Principles: asset allocation, volatility targeting, drawdown controls, rebalancing. AI for Finance: sentiment/NLP, feature design, evaluation pitfalls, simple ML pipelines. Build Your Own Algorithm: momentum/mean-reversion/factor screens, risk sizing, and execution hygiene.
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Rates
Rate
- RM321
Pack rates
- 5h: RM1605
- 10h: RM3210
online
- RM321/h
free lessons
This first lesson is free to allow you to get to know your teacher so that they can best meet your needs.
- 1hr
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