Clean, Accurate, Historical Stock Data (2)

Historical Stock PricesAdditional information on our two-for-one stock split (PDF) announced June 27, 2006 and distributed August 11, 2006. In order to keep things fair, a person is only allowed one user account, and is limited to certain amount of wins per week (6 under $200 and 3 over $200) Also, if you hit over $3,000.00 in wins in a month then you are only able to win 1 item of less than $200, and 1 item over $200 per week until the month is over. There are a lot of clothing/ costuming options, though there aren’t a lot of dolls designed to go with historical series.

Table 1 shows the performance of the stock of the two companies, in the recent period. Furthermore, it is visible that share prices of the company A are more stable i.e. have lower standard deviation than those of company B. As we said, risk of an individual shock will be measured by the related standard deviation (in economy it is often called volatility). Prices of A shares are more stable than prices of B shares; related standard deviations are 0.0184 and 0.0267, respectively. These digital books on 1920’s fashions and hairstyles are available for immediate download.

Also, it is evident that the prices are very negatively correlated (simplified explanation may be that the companies belong to the ‘opposite’ sectors: for example, company A produces ice creams whereas firm B produces umbrellas, and is currently the rainy season). In the first case, we assume that prices are very poorly correlated (say we deal with an ice cream company and a furniture factory), μa=0.1. In the second case, we assume that prices are highly positively correlated (considered companies, for example, are two ice cream companies), μb=1.

Assuming that correlation coefficient between share prices of companies A and B is 0.1, calculated standard deviation and expected return are presented in the Table 2. Obtained pairs of standard deviation and expected return form the efficient frontier (see figure). As one can see on the figure, when the prices are 100% positively correlated (i.e. μb=1), then the efficient frontier is a line between points (σ1,r1) and (σ2,r2). Even if the stock price falls in the short term, the price is going to appreciate in the long term.

The explosion in credit facilitated the creation of financial bubbles in the stock and housing markets in particular. The stock market set new records year after year and it appeared that all one had to do to get rich was borrow and invest in shares. Brokers loans increased from $3.5 billion dollars at the end of 1927 to nearly $6 billion dollars in 1929, the extra credit adding more fuel to the rise in the stock market. When the property bubble eventually burst in September 1926 following a devastating hurricane in Florida, house prices declined by an average of 30%, but up to 80% in some areas, leaving many speculators broke, and a Florida landscape littered with abandoned projects.Historical Stock Prices

Historical Stock Prices