Notes from Robert Kissell and Roberto Malamut!

– pre-trade analysis: liquidity summaries, cost & risk estimate, trading difficulty (not every order good for algorithmic implementation- why?)

– tight range: customized algorithm for a specific order

– implementation shortfall benchmark prices (e.g. investment decision price,  previous night’s closing price, arrival price), see other prices: vwap, twap, average of open, high, low and close

– previous  night’s closing price with higher risk than arrival price (timing), thus previous night’s algo is going to be more passive (overnight risk involved, higher than in the case of arival price algo)

– price-based scaling techniques: strike (lowest mean, highest risk that the static POV( follow the crowd, large order in short time)), plus (lower mean and higher risk than the static POV), wealth (higher mean but lower risk than the static POV)

-strike: more aggro in favorable conditions, less aggro when prices above the benchmark price, lower cost than the POV’s one

– plus: maximize the likelihood that the algo outperforms the benchmark price, more aggro ITM, less agro OOTM, more sensitive (risk error in the denominator),

– wealth: more passive in times of favorable prices, more aggro OOTM


– Dennis Chen: “A VWAP strategy usually requires the 20-60 days averaged historical volume curve from a stock to construct the trade plan” (VWAP = ” “history will repeat itself”)

– Dennis Chen: “TWAP is similar to VWAP except the the trade plan is a straight linear line up such that it doesn’t require historical volume curve. TWAP is used when trader believe that a stock doesnt have any volume pattern to follow, e.g. a low liquidity stock.”

– Dennis Chen: “The implementation of MOC is to look at the historical average volume curve of the stock. if the order quantity is over 30% of the close volume, we should start execute the order before the close auction and try to keep below 30% of the market.”

– Dennis Chen: “The benefit is that we have further price improvement when market is moving rapidly towards us(e.g. someone in the market sending a market type of order to take out multiple price level of orders at your passive orders side). The cost of this is the implementation complexity plus you are telling the people in the market that “I am running an algo order”.”

– Dennis Chen on limiting the trading risk: “An abosolute price change vs close/open price. e.g. the aglo will only trade within 10% variation of the last close price.”,  A “fair” price check. This can be done by some calculation with the combination of open price and last few price movement.”,  “ADV(Average Daily Volume) check. an order over 30% of this is considered to be risky and may need hand trading.”, “Trade frequency check. If a stock has only been traded average 10 times a day over the last month. Would you trust algo to trade it?”

About misha

Imagine a story that one can't believe. Hi. Life changes here. Small things only.
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