Trusted teacher: I'm currently working as quantitative analyst for a Swiss bank. In particular, I build mathematical models for complex financial products, hence in my daily job I use a variety of mathematical and programming tools. If you have just completed your Master's Degree or PhD and you would like to land a job in Quantitative Finance, I'm sure I can help you preparing for technical interviews about math, programming (C++, Python) and mathematical finance. Moreover, I can give you some precious insights about this job market. I'm also available to assist you during the preparation of maths or physics exams at university level
Financial markets lessons in Switzerland
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5 financial markets teachers in Switzerland
Ilja - Zug56Fr
Learn more about investing in the financial markets, either on a long term basis or get direct coaching for your current trading. - Learn more about Trading Psychology and the difference between losing and winning traders - Find out about fundamental and technical analysis and start to understand what drives the markets - Interest rate analysis, yield curve, macro & micro economics - Analyse your trades and understand what drives your own psychological thinking (Greed vs. Fear) - Understand the importance of risk management and trading discipline - Learn about quantitative trading and liquidity management. Personally I have more than 10 years of experience in finance and have successfully managed my personal trading and investment account for the last 5 years.
Financial markets · Personal finance · Finance
Gianmarco - Adliswil40Fr
Trusted teacher: I'm graduated in Quantitative Finance and I have a master degree in Financial Mathematics. I can confidently cover the following topics: - Derivatives pricing; - Stochastic finance and calculus; - Binomial trees; - Option pricing; - Black and Scholes formula;
Financial markets · Finance
Professeur - Geneva107Fr
Financial professional CFA graduate with many teaching experiences (professional bodies specialized in exam preparation, universities and private courses) offers courses in economics and individual and group finance. These courses are aimed at the following audience: professionals already working in finance and seeking to expand their skills. professionals and students seeking support for the preparation of professional exams (CFA, Claritas, ...) and / or academics. The topics covered are the following (non-exhaustive list): Economy: microeconomics, macroeconomics and international economics. Finance: market finance, corporate finance, financial mathematics.
Financial markets · Economics for students · Economics for adults
Mattia - Zurich67Fr
Trusted teacher: MsC in Engineering with top marks and research assistant of Econometrics for Italian top University. Business Expert in Risk Management. Academic Research in Quantitative Finance and Algorithmic Trading. Common discipline covered: Econometrics (with applications in R, Stata, SPSS, Eviews, Gretl), Statistics, Financial Mathematics, Quantitative Support for Master Degree Thesis (from Regressions to all statistical applications), Risk Management, Mathematics, Computer Science I help with assignments, exams, presentations, advanced research, dissertations, big programming projects and general skill enhancement. Proficient in all major statistical packages: R, SPSS, Stata, Matlab, EViews, Gretl. Covering university courses all around Europe: Italy, United Kingdom, France, Germany, Spain, Portugal,... Technical Skills (application and often implementation from scratch): 1) Econometrics: Multivariate Regression, Discrete variable models (i.e. Logit), Time series models (i.e. AR/MA, ARCH/GARCH), Vector AutoRegressive model (VAR), Cointegration (Engle-Granger, VECM), Long-memory process (Fractional Integration), Regime switching models (Hamilton Filter), Kalman Filter, Unobserved Components ARIMA model, Beveridge-Nelson decomposition (Hansen's approach), Copula methods, Metropolis-Hastings algorithm, Black-Litterman model (Meucci's approach), Hierarchical Risk Parity 2) Quantitative Trading (Mid-High Frequency Trading): Stat Arb & Pairs Trading models, Order Imbalance & Order Replenishment effects on intraday returns, Optimal Setup of Entry-Exit Trading Triggers for Quant Trading Strategies, Stat Arb Bertram Model, Data sampling rules for non equally-spaced data (time vs. volume clock for high freq data), Bid-Ask Bounce Bias & Sahalia Method for Microstructure Noise Estimation & Test, Hayashi-Yoshida Lead-Lag Index, D'Aspremont Method for Mean Rev Portfolios, Market Fragmentation in Financial Markets, High-Low prices & Pivot Points trading rule, Trend Following Strategy, Avellaneda-Stoikov Model for Optimal Trading Execution 3) Risk Management: P&L production & analysis for energy trading, VaR & Profit at Risk for energy trading, Merton approach for Credit VaR with/without credit rating migrations, EVT & Copula-based VaR, Stress Test models, Structured Credit Models for Regulatory Risk-Transfer, Additional Value Adjustments for Balance Sheet, Risk Aggregation, Model Risk, Interpolation Methods for multi-year PD Term Structure, Methods for Semidefinite-Positive Corr Matrix Adjustment 4) Financial Mathematics: Longstaff-Schwartz, HJM model (Glasserman's scheme), Greeks with Finite Difference Method, CPPI Products & Cushion Multiplier Setup 5) Machine Learning: Support Vector Machine, Decision Tree, Principal Component Analysis & Regression, XGBoost, Random Forest
Statistics · Finance · Financial markets