What courses in math\stat did you take? Name them for us, please. Name the topics.
What languages can you code in now? If you know R, python, what packages are you very familiar with?
Of course
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General Mathematics: Differential calculus, Integral calculus, Limits, Sequences and series, Real functions, Continuous functions, Limits
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Statistics: Summary indices for univariate variables, bivariate phenomena, Sampling schemes and construction of sample random variables
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Mathematical Finance: Derivatives contracts and their valuation, Time dynamics of interest rates, CAPM, Generalization of compound capitalization for equity securities, Option pricing (from the discrete to the continuous model)
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General Mathematics 2: Functions of two or more variables, differential calculus, Quadratic forms, (un)constrained optimization problems, Discrete and continuous probability distributions, double parametric integrals, vector spaces, bases, generator systems, Eigenvalues, eigenvectors, eigenspaces, Bilinear spaces, isometries.
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Statistics 2: Transformations and convolutions of random variables, Multidimensional random variables, Notable inequalities (Jensen's inequality, Markov's inequality, Chebyshev's inequality), sequences of random variables (notions of convergence and laws of large numbers), point estimation (properties of estimators, method of moments and delta method), Likelihood function and maximum likelihood method, Interval estimation (construction of confidence intervals), Elements of computational statistics (introduction to the R language), Hypothesis testing (significance tests, likelihood ratio tests), Estimation methods in particular situations ( profile likelihood and EM algorithm), Statistical model selection (graphical techniques, goodness-of-fit tests, likelihood-based criteria)
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Financial Econometrics: Classical linear regression model and diagnostic tests, Regression analysis for historical series (ARMA/ARIMA, Autoregressive Distributed-Lag models, Granger causality), Models to describe volatility (conditional heteroscedasticity, GARCH/ARCH).
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Actuarial Mathematics (life): Fundamental biometric functions, Traditional life insurance contracts, Annuities, Premium calculation, Risk and savings premiums and mathematical reserve formation, Life insurance reserving, Linked policies (Cox-Ross-Rubinstein model)
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Actuarial Mathematics (non-life): Determination of the risk premium, Construction of the rate premium, Personalisation of the premium, Technical management indicators, Technical reserves, The calculation of the premium reserve in the accounting balance sheet, Statistical-actuarial methods for the evaluation of claims reserves, Risk retention and reinsurance methods
- Risk Theory: Moments, Generating Functions, and Probability Distributions (Bernoulli-Binomial-Poisson-Negative Binomial-(log)Normal-Gamma-Exponential-Chi Squared-Student's) , Individual and Collective Approach in Risk Theory, Moments of the Aggregate Cost of Claims, The Risk Reserve and Its Relationship with Claim Costs, The Risk Reserve Over a Multi-Year Horizon
Python: matplotlib, pandas, numpy, scipy
R (not really familiar with): ptprocess, hawkes
