Smartphones and value for money

Ok so I took the plunge. My shiny new Nokia E71 arrived last week. This is the first time I have bought a mobile phone at its retail price. Before this, I was usually happy to choose among the free phones supplied by the carriers. But this time things are different. There are fantastic smart-phones on the market (like the E71) and I have figured out the math behind why "free" is not free when it comes to mobile phone plans and 2 year lock-in periods.

Still, spending 300-odd Euros on a phone triggered introspection. Do I really need a smart phone that is, well, so smart. Smart is a relative term. I used to sync my old Sony-Ericsson to my PC Outlook and have my contacts and calendar up-to-date. That was smart too. So the question is, is my E 71's extra smartness worth the Euros? After 3 days, here are the things I am doing with my new phone that I could'nt earlier. Offcourse Nokia advertises the things you can do with this new phone, but I seriously doubt I will ever do all that Nokia suggests.

1. Do emails on the train.
2. Use the basic English-German dictionary in the phone
3. Type SMSes faster
4. Set up appointments, to-dos easily on the phone, thanks to its keyborad
5. Get an automatic weather report in the morning
6. Solitaire
7. GPS.. well, perhaps in the summer if I get lost or something (unlikely though)
8. I can chat and Skype-out using Fring.

Well lets suppose the phone lasts 2 years. that would get its price to under 50 Euro cents per day (discounting the cost of capital). That probably makes it worth the money given the list above.

...or am I rationalizing the splurge?

Wireless broadband options in India

I am looking around for broadband services for my folks in Bangalore. They already have DSL via the state-owned BSNL. But this service is quite unreliable, being disconnected for days at a stretch. Before you draw conclusions about the India and her spotty infrastructure, be aware that this DSL broadband comes for about 5 Euros per month. That is 5 times lesser than comparable DSL in Germany. My way of looking at this is that part of the service offering (the reliability) is traded for the lower costs in India. Off course PPP (purchase power parity) will put 5 Euros in India right around 20 Euros in Berlin, but still, 5 Euros a month is a good deal - after all, people who buy broadband in India are very well off.

So we decided to shop around for cellular broadband services. The reasoning is that if you have a couple of services then at least one should be active at any time. The options are

1. Airtel (USB stick, 3G). Officially works at 115 kbps d/l, actually works at 15-20 kbps according to the salesperson, and costs 10 Euros a month for unlimited service.

2. Reliance (Antenna and coax cable, 3G). Apparently delivers upto 300 kbps, and costs 12 Euros a month for unlimited service. Requires installing an antenna on the rooftop.

I would go with option 2 for home use and option 1 for mobility. My folks have a better idea - just revert to dial-up when the DSL breaks because thats good enough for their need for checking email once a day. Cant argue with that!

Social networks - grade sheet

I found a superb data analysis of the most popular social networking websites that may be interesting for some. The data was pulled from Google Insights and Google Ad Planner.

Look how Twitter is soaring!

Eric Maskin's talk at the Berlin/Brandenberg Academy of Sciences

I had a unique opportunity to attend Eric Maskin's Nobel lecture (re-delivered) at the Berlin/Brandenberg Academy of Sciences. Eric Maskin shared the 2007 Nobel prize in Economic Science with Leonid Hurwicz and Roger Myerson for work in "Mechanism Design". This being my first brush with the topic, I expected a lecture of dense technicalities. I was mistaken.

Eric gave a great introduction to the theory and for once I started thinking of how great it would have been to take one of his classes! The idea of Mechanism Design is creating a set of rules that make selfish players behave in a way to achieve a certain outcome. In classical Game Theory the set of rules (constraints) are already given and then players try to maximize their utility (benefit) by playing by the rules via their self-chosen strategies. In the end, game theorists try to determine the steady state or Nash Equilibrium where no player can benefit by unilaterally changing his strategy.

Mechanism Design is about designing the constraints or set of rules. Eric spoke about things like writing the rules for green house emissions among the countries (the players). He also spoke about the energy sector and gave a simple example of how a mechanism can be designed to satisfy different players while making choices about which energy sources to develop.

Eric started with the brother-sister cake division example - how by letting the brother cut the cake in half and then letting the sister choose the first half the division would be fair. Mechanism Design - my brother and I(re)invented this one when we were 6 ;-) !

The rise of the Netbook

While walking in Media Markt's laptop aisle yesterday I was surprised to see the number of mini laptops (Asus EEPC, Acer Aspire 1, Toshiba netbook etc.) in the €299-500 price range. Interestingly, some of them are being sold like cellphones - with a price tag of just 1 Euro with a 2 year "3G data plan". The data plan costs 37 Euros, and probably gives customers a few GB of bandwidth a month.

So adopters get to carry their *free* netbook and Internet connection anywhere, without paying outrageous Wifi hotspot/hotel Internet charges. Perhaps in a few months this Netbook offer will spur many to switch to 3G Internet and give up on tethered Internet (cable, DSL) entirely. Are we looking at this cannibalization in the next couple of years? Low cost cellphones cannibalized fixed line telephone users. Can netbooks with 3G data plans cannibalize tethered DSL?

It all depends on the service quality of 3G data vs. DSL. Now 3G data can seldom serve more than 100s of kbps versus the multiple mbps of DSL connections. But I hazard that there is a sizeable market segment to whom the mobility (and free netbook) will appeal more than blitzy Internet connections.

Another issue will be the scalability of 3G data - 3G infrastructure has some fundamental bandwidth limits - which make a mass deployment in dense areas problematic. There is LTE, the next generation of cellular wireless networks that promises much more bandwidth, but its deployment is only planned over the next decade. Perhaps mass data demand over wireless will speed things up for LTE (or WiMAX).

The multi-person home tethered service is probably safe from wireless 3G data for now. Splitting 3G bandwidth is certainly possible via Internet sharing or a router that accepts a 3G data card and then wifis the bandwidth to multiple home PCs, but the slow speed will be an issue for demanding applications like online video, gaming, etc. 3G data is still a 'midband' service. Moreover, netbooks are difficult to use with their small screens and cramped keyboards. Presently deployed laptops and desktops are certainly more comfortable (minus their limited mobility).

The Netbooks' rise is absolutely remarkable. A couple of years ago MIT's OLPC project was the seed of the idea to create cheap affordable laptops for school children in developing countries. Then Intel threw in its own school laptop competitor. Asus stole the commercial show with its EEPC 701. Intel's spectacular strategy of creating the low-power Atom processor created a captive netbook market for Intel and allowed for smaller and lighter batteries. Microsoft resurrected Windows XP as the Netbook operating system while Linux provided a free alternative to Windows XP. And then there is the 3G data availability through USB sticks.

It all seems to have come together at the right time.

Pure gold statistics about the Internet

Figure: Internet users by age (Click to enlarge). Reproduced from here

I found an absolutely remarkable report issued by the OECD in the summer of 2008. It has got lots of goodies on OECD Internet usage. Here is the URL

The future of the Internet Economy, a Statistical profile

One graph in the report that was very interesting and it is pasted above. The graph shows OECD countries' Internet usage conditioned on the age-group. It is clear that younger people use the Internet much more than older people.

Now as time progresses the young people will age, and I do not think the young people of today will give up on the Internet as they age. Meanwhile the next generations will be even more Internet savvy than today's youngsters. So the low down is that the next 15-20 years will see a high growth period for OECD Internet broadband demand. There is about 20-30 more years of growth in this space before Internet broadband growth saturates, say, the way Electricity did.

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.

Where is all that Wall Street money?

You've all heard the news - investment houses going bankrupt, being sold off to retail banks, large insurance companies being nationalized - all within the span of a couple of weeks. What amazes me the most is the sort of numbers floating around. A year ago the market capitalization of these busted companies was 100s of billions of dollars. They employed 10s of thousands of people, including ivy league-educated finance jocks and MBAs. Their stock prices seemed to go up, up and away - a complete endorsement of their magical money making ability. Then, ignominiously, they went broke.

Monetary circulation is a closed entity - dollars don't just float away into outer space. So I am thinking - where did all those loaned dollars go? To understand that, lets look at Mr. John Doe's 4-bed/3-bath home in suburban San Diego that was built ca. 2004 and bought by Mr. Doe at a hefty price via a loan. Say Mr. Doe has fallen behind on his payments in 2008, therefore adding to the toxicity of the CDOs - Collateralized Debt Obligations - that wrongly counted Mr. Doe's mortgage as AAA+ reliable. But all this happened in 2008. Where did the money go to in 2004?

The developer bought the land from the state. Therefore a part of the loan capital went to the state. The house itself was built using superior building materials (expensive house) and therefore, part of that capital flowed into the pockets of the building material company shareholders - the glass company, the wood company, the lighting company etc. A big part of the house price was profit for the builder/architect company and therefore, it went to these companies' shareholders. There was Latin American labor to built the house, and so some of the money went to Latin America via Western Union transfers. Some more must have flowed to China for building materials, or perhaps to Italy for the Italian marble.

Now the key point is that the value of the asset handed to Mr. Doe was supposed to rise as time went by, because this house was in the San Diego area, with the beautiful Southern California climate, the wonderful, peaceful, and happy society, the good public school in the neighborhood, and consequently the never ending demand for housing as people from all over the world came looking for a piece of this beautiful part of the world. In fact, Mr. Doe bought the house factoring all this into the future equation to pay back the hefty mortgage. In the worst case (he thought), he could just sell the house and pay back the mortgage, making a neat sum for himself. And until he sold, he could live a good life in the expensive home.

Unfortunately for Mr. Doe (and everyone else), the price of his house actually fell, and this voided the whole argument of the previous paragraph. Now if Mr. Doe's house goes into foreclosure, Mr. Doe's lending bank will only recover the reduced price of the house. The notional and fluffy value described in the previous paragraph could not be converted back into hard money when it was needed in 2008. Money has been lost, and this fact bubbles up to all those CDOs on Wall Street. Until the value of the asset -that house - rises again, there is no way to fix the problem.

Hype around "Hypertargeted" advertising, and what REALLY matters in click-based advertising

This article in today's Wall Street Journal discusses Myspace's "Hyper targeted" advertising system. The system studies profiles, messages, and other information of Myspace users and divides users into more than 1000 distinct "buckets" or categories. This classification can be used to target specific customer groups very effectively. Or so News Corp. (which bought Myspace for about $580m) hopes.

The article goes on to explain that "hypertargeting" has had checkered success, with some advertising campaigns having moderate success while others doing perfectly well with less "targeted" and more generic location-based (zip code) online advertising.

There was one very interesting example in the article. Quoting from the article

"The New York Health & Racquet Club spent $5,000 on a MySpace campaign that displayed 2.3 million ads to users on the site. Though the health club could have chosen to target ads at people who say in their profiles that they enjoy rock climbing, yoga or working out, it chose instead to simply target by age and ZIP codes near its facilities. The club said it was relatively happy with the campaign, which generated roughly 1,000 clicks, a response rate of just 0.04%."

-Source: WSJ

Now lets see, the New York Health & Racquet Club spent $5000 for 1000 clicks, i.e., $5 per click. If we assume that 5% of those folks who clicked on the ad actually signed up for club membership (means 50 sign-ups) then the per-membership marketing cost is $100 per customer. Not bad, considering that the average membership is $75-$100 per month. One the other hand, if only 10 people signed up, then you have a much higher price of $500 per new customer.

The key question therefore is, what is the post-click conversion rate, i.e., yield per click. Because this determines the value of the click for an advertiser (like the health club), and by extension, the price of the click that a content syndicator like Myspace can set. Ultimately it is the advertiser's landing website that needs to make customers out of users.

The Myspaces and Googles of the online world may well find it worth their while to start helping advertisers convert clicks into dollars instead of stopping at matching the exact user profile with the exact advertiser. Hypertargeting is good, but paying customers are much much better.

What matters to me, whats in my head, and this blog

Figure: My Wordle view (Click to enlarge)

I came across Wordle - a service that lets you create a word cloud from any text, highlighting those words that occur frequently. The above figure is generated from the text of this blog. The picture says it all!!!

Tesla, EVs, and their mass adoption

Figure: Tesla Roadster, the sporty Electric Vehicle

The current Fortune has an article about the teething troubles of the Tesla Roadster, an electric vehicle (EV) being touted as an all-electric sports car (click here for more pictures). Apparently, more than a 1000 people, including some who-is-who s, have signed up to take delivery of the first fully electric sports car. The article states that excitement remains high, never mind that Tesla is having problems keeping the delivery date for most orders.

Tesla's website says that the Lithium ion cell powered vehicle can cover 220 miles per recharge. Now that is quite impressive, if you consider that according to the AAA an average American drives only 29 miles per day. As long as you are not driving cross-country the Tesla Roadster should almost replace your conventional sports car, almost because recharging the 6,831 Lithium ion cells on the Tesla Roadster takes 3.5 hours as compared to the 5 minutes of tanking-up the conventional Porche Boxster. The long recharge time is still not a deal breaker - if you can remember to charge your cell-phone every night then plugging in the car every evening shouldn't be that hard either.

The question is, will EV technology follow the conventional wisdom that early adopter products migrate down to the mass market? Does it make economic sense to buy such a car for the John Doe on the street, if not now, then 5 years into the future?

The Tesla motors website says that the operating cost for the Tesla Roadster is under 2 cents per mile. The operating cost for a comparable Porsche Boxster is about 20 cents per mile (calculated from this website, with gas at $4 per gallon)*.

Unfortunately, the Tesla Roadster 2009 edition costs about $109,000 while the Boxster costs less than half, about $50,000. Or, put another way, you will have to drive

(109000-50000)/(0.20-0.02) = 327,778 miles,

before the extra price of the Tesla Roadster can be justified!!!

Since Lithium ion batteries will not last 327K miles (neither will the rest of the car), I think that EV technology is not getting into the mass market anytime soon. Even if the price of gas triples, you will have to drive more than 100K miles in your EV before it saves you any money. And I haven't even factored in the lost opportunity of investing the $59,000 difference elsewhere.

So clearly the argument of saving on energy costs is meaningless if the EV is going to cost an arm and a leg. Question is, can EV manufacturers, or liberal government subsidies, narrow the price gap between EVs and gas-powered vehicles?





*assuming that the operating costs only cover energy costs