Evaluating General Moly, Inc. Options

Aptly Named Mt. Hope, courtesy GMO

In a previous post, I wrote about General Moly as an upside molybdenum investment. Liu Han, head of a Chinese bank financing GMO to the tune of $665M, was detained and the financing fell through. Consequently, the stock price fell through. In January 2013, GMO was a $4 stock. It's lost over half it's value since then, to $1.84 as of June 29th.

The drop is a consequence of insecure financing. If GMO can secure financing, it seems reasonable to assume that the value of the stock will return to pre-drop levels of $3-4 or have some positive correction. A supply glut in coming years leads me to conclude that molybdenum will be a lateral market in the coming years. If GMO gets financing, completes the Mt. Hope Project without unassailable piles of extra debt, it will still be a few years of lean margins with a molybdenum price depressed by supply burdens.

This in mind, here are call options on GMO from GoogleFinance since owning a development stage equity in a lateral market is unattractive. There's not much interest in these options and so a lack of liquidity might make this discussion completely irrelevant but I'm pressing on.

July 20, 2013 expiration:

Strike	Price	Change	Bid	Ask	Volume	Open Int
1.00	-	-	0.80	1.00	-	0
2.00	0.16	0.00	-	0.15	-	80

September 21, 2013 expiration:

Strike	Price	Change	Bid	Ask	Volume	Open Int
1.00	0.85	0.00	0.80	1.00	-	32
2.00	0.35	0.00	0.15	0.25	-	120
3.00	0.10	0.00	-	0.10	-	420
4.00	0.05	0.00	-	0.05	-	208
5.00	0.10	0.00	-	0.05	-	20

December 21, 2013 expiration:

Strike	Price	Change	Bid	Ask	Volume	Open Int
1.00	1.00	0.00	0.85	1.05	-	29
2.00	0.30	-0.05	0.20	0.35	4	203
3.00	0.19	0.00	0.05	0.10	-	210
4.00	0.05	0.00	0.05	0.10	-	82

If GMO can secure financing and the stock rebounds to $3, each call with a $2 strike on GMO will be worth $1.The largest window these options give GMO is until December 2013. Purchasing calls with a strike of $2 at $0.30 a pop means to break even, the stock has to rise to $2.30. Past that, you're making money. Scaling up requires a hypothetical posture since the liquidity doesn't exist. $100 into 12-21 calls with a $2 strike. $100 buys about 330 calls.  Different outcomes:

• at or below $2 at expiration means you're out $100
• $2-2.30 means you're out $100-0, and breaking even at $2.30
• above $2.30 is profit. Every cent GMO stock goes above $2.30 returns $3.30. Assuming GMO rises to $3, that position is worth $230 for a 130% gain. At $4 stock, the position is $561 and a 461% gain.

One more strange note is that September calls cost more than December calls, which would seem to be badly priced given that the more time you allow for GMO to find money, the more likely the pop is to occur.

Of course, this is a binary gamble. It does or doesn't happen so if you weren't prepared for either outcome you shouldn't think about playing an event-driven strategy. The last consideration to discuss is how reasonable it would be to assume prices would bounce back. Before GMO had ever secured financing, the stock hovered at around $2.50. After the March 4, 2010 signing with Hanlong, the price jumped to $3.60 and drifted up from there (which looks more like a consequence of a recovering 2010 market than GMO specific improvement). A mine is worth what it digs up, and that price can change. Are many investors going to have strong, personal opinions about where the mol market is going? Are they going to look thoroughly at GMO's competitive prospects, or are they going to trust existing valuations of Mt. Hope based on optimistic mol prices? In any case, if it was liquid enough and I had some money to throw away, this might be a gamble I take.

Failing Upwards in R: xyplot for NG and Oil

xyplot is nifty. It establishes a base plot to which layers can be added. Here's the process:
1. Obtain xts.
2. xyplot(xts). The output of this is called a trellis object.
3. You can add to trellis objects by calling the trellis object and adding a layer. This can be done a few ways. I did it as,
xyplot(xts) + as.layer(xyplot(xts2)),
which produces a plot that has xts and xts2 plotted. Layers can also be added to shade interesting portions of a plot. I'm still not great with how to implement conditions in R, so I can't do anything particularly interesting without tedious coding. Here are two plots I produced. The first is done by the standard R graphing procedures and the second with xyplot and layering.

First makes a plot(), a par(new=T) that allows a second plot() to be added to the original. It isn't hard to use but making it visually appealing requires understanding graphical parameters that I don't understand.

On the other hand, xyplot produces a trellis object that feeds into a command, asTheEconomist(), which is a part of the latticeExtra package. The plot below is for returns rather than levels, as above. The addition I want to make is to create a series of layers on this plot that show when both gas and oil returns are positive. Oh, right. Blue is NG, brown is oil. Labeling is not my focus. These layers will be partly transparent blocks of shading.

What does this chart tell us? It's hard to tell without the shading and even then, I don't think it'll look definitive. What I'm trying to see is how often returns in gas and oil are both positive or both negative. Good a starting point as any.