By following a quantamental investing approach, companies are merging artificial intelligence and human expertise to make savvy investment decisions.
Mining companies following a quantamental investing approach are leveraging artificial intelligence (AI) and machine learning to make informed business decisions.
Large banks and hedge funds around the world are beginning to leverage insights gained from big data for investment success. One of the most recent ways AI and machine learning technology has revolutionized investment strategies is through the marriage of two historically separate modes of stock analysis: fundamental and quantitative.
“AI will certainly play a big role in the future of the investment industry, but even a good quant trading strategy needs solid fundamentals behind it,” said Zac Sheffer, founder and CEO of Elsen, a platform-as-a-service company for large financial institutions. “One path forward is to combine the best of quantitative and fundamental strategies into a quantamental investing future.”
The mining industry, especially when it comes to junior exploration stocks, has shown potential for a quantamental approach to be applied successfully.
Quantitative investing uses mathematical and statistical modeling to analyze large volumes of data points that are indicative of future success. Quantitative investing is the driving force behind Renaissance Technologies, a US$29 billion company founded by billionaire Jim Simons. Fundamental investing techniques, on the other hand, have traditionally revolved around human judgments based on researching financial data such as earnings and balance sheets alongside economic factors and industry trends. This pure instinct approach is what made billionaire Warren Buffett famous.
Today, more and more wealth management firms are combining fundamental investing strategies with quantitative analysis that uses AI and machine learning algorithms. Known as quantamental investing (QI), this strategy uses algorithms built by data scientists that can process large amounts of information to reveal trends and generate a shortlist of high-quality stocks. Investors and hedge fund managers can then use their subjective analysis to narrow down their targets.
“Next-generation investing involves bringing together fundamental and quantitative approaches, unified through the power of artificial intelligence,” Denis Laviolette, Goldspot Discoveries’ (TSXV:SPOT) president and CEO, told the Investing News Network. “The mining industry is a perfect example of an investment sector that still needs human-lead fundamental analysis to support computer-based quant investing strategies.”
Goldspot Discoveries’ Resource Quantamental (RQ) is the first QI platform for junior exploration stocks in the mining industry. This platform harnesses the power of AI and machine learning algorithms to reduce capital risk and increase the opportunity for investment success in the resource industry. Goldspot uses RQ to identify top-shelf projects and high-quality management teams to invest in. The company recently showcased the RQ platform at the tech-industry-focused Collision Conference in Toronto.
“RQ combines four core components — product, platform, people and innovation — to identify long-term growth opportunities through partnerships, investments and royalties,” said Laviolette. “The AI-driven opportunity generator points us to ideal companies to work with based on geological data, market and macroeconomic data as well as company-specific data such as a business model, management team and board of directors. Using these criteria points, the program then selects the best investment candidates with a focus on the TSX Ventures.”
Quantamental investing in the mining industry
Long-time mining stock gurus such as Brent Cook of Exploration Insights and Mercenary Geologist Mickey Fulp will tell you that high on the list of criteria for picking winners are quality projects, favorable jurisdictions, healthy financial positions and strong management teams. The companies that carry these attributes are more likely to provide investors with value-generating opportunities.
One of the best indicators of a resource company’s future profit potential is the quality of its projects. Geologically speaking, deposit size, grade, metallurgy and mineral type are major points to consider alongside operation costs. While high grades are preferable, they might not always translate into high profit margins. Depending on the deposit size and amenability to low-cost operations, low grades can occasionally produce the high margins needed to pay back the original capital investment. Project quality also has a lot to do with the project stage as well. Properties with regulatorily compliant mineral resource estimates, established resource models, positive economic studies and approved permits carry less risk than projects that have yet to reach these critical milestones.
Some aspects of project evaluation that are more subjective have to do with identifying industry-wide trends. Certain mineral types can become more valuable than others, depending on the commodity cycle and the supply/demand fundamentals. The sociopolitical complexities of a project’s geographical location can also complicate quantitative methods. For example, a near-surface, multi-million ounce, high-grade gold deposit could offer significant potential. However, the benefits may be outweighed by the political risk of operating in the area.
Politically stable jurisdictions with transparent permitting and well-established infrastructure are key to unlocking a project’s profit potential. “Assets in mining-friendly jurisdictions, with progressive tax and royalty structures that allow companies to generate a return that is commensurate with the risks they absorb, will also be an important investment criteria,” said analyst Brent Cook.
Quality projects in premier jurisdictions aren’t the only assets that define a company’s value. Many analysts and career investors in the resource space would argue that a company’s truest asset is its management team. In the junior resource space, experience and past successes are seen as essential attributes for a management team, especially experience with projects that have moved through exploration and development. Teams should also be stacked with capital market players who can secure financing, negotiate partnerships and navigate mergers and acquisitions.
Quantamental investing: the best of both worlds
According to Morgan Stanley’s Applied Equity Advisors team, when it comes to quantitative vs fundamental investing, the “real power” lies in the combined quantamental approach. “(Investors) can benefit from two engines that can potentially generate excess returns — one that works at the market factor level and the other at the individual stock level,” writes Managing Director and Senior Portfolio Manager Andrew Slimmon and Executive Director Leslie Delany. “Having seen first-hand the benefits of combining quantitative factor modeling with traditional stock selection methods, we are avid proponents of quantamental investing.”
Investment bank JP Morgan (NYSE:JPM) and the world’s largest investment firm BlackRock are “combining the benefits of both these approaches to extract the power of big data in Quantitative methods and the business sense of experienced professionals who use the fundamental methods,” according to Data Drive Investor. “The result is a much more focused decision with the higher promise of returns.” Other financial entities moving into QI and AI platforms include Bridgewater, Goldman Sachs, WorldQuant and Sentient Technologies.
AI and machine learning technology have a lot to offer resource investors looking for new opportunities for wealth generation. Despite the importance of Big Data, machines cannot fully replace the human mind of an experienced investment analyst, especially in the resource industry. Through quantamental investing, man and machine are combining their skills to discover the projects and teams with the best chance of generating returns for investors.
This article was originally published on the Investing News Network in November 2019.
This INNSpired article was written according to INN editorial standards to educate investors.