Because of the horrific state of the world, we cover the horrors in one day, leaving the rest of the week for more fluffy stuff. This is Terrible Tuesdays.
Things are looking shaky and set to shake more than standing on an island with a malfunctioning nuclear power plant set to overheat. In our last TT, we noted how complexity theory could jumpstart the economy a lot faster once things do return to normal.
Today we will give a thought to the exasperation that quantitative analysts have in an environment of heightened risks where the rich are so convinced its the end of the world we are running out of physical gold.
To illustrate the point (and perhaps fend off further bombardment of scared clients), one head of a U.S. hedge fund described the markets to the FT as “it feels like strapping on a flak jacket and jumping on hand grenades going off every day.”
The ultra-rich might have a point. North Korea did fire two ballistic missiles into the sea on Saturday. Although its nice to see someone is acting normally during 2020, this of course still brings us closer to WW3.
“There’s no gold. There’s roughly a 10% premium to purchase physical gold for delivery. Usually it’s like 2%. I can buy a one ounce American Eagle for $1,800,” said Josh Strauss, partner at money manager Pekin Hardy Strauss in Chicago. “$1,800!”
But the masses cannot eat gold. This was a food bank in America yesterday;
Hundreds of cars wait to receive food from the Greater Community Food Bank in Duquesne. Collection begins at noon. @PghFoodBank @PittsburghPG pic.twitter.com/94YFaO7dqX
— Andrew Rush (@andrewrush) March 30, 2020
And yesterday Bloomberg noted that “Police have been deployed on the streets of Sicily’s capital, Palermo, amid reports gangs are using social media to plot attacks on stores” and further posited that “the risk is that organized crime gangs will step in to provide assistance to those in need, filling the gap left by the state.”
Leaving aside if that really is the way the world ends and its just a bunch of savages swarming via SM we do need to ask the question : Could the mafia be running Italy in two weeks from today after a revolution? How do you factor this into the FTSE MIB share price?
*A source from Palermo told DisruptionBanking that “the news about Palermo is a bit inflated, really happened one time only and the Police came.” Yes, we ask the mafia what’s happening, we are, after all, DisruptionBanking.
Enter Monte Carlo methods, simulations used to model the probability of different outcomes in a process that cannot easily be predicted due to the intervention of random variables (like 2020 today). It is a technique used to understand the impact of risk and uncertainty in prediction and forecasting models.
I did some Monte Carlo simulations for the growth of Covid-19 in different scenarios.
1. Delivery is great. Supermarkets not so much
2. Offices can spread the disease like crazy
3. Even when offices restart, we need some social distancinghttps://t.co/myE6zUJoVq— Karthik (@karthiks) March 30, 2020
According to Retail Technology Innovation Hub “Grocery retailers have failed during the coronavirus outbreak. They should have turned to Monte Carlo simulation to predict the panic buying and empty shelves that are currently making headlines.”
And because of those failures, we can say with a high degree of certainty that the $ per bushel of corn will be at the higher end of the Farm Bureau’s chart.
2009 – The people bailed out the banks.
2020 – The banks should bail out the people. https://t.co/c3aZ1Y4IYl— Chris Gledhill (@cgledhill) March 30, 2020
Although Gledhill is correct in that banks should bail out the people, model analysts are having a hard time trying to extrapolate the future owing to the fact that China’s statistics are well, questionable.
Because COVID-19 first appeared in China, and is apparently ‘over the worst’, financial analysts are desperately trying to figure out what’s in store for the rest of the world. But the models don’t work if the data is fake.
According to data released today, China’s NBS Manufacturing PMI (a gauge of the health of China’s production levels) jumped to higher levels than pre-crisis!
Bad modelling has its downsides.
According to an Investors Chronicle piece – On 13th February, a team of equity and risk researchers at US-headquartered index provider MSCI published a report that focused solely on the stress to China’s economy and its knock-on effects for various equity markets.
“A hypothetical 60-40 portfolio could lose slightly more than 5% under a stress test we conducted,” the report’s authors concluded. A month later, MSCI’s own World Index was down 30%. – although we enjoyed IC’s dry humour in that last sentence, we can be hopeful that the same set of analysts are not running Monte Carlo simulations on food supply chains.
Its one thing if money is lost, but lives are quite another.
Mr. Margaris chimed in with some terminator-themed thoughts. I mean if humans can’t create the correct simulations perhaps the robots can. But which one will feed us? Matrix or Skynet?
How long have we got
before #humans are replaced by #Artificialintelligence? https://t.co/IJxOMiEFcx #fintech #insurtech #AI #MachineLearning #DeepLearning #robotics #futureofwork @psb_dc @guzmand @sallyeaves @scroll_in @UrsBolt @mclynd @andi_staub @SabineVdL @diioannid pic.twitter.com/q9kZMt6Si9
— Spiros Margaris (@SpirosMargaris) March 31, 2020
One thing is for sure, our complexity theory fix from last week doesn’t work if the tools aren’t used correctly. Perhaps its time for a re-read of “Making Deep Learning models ready for the worst-case scenario and cross-platform ready with OpenVINO toolkit.”
Opportunities multiply as they are seized. – Sun Tzu
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