Chapter 1 - Financial Derivatives (video)
Statistics of Financial Markets
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- 4.9 Rating
- 9 Reviews
- 218 Students Enrolled
Statistics of Financial Markets
Statistics of Finance data; Quantitative finance; Forecasting
-
- 4.9 Rating
- 9 Reviews
- 218 Students Enrolled
Course Content
48 courselets
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26 min | |
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Chapter 1 - Financial Derivatives (pdf)
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1.08 K |
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Chapter 2 - Section 2.1 (pdf)
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583 | |
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Chapter 2 - Section 2.1 (video)
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24 min |
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Chapter 2 - Section 2.2 (video)
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34 min | |
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Chapter 2 - Section 2.2 (pdf)
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2.86 K |
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Chapter 2 - Section 2.3 (video)
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26 min | |
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Chapter 2 - Section 2.3 (pdf)
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2.7 K |
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Chapter 3 - Probability Theory (pdf)
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1.04 K | |
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Chapter 3 - Probability Theory (video)
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27 min |
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Chapter 4 - Stochastic Processes in Discrete Time (pdf)
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1.52 K | |
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Chapter 4 - Stochastic Processes in Discrete Time (video)
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24 min |
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Chapter 5 - Stochastic Integrals and Differential Equations (pdf)
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1.5 K | |
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Chapter 5 - Stochastic Integrals and Differential Equations (video)
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29 min |
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Chapter 6 - Section 6.1 (pdf)
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10.37 K | |
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Chapter 6 - Section 6.1 (video)
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31 min |
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Chapter 6 - Section 6.2 (pdf)
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10.37 K | |
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Chapter 6 - Section 6.2 (video)
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28 min |
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Chapter 6 - Section 6.3 (pdf)
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10.37 K | |
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Chapter 6 - Section 6.3 (video)
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30 min |
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Chapter 7 - The Binomial Model for European Options (pdf)
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6.7 K | |
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Chapter 7 - The Binomial Model for European Options (video)
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23 min |
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Chapter 8 - American Option (pdf)
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8.43 K | |
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Chapter 8 - American Option (video)
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27 min |
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Chapter 9 - Exotic Options (pdf)
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7.42 K | |
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Chapter 9 - Exotic Options (video)
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27 min |
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Chapter 10 - Section 10.1 (pdf)
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4.46 K | |
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Chapter 10 - Section 10.1 (video)
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31 min |
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Chapter 10 - Section 10.2 (pdf)
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4.46 K | |
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Chapter 10 - Section 10.2 (video)
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27 min |
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Chapter 12 - ARIMA time Series Models (pdf)
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3.73 K | |
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Chapter 12 - ARIMA time Series Models (video)
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33 min |
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Chapter 13 - Time Series with Stochastic Volatility (pdf)
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8.95 K | |
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Chapter 13 - Time Series with Stochastic Volatility (video)
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36 min |
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Chapter 14 - Section 14.1 (pdf)
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2.83 K | |
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Chapter 14 - Section 14.1 (video)
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26 min |
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Chapter 14 - Section 14.2 (pdf)
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4.27 K | |
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Chapter 14 - Section 14.2 (video)
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17 min |
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Chapter 15 - Nonparametric Concepts for Financial Time Series (pdf)
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1.33 K | |
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Chapter 15 - Nonparametric Concepts for Financial Time Series (video)
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21 min |
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Chapter 16 - Option Pricing with Flexible Volatility Estimators (pdf)
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1.41 K | |
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Chapter 16 - Option Pricing with Flexible Volatility Estimators (video)
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20 min |
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Chapter 17 - Value at Risk and Backtesting (pdf)
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2.71 K | |
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Chapter 17 - Value at Risk and Backtesting (video)
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31 min |
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Chapter 18 - Copulae for VaR calculation (pdf)
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8.55 K | |
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Chapter 18 - Copulae for VaR calculation (video)
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32 min |
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Chapter 19 - Statistics of Extreme Risks (pdf)
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3.43 K | |
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Chapter 19 - Statistics of Extreme Risks (video)
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40 min |
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Chapter 20 - Neural Networks (pdf)
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4.11 K | |
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Chapter 20 - Neural Networks (video)
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34 min |
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Chapter 21 - Nonparametric Credit Scoring (pdf)
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1.74 K | |
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Chapter 21 - Nonparametric Credit Scoring (video)
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17 min |
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Chapter 22 - Portfolio Credit Risk (pdf)
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3.28 K | |
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Chapter 22 - Portfolio Credit Risk (video)
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28 min |
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Chapter 23 - Technical Appendix (pdf)
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915 | |
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Chapter 23 - Technical Appendix (video)
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19 min |
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Chapter 24 - SPD Estimation using Rookley’s Method (pdf)
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1.82 K | |
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Chapter 24 - SPD Estimation using Rookley’s Method (video)
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9 min |
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Chapter 25 - Voles Volas Values: Implied Volatility Surface Dynamics (pdf)
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16.63 K |
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Chapter 26 - Implied Binomial Trees (pdf)
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5.07 K |
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Chapter 27 - Risk Neutral and Physical Density (pdf)
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2.1 K | |
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Chapter 27 - Risk Neutral and Physical Density (video)
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9 min |
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Chapter 28 - Empirical Pricing Kernel (pdf)
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3.41 K | |
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Chapter 28 - Empirical Pricing Kernel (video)
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13 min |
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Chapter 29 - Simulation of an Itô Integral and a General Itô Process (video)
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8 min | |
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Chapter 29 - Simulation of an Itô Integral and a General Itô Process (pdf)
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1.6 K |
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Chapter 30 - Implied Volatility Surface (pdf)
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2.02 K |
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Chapter 31 - Realized Volatility (pdf)
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3.27 K | |
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Chapter 31 - Realized Volatility (video)
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11 min |
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Chapter 32 - Optimal Exercise Boundary of American Put Option (pdf)
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2.6 K |
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Chapter 33 - Barrier Options (video)
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6 min | |
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Chapter 33 - Barrier Options (pdf)
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760 |
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Chapter 34 - Cliquet Options (pdf)
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1.15 K | |
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Chapter 34 - Cliquet Options (video)
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20 min |
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Chapter 35 - Models for Interest Rates (pdf)
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2.01 K | |
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Chapter 35 - Models for Interest Rates (video)
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18 min |
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Chapter 36 - Box Jenkins Method (pdf)
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624 | |
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Chapter 36 - Box Jenkins Method (video)
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9 min |
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Chapter 37 - Empirical Pricing Kernel and Portfolio Allocation (pdf)
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879 | |
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Chapter 37 - Empirical Pricing Kernel and Portfolio Allocation (video)
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17 min |
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Chapter 38 - Higher-Order Greeks (pdf)
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8.2 K |
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Chapter 39 - Trinomial Tree (pdf)
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1.37 K |
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Chapter 40 - Likelihood of MA(1) Process (pdf)
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1.85 K |
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Chapter 41 - Option Pricing with the Binomial Tree and Monte Carlo (pdf)
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1.75 K | |
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Chapter 41 - Option Pricing with the Binomial Tree and Monte Carlo (video)
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20 min |
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Chapter 42 - The Hurst Exponent (pdf)
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2.26 K |
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Pricing Kernels and Risk Premia (pdf)
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6.46 M | |
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Pricing Kernels and Risk Premia (video)
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30 min |
Requirements
- Good knowledge in multivariate statistical analysis
General Overview
Description
This course gives an introduction to the basic concepts of option pricing and its probabilistic foundations. Next, stochastic processes in discrete time are presented and the Wiener process is introduced. Itô's Lemma is derived and the Black- Scholes (BS) Option model is presented leading to the analytic solution for the BS Option price. Numerical solutions via binomial or trinomial tree constructions are discussed in detail. SFM is continued with Interest Rate Dynamics, valuation of options in spot rate dynamic models, like CIR or the HJM framework. A credit risk portfolio with the discussion of CDOs is finally presented.
Requirements: Multivariate Statistical Analysis (MVA) (or prove equivalent knowledge)
Material：
Statistics of Financial Markets (Franke, Härdle, Hafner), 2019, 5th ed. Springer.
http://www.springer.com/de/book/9783642545382
Statistics of Financial Markets (Borak, Härdle, Lopez Cabrera), 2013, 2nd ed. Springer.
http://www.springer.com/statistics/business%2C+economics+%26+finance/book/978-3-642-33928-8
Bibliography and Sources
- Franke, J., Härdle, W., and Hafner, C. (2019) Statistics of Financial Markets: an Introduction, 5th ed., Springer Verlag, Heidelberg. https://www.springer.com/gp/book/9783030137502
- Härdle, W., Chen, C.Y.H. and Overbeck, L. (2017) Applied Quantitative Finance, 3rd ed., Springer Verlag, Heidelberg. ISBN 978-3-662-54485-3 (372 p)
- Härdle, W., Simar, L. (2019) Applied Multivariate Statistical Analysis, 5th ed., Springer Verlag, Berlin Heidelberg. ISBN: 978-3-030-26006-4 (580 p) https://link.springer.com/book/10.1007/978-3-030-26006-4
- Hull (2005) Options, Futures, and Other Derivatives, 6th ed., Prentice Hall. ISBN 0-13-149908-4 (816 p)
- Cizek, P., Härdle, W., Weron, R. (2011) Statistical Tools for Finance and Insurance, 2nd ed., Springer Verlag, Heidelberg. ISBN: 978-3-642-18061-3 (420 p)
Recommended for you
Meet the instructors !
About the Instructor
Wolfgang Karl HÄRDLE attained his Dr. rer. nat. in Mathematics at Universität Heidelberg in 1982 and in 1988 his habilitation at Universität Bonn. He is Ladislaus von Bortkiewicz Professor of Statistics at Humboldt-Universität zu Berlin and the director of the Sino German Graduate School (洪堡大学 + 厦门大学) IRTG1792 on “High dimensional non stationary time series analysis”. He directs IDA Institute for Digital Assets,
University of Economic Studies, Bucharest, RO. His research focuses on data analytics, dimension reduction and quantitative finance. He has published over 30 books and more than 300 papers in top statistical, econometrics and finance journals. He is highly ranked and cited on Google Scholar, REPEC and SSRN. He has professional experience in financial engineering, S.M.A.R.T. (Specific, Measurable, Achievable, Relevant, Timely) data analytics, machine learning and cryptocurrency markets. He has created the www.quantlet.com platform, a cryptocurrency index, CRIX www.royalton-crix.com He is 玉山学者 （Yushan Scholar), web page hu.berlin/wkh