Data Analysis & TCA

QuantumExecute provides comprehensive Transaction Cost Analysis (TCA) for each executed order, along with simulation and backtesting tools for strategy development.

Ultra-Fast Backtesting: QE’s offline simulation engine allows users to run historical backtests of the execution algorithms at high speed. Instead of testing a strategy in live markets (which can be time-consuming and risky), you can simulate how an algorithm would have executed using historical market data. For instance, you might backtest how the Smart TWAP would perform on a 50 BTC order over the past 24 hours. The engine can replay market conditions and produce an execution simulation in seconds, whereas doing this live would take the full 24 hours. The backtester supports trying multiple parameter combinations in parallel, so you can, for example, run 10 simulations each with different aggressiveness settings to see which yields the best result. This ability to scan a large parameter space quickly helps in optimizing strategy settings before deployment.

Paper Trading (Live Simulation): In addition to offline backtests, QuantumExecute offers a near-real-time simulation mode (paper trading) that mirrors live trading without actually executing orders on the exchange. When running an algorithm in simulation mode, the platform uses live market data to emulate order placements and fills, but no real orders are sent out (or they are sent to a mock exchange environment). This gives results that closely resemble real executions – including partial fills, order book interactions, etc. – but at zero cost and no risk. The simulation mode produces the same type of execution reports as a real trade, which means you can fully practice and evaluate strategies as if they were live. It’s an excellent way to get comfortable with how parameters like participation rate or price bands behave in actual market conditions.

Transaction Cost Analysis (TCA): After each algorithmic order (parent order) is completed, QE generates a detailed TCA report to help you evaluate performance. The TCA report typically includes:

• Slippage Analysis: This compares the execution outcome to relevant benchmarks. For example, it shows the difference between the average execution price and the TWAP/VWAP over the execution interval, as well as versus the arrival price (the price at order start) to quantify slippage. It may also illustrate how the execution progressed over time relative to a theoretical even schedule (execution trajectory vs. ideal schedule). This helps identify if the algorithm was ahead or behind the expected pace and what slippage occurred at different points.

• Execution Completion & Timing: TCA indicates how much of the order was completed at various time milestones (e.g., 25%, 50%, 100% of the planned duration) and whether it finished early or needed the whole time. It will highlight if any leftover amount remains (if the order didn’t fully complete, which can happen if, say, a limit price was set and not reached).

• PnL and Cost Breakdown: The report breaks down the theoretical vs. actual PnL of the execution. For instance, if no cost was incurred (in a hypothetical perfect execution scenario), how much PnL would the trade have made or lost just from market move, versus what actually happened including costs. It itemizes things like realized PnL (due to market move during execution), explicit fees paid, market impact cost, and any unrealized PnL if the execution had an average price better than current market (or vice versa).

• Maker/Taker and Fees: QE’s TCA highlights the percentage of volume executed as maker vs taker, and the fees or rebates associated. A high maker ratio is often desirable as it indicates lower fee expenditure and often better pricing. The report may quantify how much fee was saved due to maker executions.

• Market Conditions & Liquidity: The report provides context on what the market was doing during the execution. For example, it might show the average market volume per interval, or note any major price movements. It could include metrics like order book depth or volatility encountered. If the strategy has dynamic adjustments, it can illustrate how the algorithm reacted to changes (e.g., slowed down during volatility spike).

• Child Order Log: A detailed log of child orders can be part of the TCA or an associated output. This log would list each child order’s timestamp, side (buy/sell), price, quantity, execution type (maker/taker), and execution status. It’s useful for deep analysis or troubleshooting specific behaviors (like identifying if there were periods of no fills and investigating why).

TCA reports are accessible through the platform’s UI (likely in an “Analytics” or “Reports” section). Users can view them online or download them for offline analysis. By reviewing TCA, traders can quantify the benefits of using QE algorithms (e.g., “I saved X bps vs. simple execution”) and identify areas to tweak (e.g., maybe widen the price band next time to get more fill if a lot was unfilled).

<!-- Suggested image: Example TCA report screenshot, showing a chart of execution vs price benchmarks and perhaps a table of metrics -->

Overall, the combination of pre-trade simulation and post-trade TCA feedback creates a powerful loop for continuous improvement: simulate → adjust strategy → execute → analyze → refine.