Why Invest in Commodities?

Commodities have fast become an attractive investment class for many investors looking for a well-diversified portfolio. Commodities provide a combination of potential investment benefits unique to other asset classes.

There are there key benefits that make commodities a worthwhile addition to an investment portfolio.

  1. Absolute Returns: Investors seek absolute returns from their commodity investments based on their demand/supply forecasts, i.e., the expectation for demand to rise or supply to fall.
  2. Diversification: Commodities historically have low correlations with other financial assets such as equities and bonds that make them suitable alternative for diversification.
  3. Inflation Protection: Commodity prices are closely linked to the prices of essential goods. So, during times of inflation, commodities perform well while other asset classes perform poorly.

The risk-return profile of commodities is comparable to that of equities and at the same time commodities exhibit low to negative correlation with other asset classes.

The commodity and equity investment can be distinguished as follows: Commodities offer you an asset with intrinsic value while equities offer you a financial asset with ownership to the company. Commodity assets offer you direct exposure to asset which equity does not as equity only offers residual claim to a company.

Commodities also offer unique pricing opportunities, for example in backwardation curves which are unique to commodity markets. It allows for cheap long exposure to be obtained in the underlying, when compared to an equivalent equity or fixed income investment.

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Data Science in Finance: 9-Book Bundle

Data Science in Finance Book Bundle

Master R and Python for financial data science with our comprehensive bundle of 9 ebooks.

What's Included:

  • Getting Started with R
  • R Programming for Data Science
  • Data Visualization with R
  • Financial Time Series Analysis with R
  • Quantitative Trading Strategies with R
  • Derivatives with R
  • Credit Risk Modelling With R
  • Python for Data Science
  • Machine Learning in Finance using Python

Each book comes with PDFs, detailed explanations, step-by-step instructions, data files, and complete downloadable R code for all examples.