Scorpio Tankers: In the near-win seat of Catbird’s international energy economy (NYSE:STNG)


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Investment thesis

Advances in commission-free trading automation made by securities markets to serve a continuous stream of small trades from individual investors on the Internet require market makers to have capital at risk while processing irregular “institutional” trades. valuable. They protect their capital at risk by putting at risk hedge stocks that reflect expectations of the future price range of the stocks involved – virtually any actively traded issue.

The price and structure of these hedges reveals the future price expectations of both MM protection buyers and MM industry protection sellers.

Our selection of Scorpio Tankers Inc. (NYSE: STNG) is established by its currently attractive stock price, bolstered by other fundamental analytical contributors to Seeking Alpha.

Subject business description

“Scorpio Tankers Inc., together with its subsidiaries, is engaged in the marine transportation of refined petroleum products to marine markets around the world. As of March 18, 2022, the company’s fleet consisted of 124 owned, credit- lease or bareboat charter, including 42 LR2s, 6 LR1s, 62 MRs and 14 Handymaxes with a weighted average age of approximately 6.2 years. Scorpio Tankers Inc. was incorporated in 2009 and is based in Monaco.”

Source: Yahoo Finance

street analyst estimates

Yahoo finance

Risk-reward comparisons of portfolio investment candidates

Figure 1

MM coverage predictions

(used with prior permission)

The trade-offs here are between the short-term upside price gains (green horizontal scale) considered worth protecting by market makers with short positions in each of the stocks, and the prior actual price declines experienced during of the holding of these shares (red vertical scale) . Both scales are percent change from zero to 25%.

The intersection of these coordinates with the numbered positions is identified by the stock symbols in the blue field to the right.

The dotted diagonal line marks the points of equal upward price change predictions derived from Market-Maker [MM] hedging actions and actual worst-case price declines from positions that could have been taken as a result of earlier MA predictions like today’s.

Our main interest is STNG at the location [12]. A standard “market index” of reward~risk trade-offs is offered by SPDR S&P 500 index ETF (SPY) at [1].

These predictions are underpinned by the self-protective behaviors of MMs who typically need to put company capital at temporary risk to balance the interests of buyer and seller by assisting capital-intensive portfolio managers to make volume adjustments on multi-billion dollar portfolios. The hedging measures taken with real money betting daily define the magnitude of likely expected price changes for thousands of stocks and ETFs.

This map is a good starting point, but it can only cover some of the investment characteristics that must often influence an investor’s choice of where to invest their capital. The table in Figure 2 covers the above considerations and several more.

Compare alternative investments

Figure 2

detailed comparison data

(used with permission)

The column headers in Figure 2 define the items for each rank stock whose symbol appears to the left in the column [A]. The elements are derived or calculated separately for each stock, depending on the specifics of its situation and the current forecast of the MM price range. Data in red numbers is negative, usually undesirable for “long” positions. The table cells with yellow fills are data for the main stock of interest and any issues to rank column, [R].

Readers familiar with our analytical methods may wish to skip to the next section displaying price range prediction trends for STNG.

The purpose of Figure 2 is to try universally comparable, stock-by-stock measures of a) the SIGNIFICANCE of the price gain, b) the LIKELIHOOD that the gain will be a profitable experience, c) how quickly it can happen, and d) what RISK of falling prices may be encountered during its holding period.

Column price range prediction limits [B] and [C] be defined by MM’s hedging actions to protect the firm’s capital which must be exposed to the risk of price changes from volume trade orders placed by large $”institutional” clients.

[E] measures the potential upside risks for the short MM positions created to fill these orders and rewards the potentials for the buy positions thus created. Past forecasts like this provide a history of pertinent risk of lower prices for buyers. On average, the most severe actually encountered are found in [F]during the periods of maintenance in the effort to reach [E] earnings. This is where buyers are most likely to accept losses.

[H] indicates what proportion of the [L] sample of similar past predictions made gains by causing the price to reach its [B] target or be above sound [D] cost of entry at the end of a maximum holding period limit of 3 months. [ I ] gives the net gains-losses of those [L] experiences and [N] suggests how much [E] can be compared to [ I ].

Other reward-risk trade-offs involve the use of [H] win odds and loss odds 100 – H as weights for N-conditioned [E] and for [F]for a combined yield score [Q]. The typical job retention period [J] on [Q] provides a symbol of merit [fom] ranking measure [R] useful in portfolio position preferences. Figure 2 is arranged by row on [R] among the candidate titles, with the INSP yellow line identified.

In addition to candidate-specific stocks, these selection considerations are provided for the averages of over 3,000 stocks for which MM’s price range predictions are available today, and 20 of the top-ranked (per of) of these forecasts, as well as the forecast for the S&P 500 Index ETF as a proxy for the stock market.

Recent trends in TNG MM Price Range Forecast

Figre 3

daily updates for the last 6 months

(used with permission)

This picture is not a “technical sheet” of past prices for STNG. Instead, its vertical lines show the last 6 months of price scale forecasts upcoming market actions in the coming months. The only past information is the big dot of the stock’s closing price on the day of each forecast.

This data divides the opposite predictions of the price range into bullish and bearish outlooks. Their trends over time provide additional insight into upcoming potentials and help keep perspective on what might be coming.

The small image at the bottom of Figure 3 is a frequency distribution of the daily appearance of the Range Index over the last 5 years of daily forecasts. The range index [RI] indicates how much the forecast range decline occupies that percentage of the entire range each day, and its frequency suggests what might seem “normal” for that stock, to evaluators. An RI of 57, about 57% of the range leaves the remaining 43% of upside price swing potential.

The 100 Win Odds indicates that all prior 5-year forecasts like today’s have seen the stock price exceed its entry cost, often all the way to its sell target.

Earnings Prospects of Investment Applicants

Figure 4

STNG value dominance

(used with permission)

This comparison map uses an orientation similar to Figure 1, where the most desirable locations are bottom and right. Instead of being limited to price direction, the questions are more qualitative: “how big” and “how likely” are expectations of price changes now?

Our main interest is the qualitative performance of STNG, in particular in relation to the choices of alternative investment candidates. Here STNG is at location [5]the intersection of the horizontal and vertical scales of +20% gain and +100% insurance [odds] of a “victory”.

As an industry standard, SPY is at the location [6] with a gain of +3.9% and guaranteed profitability of 75%. STNG tends to dominate all return gains in this comparison.


Among these alternative investments explicitly compared Scorpion Tankers Inc. seems like a logical buying preference now for investors looking for short-term capital gain.

Question: Is this form of comparison more or less useful to you in your selection of investment choices than one focused on industry economics or competitive stocks?


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