Effective implementation of stop-loss orders and risk controls is fundamental to preserving capital in algorithmic trading. While sophisticated models and backtesting frameworks can identify profitable edges, markets are inherently uncertain, and even the best strategies can incur losses. Without clear rules to curtail losses when things go awry, a strategy that looks robust on historical data can bankrupt an account in live markets. In this chapter, we examine four core types of stop-loss and risk controls—hard stops, soft stops, trailing stops, portfolio-level stops (often called circuit breakers), and time-based exits—exploring their theoretical underpinnings, practical implementation considerations, and illustrative examples with step-by-step calculations.

Position sizing and capital allocation represent the twin pillars upon which profitable and sustainable algorithmic trading strategies rest. Even a system with an excellent edge can falter catastrophically without proper control of how much capital is risked on each trade and how total capital is apportioned across multiple strategies. This chapter explores four foundational approaches—fixed fractional and fixed dollar sizing, the Kelly Criterion, volatility‐adjusted sizing, and the trade‐off between diversification and concentration—illustrating their theoretical underpinnings, practical implementations, and real‐world examples.

Drawdown (Max, Average) Definitions and Concepts

Definition and Overview Market risk—often called “systematic risk”—refers to the potential for losses resulting from changes in market prices and rates (Hull, 2018). In the context of algorithmic trading, market risk encompasses unfavorable movements in asset prices, interest rates, foreign exchange rates, and commodity prices. Market risk is distinguished from idiosyncratic risk (or “unsystematic risk”), which arises from firm‐specific events (e.g., a CEO scandal, product recall). Because idiosyncratic risk can be largely diversified away, market risk—affecting entire sectors or the broad market—poses the greatest threat to portfolio value.

1. Introduction In the modern financial landscape, algorithmic trading—defined as the use of computer algorithms to automatically execute trades based on preprogrammed instructions—has become ubiquitous. By leveraging sophisticated mathematical models and high-frequency data feeds, algorithmic strategies can capitalize on market inefficiencies at speeds and scales unattainable by human traders alone (Chan, 2013; Aldridge, 2013). Yet, with these advantages comes a unique and intensified set of risks. This chapter, “Introduction to Risk in Algorithmic Trading,” explores why risk management is paramount for algorithmic strategies and delineates the distinctions between discretionary and automated risk profiles.

Introduction Risk management sits at the very heart of successful trading and investing. No matter how sophisticated one’s analysis or how compelling a market thesis may appear, neglecting to manage risk effectively can spell disaster. Yet, time and again, traders overlook fundamental safeguards—such as stop-loss orders—and miscalculate position sizes, leaving them vulnerable to outsized losses that can wipe out months or even years of gains in a matter of hours or days. This article explores why risk management matters, illustrates the peril of ignoring it with a detailed sample scenario, and offers practical guidance to help traders protect their capital without sacrificing opportunity.

Abstract Market makers are vital players in modern financial markets, as they provide liquidity and ensure smoother trading operations. However, the asymmetry of information, capital, and technology between market makers and individual traders creates a significant imbalance, often to the disadvantage of the latter. This article explores the functions and strategies of market makers, the risks individual traders face, and how a robust risk management framework is essential for mitigating such dangers. Drawing on seminal works including Trading and Exchanges by Larry Harris, Market Wizards by Jack D. Schwager, Reminiscences of a Stock Operator by Edwin Lefèvre, and Trading for a Living by Alexander Elder, this article provides a comprehensive review of these dynamics and practical advice on protecting one’s investments.