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Trading commodities and financial futures : a step-by-step guide to mastering the markets
As an asset class, commodities are now as important as stocks and bonds-- and with rapid growth in demand, profit opportunities in commodities are larger than ever. But today's computer-driven markets are volatile and chaotic. Fortunately, you can profit consistently-- and this tutorial will show you how.
Book
Pricing Multi-Asset Bermudan Commodity Options with Stochastic Volatility Using Neural Networks
It has been recognized that volatility in commodity markets fluctuates significantly depending on the demand–supply relationship and geopolitical risk, and that risk and financial management using multivariate derivatives are becoming more important. This study illustrates an application of multi-layered neural networks for multi-dimensional Bermudan option pricing problems assuming a multi-asset stochastic volatility model in commodity markets. In addition, we aim to identify continuation value functions for these option pricing problems by implementing smooth activation functions in the neural networks and evaluating their accuracy compared with other activation functions or regression techniques. First, we express the underlying asset dynamics using the multi-asset stochastic volatility model with mean reversion properties in the commodity market and formulate the multivariate Bermudan commodity option pricing problem. Subsequently, we apply multi-layer perceptrons in the neural network to represent the continuation value functions of Bermudan commodity options, wherein the entire neural network is trained using the least-squares Monte Carlo simulation method. Finally, we perform numerical experiments and demonstrate that applications of neural networks for Bermudan options in a multi-dimensional commodity market achieve sufficient accuracy with regard to various aspects, including changing the exercise dates, the number of layers/neurons, and the dimension of the problem.
Journal Article
Commodity option pricing
Commodity Option Pricing: A Practitioner's Guide covers commodity option pricing for quantitative analysts, traders or structurers in banks, hedge funds and commodity trading companies.
Based on the author's industry experience with commodity derivatives, this book provides a thorough and mathematical introduction to the various market conventions and models used in commodity option pricing. It introduces the various derivative products typically traded for commodities and describes how these models can be calibrated and used for pricing and risk management. This book has been developed with input from traders and features examples using real-world data, together with relevant up-to-date academic research.
This book includes practical descriptions of market conventions and quote codes used in commodity markets alongside typical products seen in broker quotes and used in calibration. Also discussed are commodity models and their mathematical derivation and volatility surface modelling for traded commodity derivatives. Gold, silver and other precious metals are addressed, including gold forward and gold lease rates, as well as copper, aluminium and other base metals, crude oil and natural gas, refined energy and electricity. There are also sections on the products encountered in commodities such as crack spread and spark spread options and alternative commodities such as carbon emissions, weather derivatives, bandwidth and telecommunications trading, plastics and freight.
Commodity Option Pricing is ideal for anyone working in commodities or aiming to make the transition into the area, as well as academics needing to familiarize themselves with the industry conventions of the commodity markets.
eBook
Discovering Decision Rules in the Commodity Options Market for Hedging Against Oil Price Fluctuations
High volatility of commodity prices is due, among others, to sudden global events. Only recently, COVID-19 pandemic and the war in Ukraine have caused crisis in commodity markets. In particular, the prices of strategic goods such as oil have become very volatile. To hedge against adverse price movements in this commodity, business and investors use commodity options. However, making reasonable buy/sell decisions requires a good mix of market understanding, technical and fundamental analysis, and risk management. In this paper, we use association analysis to discover buy decision rules for the investors in the WTI crude oil options market. The rules are discovered based on moving averages of WTI crude oil prices and the price differences of this commodity between selected days. The effectiveness of the discovered rules is evaluated using indicators related to the level of payout of the buyer of call options and the cost of acquiring these options. The results of experiments on data from 26 August 2008 and 15 November 2022 indicate that the decision rules discovered can effectively support decisions to take a long position in call options and can significantly contribute to effective hedging against unfavorable oil price movements.
Journal Article
Real-Option Valuation in Multiple Dimensions Using Poisson Optional Stopping Times
We provide a new framework for valuing multidimensional real options where opportunities to exercise the option are generated by an exogenous Poisson process, which can be viewed as a liquidity constraint on decision times. This approach, which we call the Poisson optional stopping times (POST) method, finds the value function as a monotone sequence of lower bounds. In a case study, we demonstrate that the frequently used quasi-analytic method yields a suboptimal policy and an inaccurate value function. The proposed method is demonstrably correct, straightforward to implement, reliable in computation, and broadly applicable in analyzing multidimensional option-valuation problems.
Journal Article
Feeding unrest: Disentangling the causal relationship between food price shocks and sociopolitical conflict in urban Africa
While both academics and politicians have long acknowledged the connection between food price shocks and so-called 'food riots', this article asks whether rising domestic consumer food prices are a contributing cause of sociopolitical unrest, more broadly defined, in urban areas of Africa. In order to unravel the complex and circular relationship between rising food prices and unrest, an instrumental approach with country fixed effects is used to isolate causality at the country-month unit of analysis for the period 1990 through 2012. Two instrumental variables, changes in international grain commodity prices and local rainfall scarcity, are evaluated and used individually and jointly as instruments for changes in domestic food prices. The main finding is that a sudden increase in domestic food prices in a given month significantly increases the probability of urban unrest, especially spontaneous events and riots, in that month. Undeniably, more fundamental economic and political grievances are also drivers of such events and are likely to determine how the unrest ultimately manifests, even when triggered by rising food prices. Although more research is necessary to determine why people choose particular protest methods and targets, the findings of this research provide evidence that sociopolitical unrest of different types is driven, or at least triggered, by a consumer response to economic pressure from increasing food prices regardless of the cause of the increase.
Journal Article
Joint client selection and contract design for a risk-averse commodity broker in a two-echelon supply chain
We study an expected payoff maximization problem for a risk-sensitive broker aiming to evaluate the merits of designing and underwriting an option contract on a traded commodity with geometric Brownian motion (GBM) spot price trajectories. Candidate firms for whom the contract would mitigate the commodity’s price risk, each face Poisson demands that are currently the broker’s responsibility to satisfy. Subject to a variance risk budget and a robustness requirement, the broker’s objective is jointly to (1) choose a so-called trigger price function that will fundamentally define the option contract, and (2) select a value-maximizing set of client firms to whom the broker will offer the contract. We reformulate the problem as a bilevel program whose continuous relaxation we transform into a single-level, univariate problem with a convenient property that makes it amenable to line search methods. The optimal solution for that single-level problem is then raw material for constructing the optimal solution for the original problem. Our theoretical and experimental findings indicate that the contract’s optimal value, and optimal trigger price function are both strictly monotone increasing in a cost parameter in the model, as well as in the GBM’s volatility coefficient. The findings also show that those two quantities are strictly monotone decreasing in the GBM’s drift coefficient. We conclude with a benchmarking sensitivity study which uses real-world data to study the implications of violating a certain constraint which implicitly bounds the optimal trigger price.
Journal Article
Knowledge Discovery to Support WTI Crude Oil Price Risk Management
The high volatility of commodity prices and various problems that the energy sector has to deal with in the era of COVID-19 have significantly increased the risk of oil price changes. These changes are of the main concern of companies for which oil is the main input in the production process, and therefore oil price determines the production costs. The main goal of this paper is to discover decision rules for a buyer of American WTI (West Texas Intermediate) crude oil call options. The presented research uses factors characterizing the option price, such as implied volatility and option sensitivity factors (delta, gamma, vega, and theta, known as “Greeks”). The performed analysis covers the years 2008–2022 and options with an exercise period up to three months. The decision rules are discovered using association analysis and are evaluated in terms of the three investment efficiency indicators: total payoff, average payoff, and return on investment. The results show the existence of certain ranges of the analyzed parameters for which the mentioned efficiency indicators reached particularly high values. The relationships discovered and recorded in the form of decision rules can be effectively used or adapted by practitioners to support their decisions in oil price risk management.
Journal Article
An Efficient Dynamic Auction for Heterogeneous Commodities
This article proposes a new dynamic design for auctioning multiple heterogeneous commodities. An auctioneer wishes to allocate K types of commodities among n bidders. The auctioneer announces a vector of current prices, bidders report quantities demanded at these prices, and the auctioneer adjusts the prices. Units are credited to bidders at the current prices as their opponents' demands decline, and the process continues until every commodity market clears. Bidders, rather than being assumed to behave as price-takers, are permitted to strategically exercise their market power. Nevertheless, the proposed auction yields Walrasian equilibrium prices and, as from a Vickrey-Clarke-Groves mechanism, an efficient allocation.
Journal Article