Study topics in order, from foundations to advanced. Each path interlinks theory with practice problems.
Foundation of quantitative reasoning: counting, conditional probability, distributions, and stochastic models.
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Distributions, estimation, hypothesis testing, regression, and signal detection for quantitative finance.
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Comprehensive coding interview prep following the Neetcode roadmap: arrays, two pointers, sliding window, stacks, binary search, trees, tries, backtracking, graphs, DP, and more.
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Random walks, Brownian motion, stochastic calculus, and continuous-time models for quantitative finance.
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Pricing, hedging, and risk management for financial derivatives.
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Risk measurement, portfolio construction, hedging strategies, and fixed income for quantitative finance.
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Classic logic puzzles, lateral thinking, probability brainteasers, and game theory problems from quant interviews.
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Number theory, linear algebra, sequences, and mental math — the mathematical toolkit for quant interviews.
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Motivation, decision-making, and self-awareness questions common in trading firm interviews.
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Market mechanics, fixed income, ETFs, and financial products — the domain knowledge every quant needs.
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Supervised and unsupervised learning, ensemble methods, model validation, and feature engineering for quant applications.
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Order books, market impact, execution algorithms, and tick data analysis — the mechanics of how prices form and trades execute.
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