I learned a lot reading the applications our new InvestorGeek hopefuls have been sending in. For example…
The size of virtual worlds like Second Life and World of Warcraft (Wow) are making them more and more the target of entrepreneurs and investors. The stats are hard to calculate, but each world has about 4 million “inhabitants” and growing. Here is a quick round up of some of the business going down in these new markets.
In honor of Labor Day, we are offering to employ between 5-10 new authors. If you are interested in becoming a contributing writer for our site, please: Send your name, e-mail address, phone number, and blog URL if you have one, to contact {at} investorgeeks * com. Include a brief summary (no more than 200 (more…)
I’ve thrown together a few tools you guys can use to keep tabs on us. Subscribing to the InvestorGeeks feed is the first way, but we also do a lot of writing outside of the site. At Rollyo.com, you can use our custom-configured InvestorGeeks_Authors search engine which will search through a list of all the (more…)
On Monday, I wrote about using Google Trends as a resource for investing ideas. I took a look at three restaurant businesses which, while they were on my mind at the time, probably weren’t the best candidates for this kind of research.
Below, I’ll take a look at three Google Trends charts and compare them against some corresponding stock charts.
– Trends for “bull market” and “bear market” vs. the S&P 500.
– Trends for “bed”, “bath”, and “kitchen” vs. Bed Bath and Beyond (BBBY).
– Trends for “book” and “books” vs. Amazon.com, Inc. (AMZN).
We’ve had discussions here about different ways to use the huge amount of data freely available on the web to make better informed investing decisions. Let’s take a look at some graphs courtesy of Google Trends and see if they can inform us about which restaurant stock to purchase.
Howard Lindzon “smells a rat” at TheMoneyBlogs.com:
I called Brice (owner of TheMoneyBlgs), who picked up his own phone and asked him some questions. I immediately smelled a rat. Trading Markets will take my content and brand it in moneyblog design and keep all the advertising dollars from the aggregated data.
I love blogging and don’t mind doing it for free, but this is just plain sneaky.
If you run an investing, personal finance, business, or “money” blog, you’ve probably gotten an email from Brice Wightman of TheMoneyBlogs.com. InvestorGeeks got one, and we initially signed up since we’re proud of the relationship we have with a similar service pfblogs.org. But once we found that TheMoneyBlogs would not include a link back to our site the original article, we immediately removed ourselves from their network.
So how can you make these aggregators work for you? Find out how some people are trying to make TheMoneyBlogs work them. More importantly, I’ll go through some questions you can ask yourself to determine up front if a blog aggregator is really offering a win-win situation.
There are about as many variations on the moving average as there are investors using them. While it’s generally understood that no one configuration is going to be the holy grail of predicting stock prices, each investor has their own baselines or favorites that they come back to.
Below, I’ll talk a little bit about how I’ve been using MAs lately. Then I’ll look at some of the MA setups which seem popular online today and make some observations based on them.
Chapter 8 on “Spotting Bottoms in Stocks” is one of the best sections of Jim Cramer’s Real Money. The chapter is filled with the type of insights you would expect to get from someone with 25 years of experience in the market.
The chapter does discuss spotting bottoms in individual stocks, but Jim spends most of his time on indicators he uses to spot market bottoms. These indicators (collected into three categories) have been shared by all four of the last big market bottoms (1987, 1990, 1998, and the “double bottom” in 2002-2003).
WebWord has a good write up about Professor Feng Li who data mined the annual reports of 34,180 companies with some interesting results. Li counted the number of times words like “risk” and “uncertain” showed up in the reports and compared the data to previous years. Professor Li discovered that a “big jump in words (more…)