My splintered digital world

I get the feeling that my digital life is divided, unequally, among my email accounts, my phone, my USB stick, my laptop, my desktop, my cameras, my linux workstation, my disks, my backups, my Facebook, my Linked in, my blog, my webpage, my o my o my.

When I first started using the PCs 2 decades ago I had a nice floppy disk to carry my digital data. It fit in, or it was thrown out - great garbage removers those 360kB DSDD disks. Well I am not going to go down the Luddite path here, I am perfectly happy with todays infinite storage. But I am concerned about data splintering. My data is in all these various formats, versions, and names somewhere in various parts of my digital ecospace.

Now not to conclude that I don't have a system to file different things in different directories and the like. But too much information may result in suboptimal storage. For example, I have nicely named and dated folders for my pictures. But when 94 photos of my niece arrive via email it takes precious minutes to download and store each picture. How do I aggregate information quickly and without manual labor?

Algorithmic search presents the next best alternative - just keep everything anywhere and then have your computers crawl abd index the information. But search does not span devices (At least right now). How do I pull up the phone number stored in my home phone's caller ID while sitting at work?

Problems problems problems. Thats great because this means there is a whole lot of work to do in this area. Start-up anyone?

Smartphones or flash drives to replace the laptop (?)

I am intrigued by the possibility to leave my laptop at home (or work) instead of carrying it around every single day, as discussed in this WSJ article. Are we already there?

I have been running a small experiment on myself for the past few months about the feasibility of this approach. My use case is one with heavy usage of my Outlook mailbox, lots of documents, and some software like MS Office, Emacs and Matlab.

In my experiment I have stored all my working data files in an 8 GB Sandisk cruzer USB drive. I plug the cruzer drive into various computers I have access to, just as I would a smartphone with so much flash memory. It mostly works (i.e. I don't miss my laptop), but here are the unresolved issues

1. Security: Yes I mean the consequence of loosing the flash drive (smartphone), but also the issue with secure corporate Outlook email on my laptop via VPN and certificates. It is impossible to have the same corporate setup at home on another computer (at least where I work). But this may not be an issue for those who use web mail.

2. Software: Well lets face it, not all software can be installed on every computer. The other option is trying to install software on the flash disk, but then many software installations bind themselves to the computer - for example - those registry keys of MS Office installations. Perhaps this is an area where more innovation is needed to untether software from hardware. For now, I use my computer agnostic Emacs editor as my data input tool out side of my laptop. Oh, and I also use it when I am on my laptop. I love it!

3. Customization: There are ways to copy your browser favorites, screen savers, wall papers etc. on your flash drive or smartphone, but I would say figuring all this out is cumbersome. Instead there is this cool Mokafive concept of carrying your whole OS and data and customized software all on one flash drive! Just boot off the USB drive and you are done. I found out from the IT guys though that security software will complain about this. Another problem is that loading and running an OS off the USB drive will be slowwwwwwwww.

Lala, streaming for life, cloud computing, bandwidth, and the ISP

Lala says it will sell you the right to stream a song, for life, for 10 cents. Thats quite a sweet deal for someone who listens to music on the computer only. In case you really want to take the song on the go, you can buy the song permanently for your music player for the same 99 cents. Lets do some bandwidth Math now.

Use case 1: Fixed line user
A user streams 8 hours of music every day @ 128 kbps from Lala. First off, 8 hours at 4 minutes per song is about 60*8/4 = 120 songs. If the user's Lala library has a different 120 songs for each day of the week, s/he has 600 songs (= 120 * 5). An investment of $60, for a lifetime. Now this is quite a good deal compared to the corresponding $600 based on the current 99 cents-a-song model. Offcourse you loose the right to download the song into your iPod, but for this use case lets say it doesnt matter to the user. The critical point is, users will not download the song one time as in the current model but will download it everytime they want to hear it.

Now lets do the bandwidth calculation.

(8 * 3600) seconds * 128 kbps = 460MB

So we have a 460 MB sustained streaming download per day. For 20 week-days a month, we are talking about a bandwidth usage of 9GB per month. This usage certainly puts use case 1 into the ISPs' "power user" category. Do we have enough bandwidth provisioning in the core and access networks to deal with large numbers of such users?

Use case 2: Mobile Internet user
Use case 2 is a mobile internet user (think UMTS on a laptop) user. Even if we cut the music streaming about 1 hour per day, we have a usuage of over 1GB per month just for music. Do we have that sort of bandwidth on 3G networks and will flat-rate data plans tolerate such perfectly legal users?

Van Goghs from the S&P Stock Index

(Figure 1: Click to Enlarge)

I was playing around with the S&P historical data (monthly averages from 1871 to 2008) and came up with Figure 1. In this figure I show the value of $100 invested at each month since 1871 in an S&P index fund (see my related post) and this is the first independent axis. Another independent axis varies the lead time to sell, i.e., the time the investor waits for before selling the invested fund. Finally the dependent (z, vertical) axis shows the total return (principal + profit/loss) on the $100 that was invested initially.

This 3-D graph is in itself quite interesting although it is too dense to offer any direct insights. So I flew to the top of the graph (the virtual geek way - I set the viewing azimuth to 0 and the elevation to 90 degrees). And then I created my Van Goghs of the S&P Stock Index!

Figures 2a (24 months) , 2b (5 years), and 2c (10 years)
Click to enlarge

In Figures 2a, 2b, and 2c, the vertical axis is the time of making the investment of $100 in the S&P index fund. Blue signifies losses, and hotter colors (reds, yellows) signify profits in the color maps - notice that Matlab has assigned different colormap scales to each of the figures.

The horizontal axis is the time for which the investor holds on to the index fund before selling it (in years). Note the dark blue streak around the Great Depression (1929-) in all the graphs. It gets thinner as you move from right to left - since someone who exited just before the big fall saved themselves, but those who had invested earlier but held on lost (blues). You see blue lines around the year 2000 - when the Internet stock bubble burst. But you also see the dark red streaks of pure profits interspersed throughout the graphs.

Search for the rare combinations of small lead times and large profits in the 3 figures. Thats where investors invested and were quickly able to make large profits - if they exited wisely. And that will make for a wistful "if only I had invested and divested in those red streak times!"

Impressionist no doubt!

Why to (still) believe in the Stock market

( Click to enlarge)

One of the most exciting things about the stock market is its unpredictability. Some liken it to casino gambling in that there is randomness in the return on investment. Moreover, the conventional thinking is that the odds are stacked against the small invester since he is competing against highly organized hedgefunds and mutual funds with talented fund managers. So the question is, can the ordinary investor make money on the stock market. I know the answer is yes, but by "ordinary investor" I mean someone who just uses a simple mechanism of buying stocks at a low price and the selling them after a certain time lag when prices are high. Nothing fancy like short selling, derivatives, etc.

I did some basic analysis on S&P historical data to debunk the first misgiving about the stock market being a casino, and events for the last couple of weeks (Oct. 2008) have debunked the myth of the know-all big fund. They are all bleeding red ink as much as small investors (no, portfolio diversity didnt save the day for them, but that is for another blog post).

Lets get back to the S&P historical data. I obtained the monthly S&P averages from the January 1900 till May 2008. I then wrote a Matlab script to invest in an S&P index "fund" during each month an amount of $100, and sell this after a pre-specified lag (1 month, 12 months, 5 years, 10 years). The figures for the different lags are given above (click to enlarge) and show sale value (Y axis) of the $100 investment that was made in the S&P index in the time specified on the X axis. These graphs are not adjusted for inflation.

For small lags (1 month, 12 months), the graphs look random and seem to support the casino effect. However, for larger lags (60 months - 5 years, and 120 months - 10 years) there is a clear trend. Some times were better investment times than other times. For example, it was smart to buy in the late 80s when the stocks were low and sell during the late 90s when the stocks were high (120 month lag).

Some conclusions from this basic analysis are

1. There is room for applying basic intelligence, and hence, this is no casino play where winning follows a certain probability distribution.
   
2. Timing is everything when considering stocks as an investment. It is as important to guess the selling time as it is the buying time. For example, folks who bought in 1920 did very well by selling in 1925 rather than 1930. Buying and then keeping stocks away like fixed-term treasury certificates is a bad idea.
   
3. Short term gains in index funds are hard to come by. Try specific stocks for this (and assume the greater risk of no diversity in this case).

I am still working on this analysis. Will keep this blog posted If you want the Matlab scripts just email me.