Notes by Lex Toumbourou

Week 1

Module 1

• In the overview it mentions students will grade each other - though that was incorrect (unless I missed something!)
• A few books are recommended though I'm not sure I'm interested enough to pick them up.

Module 2

• Basics for hedge fund managers -- computation is barely touch on

2.1

• Incentives for portfolio managers discussed
• Attracting investors
• general info about the types of investors and how to attract them
• Types of fund goals

2.2

• Common metrics for funds
• Annual return
• Risk (calculated as standard deviation of return)
• Risk (draw down?)
• Reward/Risk: Sharpe ratio
• Sortino Ratio -- only counts risk when it goes down
• Calculating Annual return
• metric = (value[end] / value[start]) - 1 = (100 / 50) = 1 = 100%
• Standard deviation of daily return
• daily_rets[i] = (value[i]/value[i-1]) - 1 # where i is the day of the year
• std_metric = stdev(daily_rets)
• Max draw down -- not really described in detail

2.3

• Sharpe ratio
• Used to compare "risk" of similar portfolios
• higher sharpe ratio == more return for the same risk
• Reward/Risk
• metric = k * mean(daily_rets)/stdev(daily_rets))
• k = sqrt(250) for daily returns

2.4

• Learn how to calculate metrics from last two modules
• Adjusted close -- includes dividends -- covered in depth later

Module 3

3.1

• Types of orders
• Buy, Sell
• Market, Limit
• Shares
• Price (if limit)
• Understanding order book at exchanges
• Crossing the spread == when somebody with a bid pays the asking price

3.3

• Exploiting the market as a hedge fund manager
• Order book observation (needs low latency)
• Arbitrage (when markets go out of sync -- very rarely works)

3.4

• Mechanics of the Market
• Overview of how computing works inside a hedge fund
• News packets

Module 4

4.1

• Interview with Paul Jiganti -- trader
• A market maker?
• Fairly difficult to follow
• Dark pools?

4.2

• How orders flow through the system?