29-05-2013, 10:28 PM
I decided to start this thread to continue the discussion which sgd started started over in APPT thread.
Basically, it was his contention that an IPO is worth subscribing only if it has 2 or fewer underwriters:
I then summaried his observations as follows:
In summary:
1 underwriter: DIE DIE MUST BUY!
2 underwriters: CAN BUY!
3 or more underwriters: YOU BUY YOU DIE!
I decided to test the validity of his observations by using data available from shareinvestor. I plotted the 1st day % change / 1st week % change against the no of underwriters for IPO since Mar 2012. I concluded that the 'underwriter' theory is without merit based on the fact that there appears to be no correlation in the scatter plots.
This is what I got:
[Image: UnderwritersVsGains_zps3a255348.jpg]
kopikat made the following observations from my chart:
Finally, zf87 was of the opinion that "if you plot the average gain Vs numbers of underwriters probably you will appreciate the merit. Moreover, the non-underwriter case may not be included in the plots, since the "theory" says the fewer the underwriters, the more responsibility/risk they take."
Feel free to add on to the discussions and other observations.
zf87 suggested I plot average gain instead; but how should we calculate average gain? I'm prepared to refine the charts based on suggestions and other inputs.
Basically, it was his contention that an IPO is worth subscribing only if it has 2 or fewer underwriters:
sgd Wrote:how to tell "before hand" whether an IPO will be good to subscribe or not? I learned from very experienced sifu many years ago. Generally If there are 2 underwriters is a good IPO. If there is only 1 underwriter for the IPO then just sell your farm and buy that stock as much as you can.
Underwriters have a lot of risk they don't earn commission for nothing, if the IPO launch is not well taken up they have to absorb all the unsold shares. So if IPO prospectus indicate there is only 1 sole underwriter means that underwriter is very confident of the launch to be a success. And If is good deal why need/want to share your commission with others?
But if underwriter is not confident they will try to get others to co-underwrite means if the launch is not successful everybody has to take a share to absorb unsold stock. In this case there were so many underwriters.
So rather than they absorb and stuck with it, they throw it to those kiasu people who oversubscribed.
I then summaried his observations as follows:
In summary:
1 underwriter: DIE DIE MUST BUY!
2 underwriters: CAN BUY!
3 or more underwriters: YOU BUY YOU DIE!
I decided to test the validity of his observations by using data available from shareinvestor. I plotted the 1st day % change / 1st week % change against the no of underwriters for IPO since Mar 2012. I concluded that the 'underwriter' theory is without merit based on the fact that there appears to be no correlation in the scatter plots.
This is what I got:
[Image: UnderwritersVsGains_zps3a255348.jpg]
kopikat made the following observations from my chart:
kopikat Wrote:1. During bullish times (since 2012), the chances of making $$ from IPO stags (1st day) is very high. In your charts, only 1 is underwater. Almost no one (those who applies for the IPOs anyway) bothers too much about company fundamentals..
2. After only 1 week, we start to see more of them going underwater (4 in your charts, with 2 from Catalist). Perhaps, the smarter ones have already taken profits, especially from the stocks of poorer fundamentals (?). Guess who'll usually be left carrying the babies? Most likely the less informed and "uneducated" (as in stocks "education") ones... I used to be one of them...
It'll be interesting to see the longer term performance, especially when we hit a negative mkt sentiment period of time...
Finally, zf87 was of the opinion that "if you plot the average gain Vs numbers of underwriters probably you will appreciate the merit. Moreover, the non-underwriter case may not be included in the plots, since the "theory" says the fewer the underwriters, the more responsibility/risk they take."
Feel free to add on to the discussions and other observations.
zf87 suggested I plot average gain instead; but how should we calculate average gain? I'm prepared to refine the charts based on suggestions and other inputs.