I work every day as a programmer on a quantitative stock analysis team that manages billions of dollars in assets. That position has given me a lot of insight into how such a professional quantitative stock analysis process works.

There are a number of distinct steps involved in getting a quantitative stock analysis model running.

Start with a list of stocks. This is the entire domain of stocks that you'll be considering so you might want to include the entire NASDAQ. There are a number of considerations when choosing the stock list. First, the more stocks the longer it'll take for the computer to calculate everything. Second, there are differences in behavior between for example large cap **and** small cap or between different sectors that make it hard to treat them all the same.

For each stock in the stock list selected the second part of the quantitative stock analysis process is to load all the data you can about them into a database. Some basic information might include price, earnings, forecasted earnings, cash flow, assets, **and** debt leverage. The more information you can get the potentially more thorough the quantitative stock analysis will be.

Third, with all this basic information about every stock the next thing to do is to calculate indicators. These are usually basic ratios, so from price **and** earnings you can get the Price-Earnings Ratio, or EPS Yield. If you're maintaining this information over time then you can calculate things like price momentum. This is a vital step to the effectiveness of any quantitative stock analysis model. Tweaking these indicators can have a huge impact on the outcome of the process.

Next there is a mathematical process. Since we can't directly compare price momentum to EPS yield there is an intermediate step that puts everything into standard deviation space. For each indicator we have to calculate it's standard deviation from the mean over all the stocks. This should result in numbers that are roughly within the range -3 to +3. With this calculation done it's possible to compare very different indicators.

Getting close to the end of the process is another very key part of the quantitative stock analysis calculation. To get one final number for each stock you take some weighted combination of the standard deviations of the indicators. It doesn't necessarily have to be a linear calculation. This function decides the importance of the different indicators in the overall analysis. At this point it is also possible to split out a few different final analyses using the same inputs. For example a growth strategy would be heavily weighted towards the growth indicators, **and** a value strategy would be weighted towards value based indicators. This formula requires lots of back testing to get just right **and** should be revised from time to time to deal with changes in the markets.

The final step is to rank each stock. Simply sort the stock list by the number that came out of the previous step. The result should be a list of stocks in which the ones at the top are probably the best buys, **and** the ones at the bottoms are probably the best to short. It's important to remember that the analysis is only as thorough as you make it so if you haven't accounted for things like merger speculation or growth through acquisitions then you may want to do some further checking before placing any orders.

The final list is very valuable **and** can be used for different strategies. There's still a question about how much of each stock should be bought or sold or whether or not to short the worst ranked stocks. Every investor should decide how to do this on their own based on a lot of back testing.

That's a very high level over view of how a quantitative stock analysis could work. Of course there are many potential variations. The work involved in getting something like this set up for personal investing is probably prohibitive. Check out my website for some ideas about how to start using a quantitative approach today. Click here

Matt Warren,

Computer Programmer **and** Stock Market Enthusiast,

http://quantitativestocksecrets.com

Source: www.articlecity.com