1. Enhancements to server-side Pricing “Modes” spread, yield, price - when are they used? VaR of the book Expected vs Potential Confidence interval, “holding period” Day1 and Day2 - how did VaR change? Risk “Attribution” - interest Rate (IR01) or credit spread (CS01)? Segregate book by quality - above/below inv grade We will run different scenarios by quality - why?

2. When do we start with price? Tracking benchmark or not Absolute or relative (yield or price) High yield bonds are priced using “price” not spread or yield Relevance to VaR Equities example

3. VaR methodology we will use Historical simulation 1 day change, 90% confidence interval 10 days of historical data (in practice several years) Each security will have an associated historical file Name will be the unique ID in our data file for ex., “SBB_0001” For investment grade spread and benchmark yield For high yield (junk) historical file will have price Column based When not starting with price, full re-val or “greeks-based” - (taylor series) Pros/cons

4. Server-side Mechanics Socket code fragment Server-side API is determined by how you craft a message set Message set choices Ascii or Binary? Balancing process hop frequency vs grouping of results Client-side concerns Recovery Sync or async Python, Ruby, Java, C# all have socket abstractions/free libs Case study - Govt bond trading desk pricing/risk app

5. For Next Week Third and final quiz on MMM Client and server communicating on laptop Some of spec implemented Drill down into VaR methodologies VaR requirement to our front end Specifics on how we will calculate our VaR and our historical data file schema…