Financial market data analysis
6 ECTS
Master's
Czech
Petr Hájek
The aim of the course is to provide students with knowledge of financial markets, both in theory and in practice. Emphasis is placed especially on mastering technical and fundamental analysis, trading simulations and predictive models using statistical and econometric tools.
Course outline
Financial trading terminology(Ask, bid, spread, tick value, tick size, pip, slippage), trading orders, trading hours, market liquidity over time, types of brokers (ECN, systematic internaliser). Bond pricing and yield curves.
Derivatives tradingCommodity (forwards, futures) and currency contracts. Rolling of contracts, swap calculations in the currency market. Options (call, put), LEAPS, Greek letters and introduction to option pricing. Margin, leverage. Analysis of Commitments of Traders. Break-even points and option profitability calculations.
Option strategies and their applicationSpreads (all four variants), Iron Condor, Iron Butterfly. Profitability analysis of option strategies. Trader responses to market movements and the time evolution of option contract prices.
Technical analysisTechnical analysis. Patterns. Price action trading strategies. Application of price action strategies to time series of assets. Examples using option contracts. Methods of calculating stop-loss and profit targets. Calculation of Risk-to-Reward Ratio.
Mathematical models of money management and risk controlAnalysis of the impact of money management and related risk control on the profitability of trading strategies.
Fundamental analysis, intrinsic value of a companyPractical demonstrations of fundamental analysis.
Option flow and its use as a leading indicator of stock market developmentsAnalysis of the combination of option flow with technical analysis (price action strategy) and fundamental analysis.
Stock market vs. economic cyclesRisk analysis in fundamental analysis, combined with technical analysis.
Basic statistical and econometric tools used in financial data analysisProbability, law of large numbers, central limit theorem, convergence, stationarity and ARIMA models. Applications on financial time series, model evaluation and cross-validation. Benchmark construction and naive models.
Markov chains, Monte Carlo and simulations in financeGambler’s ruin problem and applications of Markov chains.
Portfolio optimisation, Markowitz model, extended Markowitz modelApplications to stock exchange data and cryptocurrency data, stress scenario simulations.
Black–Scholes equation and approximation methodsEstimation of the Black–Scholes model on data. Lognormal distribution, pricing functions and value development, estimation of implied volatility.