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“Convexity” as a book category gathers works that examine how curvature and nonlinearity shape outcomes—where small changes can accelerate effects, diversification can create upside, and averages can outperform extremes. It spans rigorous mathematics on convex sets, functions, and optimization, along with practical applications in machine learning, operations research, economics, and engineering. It also includes finance titles on bond duration/convexity and derivative payoffs, as well as accessible essays on decision-making under uncertainty, risk, robustness, and optionality. Readers will find textbooks, primers, and case studies that use tools like duality and subgradients to solve real problems, plus broader explorations of how “convex thinking” helps design strategies and systems that benefit from volatility and avoid nonlinear downsides.

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