StockReader: Motivation and Background

This software has evolved gradually, and from the beginning I had no intention to make this kind of software.

A couple of years ago, I started to invest in stocks. After some painful experiences from the "buy-when-someone-recommends-a-stock"-period, I tried to be more systematic. I wanted to rank the stocks after some key numbers in order to automate the initial screening.

I created a spreadsheet document where I entered some key numbers for stocks, such as dividends, price/earnings, earning marigin, stock price, net asset value and some more parameters. Updating those values by hand was a very time consuming task, even for a very small number of stocks.

The next step was to experiment with linking to external webpages in OpenOffice. I found that task very time consuming too, as the incoming data spanned over different areas each time – sometimes, that data occupied five rows, sometimes seven rows. That brought a lot of work to adjust the spreadsheet. Also, it took OpenOffice some two to tree seconds to fetch the data (with a good internet connection).

The final step was to build a C++/Qt program that downloaded the stock data, analysed it and sent it to a csv file. My stockList spread sheet linked finally to that document. Now, it takes my quite-slow-and-quite-old computer some 80 seconds to download and update the stock information (12 data fields per stock) of some 300 stocks.

Lecture Notes: Financial Markets (Swedish notes)

Here are the lecture notes from my second course in National Economics: Financial Markets.

The notes are unfortunately in Swedish (I had no thoughts about blogging initially) and are meant as an inspiration. I recommend any student to write his/her own lecture notes him/her self.

The PDF file can be found at:
https://dl.dropboxusercontent.com/u/3587964/FinansHansBystrom.pdf

As before, I can guarantee that there are logical and factual mistakes, missing pieces and other flaws. However, I passed the exam with a good grade.

Mozambique, MZ: Heavy escort (day 34)

Police stops at an hourly basis has become "business as usual" for our trip. This stop proved to be different.

We were stopped by soldiers with machine guns and rifles. They told us that we had to wait for enough cars, buses and trucks to come so that they could form a convoy.

We spent one hour, drinking beer, eating and looking around in the village. Our trip leader told us not to take photos of any police, military or such vehicles/buildings.

Two armed soldiers were inspecting and counting the souls on the bus. Shortly after leaving the bus, they boarded again, screaming "camera, photo, phone!". They thought we had taken photos of them and they started checking the camera belonging to the suspected. The soldiers checked all (that means, all) pictures, including some high school graduation pictures (he gave a cocky answer when the soldier asked about that picture...). No illegal photos were found and he got the phone back after the soldier had threaten to break the phone.

The 115 km trip lasted for two hours under the protection from armoured combat vehicles and lots of soldiers. We saw one burnt wreck from a bus on the road, some destroyed trucks, a repaired bridge and a military camp.

In the beginning, it felt like an adventure, but I quickly realized that this is for real. There has been attacks on that road before, and people have been killed in those attacks.

For reasons that should be obvious for the reader, I have no photos of the convoy. I'll try to summarize the background of the conflict in a later post.

StockReader: Bringing Hundreds of Stocks to one Spreadsheet

My other project is StockReader. That program scans key numbers from some three hundred Swedish stocks and makes that data accessible from a spread sheet program.

That program analyses stock data from some web pages, extracts the interesting information and arranges it in a comma-separated-value file that is linked to a spreadsheet, where I can rank the stocks after some criteria.

This way, I can assign different points/grades to stocks, depending on how they perform with regard to, for example the price/earnings value. Companies with big losses will get a "bad" grade, and companies with good earnings will get a "good" grade.

The final result of the program: Stock data collected to a Spreadsheet

After summing the grades for each key number, I can easily identify the companies with high dividends, good earnings, good net asset values, ... After having my computer doing all the dull work, I can continue with cherry-picking the best stocks.

Nowadays, I am advocating the efficient market hypothesis, meaning that all public information about assets will be reflected by the price. So stock-picking will be more of a hobby for me with no intentions of beating the market.

I've learnt a lot when creating the program and I want to share it with my readers in future posts.

Bricks: Buiding a Helicopter