The use of algorithms to automate trading decisions based on predefined criteria, enhancing efficiency and speed.

The process of testing a trading strategy using historical data to evaluate its effectiveness before live implementation.

Refining trading algorithms to improve performance metrics, such as maximizing returns or minimizing risk.

A measure of risk-adjusted return, indicating how much excess return is received for the extra volatility endured.

The peak-to-trough decline during a specific period, representing the maximum loss from a peak to a subsequent trough.

A high-level programming language widely used in finance for data analysis, algorithm development, and backtesting.

Quantitative measures used to evaluate the effectiveness of trading strategies, including returns, volatility, and risk.

Practices that ensure fairness and compliance with regulations in algorithmic trading, emphasizing responsible decision-making.

A systematic plan designed to achieve profitable trading outcomes, often based on technical or fundamental analysis.

The graphical representation of data to identify trends and patterns, enhancing the understanding of trading performance.

The structure and processes that govern how financial markets operate, including order types and execution.

A set of rules or calculations used to solve problems or perform tasks, crucial for automating trading decisions.

The use of mathematical models and computational techniques to analyze financial markets and securities.

Past market data used for backtesting strategies, providing insights into potential future performance.

A technique used to determine how different values of an independent variable impact a particular dependent variable.

An indication to buy or sell an asset, generated by a trading algorithm based on specific criteria.

A detailed trading plan that incorporates various elements such as entry, exit, and risk management.

The process of adjusting, organizing, or transforming data to prepare it for analysis or visualization.

A structured approach for developing trading algorithms, often including libraries and tools for backtesting.

Laws and guidelines that govern trading practices, ensuring transparency and fairness in financial markets.

A process where colleagues evaluate each other's work, providing constructive feedback to enhance quality.

The culmination of the course where participants showcase their developed trading strategies to industry experts.