About three months ago, I wrote a post about why it’s dangerous to listen to self-proclaimed stock “experts” instead of doing your own research. In that post, I included the same graph of my portfolio compared to the S&P 500 that can be found on the cover (and throughout the inside) of my book. Continue reading
The big news when it came to Amazon this morning was that the company bought Twitch for $1 billion. After reading countless analysts’ opinions of the purchase on CNN Money and Yahoo Finance and then turning on CNBC and getting several more earfuls, I felt I had a pretty clear picture of the analysts’s opposing views of Amazon’s acquisition. I read that Twitch was, “a service that lets users watch and broadcast video game play.” I also read all of the statistics, including 55 million monthly visitors and more web traffic than HBO GO. So I had done all the research that could be reasonably done about what exactly Twitch brings to the table from a nuts-and-bolts perspective.
I am not a gamer. My nerdiness has always been focused in a different direction. So this morning, I had the briefest of chats with one of my best friends about Twitch. I simply asked what his impression was of the site. He told me, “It’ll probably end up being like a nerdy youtube. ‘Professional’ gaming is a thing now, and Twitch has that market pretty well covered.” Continue reading
Hewlett-Packard released their quarterly earnings last week, and the market’s reaction to the news has been awesome so far for shareholders like me. The company produced earnings that were in line with expectations and issued forward guidance that was at the high end of the expected range. There are plenty of summaries of the numbers online, such as this concise article by Mark Vickery on Zacks. Today, I’m going to focus on a particular part of the Hewlett-Packard story: how and why the stock market consistently gets ahead of itself. Continue reading
On Wednesday, I wrote about the Maximum Pain Theory and the role it plays in share price movement. The main idea is that the actions of option writers drive share prices toward nice, round numbers, or the “max pain” strike price.
The example I looked at was Apple, which, after breaking above $100 for the first time since it’s stock split earlier this year, has seemed to be “stuck” right around that level all week. I predicted that, because of the large number of outstanding Apple options with $100 strike prices, “It wouldn’t be surprising if Apple toes the $100 line for the rest of the week and ends up ‘pinned’ very near $100 at the end of the trading day on Friday.” Continue reading
I mentioned Tuesday in my post about Apple breaking the $100 mark that the rest of the week would be critical for Apple shareholders. Today I’d like to talk about one reason why the rest of the week might end up being pretty boring for Apple shareholders. This reason is also yet another reason round numbers are so tough for stocks to break through.
I don’t talk much about options on this site because I don’t trade options very often. They are extremely risky and volatile, and I see no reason to fool with them unless very specific scenarios play out. There are plenty of people who have extremely complicated option-trading strategies to limit risk. But I always think to myself, “You know what else limits option-trading risk even more than this complicated trading strategy? Not trading options!” Continue reading
Apple closed the day above $100 per share for the first time since its stock split earlier this year. I made mention of this “round number roadblock” for Apple back on August 1. While Apple’s first close in the triple digits is certainly a good thing for shareholders, today’s trading doesn’t necessarily mean we are out of the woods just yet. Continue reading
To conclude my three part series on volatility (part 1 and part 2 here), I wanted to take a look at exactly how “safe” low-beta stocks are when it comes to market downturns. After all, isn’t the whole point of owning low-beta stocks to reduce risk?
So we’re going to hop in the time machine back to 2008, one of the worst years for the stock market in history. The S&P 500 fell 37.6% that year, and billions of dollars of stock market wealth evaporated into thin air. That is every trader’s worst nightmare and the driving force behind the desire to control portfolio risk. Continue reading
Yesterday I wrote about beta and discussed how it is calculated and what it means. But unless you know how to use beta to your advantage, it’s no more than a fun fact.
Last week, I read an article on CNN by Paul La Monica entitled “How to Stay Safe in a Scary Market.” In the article, La Monica says
So now’s the time… to be looking at blue chip, dividend-paying companies that can hold up well during rocky periods for the broader market.
The idea is that, when times get scary (as I have suggested they have become lately), you should build your portfolio around solid, low-volatility, low-risk stocks. I look at a lot of stock charts here on Trading Common Sense, and hopefully by using a little bit of common sense it’s easy to identify which stocks are more volatile in certain cases. Continue reading
The other day I got to thinking about the Efficient-Market Hypothesis (EMH). EMH is the idea that the stock market is “informationally efficient,” meaning that a stock is always accurately valued at any given time based on the information that is publicly available about the stock at that time. In other words, day-to-day changes in share price are simply due to changes in information available to the market.
I do not subscribe to this theory, and neither should any other stock trader. Here’s why: if you believe EMH is true, there’s no point in trading stocks. According to EMH, there’s no such thing as an “under-priced” stock, and the smartest, hardest-working investment banker at Goldman Sachs has no trading advantage whatsoever over your doofus cousin who once tried to make “Super Deodorant” out of after-shave, cologne, a bar of soap, and a pack of Doublemint gum. It’s pointless. If EMH is true, every stock is accurately priced at all times. Continue reading