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Johnson W: Quantitative Trading
Strategies

Quantitative Trading Strategies

A Guide to Market-Beating Algorithms

This book investigates some of the key economic and societal transitions that define our contemporary world. Analysing financial contagion during crises, shifts in macro-financial linkages, transformations in gender equality and industrial structures, or the potential of fintech to foster intergenerational mobility, the authors seek to illustrate the forces reshaping economic systems and societal outcomes in emerging and industrialized countries. Particular attention is given to the relationship between Europe and Asia, with insights into the structural changes, including deindustrialization, energy transition, and gender inequality, seen within these parts of the world. The conference offered a space for lively debate and critical reflection on the varied but interconnected ways economies and societies have responded to new global conditions. The book can be read as a contribution to broader academic and policy debates. The book will be relevant to students, researchers, and policymakers interested in international economics and economic policy.
&nbsp;
Gilles Dufrénot is Professor of Economics at Sciences Po Aix and AMSE and Associate Researcher to the CEPII. His research topics covers growth and international economics.
Takashi Matsuki is Professor of Economics at Ryukoku University. His main topics covers policy-oriented issues and applied econometrics.

Financial Markets, Structural Change and Economic Development

Challenges of Global Economic and Social Transformations

"Quantitative Trading Strategies: Applying Tree-Based and Linear Models"

Quantitative Trading Strategies: Applying Tree-Based and Linear Models is a practical guide for quants, systematic traders, and data-driven portfolio managers who want to design, test, and deploy robust trading strategies. Bridging statistical rigor with market reality, the book walks readers from foundational mathematics and market structure through to fully specified, execution-aware strategies. It is written for practitioners and advanced students who seek to move beyond ad hoc backtests and toward disciplined, model-based trading research.

The book develops a complete workflow for building signals with linear and tree-based models, including OLS, regularized regression, decision trees, random forests, and gradient boosting. Readers will learn how to engineer predictive features from financial time series, frame problems as regression or classification, and perform time-aware hyperparameter tuning and model interpretation. Dedicated chapters cover data integrity, time-series cross-validation, event-driven backtesting, transaction cost modeling, portfolio construction, and risk and performance attribution, culminating in realistic case studies that tie all components together.

Assuming comfort with basic probability, statistics, and Python, the text deepens these skills in a focused, market-centric context. Presented in a LaTeX-friendly structure with clear notation and self-contained sections, it emphasizes reproducibility, governance, and implementation details often glossed over in academic tre

Applying Tree-Based and Linear Models

The integration of technology in emerging economies is reshaping industries, transforming communities, and redefining global market dynamics. By driving innovation in service and production sectors, technology enables these economies to compete on a global scale while addressing local challenges. Understanding this intersection is crucial for fostering sustainable development, enhancing economic resilience, and narrowing global disparities. The technological advancements in these markets not only spur growth but also have far-reaching implications for global trade, collaboration, and progress. Converging Economic Policy, Corporate Strategy, and Technology for Emerging Economies explores the dynamic interplay between emerging markets' service and production sectors and technology. It illuminates the tactics, obstacles, and advancements determining how technology is incorporated into these crucial industries and how it affects economic environments. Covering topics such as capital structure, herding behavior, and stock market, this book is an excellent resource for business professionals, executives, entrepreneurship, academicians, researchers, policymakers, government officials, investors, financiers, students, educators, and more.

Converging Economic Policy, Corporate Strategy, and Technology for Emerging Economies

What if the most important question about a financial system is not where its price will move next, but what the system will still be able to do afterward? Beyond the Price introduces Wave Liquidity Redistribution Theory (WLRT) - a framework for understanding liquidity not simply as an amount of money or an ability to buy and sell, but as a dynamic system of states, constraints, transitions, and redistributions. Beginning with familiar questions about money, markets, and price, Petr Popov gradually develops a different way of seeing financial systems. The book introduces redistribution waves, Phase Time, Adaptive State Space, Liquidity Redistribution Capacity, Fragility and Compensation, and the three laws of WLRT. It then tests how far this language can travel - from financial markets to adaptive systems, machine agents, and asynchronous environments. At the center of the book is a simple but consequential idea: two systems of equal value may possess very different capacities for future action. A successful decision may increase immediate gain while reducing future flexibility; a reserve may be valuable not because it earns more today, but because it preserves possibilities for tomorrow. Written as a scientific-popular introduction rather than a technical monograph, Beyond the Price combines conceptual reasoning, simple formal models, thought experiments, and practical intuition. It does not promise certainty about the future. Instead, it asks how systems can remain capable of acting when the future is uncertain. Ultimately, the book moves beyond the question "How much is it worth?" toward another:

Liquidity, Redistribution, and the Hidden Architecture of Complex Systems

Beyond the Price

Perspectives in Behavioral Economics and the Economics of Behavior

Keynesian Behavioral Macroeconomics analyzes Keynes’s landmark contributions in behavioral economics and develops a new and fresh genre of macroeconomic analysis. It compels us to consider seriously the earlier-generation warnings about the impact of investors’ animal spirits and financiers’ liquidity-presence using cognitive-based and social psychology heuristics. Innovative in its subject matter, approach, theoretical development and policy prescriptions, this constructivist pluralist approach can contribute to important debates. This fresh look in macroeconomics can fruitfully be applied by macroeconomists, policymakers, and market participants to prevent effective demand shortages, stimulate the economy, preserve job creation, and impact redistribution, sustainability and social inclusion. In this timely book, Theodore Koutsobinas develops a synthesis of Keynes’s macroeconomic theory with contemporary developments in behavioral macroeconomics to analyze urgent real-world challenges, and he proposes successful solutions for macroeconomic policy. This volume uniquely explains how Keynes’s magnificent, crucial, but long-forgotten dynamics can be analyzed on the basis of behavioral foundations to explain amplified global finance cycles, booms and busts, and macroeconomic instability with harmful effects on incomes and jobs.

Keynesian Behavioral Macroeconomics

A revelatory and unexpected examination of the political economy of the past century—and an argument that policymakers in government, not the mythical “free market,” created the most dynamic economy the world has ever known. For many decades, a sacred myth has ruled the minds of policymakers and business leaders: free markets, untouched by the soiled hands of government, bring us pros­perity and stability. Economist and writer Chris Hughes demolishes this fantasy by chronicling the hidden history of American capitalism: a centuries-long tradition of industrial policy where the state’s guiding hand has been essential to prosperity. Markets do not exist in a vacuum but are the product of a deliberate political order, a practice he calls “marketcraft.” This groundbreaking book takes readers through the high-stakes evolution of our most critical industries, from the state-led management of our banking and financial systems to the intentional development of energy, aviation, healthcare, and semiconductor markets. American government has always done far more than just react to “market failures.” Tracing a lineage from Alexander Hamilton to the architects of Trump and Biden industrial policies, Hughes introduces the “marketcrafters”—the technicians and organizers who combined expertise with judgment to cultivate the economy like a garden. By studying their triumphs and failures, we can pursue a smarter industrial policy for the future. As we navigate the transformative potential of artificial intelligence and the urgent demands of the climate crisis, this book serves as an essential road map for harnessing the power of markets to build a stable, inclusive, and abundant future for all Americans.

The 100-Year Struggle to Shape the American Economy

Marketcrafters

Understanding Fundamental Analysis, Technical Analysis, and Financial Assets

Demystifying the Markets

Named one of Financial Times’s Best Books of 2025, that bestselling author Tim Hartford called "fun" and "nerdy in the best way" Nobel Prize winner Richard H. Thaler and rising star economist Alex O. Imas explore the past, present, and cutting-edge future in behavioral economics in The Winner’s Curse. Why do people cooperate with one another when they have no obvious motivation to do so? Why do we hold on to possessions of little value? And why is the winner of an auction so often disappointed? Over thirty years ago, Richard H. Thaler introduced readers to behavioral economics in his seminal Anomalies column, written with collaborators including Daniel Kahneman and Amos Tversky. These provocative articles challenged the fundamental idea at the heart of economics that people are selfish, rational optimizers, and provided the foundation for what became behavioral economics. That was then. Now, three decades later, Thaler has teamed up with economist Alex O. Imas to write a new book with an original and creative format. Each chapter starts with an original Anomaly, retaining the spirit of its time stamp. Then, shifting to the present, the authors provide updates to each, asking how the original findings have held up and how the field has evolved since then. It turns out that the original findings not only hold up well, but they show up almost everywhere. Anomalies pop up in people’s decisions to save for retirement and how they carry outstanding credit card debt. Even experts fail to optimize. The key concept of loss aversion explains missed putts by PGA pros and the selection of which stocks to sell by portfolio managers. In this era of meme stocks and Dogecoin, it is hard to defend the view that financial markets are highly efficient. The good news, however, is that the anomalies have gotten funnier. With both readability and rigor, The Winner’s Curse is for anyone, from those with a cursory understanding of economics to fellow economists. Each chapter provides a key insight into human behavior so readers learn how to better understand the choices made by their friends, colleagues, and customers, and they might just become better at making decisions themselves. Only recommended for humans.

Behavioral Economics Anomalies, Then and Now

The Winner's Curse

Springer Texts in Business and Economics

The third volume of this textbook contains problem sets that allow models to be applied to specific scenarios. The aim of these problems is to show the relevance of the results these models provide to analyse events, provide recommendations, or critique decisions made. This is achievable without referring to the details of the model and the formal mathematical results but using the often scarce information provided to approach the problem intuitively, informed by the models discussed in volumes I and II. Using such an approach also strengthens the understanding of the implications these models have for decision-making in banks or by policymakers.

The third volume of this textbook contains problem sets that allow models to be applied to specific scenarios. The aim of these problems is to show the relevance of the results these models provide to analyse events, provide recommendations, or critique decisions made. This is achievable without referring to the details of the model and the formal mathematical results but using the often scarce information provided to approach the problem intuitively, informed by the models discussed in volumes I and II. Using such an approach also strengthens the understanding of the implications these models have for decision-making in banks or by policymakers.

Problem Sets

Theoretical Foundations of Commercial Banking - Vol.3

The integration of machine learning and modeling in finance is transforming how data is analyzed, enabling more accurate predictions, risk assessments, and strategic planning. These advanced techniques empower financial professionals to uncover hidden patterns, automate complex processes, and enhance decision-making in volatile markets. As industries increasingly rely on data-driven insights, the adoption of these tools contributes to greater efficiency, reduced uncertainty, and competitive advantage. This technological shift not only drives innovation within financial sectors but also supports broader economic stability and growth by improving forecasting and mitigating risks. Machine Learning and Modeling Techniques in Financial Data Science provides an updated review and highlights recent theoretical advances and breakthroughs in professional practices within financial data science, exploring the strategic roles of machine learning and modeling techniques across various domains in finance. It offers a comprehensive collection that brings together a wealth of knowledge and experience. Covering topics such as algorithmic trading, financial technology (FinTech), and natural language processing (NLP), this book is an excellent resource for business professionals, leaders, policymakers, researchers, academicians, and more.

Machine Learning and Modeling Techniques in Financial Data Science

An empirical analysis and new theoretical framework for understanding economic expectations and decision-making in different historical settings. Expectations play a crucial role in shaping economic behavior. But how are expectations actually formed, and how has this changed over time? The financial crisis of 2007–08 cast doubt on traditional theories of expectation formation, particularly the rational expectations framework. In Contingent Expectations, Alexander Nützenadel and Jochen Streb examine the ways that past experiences influence the economic expectations and decision-making of households, investors, and policymakers through history, and offer an alternative perspective. Combining a comprehensive empirical analysis of expectation formation from the eighteenth century to the present day with an assessment of the relevant economic theory, Nützenadel and Streb present a new theoretical framework, contingent expectations, for understanding economic expectation. Nützenadel and Streb show how economic actors developed new forecasting methods in response to rising uncertainty brought on by the Industrial Revolution, the expansion of global trade, financial market integration, and environmental crises. Tracing the evolution of economic theories on expectations, they find that when growing market volatility made forecasting more complex, economic agents often adapted with remarkable flexibility to changing circumstances. Challenging prevailing concepts of expectations, including rational choice and adaptive expectations, Nützenadel and Streb emphasize the heterogeneity of economic agents’ cognitive practices—in particular, the need to consider variation in information costs and historical experience. Expectation formation, they argue, is contingent on each individual’s current decision-making situation. Their account of the history of economic expectations has significant implications for current debates in economics.

Uncertainty, Risk, and Economic Behavior in Historical Perspective

Contingent Expectations

Every trading desk has a moment like this: the market sits still, then snaps ten points in one direction and never looks back. Somewhere on the options desk, someone always says the same thing - the option chain saw it coming first. The Hidden Tape takes that claim seriously, and builds something real out of it: ProjectX, a live, running, multi-layer trading system for BankNifty index options that reads the option chain's microstructure - dealer positioning, volatility skew, open-interest momentum - alongside price, to answer one question. Does the options market know something the price chart doesn't? This is not a research paper dressed up as a book, and it is not a promise that AI can predict the market. It is the story of building a real system from the ground up: a regime classifier, a multi-timeframe price network, an options microstructure model, and a weighted ensemble that learned to combine them - and the day one of those models quietly stopped working, and what it took to notice. Written for beginners and professionals alike, The Hidden Tape walks through option chain mechanics, dealer gamma hedging, machine learning architecture, and the honest limits of live paper-trading, including a finding that reframed the whole project: the "options" model's biggest jump in accuracy came from adding price context, not from the options data alone. The authors do not oversell what they have built. They show their work, including the mistakes, the corrected assumptions, and the open questions still being tested, because a system that can admit what it does not know is more useful than one that pretends to know everything.

Building a Live AI Trading System on What the Options Market Knows Before the Price Chart

The Hidden Tape

Quantitative Trading Strategies

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