We provide an infrastructure for testing and validating various trading algorithms.
The algorithms we propose are derived using discrete and continuous stochastic optimal control.
Tests and simulations done in this web application are performed with historical and live market data.
Minimum shortfall
This algorithm finds the optimum selling/buying price and volume while
minimizing the overall execution shortfall. The price dynamics follows
the traditional geometric Brownian motion. The volatility and return are
calibrated dynamically using an appropriate linear filter. The VWAP of
this strategy usually exceeds the market VWAP for large execution order.
More details »
The example below shows how this algorithm can be implemented with historical intraday data.
Select the stock from the dropdown list, enter the arrival price, the permanent impact factor
and the Lagrange multiplier. The Lagrange multiplier helps control the total numer of shares
you want to sell/buy.
Optimal VWAP
This trading algorithm returns the recommended trading (selling/buying) volume
and share price so as to optimize the overall trade VWAP (Volume Weighted
Average Price).The main assumption is that the share price follows a
discrete geometric Brownian motion process. The return and volatility are
dynamically calibrated with the Kalman Bucy linear filter.
More details »
The example below shows how this algorithm can be implemented with historical intraday data.
Select the stock from the dropdown list, enter the arrival price, the permanent impact factor
and the Lagrange multiplier. The Lagrange multiplier helps control the total numer of shares
you want to sell/buy.