At U.S. Global Investors, we strive to serve our clients by detecting and accounting for trends and patterns not just in the market, but also the world at large. One important theme for investors to keep in mind is that many assets flow through cycles and exhibit patterns of volatility, or price swings. By anticipating before participating in the market, investors are better able to manage their expectations.
The Importance of Cycles in the Investment Management Process
Financial markets are influenced by relatively predictable cycles. A keen awareness of the ebbs and flows of historical and socioeconomic conditions, on both the macro and micro scales, allows our investment management strategy to be more proactive than reactive. Examples of these cycles include gold mines, stock market performance during presidencies and gold jewelry demand.
Gold’s Seasonal Trading Patterns
Gold is a classic example of a commodity that rotates through seasonal cycles year after year. It’s largely driven by gold jewelry gift gifting during holidays in China and India, the world’s two largest consumers of the yellow metal. We call this the Love Trade. Jewelry demand historically spikes in August and September leading up to the start of wedding season and Diwali.
Government Policy Is a Precursor to Change
At U.S. Global we like to say that government policy is a precursor to change, and no person in the nation has more influence over policy than the president. The decisions they make and actions they take have far-reaching consequences in markets both domestic and international. Historically, volatility has increased and markets have dipped leading up to midterms on uncertainty, but afterward they’ve outperformed.
Understanding the Lifecycle of a Mine
Knowing where a company is on the mine lifecycle can be a tremendous asset to gold equity investors. It’s another tool they can use to try to manage expectations of volatility. Years can and do divide the time when a mine is discovered and when production begins, so it’s imperative to know which stage of its lifecycle the mine is in to make a better-informed decision on whether to invest, withdraw or wait.
Learning From Standard Deviation and Mean Reversion
Standard deviation, also known as sigma, is a probability tool that gauges a security’s volatility. Specifically, it measures the typical fluctuation of a security around its mean, or average return, over a period of time ranging from one day to 12 months or more. A higher sigma generally means greater volatility. Mean reversion is the theory that, although prices might trend up for many years (as in a bull market), or fall for many years (as in a bear market), they tend to move back toward their historic averages eventually.
Each Asset Class Has Its Own DNA of Volatility
Every security has a different sigma for a specific period of time. As such, your expectations should reflect these differences – we call this the DNA of volatility. Gold has an average daily sigma of 1 percent for the one year period through December 31, 2018. So if gold’s return falls within a range of +/- 1 percent on any given day, it’s behaving normally, as this is only one sigma. Anything more than a two sigma move would trigger a possible time to buy or sell. It’s all about managing your expectations and emotions.
Identifying Value Drivers for Superior Performance
One of the invaluable tools we use to navigate around volatility, regulate emotion and focus on facts and fundamentals is a model we call the portfolio manager’s cube. It draws attention to the intersections among a resource company’s production, cash flow and reserves (rows) and relative value, momentum and event drivers (columns). Using this model, we compare stocks on a relative basis to find attractive opportunities and overpriced risks
The 5 Ms of Picking Gold Stocks
In order to find the diamonds in the rough, we use the 5 Ms for picking gold mining stocks: market capitalization, management, money, minerals and mine lifecycle. It’s essential to use a variety of factors to evaluate a company and determine if it fits your investment portfolio.
The Best Statistical Times to Trade
What are the best months, weeks, days and times to trade? This quote from Mark Twain might provide some insight: “October: This is one of the peculiarly dangerous months to speculate in stocks. The others are July, January, September, April, November, May, March, June, December, August and February.” Point being anytime you trade or participate in the market there is inherent risk. However, there is research that demonstrates certain times of the year or of the day have historically seen better returns than others.
Investing in the Age of High-Frequency Trading
In the past few years, price discovery—or the act of finding the “right” price for a security—has become much more challenging because of growing high-frequency trading (HFT), whereby automated computers use algorithms to transact orders at lightning-fast speeds. In a process called latency arbitrage, high-speed traders are able to gain access to crucial order information and other market data milliseconds before “normal” or “slow” traders.
Falling Volumes and Widening Bid-Ask Spreads
Price discovery has also become more difficult due to falling stock volume and widening bid-ask spreads. These challenges are directly attributable to the infiltration of high-frequency traders into the market, not to mention the expansion of dark pools and non-exchange trading. So what do we do as active managers? We use statistical models to try and sniff out both value at a reasonable price and accumulate at attractive relative prices, even when there are so many new factors to consider.
All opinions expressed and data provided are subject to change without notice. Some of these opinions may not be appropriate to every investor.
Standard deviation is a measure of the dispersion of a set of data from its mean. The more spread apart the data, the higher the deviation. Standard deviation is also known as historical volatility.
Free Cash Flow (FCF) represents the cash that a company is able to generate after laying out the money required to maintain or expand its asset base.
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