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# Algorithmic Trading ## What is Algorithmic Trading? - Also known as "Algo Trading" or "Black-Box Trading" - Uses computer programs to follow a defined set of instructions (an algorithm) for placing a trade. - The algorithm is based on timing, price, quantity, mathematical model. ## Why Algorith...

# Algorithmic Trading ## What is Algorithmic Trading? - Also known as "Algo Trading" or "Black-Box Trading" - Uses computer programs to follow a defined set of instructions (an algorithm) for placing a trade. - The algorithm is based on timing, price, quantity, mathematical model. ## Why Algorithmic Trading? - Reduces transaction costs. - Execute trade orders at the best possible prices. - Reduced the possibility of manual errors when trading. - Trade execution speed and accuracy. - Backtesting. - Reduced emotional and psychological factors. - Increased profit. ## Types of Algorithmic Trading Strategies ### Trend Following Strategies - Moving averages - Price breakouts - Channel breakouts - Historical data ### Arbitrage Opportunities - Exploit the inefficiencies in pricing of securities in different markets or forms. - Example: Buy a stock on one exchange and simultaneously selling it on another exchange at a higher price. ### Index Fund Rebalancing - Involve adjusting the holdings of a fund to match the weighting of the underlying index it tracks. - Algorithm to automatically rebalance the fund's holding to align with the index. ### Mathematical Model Based Strategies - Use mathematical models such as: - Regression - Time Series - Machine learning ### Execution algorithms - Volume Weighted Average Price (VWAP). - Time Weighted Average Price (TWAP). - Implementation Shortfall (IS). ## Common tools & platforms - Python - Matlab - R - Trading Technologies - Bloomberg - Refinitiv ## Pitfalls of Algorithmic Trading - Technical Glitches - Model decay - Over-optimization - Data mining bias - Market regime changes - Regulatory risk