Interesting probability fact "Sally Clark’s life was ruined by a wrong-headed assumption of independent probability. Her first child died of SIDS (called “cot death” in her native UK) in 1996. When her second son also died of SIDS the following year, she was accused of murdering both her children. The prosecution’s argument was that the chances of one child dying from SIDS were 1 in 8543, so the probability of two such deaths in the same family were one in 8543 × 8543 or about 73,000,000, too small to be a coincidence. This argument was persuasive and in 1999 she was convicted of murder and sent to prison. The Royal Statistical Society (RSS) objected to this misuse of probability in 2001. The two children were brothers, sharing common genetics and a common environment. Their circumstances were not independent. Wrongfully assuming independence lead to a probability estimate that was likely much too small. The RSS also objected that the probability, even if it were correct, was being used inappropriately. In 2003 Sally Clark’s conviction was overturned. Although she was released from prison, she never recovered from her ordeal and died of alcohol poisoning in 2007."
Interesting stock is this DRYS, a shipper. one of the few that sorta goes down exponentially rather than up as a lot of stocks do
You need a log chart to be able to understand what is going on there, thats why I say this. its down 99.99% from the highs and it just continues to go down, over and over
In terms of P&L, one wouldnt be able to see the exponentiality as a long would soon be down almost all of his investment and a short would have a neglegible amount of money short. but if the trader is adding to the position (long or short), then the "convexity" will be there. Even though its to the downside It took me too long to realize this, i have been playing this stock short for a few months but always on tiny size. I was too scared about the potential for a huge squeeze, but I didnt realize that the "convexity" for downside moves was also there. Its just unusual to see this
I'm always fascinated by things like this, the exception to the rule. Yes a stock investment usually have unlimited upside and limited downside, but in some situations, if the person is adding to the investment, this can be flipped. DRYS is a stock with giant downside for a long that averages losers (they can lose everything they have, or more if the borrow), and it also has a huge potential gain for a short that adds to winners. Its resembles convexity very much so, but in a short. DRYS is like an anti-stock
IIRC, the stock was at $100,000+ (split adjusted) a bunch a months ago, now its a $2 and the spiral continues
Now having said all that, the borrow rate is 100% and there are a lot of shorts in. Its not free money by any means. I do expect the Nasdaq or the SEC to shutdown this robbery of shareholders soon, but in the meantime, the stock can do anything
Over the last 6 months DRYS average losing day was -12.3%, the avg winning day was +10.76%. Losing days outnumbered winning days by 2-1 (81 vs 41). Worst day was -39.76%, best day was +105.28% Price fell from $4,500 down to $3. If one were to invert the signs of the gain and losses, it would look like a typical tech stock on a monster momentum run. Thats why this to me resembles convexity. Its a short that appears to have had some sort of convexity. The stock is a blackhole. I doubt the SEC/Naz will let this scam go on for much longer, its a scheme designed to enrich insiders at the expense of public shareholders. I have seen the SEC shutdown a lot of these over the years, usually when they reopen on the grey sheets, they are down 50-90%
I plan to continue to play this like I have been doing, small shorts here and there (with stops). This is more of a day/swing trade which is not the point of this journal. But I just thought it was very interesting to bring this up because its a situation that is so unusual
"My anger with "empirical" claims in risk management does not come from research. It comes from spending twenty tense (but entertaining) years taking risky decisions in the real world managing portfolios of complex derivatives, with payoffs that depend on higher order statistical properties —and you quickly realize that a certain class of relationships that "look good" in research papers almost never replicate in real life (in spite of the papers making some claims with a "p" close to infallible). But that is not the main problem with research. For us the world is vastly simpler in some sense than the academy, vastly more complicated in another. So the central lesson from decision-making (as opposed to working with data on a computer or bickering about logical constructions) is the following: it is the exposure (or payoff) that creates the complexity —and the opportunities and dangers— not so much the knowledge ( i.e., statistical distribution, model representation, etc.). In some situations, you can be extremely wrong and be fine, in others you can be slightly wrong and explode. If you are leveraged, errors blow you up; if you are not, you can enjoy life. So knowledge (i.e., if some statement is "true" or "false") matters little, very little in many situations. In the real world, there are very few situations where what you do and your belief if some statement is true or false naively map into each other. Some decisions require vastly more caution than others—or highly more drastic confidence intervals. For instance you do not "need evidence" that the water is poisonous to not drink from it. You do not need "evidence" that a gun is loaded to avoid playing Russian roulette, or evidence that a thief a on the lookout to lock your door. You need evidence of safety—not evidence of lack of safety— a central asymmetry that affects us with rare events. This asymmetry in skepticism makes it easy to draw a map of danger spots." https://www.edge.org/conversation/n...th-quadrant-a-map-of-the-limits-of-statistics