Below you will find pages that utilize the taxonomy term “Markets”
It’s Saturday and the month of April is almost over. It WAS Saturday when I started writing this but now it’s the last day of April. It’s been especially cold this April and the leaves aren’t even out on the trees where I live. That’s been a big bummer. There have been a few days this month that have been perfect Spring days and my body is ready for the warm weather.
Some of yesterday’s winners or most active should be no news to any who looks at the markets. Gilead Sciences announced some positive results working on Covid19 related drugs. Good, we need more stuff like this to get our lives back to normal. I don’t know about you but I’m getting stir crazy after being in ‘lockdown’ for two months now.
My chart generator is showing me that there’s only a support line down at $64, so congrats to all the stock pickers.
I should really use the python scripts I’ve written to make chart generation easier for me. Right now I need to spin up a Jupyter instance and run them by hand if I want to make something custom.
I’m taking a quick stroll through the Healthcare ETF (XLV), the Q’s (QQQ), and the general S&P500 (SPX) ETFs.
I’m using my own dynamic implementation of autogenerated support and resistance lines. If I squint real hard I can see some ETF’s running out of steam and others bumping heading toward resistance.
The Oil markets are a really dumpster fire these days. With the Russian and Saudi oil wars going on the result has been a flood of oil in the markets. Prices collapsed for the May 2020 contract to -$37.63 a barrel. That’s nuts.
I’m starting to see prices being pushed down at gas stations too. Since Covid19 put a damper of travel, I think well see sub $10 a barrel oil coming.
I really like it when Ray talks more history and how economic systems work rather than his philosophies on living.
Here’s the LinkedIn video. The embedding doesn’t work right.
With over 20 million unemployment claims, the markets are trying to shrug off the Covid19 pandemic and look toward better times. Not sure if that’s going to fly but Main Street is hurting bad.
Everywhere I look, small businesses are shuttered. Some friends are out of jobs and everyone is adjusting to the ‘new normal.’ Except this is NOT normal, it should be called the ‘new abnormal.’
I don’t trust this market ‘rally’ one bit and I believe the market has more room to fall.
Like any other red blooded American male, I spend a lot of time at Home Depot. Now that spring is here, my local Home Depot is packed with men, women, and kids in tow. Feels good to see that people are still beautifying and upgrading their properties.
Still, if you looked at the HD chart, you’ll notice that it’s nearing a death cross (50DMA below 200DMA) on the daily chart. Is this the classic “sell in May and go away” syndrome or the first parts of “Taper” finally working its way through the system?
With everyone scrambling to see how low the Dow, Nasdaq, and S&P500 will go, I’ve decided to throw my Monte Carlo simulated price targets into the mix. They’ve been pretty accurate so far and I use this system to find my Forex stops and limit BUY/SELL points. I also use it for work creating complex budget risk Excel spreadsheets but you wouldn’t care about that.
The benefit of the using the Monte Carlo simulation is that you can update the model with new information and get a fresh perspective on where the â€œkeyâ€ price areas in the market and how you can profit from them.
Yesterday, on Black Friday, we saw a nice relief rally in the markets but the cynic in me says it won't last. The markets have room to go lower and everybody's wondering if Santa Claus will skip Wall Street this year. The initial results from my S&P500 Volatility model is showing elevated volatility still remains and any news on more subprime write downs would be sure to push the index lower.
In a few previous posts I explored how percent gain and loss distributions for indices tend to follow a power law distribution instead of the widely accepted Gaussian distribution (bell curve). I tried to show that “way out there” events, both positive and negative, tend to occur more frequently in real life than under the standard bell curve. The negative outlier events are called “Black Swans” which was coined by Mr.