SFM SFS exercise Chap 1 Derivatives

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SFM SFS exercise Chap 1 Derivatives

SFM SFS exercise Chap 1 Derivatives

  • 0 Rating
  • 0 Reviews
  • 5 Students Enrolled
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Courselet Content

1 components
SFM SFS exercise Chap 1 Derivatives (pdf)
8.54 M

Requirements

  • MVA knowledge

General Overview

Description

  1. Forwards and futures create obligations; options give buyers the right to buy or sell an underlying asset.

  2. Calls give the right to buy, puts the right to sell; European options exercise at maturity, American options also earlier.

  3. A bull call spread combines a long lower-strike call with a short higher-strike call, limiting both gains and losses.

  4. Butterflies benefit from prices near the middle strike; long straddles and strangles benefit from sufficiently large moves.

  5. Payoff describes the terminal contract value; profit also accounts for premiums and, where relevant, financing costs.

  6. No-arbitrage pricing links forwards, stocks, bonds, and European options through replication and put–call parity.

  7. Binomial models price derivatives by discounting expected payoffs under risk-neutral probabilities.

  8. Probability distributions, moments, and dependence underpin financial models; zero covariance does not imply independence.

  9. Random walks model discrete price changes, while martingales have conditional expected future values equal to their current values.

  10. Brownian motion, Brownian bridges, geometric Brownian motion, and Itô’s lemma provide tools for continuous-time financial modelling.

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Meet the instructors !

instructor
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