Essential concepts for quant trading, research, and interviews — explained clearly.
40
Concepts
7
Categories
6 concepts
Monte Carlo simulation uses repeated random sampling to model the probability of different outcomes in complex systems, making it essential for derivatives pricing, risk analysis, and strategy evaluation.
Expected value is the probability-weighted average of all possible outcomes of a random variable, forming the mathematical foundation for every rational trading and betting decision.
Bayes' theorem provides a mathematical framework for updating the probability of a hypothesis as new evidence becomes available, making it central to both quant interviews and trading decision-making.
Conditional probability is the probability of an event occurring given that another event has already occurred, forming the basis for Bayesian reasoning and many quant interview questions.
The normal (Gaussian) distribution is the bell-shaped probability distribution that appears throughout statistics, finance, and natural science, characterized by its mean and standard deviation.
The Law of Large Numbers states that as the number of trials increases, the sample average converges to the expected value — the mathematical justification for why systematic trading works.
Our bootcamp covers probability, market making, options, and every topic you need to ace interviews at top quant firms. Get 1:1 mentorship and 500+ practice questions.
Book a Free Quant Consult