Central Limit Theorem
The Central Limit Theorem states that the sum (or average) of a large number of independent random variables tends toward a normal distribution, regardless of the original distribution shape.
Essential concepts for quant trading, research, and interviews — explained clearly.
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The Central Limit Theorem states that the sum (or average) of a large number of independent random variables tends toward a normal distribution, regardless of the original distribution shape.
A Markov chain is a stochastic process where the probability of transitioning to the next state depends only on the current state, not on the history — the 'memoryless' property.
Stochastic calculus extends classical calculus to handle random processes, providing the mathematical foundation for derivatives pricing models like Black-Scholes and modern quantitative finance.
Brownian motion (Wiener process) is the continuous-time random process that models the random component of asset price movements and is the foundation of the Black-Scholes model and stochastic calculus.
Random walk theory suggests that stock price changes are independent and identically distributed, meaning past prices cannot predict future movements — a foundational concept in financial economics.
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