1. Probability Basics: 👨💻👨💻👨💻

- Definitions of probability, sample space, events, and outcomes.

- Laws of probability: addition and multiplication rules.

- Conditional probability and Bayes' theorem.

- Independence of events.

2. Random Variables and Distributions:🧑🏻🏫🧑🏻🏫🧑🏻🏫

- Discrete and continuous random variables.

- Probability mass functions (PMFs) and probability density functions (PDFs).

- Cumulative distribution functions (CDFs).

- Expectation, variance, and moments of random variables.

3. Common Probability Distributions:📈📈📈

- Bernoulli, binomial, and Poisson distributions.

- Normal distribution and its properties.

- Log-normal distribution for modeling asset prices.

- Exponential distribution and its relation to waiting times.

4. Joint and Conditional Distributions:🐍🐍

- Joint probability distributions for multiple random variables.

- Marginal and conditional distributions.

- Covariance, correlation, and their interpretation in finance.

5. Stochastic Processes: 📚📚📚

- Basics of stochastic processes, including discrete-time and continuous-time processes.

- Random walks and Brownian motion.

- Wiener process and properties of Brownian motion.

6. Markov Processes: 🙌🙌🙌

- Definitions and properties of Markov processes.

- Transition probabilities and Chapman-Kolmogorov equation.

- Applications of Markov processes in modeling financial markets.

7. Monte Carlo Simulation:🚀🚀🚀

- Basics of Monte Carlo methods for numerical approximation.

- Using Monte Carlo simulation for option pricing and risk assessment.

8. Law of Large Numbers and Central Limit Theorem:👩🏫👩🏫👩🏫

- Statements and applications of the law of large numbers.

- Statement and applications of the central limit theorem.

9. Martingales:👩💻👩💻👩💻

- Definitions and properties of martingales.

- Applications of martingales in modeling fair games and financial markets.

10. Black-Scholes Model and Option Pricing:

- Understanding the probabilistic foundations of the Black-Scholes option pricing model.

- The role of the normal distribution in option pricing.

11. Risk and Portfolio Management:

- Using probabilities to assess risk and potential returns.

- Portfolio diversification and risk reduction.

12. Volatility Modeling: 🏡🏡🏡

- Concepts of volatility and its importance in finance.

- Stochastic volatility models and their applications.

Remember to practice solving problems related to these topics and understand how they relate to trading and finance. Interviewers often value the ability to apply probabilistic concepts to real-world scenarios.

#Financialengineering #QuantitativeFinance #RiskManagement #StockTrading #QuantTrader #Trader

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