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Trend following : how to make a fortune in bull, bear and black swan markets
\"The legendary trading strategy in depth from A to Z Michael Covel's Trend Following reveals the truth about a trading strategy that makes money in up, down and surprise markets. By applying straightforward and repeatable rules, anyone can learn to make money in the markets whether bull, bear, or black swan-by following the trend to the end when it bends. In this timely reboot of his bestselling classic, Michael Covel dives headfirst into trend following strategy to examine the risks, benefits, people, and systems. You'll hear from traders who have made millions by following trends, and learn from their successes and mistakes-insights only here. You'll learn the trend philosophy, and how it has performed in booms, bubbles, panics and crashes. Using incontrovertible data and overwhelming supporting evidence, with a direct connection to the foundations of behavioral finance, Covel takes you inside the core principles of trend following and shows everyone, from brand new trader to professional, how alpha gets pulled from the market. Covel's newest edition has been revised and extended, with 7 brand new interviews and research proof from his one of kind network.℗¿ This is trend following for today's generation. If you're looking to go beyond passive index funds and trusting the Fed, this cutting edge classic holds the keys to a weatherproof portfolio. Meet great trend followers learning their rules and philosophy of the game Examine data to see how trend following excels when the you-know-what hits the fan Understand trend trading, from behavioral economics to rules based decision-making to its lambasting of the efficient markets theory Compare trend trading systems to do it yourself or invest with a trend fund Trend following is not prediction, passive index investing, buy and hope or any form of fundamental analysis. It utilizes concrete rules, or heuristics, to profit from a behavioral perspective. Trend Following is clear-cut, straightforward and evidence-based and will secure your financial future in bull, bear and black swan markets. If you're finally ready to profit in the markets, Trend Following is the definitive treatise for a complex world in constant chaos\"-- Provided by publisher.
Book
New Evidence on the Financialization of Commodity Markets
This paper uses a novel dataset of commodity-linked notes (CLNs) to examine the impact of the flows of financial investors on commodity futures prices. Investor flows into and out of CLNs are passed to and withdrawn from the futures markets via issuers' trades to hedge their CLN liabilities. The flows are not based on information about futures price movements but nonetheless cause increases and decreases in commodity futures prices when they are passed through to and withdrawn from the futures markets. These finding are consistent with the hypothesis that non-information-based financial investments have important impacts on commodity prices.
Journal Article
The global diamond industry
\"The Global Diamond Industry: Economics and Development brings together a collection of papers covering various aspects of the diamond industry including economics, law, history, sociology and development. These volumes are motivated by one objective alone and that is to provide intellectual light where none exists. The diamond industry is one that is long steeped in secrecy and each chapter and even each well researched anecdote helps others to understand this commodity and what are at times mysterious operations of the industry. This first volume presents literature tackling broad issues around the structure of the industry and demand and pricing of diamonds\"-- Provided by publisher.
Book
Financialization of Commodity Markets
The large inflow of investment capital to commodity futures markets in the past decade has generated a heated debate about whether financialization distorts commodity prices. Rather than focusing on the opposing views concerning whether investment flows caused a price bubble, we critically review academic studies through the perspective of how financial investors affect risk sharing and information discovery in commodity markets. We argue that financialization has substantially changed commodity markets through these mechanisms.
Journal Article
Policy, politics and poverty in South Africa
\"When South Africa finally held its first democratic elections in 1994, the country had a much higher poverty rate than in other countries at a similar level of development. This was the legacy of apartheid. Twenty years later, poverty was still widespread. Seekings and Nattrass explain why poverty has persisted in South Africa since 1994. They demonstrate who has and who has not remained poor, how public policies both mitigated and reproduced poverty, and how and why these policies were adopted. Their analysis of the South African welfare state, labour market policies and the growth path of the South African economy challenge conventional accounts that focus only on 'neoliberalism'. They argue, instead, that policies were, in important respects, social democratic. They show how social democratic policies both mitigate and reproduce poverty in contexts such as South Africa, reflecting the contradictory nature of social democracy in the global South\"-- Provided by publisher.
Book
Transición energética en Europa, extractivismo verde en América Latina?
La transición energética en Europa sugiere un posible nuevo boom de los commodities. Además, existe un constante aumento de las energías renovables almacenables, especialmente de hidrógeno verde. ¿Hasta qué punto este desarrollo conduce a un nuevo extractivismo, esta vez bajo un signo «verde»? En el marco de la transición energética, los movimientos sociales se enfrentan al reto de actuar no solo contra la expansión de la explotación de los recursos, sino también contra un discurso hegemónico verde-tecnológico y tecnoeconomicista que dificulta la creación de alianzas internacionales.
Journal Article
Law Enforcement and the History of Financial Market Manipulation
First Published in 2014. Routledge is an imprint of Taylor & Francis, an informa company.
Introduction 1. Manipulation: Some History 2. Market Manipulation and the New Deal Legislation 3. Postwar Manipulation and Speculation 4. Manipulation of Commodity Prices in a Time of Inflation 5. Manipulation Setbacks Under the Federal Securities Laws 6. The Battle over OTC Derivatives 7. The Dodd-Frank Act 8. Challenges for the New Manipulation Standards
Jerry W. Markham is a Professor of Law at the Florida International University College of Law in Miami, USA.
\"Professor Markham has written another masterpiece. His book provides a rich history and detailed analysis of financial fraudulence, commonly known as manipulation, from a regulatory policy perspective, and the ways that case law has evolved and characterized this fraud. Markham then properly addresses the new theories that have been developed since the passage of Dodd-Frank in 2010 and places them in the context of the rich enforcement traditions of the Commodity Futures Trading Commission, the Securities and Exchange Commission, the Federal Trade Commission, the Federal Energy Regulatory Commission, and others. The book is a must read for financial services lawyers and regulators as well as academics.\" -- Ronald Filler, New York Law School
\"Jerry Markham as always provides an insightful analysis on the history of the financial markets--this time focusing on law enforcement and market manipulation.\" -- Thomas Lee Hazen, School of Law, University of North Carolina at Chapel Hill
eBook
Forecasting wholesale prices of yellow corn through the Gaussian process regression
For market players and policy officials, commodity price forecasts are crucial problems that are challenging to address due to the complexity of price time series. Given its strategic importance, corn crops are hardly an exception. The current paper evaluates the forecasting issue for China’s weekly wholesale price index for yellow corn from January 1, 2010 to January 10, 2020. We develop a Gaussian process regression model using cross validation and Bayesian optimizations over various kernels and basis functions that could effectively handle this sophisticated commodity price forecast problem. The model provides precise out-of-sample forecasts from January 4, 2019 to January 10, 2020, with a relative root mean square error, root mean square error, and mean absolute error of 1.245%, 1.605, and 0.936, respectively. The models developed here might be used by market players for market evaluations and decision-making as well as by policymakers for policy creation and execution.
Journal Article
A novel agricultural commodity price prediction model integrating deep learning and enhanced swarm intelligence algorithm
The volatility of agricultural commodity prices significantly affects market stability and financial market dynamics, especially during periods of economic uncertainty and global shocks. Accurate price prediction, however, remains challenging due to the complex, nonlinear characteristics of agricultural markets and the diverse range of influencing factors. To overcome these challenges, this study develops a novel price forecasting framework that combines advanced time series decomposition, swarm intelligence optimization, and deep learning techniques. The proposed framework employs successive variational mode decomposition (SVMD) to deconstruct the raw price data into multiple components, effectively capturing the underlying nonlinear patterns and dynamic features. These components are then fed into a CNN-augmented BiLSTM model, enhanced with an attention mechanism to extract both temporal dependencies and intricate data relationships. To fine-tune the model's hyperparameters, this study introduces a multiple strategies dung beetle optimisation algorithm (MSDBO), which integrates four strategic modifications to improve the balance between global search, local exploration, and convergence efficiency. Using historical data from corn and wheat markets as case studies, the experimental findings demonstrate that the proposed SVMD-MSDBO-CNN-BiLSTM-A model significantly outperforms nine baseline approaches. Specifically, it reduces the Mean Absolute Percentage Error (MAPE) by 25.78% and 37.57%, respectively, and enhances directional accuracy (Dstat) by 1.15% and 14.53% compared to the top single models.
Journal Article
Informational Frictions and Commodity Markets
This paper develops a model with a tractable log-linear equilibrium to analyze the effects of informational frictions in commodity markets. By aggregating dispersed information about the strength of the global economy among goods producers whose production has complementarity, commodity prices serve as price signals to guide producers' production decisions and commodity demand. Our model highlights important feedback effects of informational noise originating from supply shocks and futures market trading on commodity demand and spot prices. Our analysis illustrates the weakness common in empirical studies on commodity markets of assuming that different types of shocks are publicly observable to market participants.
Journal Article