“[Certainty can] seem like a good idea, but actually lead us into trouble… The story here revolved primarily around the stochastic nature of product development… Succeeding in product development requires the discovery and exploitation of options where there is an asymmetry to the payoff function.” […]
Image source: Imperial Oil Corp. Corporate Overview – Winter-Spring 2017. pg. 5
- Imperial Oil Corp is a rationally integrated enterprise — assessing any given business segment in isolation ignores synergies which are especially important during the lower half of the commodities cycle.
- The upstream business segment, by far the largest in terms of capital investment, is heavily exposed to Canadian oil sands projects which are marginal in the current commodity prices environment.
- Yet, records profits from the downstream and chemical business segments demonstrate how they have benefited from cost advantaged feeds.
- In the current commodity price environment, IMO’s common shares are likely fairly valued $22 to $32 per share; there is significant uncertainty in that estimate.
- Given non-compelling valuation and risks, I do not hold the equity outright. However, I believe that call options may provide favorable risk-reward characteristics given their leverage to crude oil prices.
- Cenovus’ expanded asset base, following the $C17.7 Bn acquisition from ConocoPhillips, will be largely of high quality and is expected to more than double 2017 production.
- Its oil sands position is not terribly exciting in terms of growth, but it does promise commodity-price resilient cash flows which can be used to fund future growth.
- The companies largely expanded position in the Canadian Deep Basin may be largely under-recognized as a leading foothold in what my be aptly called “The Permian in the North”.
- Pre-acquisition, I posit that the current stock price of around $10 moderately undervalues the company and largely discounts potential commodity price driven and/or geological upside.
- Given the dearth of apparent opportunity in the upstream oil and gas space, CVE is favorite yet long idea of 2017.
Date of Source: 2016
Commodities trading – supply of the basic staples that are converted into the food we eat, the industrial goods we use, and the energy that fuels our transport and heats and lights our lives – is one of the oldest forms of economic activity, yet it is also one of the most widely misunderstood. At no time has this been truer than in the last 20 years, with the emergence of a group of specialist commodities trading and logistics firms operating in a wide range of complex markets […]
My intent is that this post become a living document which houses my own personal magnum opus on asset valuation. Herein and throughout I will posit certain axioms of asset valuation that I believe to be relevant for distinguishing between a thing’s market versus true value. Upon review, one might (correctly) deduce that none of these axioms are my original ideas.
Since late 2014, I’ve been trying to understand how to value upstream oil and gas companies in a way that anticipates future equity returns. Industry standard practices for financial modeling were illuminating, but they left me unconvinced that I could somehow out-compete smarter, more sophisticated, and better connected institutional investors at their own game. Moreover, nearly every time I tried to apply conventional (i.e., right-headed) valuation techniques to upstream companies, I came up with valuations that were either zero or far-below the current equity market capitalization. This suggested that some heavily discounted bonds would very likely repay par with interest. But seeing as I was full-time employed (and deployed) during those crazy times, I failed to act. Anyway, that boat has sailed…
Despite my lack of early success, I was driven on by a single premise: the lack of differentiation of upstream companies makes them incredibly easy to value once the initial learning curve has been surmounted.
- Equity investments into upstream oil and gas companies are largely levered commodity price plays; long-term total returns barely offset the carry costs of taking a long position in oil futures.
- There are multitudes of ways by which experts seek to forecast future commodities prices; most don’t work.
- The failure of forecasting should not be surprising if the Efficient Market Hypothesis is even partly correct.
- Even barring market efficiency, behavioral models provide ample reason for the widespread inaccuracy of forecasts.
- The idea that commodities prices — including oil — follow a random walk is both overwhelmingly supported by evidence and practical.
Figure 1: Black Gold
Source: Andy Thomas. Black Gold
Evidence overwhelmingly supports the notion that investments into upstream oil and gas producers are basically levered commodity price plays. This, and the fact that commodities producers are price-takers, indicates that petroleum economics are overly levered to commodities prices. It should follow, therefore, that an ability to accurately predict petroleum prices could result in advantageous market timing — i.e. investments in the right petroleum producing assets during the right times in the cycle. As a result of this ostensible potential for riches, prognosticators have devised multitudes of ways to forecast oil prices. Unfortunately, most of these efforts fall short of useful — no known forecasting approach, not even futures strip prices, significantly outperforms the assumption that price evolutions are random walks using out-of-sample data. This failure is not surprising, however, if we are to believe even a watered-down form of the Efficient Market Hypothesis (EMH).
- Discount rates are a cornerstone of modern valuation methods for discounting the value of expected future cash flows.
- Upstream valuation professional systemically utilize elevated discount rates well in excess of rational expectations for long-run capital growth.
- The use of elevated discount rates may have roots in Modern Portfolio Theory, heuristics regarding the aggregation of well-level economics, and as proxies for high expected rates of depletion.
- Re-calibration of investors’ rational expectations indicates that lower discount rates may be more appropriate for evaluating long-run returns.
- Discount rates are simply a means by which to equate dollars in different time-periods — any further deliberation is likely to suffer from diminishing returns.
Figure 1: Sunburst – Pumping UntSource: Greg Evans. Sunburst – Pumping Unit. Art Gallery of Greg Evans
It used to be that making money in stocks was relatively easier. Father of value investing, Benjamin Graham, was known for his predilection of “cigar butt” stocks. That is, stocks which the market has thrown to the curb, forgotten, but which still might have at least “a few puffs” left in them. Harvest Natural Resources (NYSE: HNR), a small-cap oil and gas exploration and production (E&P) outfit focused on the development of known hydrocarbon deposits worldwide, may prove to be a classic example of such a stock.
With a market cap of $74.4 MM, and an indicated net current asset value (NCAV) very near that, Harvest Natural Resources, as a company, does not appear to be dead money. On the contrary, following an imminent sale of its Gabon asset for $32 MM, the company’s cash and receivable balance, less total liabilities, will exceed its market capitalization by $25 MM, implying that the market assigns a negative value to its expected future cash hoard. Worst case, investors could expect to get nearly all of their money back even after a 30% tax on a special dividend. However, if management can figure out a tax-advantaged means by which to utilize that sum, investors could benefit. A tax-free return of capital, which might be allowed under US tax law, implies a 33% short-term, low-risk return.
Date of Source: 12 Apr 2016
As quants, we’re all aware that every model has a shelf-life… a similar pattern applies to the world of data. Rare, unique and proprietary data eventually diffuses and becomes commonplace, easily available, edgeless data. The best analysts constantly reinvent their models, to avoid their inevitable obsolescence. Today, they’re venturing into the world of alternative data as a new source of alpha. […]