Backtesting
benchmark
A reference series used to evaluate strategy returns, risk, exposure, or opportunity cost.
- Choose a benchmark that matches the strategy's universe, currency, and investable alternatives.
Related: alpha, beta, drawdown
Glossary
IBKR + Python glossary
A shared vocabulary for Interactive Brokers, TWS, Gateway, market data, order handling, backtesting, portfolio metrics, and Python workflows.
Search and filters
IBKR
Interactive Brokers account, contract, routing, and API concepts.
7 terms
TWS
Trader Workstation terms for desktop API development and manual review.
5 terms
Gateway
IB Gateway terms for lighter, longer-running API sessions.
3 terms
Market data
Live, delayed, historical, and permissioned data terms.
8 terms
Orders
Order types, identifiers, controls, and safety vocabulary.
8 terms
Backtesting
Research validation terms and common sources of overstatement.
7 terms
Portfolio metrics
Return, risk, exposure, and performance measurement terms.
8 terms
Python
Python environment, data, async, and reproducibility terms.
8 terms
Results
7 matching terms
Backtesting
lookahead bias
A research error where a strategy uses information that would not have been known at the simulated decision time.
- Timestamp alignment, adjusted data, and signal calculation windows are common sources.
Related: out-of-sample, walk-forward, data leakage
Backtesting
out-of-sample
Data reserved for evaluation after strategy rules or parameters have been selected using separate development data.
- Repeatedly tuning to the out-of-sample set turns it into another in-sample set.
Related: in-sample, walk-forward, overfitting
Backtesting
slippage
The difference between an assumed execution price and the actual or modeled fill price.
- Slippage assumptions should vary by liquidity, order type, volatility, and trade size.
Related: market order, transaction costs, fill
Backtesting
survivorship bias
A research error caused by testing only instruments that still exist or remain listed, excluding failed, delisted, or removed instruments.
- Survivorship bias can make historical strategies look more robust than they were.
Related: universe selection, benchmark, sample period
Backtesting
transaction costs
Costs associated with trading, including commissions, fees, spreads, market impact, borrow costs, and taxes where relevant.
- Backtests that ignore realistic costs often overstate performance.
Related: slippage, turnover, spread
Backtesting
walk-forward analysis
A validation workflow that repeatedly trains or selects parameters on one time window and evaluates them on a later window.
- Walk-forward testing helps reveal parameter instability, but it does not guarantee future performance.
Related: out-of-sample, overfitting, sample period
Educational boundary
This content is for educational and technical research purposes only. It is not financial advice, investment advice, trading advice, tax advice, or legal advice. Backtests and examples may contain errors or omissions. Past performance does not guarantee future results. Always test code in a safe environment before using it with real accounts or live trading systems.
Interactive Brokers, IBKR, Trader Workstation, and IB Gateway are trademarks or registered trademarks of their respective owners. InQuantWeTrust is independent and is not affiliated with, endorsed by, or sponsored by Interactive Brokers.