2. Gap . Everybody hates retailers right now, so of course contrarians look for bargains. Gap, at $13, is a blue chip that looks dirt cheap. It's down 40% in a year, trading for just six times cash flow, yielding an OK 2.6%. And the balance sheet is solid.

3. The Vanguard Extended Duration Treasury exchange-traded fund. It tracks long Treasurys. Everyone's rushed into Treasurys for "safety." Ahem. The 30-year bond now yields just 2.63%. Safe? This is Russian roulette… with five bullets. Every outcome except massive, Depression-style deflation will kill these bonds.

4. The iShares Silver Trust . Silver has plunged amid fears of falling industrial demand. Platinum, too. But governments are borrowing and printing money like crazy to prevent a meltdown. That's usually terrible for paper money, and good for precious metals. Both these metals now look very cheap compared to gold.

5. The iShares Dow Jones Home Construction Index Fund . Expect any recovery in the housing market to show up among homebuilding stocks first. These actually outperformed other equities last year, but they're still 85% from their 2005 peak. History usually says that's the time to buy.

6. CGM Focus Fund . It's never a dull moment with fund legend Ken Heebner, aka "the mad bomber." His fund crashed this year after he turned disastrously bullish in the summer. I'm fascinated to see what he does next, and whether he can recover in 2009.

7. US Geothermal . A high-risk, speculative stock. HTM is a leveraged alternative-energy play. It's an interesting situation. It's building and operating geothermal power plants out west, and has plenty of cash. The shares have collapsed from $4 to just 70 cents, valuing the company at about $47 million.

8. The iShares MSCI EAFE Small Cap Index Fund . This spreads its bets across smaller companies in Japan, Europe and other developed markets. Some very smart people say that's where the real bargains are now.

9. Clough Global Opportunities , a flexible, global fund run by veteran hedge fund manager Chuck Clough and mentioned here before. In this market, of course, it is (yikes) cheaper now. It's selling for just 77 cents per dollar of assets. Closed ends are being given away today. This fund is merely one of many that look very interesting.

10. CurrencyShares Japanese Yen Trust . Everyone laughed at the Japanese for 15 years. Turns out they were quietly running a massive trade surplus and saving tons and tons of cash. That's usually great for a currency. Somehow our strategy, of doing the exact opposite, doesn't seem quite so clever now.

Write to Brett Arends at brett.arends@wsj.com

• Packing Tips
• Start preparing to pack a few days before you travel. Keep a running list of things to take, or put items out on a table or dresser as you think of them.
• Use a diaper bag with a waterproof lining and a shoulder strap.
• Pack an extra shirt for yourself in your carry-on bag.
• Prevent leaks by packing medicines and toiletries in resealable plastic bags.
• Keep your baby's outfits together in one suitcase so you can find them easily.
• Take your camera — and don't forget the battery charger if it's digital, or plenty of film if not.
• Take a clip-on reading light so you can read without disturbing your baby.

How We Invest

Mobile location-based services (LBS) are generating renewed interest as both the market and technology mature to support the growing set of innovative services being released and in development today. This is being driven by new Location APIs and new location technologies, which are making it easier for mobile location developers to gain access to location information and develop innovative new LBS apps.

This article is a brief primer on the key location technologies that are emerging.

Positioning Technologies

This section will review the primary positioning technologies in use today.

GPS

GPS is a system of 32 satellites orbiting 12,600 miles above the earth.The system was designed such that 6 (and usually more) satellites should be visible from any vantage point on earth. GPS works by making extremely precise distance estimates from timing the delay time of signals (1 ns ~ 1ft)sent from the GPS satellites to earth. Trialateration (triangulation) is used to determine the device’s location given at least 3 or more satellites. When a GPS receiver is turned on, it looks for and locks on to visible GPS satellites to begin receiving and decoding the GPS broadcast signal. The GPS almanac data provides a list of visible satellites. The GPS ephemeris data provides precise timing and location information for each satellite. Latitude, longitude, time and altitude are the 4 dimensions that must be solved for (usually the first 3). Position acquisition time is driven by previously collected GPS information and GPS signal quality. GPS is accurate to 5-20m depending on environmental conditions.

Assisted GPS or A-GPS

Assisted GPS is an improvement on GPS, primarily for mobile devices with network connectivity. Since mobile devices are connected to a wireless network on a known wireless base station, the location of the base station can be used to aid the GPS calculation. Assisted GPS takes the known location of the base station and provides synthetic or seed data to the mobile device’s GPS chip to improve the speed of GPS signal acquisition. For instance, if the GPS chip knows that it should “see” a specific set of 4-5 GPS satellites at it’s coarse location, the GPS chip is able to narrow the search of signals to acquire. This reduces the amount of time required for the GPS chip in collecting ephemeris data and improves the sensitivity of the GPS chip in processing noisier GPS signals. This allows for a faster location fix time and makes possible GPS use in some indoor environments.

Assisted GPS does require device chipset support and network communication. The A-GPS server has traditionally resides in the operator’s network. However, there is trending towards device manufacturers offering similar services for their devices specifically. For A-GPS to work, an initial position estimate is required. This has traditionally been via the operator’s Cell-ID database. Additional initial position estimate options are being made available with 3rd party Cell-ID and WiFi databases.

Network Base Station Database

Since mobile devices (both cellular and WiFi) are associated with a wireless access point / base station, it is possible to use the position of the base station as a proxy for the location of the device. In a simple case, the base station the device is associated with is returned as the device’s location. Mobile operators view their base station databases as proprietary network information and have not generally shared it with 3rd parties. There are a number of 3rd parties who have begun to accumulate detailed Cell-ID and WiFi databases that can then be used to locate devices.

Network database collection approaches fall into two camps: 3rd party driven or user-generated. SkyHook is the best example of a 3rd party driven approach where SkyHook employs a fleet of drivers that drive cities collecting WiFi access point information. Google and Navizon are companies that employ user-generated approaches where data is fed back from mobile devices with the appropriate client software installed. To build a database, these user-generated approaches can either leverage the collection of both GPS and base station signals, or leverage the collection of base station signals with existing known reference base station locations. It is likely a mix of fleet and user-generated approaches will be necessary to ensure high accuracy, rapid updating intervals, and low acquisition costs going forward for both Cell-ID and WiFi database collection.

3rd party Cell-ID databases have focused primarily on GSM/WCDMA networks since GSM/WCDMA base station identifiers have been relatively static over time. In contrast, CDMA networks change base station identifiers much more frequently, making it harder to build an accurate base station database without carrier involvement. The accuracy of a Cell-ID position will depend on the density of the wireless network. Urban areas will lead to more precise estimates, rural areas to much less precise estimates. Accuracy should be in the 100-5000m range depending on the network density of base stations. However, Cell-ID will at best provide a coarse level estimate of location. (WiMAX networks use a higher frequency than cellular network, requiring denser base stations, resulting in higher accuracy Cell-ID location.)

3rd party WiFi databases have propagated in the last few years. These take advantage of WiFi standard beacons that broadcast both the SSID and MAC address of the access point constantly. The SSID is used to create the list of available WiFi access points seen on many WiFi laptop connections. The MAC address is a unique identifier that can be collected and used to roughly identify where the receiving device is located. Since most WiFi signals propagate a maximum distance of 100-150m, if a WiFi access point is observed, a relatively precise position determination can be made.

Both Cell-ID and WiFi approaches can benefit from observing multiple base stations and incorporating radio strength information to calculate more accurate Cell-ID derived location.

Network Triangulation (signal strength-based)

The majority of positioning determination innovation is occurring in the area of leveraging the RF signal strength of signals received by the device and incorporating network information (known position of base stations). The algorithms range in complexity and depend on the availability of modeled or true RF signal propagation characteristics. RF fingerprinting takes the locations of known base stations, either empirically or analytically calculates the propagation of RF signals, and uses the resulting RF base map and signals received at the device to estimate the device’s position. There are also a number of client-side solutions that are leveraging the availability of multiple cell-ids on the device to more accurately determine device location. RF based approaches are also being incorporated as a fall-back techniques when A-GPS is not available.

Network Triangulation (time-based)

There are some position technologies that make use of signal timing information from the network to make a position determination (vs. GPS which uses timing informationfrom satellites). Time Difference of Arrival (TDOA) and Advanced Forward Link Triangulation (AFLT) are two of the more well known methods. The primary difference in methods is where the timing difference is determined: in-network or on-device.

TDOA was the positioning technology selected by GSM/WCDMA operators in the US for E911 purposes. Unfortunately, the amount of signaling traffic required to make a position estimate is not trivial. This has made the TDOA technology not a viable option for commercial LBS services.

AFLT is a CDMA specific technology that uses the signaling characteristics of a CDMA to make a positioning determination. This acts as a fall-back method for CDMA devices if A-GPS is not successful and the network was requested to make a location determination.

Enhanced Cell-ID is an approach that uses signal strength and timing received from the GSM signal to make an in-network calculation of location which is more accurate than Cell-ID alone. Enhanced Cell-ID also can make use of sector information since many cellular base stations are directional in nature (IE 3 sectors with each sector covering 120 degrees from the base station).

Network triangulation is accurate to 40-400m depending on environmental conditions.

Hybrid approaches

From the descriptions above, it should be clear no one position technology is best for all use cases. The positioning technology market is pursuing hybrid approaches where the strengths of each technique are leveraged where appropriate. Since A-GPS requires a location estimate to start with, other less accurate location technologies can be leveraged to seed the A-GPS algorithm. Each location technique also is more successful in different environments (namely urban vs. rural and in-doors vs. out-doors). Luckily, the strengths and weaknesses of many of these position technologies are complementary, motivating further exploration of hybrid location approaches.

Evaluating Positioning Technologies

After a brief understanding of position determination methodologies, it is valuable to define how each positioning method should be evaluated. A few key categories are listed below and described. There are of course others that could be relevant depending on the location use case. Each position determination technique has strengths and weaknesses across each dimension that will be discussed in the following section.

Positioning Accuracy and Uncertainty

Accuracy will vary depending on environmental conditions (indoors, urban environment, signal quality, etc.). Accuracy can vary from 5-20m (GPS) to 50-5000m+ (Cell-ID). Each positioning technology will also have varying error ranges depending, again, on a broad set of environmental conditions.

Generally, the positioning industry has been driven by GPS chipset manufacturers who are motivated to provide the highest accuracy, lowest uncertainty possible location solution. GPS-level accuracy is necessary for navigation and other turn-by-turn level accuracy user cases. However, there is a wide range of LBS apps that can make do with “lower” levels of accuracy which can be provided by WiFi, Cell-ID or other hybrid approaches. Accuracy is important, but it is only one of the factors that should be considered in weighing available positioning options.

Positioning Latency or Time To First Fix (TTFF)

Positioning latency is a critical factor in driving the usability and responsiveness of a location-aware app. In the mobile app space, acquiring a location quickly is paramount to offering a compelling user experience.

Positioning latency or TTFF is most commonly associated with portable GPS receivers or Personal Navigation Devices (PNDs). Without network assistance, GPS receivers can take on the order of 5-10 minutes before a first fix. This is a function of the time required to lock on to and receive enough information from the GPS satellites in space. Assisted GPS is able to improve this fix time to 10-30 seconds by synthetically seeding the GPS receiver with network data and accelerating the GPS acquisition and position determination process. Assisted GPS still requires data exchange and computation on both a network server and on the device, making it challenging to reduce TTFF further. Other non-GPS based technologies are able to determine a location estimate in below 10 seconds (IE WiFi or Cell-ID were looking up a location in a database is all that is required).

Positioning Determination Ubiquity

A positioning technology is not useful if it is not available in the area where your mobile device is. GPS-based methods have a strong advantage here since it is a globally accessible method and will work even if the mobile device is not associated with a mobile network (there are clear disadvantages in that situation, but it could work). WiFi methods are constrained to areas where there are wireless WiFi Access Points. This is generally not a problem in urban or suburban areas (where most interesting LBS Apps are targeting).

Indoors vs. outdoors is another factor to consider. GPS, generally, does not work well inside buildings. Whereas, WiFi is most likely best suited for indoor positioning determinations.

Positioning Fallback Options

Related to positioning ubiquity and hybrid approaches, devices are expected to make the best location calculation given available information. IE if GPS fails, a network-based method or Cell-ID location is desired to be returned vs. a message of “failed, try again later.” The challenge is since many methods rely on base station databases, the device must optimize how the a LBS App location request is handled. If the network is asked to make the location calculation (IE A-GPS MS-Assist), then all available network information can be used. Hybrid approaches on-device and off-device must take into consideration returning the best known position estimate in a timely manner, even if the preferred method fails.

There are also a number of device-specific dimensions that are critical to keep in mind which drive position determination implementation on device.

Device Impact (battery, CPU drain)

Assisted GPS chip performance has improved considerably over the last few years. However, receiving and processing signals from space still takes a large amount of energy. GPS antenna placement is also critical as more devices add additional RF technologies (WiFi, Bluetooth, additional cellular bands). GPS integration continues to be an important art for device manufacturers.

Most of these positioning technologies involve some level of network data connectivity that can also impact device battery life. There are a number of on-device caching solutions that are evolving for both GPS and WiFi/Cell-ID approaches that minimize the amount of network traffic required to make a position fix. However, given most LBS Apps are making use of network connections, location becomes a limited portion of App traffic.

Device Prevalence / Support

Assisted GPS was adopted by CDMA carriers to support the FCC’s E911 mandate. Qualcomm has added GPS chips to it’s line of core chips. This has enabled CDMA operators worldwide to deploy innovative mobile LBS Apps leveraging A-GPS. The GSM/WCDMA world has been slow in adopting A-GPS, with forecasts of 2009-2010 being the year of broader device support.

WiFi has seen relatively limited support in mobile devices to date. There are a growing set of high-end smart phones that are integrating WiFi and driving the market (namely the Apple iPhone, HTC, Nokia, RIM and others). WiFi could be viewed as a competitor to 3G data services operators are interested in up-selling users with. WiFi also creates additional technical challenges (antenna placement, additional battery draw, etc.) which continue to improve, but remains important considerations for device manufacturers.

Device Location APIs

The availability and accessibility of Location APIs on mobile devices has been spotty at best to date. RIM, Nokia and Motorola iDEN have provided device specific Location APIs that have motivated strong initial interest from developers. The Apple iPhone and Google Android Location APIs will spur additional interest ongoing. Existing J2ME (JSR-179) and BREW (IPOSDET) API exist today for a wide set of feature phones.

However, operator involvement has made it challenging for some developers to gain easy access to location. It is clear device vedors are using location as a competitive differentiator to better position their device platforms relative to others. However, universal Location APIs still remain a challenge with the fragmentation of different APIs, devices and operator policies.

The Other Reason for Warren Buffett's Success

Yes, There Is His Stock-Picking Prowess, But Exclusive Deals Add to Berkshire's Fortunes

• By JASON ZWEIG

Wouldn't it be nice, in this miserable market, to be Warren Buffett? Fortunately, a cottage industry has sprung up to teach investors how to emulate the master. Unfortunately, you might as well try to catch a bolt of lightning in a paper cup.

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Heath Hinegardner

Should you be like Warren Buffett?

For the first two decades of his career, Mr. Buffett built the bulk of his fortune through his investing prowess, producing one of the best long-term track records of any money manager in history. More recently, however, Mr. Buffett has succeeded not through investing prowess alone, but also through exclusive deals that have come to him because of it.

Only a part of Mr. Buffett's market-beating performance has come from stock-picking. Even more of his edge has been generated by the operating subsidiaries of his Berkshire Hathaway Inc., like Benjamin Moore paint and Geico insurance. "There's no question about it," Mr. Buffett told me during the week. "Certainly over the last decade at least," the earnings of Berkshire's operating businesses "have grown at a much faster rate than the [value of the] marketable securities per share."

It is a lot harder than it used to be to measure just how good a stock-picker Mr. Buffett is. When I asked him if he knew how well Berkshire's stock portfolio has done in recent years, he answered: "I've no idea what the rate of return would be. But, knowing myself how hard it would be to do the calculations right, I'm suspicious of anybody's numbers."

An outsider, then, can barely get in the ballpark. Since the end of 1988, Berkshire's stock portfolio has grown from $3.56 billion to $69.51 billion. That is a spectacular average annual increase of 16.5%, far surpassing the 10.5% annualized return of the Standard & Poor's 500-stock index. Of course, this calculation is only a crude approximation, since it ignores the cash that Mr. Buffett added in -- and moved out -- along the way.

Over the same period, the growth in Berkshire's book value per share, which reflects all of Mr. Buffett's activities, not just his stock-picking, was 19.9%.

In other words, Mr. Buffett's skill at picking publicly traded stocks pales alongside the value he has added to the company through other means.

As recently as 1995, 73.5% of Berkshire's total assets consisted of a portfolio of publicly traded stocks that (at least in theory) any investor could have replicated. As of June 30, though, Berkshire's stockholdings made up just 25% of its total assets.

Mr. Buffett's stock picks used to drive the train; lately, they are more like the caboose. He has been buying private firms outright and landing "sweetheart" deals in public companies.

Since the beginning of 2006, Berkshire has spent nearly $17 billion buying private companies lock, stock and barrel, including an Israeli cutting-tool maker and a distributor of electronic components.

Meanwhile, on the sweetheart front, in 2008 alone Mr. Buffett has sunk $5 billion into Goldman Sachs Group , $3 billion into General Electric Co., $3 billion into Dow Chemical Co. and $6.5 billion into the merger of Mars Inc. with Wm. Wrigley Jr. Co. -- all with preferential terms.

Twenty years ago, Mr. Buffett struck similar bargains with companies whose quality ranged from purebred Gillette to mutts like Champion International, Salomon Brothers and USAir Group. His results were mixed. The lesson here is that even Mr. Buffett learns lessons. In his latest round of sweetheart deals, he gets a generous upside and virtually eliminates any downside, a "heads I win, tails I win" structure that other investors can only dream about.

Whether he buys stocks in what he calls the "auction market" or private businesses in the "negotiated market," Mr. Buffett tries to secure a margin of safety. That term, defined by his mentor Benjamin Graham, means that the price is so far below a business's underlying value that severe loss is improbable.

"We do try to buy our businesses like we buy our stocks," Mr. Buffett told me, "and buy our stocks like we buy our businesses." By that he means, among other things, that he wants to understand how the enterprise generates cash, how well-managed it is and whether its customers would stay loyal even if it raised the prices of its goods or services. Note carefully: None of these factors are contingent on the current price of the stock.

"Being a businessman makes me a better investor and being an investor makes me a better businessman," Mr. Buffett explained. "Most businessmen limit themselves to their own field, and most investors don't really think about businesses. And many businessmen are semi-oblivious to the yardsticks other people use outside that field. I'm always comparing everything to everything else. The question I want to answer is. 'Where do we get the most for our money in something we can understand?'"

"I prefer, and [Berkshire Vice Chairman] Charlie [Munger] prefers, the permanent ownership of [private] businesses," Mr. Buffett added. "That's been my focus for well over 20 years. But it's just that sometimes, marketable securities are so much more compelling." Mr. Buffett didn't say whether he thinks now is one of those times, but he did state publicly earlier this month that "I've been buying American stocks."

Any investor who picks stocks can try to think like Mr. Buffett and, as he pointed out, "the individual actually has an advantage over us, because their costs of buying and selling [stocks] are a helluva lot less than ours." But that advantage applies only if you actually can think like Mr. Buffett. Above all, there is much more to his success than stock-picking alone. Throughout Mr. Buffett's long career, he has changed tack repeatedly. At this point, he is on a course most investors will no longer be able to follow.