CFA Level 2 Exam – 21 Week Study Plan, Part 5 of 6

Introductory Remarks and General Guidelines – See Part 1

Week 15 – Derivatives, Part 1

The CFAI has been very generous to you and saved some of the most challenging material for the home stretch.  I would lump derivatives into the middle tier with Corporate Finance and Fixed Income.  Don’t worry, you can do it.

Derivatives starts with the easier stuff and builds to the more challenging material.  In part 1, look for forward basics, currency forwards (think back to Econ), forward rate agreements, futures basics, interest rate futures, and US Treasury bond futures.

Like Fixed Income, Derivatives is a great place to incorporate flash cards.

Week 16 – Derivatives, Part 2; Progress Test 3

Options – you will see both the binomial and Black-Scholes models; both are fair game.  Interest rate options and put-call parity are other important topics.

Swaps & Swaptions – look for interest rate swaps, equity swaps, and currency swaps.  The ability to draw and interpret a swap diagram is a must have skill set.  You will also be introduced to swaptions.

Progress Test 3 – Now is the time to do a progress test through Derivatives.  Hopefully you are noticing improvement over the first two progress tests.  Fixed Income and Derivatives may take additional effort given the volume and complexity of some of the material.  This will be your closest experience to date with a full on practice test, so take it seriously.

Week 17 – Portfolio Management

The last section!  With expectations of one to two item sets, CFAI probably gives more information than a candidate needs or wants at this point, but this section is really a preview of things to come in Level 3.

You will see portfolio variance, CAL, CML, CAPM, SML, the Sharpe ratio and its offspring, problems with mean-variance analysis, multi-factor modeling (remember Quant?), performance measurement issues, flaws of CAPM, intro to ICAPM, the portfolio management process, and the impact of taxes on investor returns.

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Data Science in Finance: 9-Book Bundle

Data Science in Finance Book Bundle

Master R and Python for financial data science with our comprehensive bundle of 9 ebooks.

What's Included:

  • Getting Started with R
  • R Programming for Data Science
  • Data Visualization with R
  • Financial Time Series Analysis with R
  • Quantitative Trading Strategies with R
  • Derivatives with R
  • Credit Risk Modelling With R
  • Python for Data Science
  • Machine Learning in Finance using Python

Each book comes with PDFs, detailed explanations, step-by-step instructions, data files, and complete downloadable R code for all examples.