🎯 IB Algo Bandit Optimizer

Quant decision engine for evaluating Interactive Brokers order-fill algorithms

Overall Success Rate

0.0%

Fills meeting success threshold

Total Trades Logged

Across all active algorithms

Active Choices (Arms)

Algorithms currently in comparison

Next Trade Recommendation Exploitation

Calculating optimal algorithm path...

Probability Best 0%

Expected Win Rate 0.0%

Log a New Trade Record order fill results

Ticker Symbol *

Trade Side

Order Qty (Shares)

IB Algorithm Used

Opening Price ($) *

Avg Fill Price ($) *

Expected Success Outcome

Pending Pricing Input

Criteria: Buy Fill ≤ Benchmark

Expected Success Rates 95% Bayesian Credible Intervals (Error Bars)

Probability of Being Best Monte Carlo simulation share

Cumulative Performance Success rate trend line over time

Trade Execution Log Complete history of logged comparisons

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Date	Ticker	Side	Qty	Algorithm	Benchmark	Fill Price	Slippage ($)	Result	Actions

Success Criteria Definitions Change metrics and acceptable tolerances

Benchmark Metric Type

Slippage Tolerance ($ per share) Allow the fill price to be slightly worse than the benchmark. E.g. $0.02 tolerance means a buy order is a "Success" even if filled up to $0.02 above the benchmark.

Active IB Algorithms (Bandit Arms) Define the set of choices available

Database Administrator & Backups Synchronize local data and clear history

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Raw JSON Database State Click text box to select all, copy, and save to a text file for a raw database backup.