A fun article appeared today on Silicon Alley Insider:

Silicon Alley Insider: What’s It Like Working for LinkedIn by Nicholas Carlson

It’s a short piece that covers the basics of working for a hyper-growth, late stage web 2.0 startup.  The piece begins with the following:

During a recent trip out to the Bay Area, we swung by the LinkedIn world headquarters.

We learned that LinkedIn may be the “serious” social network, but the people behind the site know how to have fun.

They wear gorilla suits to the office. They play frisbee golf around cubicles. Sometimes, they build robots modeled after each other.

Sounds like fun, right?  The article has a 24-slide series of photos to illustrate the trip.   The slide show is called:

LinkedIn is Made by Robots and Men in Gorilla Suits

It turns out that I am, in fact, the Man in the Gorilla Suit.

On Slide 17, you see a picture of the large stuffed gorilla that sits next to me at work:

I asked Kay, “what’s with the stuffed bear?” Her answer: “Get your facts right, it’s a stuffed gorilla. Sheesh.” It belongs to VP Adam Nash…

On the next slide, they provide the snapshot from the FAQ page on the company store, where I’m posing in gorilla suit, wearing a LinkedIn t-shirt:

…who is sometimes known to wear a gorilla suit around the office.

As my brother would say, “It’s funny because it’s true.”

It turns out that the Gorilla suit is just about my favorite Halloween costume.  Originally an eBay purchase in 2005, I wear it every year to the office.

So now you know.

It has been quite a long time since I posted here about eBay.  I still use the site regularly (I typically still list at least a few things every month), and while I may tweet about things from time to time, I rarely feel the need for a full blog post.

On January 21st, Ikai Lan (@ikai) posted this tweet:

What’s the big deal, right?  So what if Ikai found a better deal on Amazon for his Star Trek geekfest?

Here’s the big deal. This was my response to Ikai:

The issue here isn’t that I was somewhat obnoxious (although clearly, I was a bit obnoxious).  Ikai & I worked together at LinkedIn, so it’s not unexpected to have a little bit of fun with the back & forth on Twitter.

The problem is that Ikai is a smart, technical guy.  He’s also someone who looks for a good deal.  If someone like Ikai thinks that Amazon has a cheaper price on an item like the complete DVD collection for Star Trek DS9, then eBay has a real problem.

eBay’s Value Problem

When I wrote my Eulogy for eBay Express in 2008, I talked about four key value propositions that eBay navigates: value, selection, trust and convenience.  One of the motivating factors behind eBay Express was trying to find a way to leverage eBay’s huge advantages in value and selection, while shoring up perceived weaknesses in trust and convenience.

But here we are in 2010, and while eBay has the item, apples-to-apples, for over $100 less than Amazon.com – Ikai didn’t know it.  And you know what?  If a low price falls in the forest and no one is around to hear it, it doesn’t make a sound… or a sale.

eBay’s Value Problem is actually a Search Problem

The point is, despite the fact that Ikai is an engineer working at Google, he couldn’t find the item.  So a $115 price advantage was nullified.   Why?

I’m not a 100% sure what Ikai did to identify the proposed “$350 price”.  When I searched on eBay, I found literally dozens of items priced below $300, many of which were from top sellers, and many of which that offered returns.  In fact, I saw items as low as $130, but I tried to find the lowest priced item that matched the quality of service Ikai would expect from an Amazon third party seller.

Of course, I’ve been on eBay since 1998, and I spent years working on structured data and search products at eBay, so I have a hunch why I found the items and he didn’t.

He typed the wrong query. My guess is that he typed something like this “Star Trek DS9 season 1-7” in the DVD category.  Makes sense, right?  Unfortunately, this only returns two items, the cheapest of which is $299.

Despite years of investment, the eBay search engine still doesn’t understand that “DS9 = Deep Space Nine”, and that “1-7″ is a range, and that “season” is an attribute that DVD sets for television series can have.

Now, what I did do?  Simple:

1. I typed the query “deep space (nine, 9)”
2. I selected the category for DVD
3. I selected “Buy It Now” for listing type
4. I sorted from highest price to lowest

Let’s review the tricks I used:

1. The () notation is how the eBay search engine does OR.  So I was able to find listings with both “nine” and “9″ in them.  To be fancy, I could have used “DS9″ in there too, but it wasn’t necessary.
2. Filter to DVD category to clean out other clutter.
3. I figured Ikai didn’t want to bid on an auction
4. Sorting from high to low is a counter-intuitive trick, but if you assume that the collection will be more expensive than individual DVDs, it makes sense.  I use this all the time with high priced items, since quality tends to float to the top.

I then scanned down the list to find the cheapest collection sold by a credible seller (someone with high feedback and % satisfaction).  And then I tweeted it to Ikai.

Would anyone else know how to do this? Would anyone else want to do this?

I do it, largely because I still love eBay, and because I actually know how to do it.  Plus, I really appreciate saving money on items like this, so the $115 is worth a few minutes.

But all I know is that if eBay can’t leverage it’s intrinsic price advantage with buyers like Ikai, then it has a serious problem.  They can never beat Amazon or traditional retailer e-commerce sites on trust and convenience.  They can, however, beat them on price and selection.

But customers have to be able to find those advantages to value them.

The incredible (and somewhat predictable) success of Avatar at the box office (and the Golden Globes) has everyone talking about a sequel to Avatar.  In fact, this quote from James Cameron suggests a trilogy:

To some it’s a mashup of “Dancing With Wolves” and “Ferngully: The Last Rainforest.” But James Cameron’s “Avatar” has stormed the international box office with a global taking of more than $1.6 billion and may very well be on its way for a sequel … or two.

“I have a trilogy-scaled arc of story right now,” Cameron told MTV. “But I haven’t really put any serious work into writing a script.”

Avatar is highly derivative of other stories and science fiction, and as an avid reader of the genre, I thought I could take a crack at a potential, obvious premise for the backstory of Avatar 2.

Premise: It’s five years after the first movie.  There has been peace on Pandora, as Sully and Neytiri have ushered in a new age of cooperation and understanding between the tribes of the Na’vi.  The humans have been evacuated, with the exception of a small set of scientists who have been given permission to continue their efforts to bridge the learning and knowledge of the two cultures.

However, there have been unusual occurrences on the planet.  The behavior of the flora and fauna on Pandora has been unpredictable, confusing Neytiri who utters more than once that “this has never happened before”.   Modifications of some species begin to appear, as well as completely unknown species are discovered.  The scientists can’t explain it, and Sully tries more than once to communicate with Eywa, with no answers.

Silently, a massive human invasion fleet is on its way to Pandora.  The resources of Pandora are too valuable, and once the Na’vi attacked the corporation, it justified a larger military involvement at 100x the scale of the original movie.

It turns out, however, that the biology of Pandora was too idealistic to have naturally evolved.  After all, every creature sharing a common communication link is incredibly unlikely.  10 foot humanoids with carbon fiber skeletal structures also seems a little far fetched.  It turns out that Pandora is a very special planet, because it’s entire eco-system of creatures was engineered by an advanced race.  That race left Eywa, a massively parallel organic computer, in place, dormant, to monitor the situation and ensure that Pandora progressed as planned.

When Eywa awoke, it began taking emergency measures to modify and enhance existing species against the potential threat.  And it sent an interstellar signal to its creators, to let them know that all was not well with Pandora.  That’s right.  The creators are coming…

… there.  That’s enough for Avatar 2.  Avatar 3 can then focus on what the master plan of the creator race was after all, when the Pandora experiment goes awry.

Given the evolution of the Aliens story (also by James Cameron), I actually think this is a plausible direction.  There is a parallel between the plot surrounding a single ship facing one alien in the first movie, and a massive military engagement with a massive alien force (and new creatures) in the second movie.

Please note: I have absolutely no data whatsoever about the actual direction of Avatar 2.  This is just speculation on my part, as a science fiction lover.  Any reflection of the real plot or premise for Avatar 2 is purely coincidental.

So I take the time to create a whole new post for Café World in 2010, and what does Zynga do?  They roll out some new crazy dishes based on an alien invasion, and now I’m 1.6M Café coins poorer.  Oh well.

Since I’ve written three previous articles on the topic:

• Café World Economics: Profit & Café Points
• Café World Economics: Updated Tables
• Café World Economics: Real World Hourly Wages
• Café World Economics: Profit & Café Points (2010 Edition)

I find it fairly interesting that Zynga is clearly mapping the same thematic variants from Farmville to their other games.  I remember when they did the space theme for Farmville (I still have 5 alien cows that produce Milktonium as proof…)

I won’t repeat the previous analysis. As a reminder, all of these numbers assume:

• The numbers are per dish, per stove
• The numbers assume the cost (15 coins) and experience (+1) of cleaning the stove each cycle
• Profit & Cafe Points tables assume “instant” cleaning time.
• Real World Hourly Wages assumes a cleaning time of 1 minute per stove.

You can read my previous posts for the rational behind these assumptions.

Profit per Dish

Here are the dishes, sorted by profitability as measured by profit per dish per day.

Café Points per Dish

Here are the dishes, sorted by café points per dish per day.

Real World Hourly Wage per Dish

Here are the dishes, sorted by the real world hourly wage for each dish per day, in US dollars.

Special Bonus: I’ve now moved my spreadsheet over to this Google Spreadsheet.  Now you can see all the rows of calculation for some insight into Café World Economics.  As usual, let me know if you find mistakes or have questions…

What better way to spend the waning hours of the first day of the new decade than to update all of the tables for the new dishes on Café World?  Zynga has added a number of new dishes over the past few weeks, so it’s about time for updated data on all the dishes.

Since I’ve written three previous articles on the topic:

• Café World Economics: Profit & Café Points
• Café World Economics: Updated Tables
• Café World Economics: Real World Hourly Wages

I won’t repeat the previous analysis.  As a reminder, all of these numbers assume:

• The numbers are per dish, per stove
• The numbers assume the cost (15 coins) and experience (+1) of cleaning the stove each cycle
• Profit & Cafe Points tables assume “instant” cleaning time.
• Real World Hourly Wages assumes a cleaning time of 1 minute per stove.

You can read my previous posts for the rational behind these assumptions.

How to use these tables. For me, I use the tables as follows:  If I know I won’t be able to check on my Café for the next 24 hours, I go down the table I’m trying to optimize for (money or experience) and I look for the first dish in the list that is 1440 minutes AND that I have enough experience to cook.  For example, I’m currently at level 42, so if I’m looking for a “1 day” dish, the first one for experience is Grand Tandoori Chicken.  But since I can’t buy that yet, I have to keep going down until I hit King Crab Bisque.

Table #1:  Profit per dish

Table #2: Café Points per dish

Table #3: Real World Hourly Wages per dish

Once again, a thank you to Simple Think, which continues to have the most up-to-date raw data on Café World dishes at all levels…

Update: I’ve now posted additional articles on Café World Economics:

• Café World Economics: Alien Invasion & Google Docs

Just a quick note to say that the new version of LinkedIn for iPhone is now live in the iTunes App Store.

Download LinkedIn for iPhone

I wrote a fairly lengthy piece on the official LinkedIn blog, so no need to replicate the full walk-through here.  In any case, check out this new home screen:

This application represents a huge achievement for the team.  It’s really a complete redesign and re-architecture of the entire stack supporting the application, based on an end-to-end design that was driven by user feedback and business metrics.

Building iPhone apps is a wonderful throwback in some ways to the days of client software, except with the advantage of over a decade and a half of web-based architectures.  There is a richness to client applications that the web still doesn’t replicate, and a complexity and depth to their design that is often under-appreciated.

Of course, the team had fun too.  The “Themes” feature, for example, was never part of the original plan.  It was originally a last minute easter egg that we included for fun in internal testing.  It proved so popular, however, we felt like we had to include it for everyone.

There are hundreds of things I love about this new application.  Even the way it presents a user’s profile is thoughtful, as LinkedIn is designed to allow you to put your best foot forward as a professional:

Of course, I wouldn’t be a product manager if I didn’t also have hundreds of things I’d like to see improved in the application.  It has been fun to watch the Twitter stream all day, as the feedback has been mostly positive.  Still, while this application represents a big leap forward for LinkedIn on the iPhone, it’s really just a beginning.  What’s most exciting about the architecture of this application is that it will let us rapidly innovate and improve the mobile experience through 2010 and beyond.

So here’s a quick shout out to the team – thank you for the hard work and effort in 2009 to produce an iPhone app we can be proud of.   I couldn’t be more excited for 2010, as we change the way people think of mobile business applications.

The traffic to my blog from my first two Fishville blog posts has been staggering. How can I resist? That’s right, it’s time for Yet Another Fishville Post (YAFP). Come on, you know you want to read more…

I’ve been a little surprised to see how few accurate blog posts exist out on the web that break down the profit & experience for Fishville.  For reference you can still find my first two blogs posts here:

• Fishville Economics: Points, Experience & Levels
• Fishville Economics: Points, Experience & Levels Part 2

Fortunately, I have found at least one new useful resource:

• The Fishville Wiki (on wikia)

I’m at Level 42 in Fishville, so I can get almost all of the data myself.  However, I’m still missing the data for the last two fish:

• Blueline Trigger
• Longhorn Clownfish

If you have the data on either of these two fish, please post here in the comments.

In the past few weeks, Zynga has rolled out a number of new fish.  I’ve updated my Google Doc with all the updated numbers.

The most interesting addition has been a series of fish that you can only purchase with Sand Dollars, which is the Fishville denomination for game money that you have to buy with real money.

This poses a dilemma for my calculations, since I base profitability on coins spent to coins earned.  As a result, I needed a conversion ratio from Sand Dollars to Coins.  Although you can’t buy Sand Dollars with Coins, you can buy both with real US dollars ($) from Zynga with a scaling price table:

Notice anything strange?

According to this table, the ratio of coins to sand dollars varies between 300 and 287, and in a non-linear fashion.  It’s as if Zynga didn’t compare the volume discount on coins to the volume discount to sand dollars when they generated these prices.

Since it’s non-linear, I decided to take the “average” ratio as my conversion.  So, for the purposes of this blog post, one sand dollar = 292.75 coins.

Using that ratio, I was able to regenerate my graphs.  Here is the graph showing profitability of each fish, per level.  All the assumptions from my second blog post still hold:

What you’ll notice is that some of the “sand dollar” fish are actually money losers for the first two levels.  That’s right, assuming my conversion ratio, you’d be better off just buying coins with your money, rather than buying sand dollars and then growing these fish!

Now, the updated experience points chart tells a different tale:

In this case, you can clearly see that the best fish for experience, excluding the “fast fish”, are the sand dollar fish.  As a result, it’s pretty clear that what you are buying with your sand dollars is a fast path to rise up levels.  If you’re willing to spend the money on Batfish, you’ll be able to climb those levels quickly, and with much less work than minding 5 minute fish…

You can reference the full data in my Google Doc.  Let me know if you see any issues with the calculations.

For reference, I’ll include the Level 1 tables here, just in case there are issues reading the now huge Google Doc.

Profit per Fish when you harvest at Level 1:

Experience per Fish when you harvest at Level 1:

Enjoy.  Happy Holidays.

I apologize for the reference to Spinal Tap, but this is my personal blog after all.

I normally don’t post most LinkedIn announcements here, but this one is too big to ignore.

On Monday, LinkedIn made faceted search available to all members.  This effort brought to fruition efforts that date back to 2007 to completely rearchitect and redesign the LinkedIn search experience based on the unique characteristics of people search.

Rather than try to describe the feature here, I’ll just point to the formal LinkedIn blog post by Esteban Kozak, and embed his great youtube video on the feature:

The news coverage has been flattering:

• Mashable: Facebook Could Learn a Thing or Two from LinkedIn’s Faceted Search

What’s most exciting to me, however, is that these are still very early days in the development of the LinkedIn search platform.  It took LinkedIn over five years to amass its first billion queries.  This year alone, LinkedIn will exceed that number by a wide margin.  People search requires unique investments in structured data, relationship information, search intelligence, and personalized relevance.  (If you’re curious, the Boolean Black Belt got a sneak peak at some upcoming features).

I just wanted to take a moment to say kudos to the entire search team for this tremendous achievement that cuts across all areas – product, design, research, web development, engineering, marketing & operations.

Twitter integration, Open developer program, Faceted Search.  What a great way to launch into the holidays.

Can’t wait for January

This past week, the US Mint sold out of the one ounce 2009 Proof Platinum Eagle.  As no bullion coins or fractional sizes were minted this year, it was the only US Platinum coin produced in 2009.

From CoinNews.net:

Released at Noon Eastern on Thursday, December 3, 2009, the Platinum Eagles were limited to a mintage of only 8,000. Over 7,200 of those sold in the first few days, even with a household order limit of 5 pieces in place. The US Mint sold just 4,769 of the one ounce proof coins during all of last year.

Some had theorized that this year’s run would be challenged by the high price of the coin ($1792.00) and the relatively unpopular new design.  However, given the huge demand for precious metals this year for investment (gold, silver, platinum, palladium), it’s hard to be completely surprised that this coin sold out so quickly.

Nope.  2008 the US Mint only sold 4,769 coins.  This year, they sell out early at 8000 coins.

The case for buying platinum right now is fairly strong:

• The relative price of platinum to gold is extremely low, given gold’s huge run up.  A few years ago, platinum cost over 3x an equivalent amount of gold.  At current prices, the two metals are approaching parity.
• Simple investment vehicles in Platinum and Palladium, like ETFs, do exist (they trade in London), but don’t have popular US versions (yet), so investment demand remains weak compared to it’s ETF-rich brethren of gold (GLD) and silver (SLV).
• The automotive industry, which is the largest consumer of platinum and palladium, is extremely depressed.  However, since the demand for fuel efficient cars is growing, the use of these metals in catalytic converters and fuel cells seems to forecast significant future demand when the industry recovers.

That being said, I was surprised when I searched eBay for completed listings for the 2009 Platinum Eagle.  Normally, when there is a sell out at the US Mint, you immediately see panic buying on eBay for huge premiums over the US Mint price.

Here is the query.  What you see is that, as of December 12, the prices range from $1727 to $2050, hardly a premium given the transaction costs of eBay / PayPal which can easily run 8-9%.

As a result, I have to wonder:

• Was the sell out the product of true individual demand for the coin?  Or was this a case of coin dealers speculating on a sell out and premium collectible opportunity?

The problem with the Platinum Eagle series is that it’s unclear how many collectors actually try to build “the complete set” of these expensive coins.  Set building is typically the primary driver for premium values for the silver and gold eagle series.

I’ll be watching the completed auctions closely this coming week.  There are a couple sellers already experimenting with higher prices.  Let’s see if they stick.

I’ve been distracted by Fishville lately, but the Zynga team has been busy rolling out new dishes for Café World, so I thought it was time for a new post on Café World Economics.

This post is the third in the Café World Economics series:

• Café World Economics: Profit & Cafe Points
• Café World Economics: Updated Tables

But before I get to the new tables, I did some additional analysis based on my popular Farmville post, “The Personal Economics of Farmville“.  I’ve produced a table that ranks all the Café World dishes based on the equivalent US $ / hour wage you are valuing your real world time when you play the game.

In order to do this, I needed to find some additional data.  The first was an effective value of Café World coins.  To do this, I used the payment schedule that Zynga has in the game (as of 11/30/2009):

Note the wide disparity in values!  If you pay the bare minimum ($4.99), you are valuing Café World coins at 3062.12 per dollar.  But if you pay at the high end ($49.99), you get 6667.33 coins per dollar.

Since there is such a wide disparity of values, I decided to calculate both a high and a low estimate for my table.

The second new piece of data needed was the “time spent per dish“.  This is something that I left out of my initial calculations, but makes sense in this context.

Since all of my tables are “per dish per stove per day”, I estimated that you need to spend one (1) minute per cycle to clean the stove, buy the dish, and click through the 3 ingredients, and then get the finished dish.  This might be a tad high, but it’s in the right ballpark.

What this means is that a dish that takes 5 minutes to cook is now estimated to have a cycle time of 6 minutes, with 1 minute of “real world time” spent.  So, 1440 / 6 = 240, which means to cook a 5 minute dish all day you’d need to cook 240 cycles, which implies a sign up for 240 minutes of “real world time”.

This allowed me to do the simple algebra to weigh the profit per dish per day, in Café World coins, and then subtract the real world time, and figure out the effective “hourly wage” of each dish.

As it turns out, whether you use the high value or low value for coins, the sort order is the same.  Here are all Café World dishes, sorted by “hourly wage”:

Now, these figures are a little misleading, because the dishes that result in high profit (like the Impossible Quiche) and that have long cycle times result in very low amounts of real world time. As a result, if you can make $2 in a minute, you effectively get $120/hour. Still, it makes a point. If you are trying to minimize time spent in Café World for maximum profit, this is a pretty good list to go by.

First thing you’ll notice, is that Chips & Guacamole may build your Café World coin stash, but they are not valuing your time very highly.  In fact, you have to get to Kung Pao Stir Fry to break above the living wage in California, at the low valuation for coins.

However, it also shows that the economics of these coin values are unsustainable. If Zynga allowed people to convert coins to US $ at these rates, then the value of opening up 50 Facebook accounts and cooking Impossible Quiche all day would beat most jobs.  ($200/hour = approx $400K per year!)

Just one of the interesting things you find when you crunch the numbers.

For those of you looking for updated tables with the new dishes, see below.

Café World dishes, sorted by profit per dish per day:

Café World dishes, sorted by Café World points per dish per day:

Enjoy.

Update: I’ve now published updated information on Cafe World Economics.

• Café World Economics: Profit & Café Points (2010 Edition)
• Café World Economics: Alien Invasion & Google Docs

Only a long time Quicken user will empathize with the trauma of having your Quicken data file fail to open.  It happened to me this weekend, and after a couple days of experiments, I finally solved the problem.  I’m posting this here on the blog because my Google searches on the topic turned up *nothing*, and the Intuit boards were useless on this topic.

First, background:

• I’m using Quicken 2007 for the Mac, updated with the R2 updater and the R3 Certificate updater.  This is the most recent version.
• I’ve used Quicken since 1994 to keep track of my expenses and investments.  That’s right, this file has 15 years of meticulous data in it.
• Quicken for the Mac users at some level are masochists.  Circa-2000, Intuit decided that the Mac market wasn’t worth supporting, and effectively ended support for the product.  As Steve Jobs brought the Mac back, Intuit brought back support… but very little enhancement to the product.  Quicken 2007 is largely the same as the Quicken 1999 product, except far more rickety and long in the tooth.

OK, so here’s the story:

1. About 3-5 weeks ago, when downloading stock quotes, I got a very strange error.  It said something like “Unable to create INTC. Security already exists.”  (Of course it exists, I’ve been tracking INTC for more than 10 years…)
2. About 2 weeks ago, I quit and relaunched Quicken for some reason (my machine tends to stay up for weeks at a time.)  On relaunch, all of my “manually entered” stock quotes were gone.  After a brief panic, I restored a file from Time Machine from a week prior, and all was forgotten.
3. Periodically, I received that error when downloading stock quotes.
4. On Friday, I restarted Quicken and got a spinning beach ball.  I thought it hung, so I force quit it, and restarted.  Spinning beach ball.
5. No worries, right?  I have multiple backups.  I use Time Machine to get an older file.  I launch. Spinning beach ball.
6. Uh oh. Mild panic.  I tweet.  No one tweets back.
7. I go to the “Quicken Backup Folder”, which is created automatically in your Documents folder.  I select several of the backups, duplicate them, and try to launch them.
8. Good news, the file from November 12 actually works, but all security prices are missing.
9. Bad news, it’s missing two weeks of data!  A lot of manual re-entry of the last two weeks.  Not too bad though.
10. On Saturday, I quit Quicken and relaunch as part of a reboot.  Spinning beach ball.
11. Uh oh. Time Machine backups don’t work.  I tried five of them from the last three weeks.
12. Double Uh Oh. The only file that seems to work is that one from November 12.  But it gives me an error “Unable to save security”.  It works, but is missing all security prices. But it’s missing the two weeks of transactions.
13. A bit of panic here. I search Intuit boards.  No luck.  I post a question anyway, even though the community on the boards gives me no confidence of ability to help or desire to do so.
14. I delete Quicken 2007 and all preference files, and try to reinstall + updaters.  No luck.
15. Tweets return nothing, except strange semi-taunts like, “I hate Quicken too.”
16. Finally, I realize I may have to create a new file, then export/import all the transactions to create a new clean file.  Creating the file works.  Trying to export QIF and reimport into the new file leaves totally bizarre numbers and transactions.  Seriously, has QIF export ever worked in the past two decades?  Will it ever work?
17. Desperation.  I start seriously contemplating doing all my finances in Mint… except Mint doesn’t actually support managing accounts without online access that well.  I like Mint, but I use it differently than Quicken…
18. Hail Mary. The Quicken file isn’t really a file, it’s a Mac OS Package.  It’s a fancy name for a directory of files that is tagged to act like a single file for the Finder.  Looking inside, I find a data file for “Quotes” and a directory for “Quotes Details”.  I delete both.
19. Salvation.  I launch Quicken.  No beach ball.  Works beautifully.   All stock quotes are gone, but a quick click to download quotes fixes that.  I manually re-enter the few securities that don’t have ticker symbols.  Everything is wonderful again.

So, just to capture some trouble-shooting for you, here is what I saw:

• Launching Quicken with the corrupted file led to a spinning beach ball for over 30 minutes
• When it did finally load, it gave me an error “Unable to open file”
• There was a history of getting errors related to the downloaded stock quotes for securities

Solution was:

• Make a duplicate of your Quicken file (always, always have a clean backup)
• Right-click (or control-click) on the Quicken file.
• Select “Show Package Contents…” from the Finder.
• Double-Click on the “Contents Folder”
• Select the “Quotes” file and the “Quotes Details” folder
• Drag them to the trash, and empty trash
• Relaunch Quicken with the file

Thus, I am still a Quicken user, at least for a little while longer.  Intuit, if you are reading, please get Quicken 2010 (which has been promised for two years) out the door.  And make sure the import from Quicken 2007 files is *flawless*.

The traffic to my blog from my first Fishville post has been staggering.  How can I resist?  That’s right, it’s time for Yet Another Fishville Post (YAFP).  Come on, you know you want to read more…

I’ve been a little surprised to see how few accurate blog posts exist out on the web that break down the profit & experience for Fishville.  Based on comments to my original post, I made some mistakes.  As a result, I’m posting this follow up to help address the most common concerns:

• What about Level 5 (and 6 and 7…). I classify my charts based on the completion of levels, which is a little confusing because in Fishville, your fish is “Level 1″ until it completes the level, and then it is Level 2, etc.  As a result, you don’t get the “Level 1″ experience until your fish reaches Level 2.  Confusing.  Even more confusing, after completing Level 4, your fish can continue to go up levels… it just won’t be worth anything more.  As a result, I ignore all levels above 4.
• Why doesn’t my experience number match yours? It’s because I’m including the experience you get from dropping the egg in the tank, not just the experience you get from harvesting.
• Level 4 doesn’t take the same time as the other levels. Oops.  This is correct.  I still don’t have accurate info on whether the “Level 4″ time is the same for all fish (2 days) or different.  For this post, I use the 2 day number, which changes the economics considerably.  (Hint: It’s not worth your time to ever let this happen)
• Can you post a Google Doc of all your tables & charts? See the end of this post.  First time for everything.

To recap, here are the assumptions for my tables & charts:

1. I assume harvesting & buying fish is instantaneous. Yes, I know its not.  Fodder for a future post.
2. All profits are calculated per fish. Same with experience
3. Total Experience = Experience from dropping egg + Experience from the level(s) of growth
4. Total Profit = Revenue from harvesting the fist – Cost of the egg

In my last post, I described how your “profit per minute” increases with levels, but your “experience per minute” falls with levels.  A lot of people didn’t understand this, so I decided to try some charts to illustrate.

Here is a chart I made in Google Docs showing the effect of increasing levels on Profit / Minute.  Because there is a fixed cost to buying a new fish, the linear increase in profit per level helps your profit / minute.  Of course, it falls off a cliff once you hit Level 4, and it takes up to 2 days to complete.

This means that, from a profit per minute perspective, it’s better to let your fish grow to complete Level 1, Level 2, and Level 3 before harvesting.

But there is a catch.  Because you get XP every time to buy an egg, the effect on experience points per minute is the opposite.  Every level you go, your experience points per minute drops!  See this chart to visualize:

Based on the comments to my original blog post, it’s very obvious that most players continue to ignore the experience points you get for dropping an egg in your tank – choosing instead to focus only on the experience points you get when you harvest the fish.  Big mistake, because this leads you to keep fish around too long.

Since my last post, I’ve also been able to complete my tables for all current fish.

Here is the profit table for Level 1 profits:

Here is the experience table for Level 1 experience.  Note that I included the experience you get for dropping the egg, as well as the total experience you get for completing level 1.  Remember, Total = Dropping Egg + Level XP:

As promised, here is a link to the Google Doc with all my tables and charts.  Please post additional info, corrections, or data in the comments below.

Updates:  I’ve now posted additional columns on Fishville:

• Fishville Economics: Points, Experience & Levels Part 3

My Zynga addiction clearly knows no bounds.  Last week, Zynga launched a new game called Fishville, and clearly at this point I have no ability to resist any new Zynga game.

Fishville has a deceptively simple frame:  you have a fish tank, and you buy fish eggs for it.  The fish hatch, you feed them, and then when they are fully grown, you sell them for profit.

What I’ve found most interesting about the game is the new dimensions they are exploring in the economics of the game.  Fishville adds a couple distinguishing twists versus Farmville or Café World:

1. Multiple Tanks. How many people wish they had more than one farm in Farmville?  In Fishville, Zynga has two types of expansion – the ability to put more fish in a single tank and the ability to buy new tanks.  This may not seem relevant from a structural standpoint – after all whether you add 20 fish to one tank or 10 to 2 tanks shouldn’t matter – but it should create a new dynamic around buying virtual goods to decorate different tanks.
2. Harvest Levels. This is the real twist to the economics.  Fish grow up in stages, up to four levels.  The revenue in coins and the experience you get goes up linearly with each level.  So if you have a 4 hour fish, you can harvest them at 4 hours at Level 1, or 16 hours at Level 4.  You still have to feed them or they die (similar to withering crops in Farmville), but you don’t need to “replant”.

The Harvest Levels have the most impact on the game economics.  In financial terms, each fish now has a fixed cost and a variable cost, as well as a fixed experience pay-off and variable experience pay-off.

For example, let’s take the Mini Dart Goby, the first fish.

The Goby costs 7 coins for an egg.  That’s a fixed cost.  If you grow it to Level 1, you’ll get 18 coins, for a profit of 11 coins.  Easy, right?  Hold on.  If you wait until Level 4, you’ll get 72 coins over that same 7 coin cost, for a profit of 65 coins.

The fixed cost means that your “profitability” or “profit / minute” goes up the longer you wait to harvest.

Seems like a no-brainer to wait until Level 4?  Not so fast.

With Experience Points, the math works in reverse.

The Mini Dart Goby gives you 2 XP for dropping the egg.  At Level 1, you’ll get 8 XP, for a total of 10 XP.  But if you wait until Level 4, you’ll get 32 XP, for a total of 34 XP of the time period.  In this case, your “XP / Minute” goes down the longer you wait to harvest.

It gets even harder.

You can harvest a fish in-between levels… but you don’t get any credit for the time between levels.  So if you are half-way between levels, your “profit / minute” and “experience / minute” will be terrible.  In fact, the math says you need to harvest at level boundaries pretty closely.  (I think in a future blog post, I’ll graph this.)

For now, here are some tables I’ve made for the fish I have data on.  Unfortunately, this game is so new, I can’t find any guides online with data for all fish.  Special thanks to Erin Hoffmann, who serves as both data provider and my toughest competitor in Fishville.

The most interesting aspect to these tables is that while the profitability / minute rises for each level, Zynga has kept the fixed costs proportional enough that the ranking of the fish does not change significantly between 1 level or 4 levels.

Here is the profitability of different fish at Level 1:

Here is the profitability of different fish at Level 4:

Here is the experience productivity of different fish at Level 1:

Here is the experience productivity of different fish at Level 4:

If you’d like to help, I’m missing data for the following fish:

• Blue Damsel
• Inland Silverside
• Pajama Cardinal
• Longnose Hawkfish
• Annularis Angelfish
• Blue Spot Grouper
• Blue Hippo Tang
• Bartlett Anthias

For each, please leave a comment with:

• XP / Egg
• Revenue / Level
• XP / Level
• Minutes / Level

Hope this helps the new Fishville players out there.  Enjoy.

Update (11/14/2009): New blog post coming tomorrow, with updated tables and new info.  Also, fixing the issue around the whole “Level 4/Adult” confusion, and publishing a Google Doc to help others benefit from the raw data.  I’m still finding that people are ignoring the XP from the dropping of the egg, and only focusing on the XP from harvesting, so I’ll update tables to make that more clear.

Updates:  I’ve now posted additional columns on Fishville:

• Fishville Economics: Points, Experience & Levels Part 2
• Fishville Economics: Points, Experience & Levels Part 3

I really haven’t had enough time to write the second post I had been planning on Buzz measurements and the profitability by unit time of different dishes.  So, instead, this week I’m posting updated tables for some of the new dishes that Zynga has rolled out.  (Still looking for an accurate breakdown of CP for Impossible Quiche, BTW.  I’m only at Level 25 myself…)

This is the second post in my Café World Economics series.  The first one is here:

• Café World Economics: Profit & Café Points

Here are my Café World tables, updated for the three new dishes Zynga rolled out last week.

First, the table of dishes, sorted by total profit per day:

Here is the second table, dishes sorted by Café Points per Day:

As per some of the comments, I’ve realized that there is an overhead in time for setting up a dish. It’s likely small (15-20s), but still, that’s a material increase on a 5 minute dish. I’ll provide that update in a future post.

In truth, I had hoped to have my first FishVille Economics post up by now. Unfortunately, the little spat between Zynga & Facebook seems to have precluded it for now. Fishville has been down all day.

Update:  New Café World Economics posts are available:

• Café World Economics: Real World Hourly Wages
• Café World Economics: Profit & Café Points (2010 Edition)
• Café World Economics: Alien Invasion & Google Docs

Zynga launched several new crops this week: Cranberries, Pattypan Squash, and Acorn Squash, so I thought I’d update my tables for active players out there. So yes, this is Yet Another Farmville Post (YAFP).

For quick reference, here are the links to my first seven Farmville posts:

• The Personal Economics of Farmville
• The Personal Economics of Farmville, Part 2
• More Farmville Economics
• Farmville Economics: What Price Experience?
• Farmville Economics: Risk Adjusted Crop Profitability
• Farmville Economics: Sweet Seeds are Almost Genius
• Farmville Economics: Flowers & Updated Tables

I’ve updated my tables to include the new crops.  You’ll notice that none of the new crops are significantly differentiated by either experience or profit.

Please remember, all tables normalize the values for one square per day (24 hour day), and include the cost and experience involved with plowing the square per cycle.

Here are the crops, ranked by Profit / Day:

Here are the crops ranked by Experience / Day:

Here are the crops ranked by Profit + Experience / Day (using 15 coins for XP value):

And here are the crops by Risk Adjusted Profit / Day:

Enjoy. Happy Farming.

I suppose it was inevitable.  There comes a point when you have reached a level of wealth in Farmville where you can buy anything (even the Villa).  A point when you have enough experience that you can plant any crop.

It’s natural at that point for the eye to wander, seeking out the next great Zynga game.  And for me, that happened a little over a week ago when I decided to take the plunge into Cafe World.

Cafe World has a number of elements that I had originally suggested for Farmville:  animated sims, shorter time spans, more functional enhancements.  It’s a much more complicated simulation, and as a result, it took me quite a bit longer to get the hang of it.

There are a few very interesting new aspects to the game that make modeling the economics difficult.  Expect future posts from me on how to model “The Buzz Factor”, which affects the velocity that your food is consumed over time, and how to model “Spoilage”, which is similar to Farmville but more absolute.

A couple quick tips, for the fans out there:

• Your Buzz Rating drops by 1.0 for every customer who comes in and leaves without food.  The minimum is 5.0, the maximum is 105.0.  There are two ways to preserve it, however.  First, when you run out of food, remove the doors on your restaurant.  This will close the cafe, and keep your Buzz rating flat.  Second, your buzz rating will not fall if you are not actually running the game.  That means it’s safe to run out of food, as long as you aren’t watching…
• If you block your waiter(s) in, then they will serve the food infinitely fast.  This is just like the Farmer trick from Farmville.  I highly recommend doing this with the three serving stations against a corner.  One warning – for this to work, you need to give the waiter/waitress *two* squares of freedom.  With just one, it doesn’t seem to work.

To get things started, however, I thought I’d just run the simple numbers on profitability and experience for each recipe.  I found elements of this information on various posts across the web.  (Here is one from Cafe World Strategy.  Here is another from Cyberanto.  This one was the best, from Simple Think.)  Unfortunately, no one seems to know the Café Points experience breakdown between preparing & serving the Impossible Quiche… I guess no one is at that level yet. (I had to guess in my table).

First, profitability.  Each dish below is normalized as follows:

• All values are normalized for a 24 hours day
• A “cycle” is based on cooking time, but includes the cost & cafe points for cleaning the oven once
• I assume an infinitely fast player for cleaning/preparing/serving

The next table shows the same information, but for Café Points instead of profit. This is more useful if your primary concern is “leveling up”.

Two things seem clear to me from these tables:

1. Overstuffed Peppers is the dish to beat.  12 hours cooking time means you don’t have to babysit the game endlessly.  One of the most profitable, and does a fair job of building experience.
2. Fast Food is King. If you have the patience and time, serving burgers can’t be beat.  All the numbers are incredibly weighted towards the foods with short cycles.  After all, when you can literally serve something 288 times in a single day, that’s a huge multiplier.

In future posts, I’ll try to rebalance these numbers across risk of spoilage and personal time value, to bring some sense to the madness.  I can tell already, however, that the Overstuffed Peppers is going to be the best balance of time & profit.  Of course, my cafe is still dawdling at Level 14…

Update:  New Café World Economics posts are available:

• Café World Economics: Updated Tables
• Café World Economics: Real World Hourly Wages
• Café World Economics: Profit & Café Points (2010 Edition)
• Café World Economics: Alien Invasion & Google Docs

Zynga launched several new crops this week in the form of cut flowers, so I thought I’d update my tables for active players out there.  So yes, this is Yet Another Farmville Post (YAFP).

For quick reference, here are the links to my first six Farmville posts:

• The Personal Economics of Farmville
• The Personal Economics of Farmville, Part 2
• More Farmville Economics
• Farmville Economics: What Price Experience?
• Farmville Economics: Risk Adjusted Crop Profitability
• Farmville Economics: Sweet Seeds are Almost Genius

I’ve updated my tables to include both Sweet Seeds and the new cut flowers.  You’ll notice that, as per my last post, Sweets Seeds really aren’t as good as they should be.  At least, it’s not clear to me why Super Berries were so much better.

Please remember, all tables normalize the values for one square per day (24 hour day), and include the cost and experience involved with plowing the square per cycle.

Here are the crops, ranked by Profit / Day:

Here are the crops ranked by Experience per Day:

Here are the crops ranked by a sum of profit and experience per day (see previous posts for why I ascribe 15 coins to the value of one point of experience):

And finally, the most important table: Risk Adjusted Profitability.  This takes into account the risk of spoilage and the time it takes for each crop to harvest.  I’ve found this to be the best table to answer the question of “what should you plant”:

Stay tuned for my next post, my very first on Café World, my new Zynga addiction.  Very different simulation & economics, and should be good for a few interesting analytical posts.

Updates: I’ve now posted follow-on posts about Farmville Economics:

• Farmville Economics: Cranberries, Pattypan Squash, Acorn Squash

It would be cool enough to see a new version of LinkedIn for iPhone go live in the App Store, but the fact that the credit goes to our two-time intern Andrew He makes it truly exceptional.

Full story here on the LinkedIn blog.  You can download LinkedIn for iPhone v1.5 here.

I’ve been encouraged by a few friends to spend a bit more time writing blog posts about finance and economics in the real world, as opposed to Farmville.  (Hopefully the Zynga fans will allow me brief distraction with the real world.)

An article last week in the Wall Street Journal on investing in gold reminded me of a topic I had meant to cover this past summer:

What is the best hedge for a crisis?

The last two years have validated the fundamental premise of The Black Swan theory.  That premise is that, due to incomplete information and faulty statistical assumptions, the market generally underprices risk at the “tails” of the distribution.

In other words, while the outcomes of the market tend to look like a normal distribution, in reality, more “rare” events happen than would be predicted mathematically.

Given a potential fear of crisis, what is the best way to hedge?  What’s the best way to have some fundamental security in the face of these events?

For Nassim Taleb, the author, he has made his investment approach well known.  He keeps the vast majority of his money in cash, and periodically invests a small percentage in out-of-the-money puts on the market. In 2008, this made for extremely high returns (between 65% and 115%).

Unfortunately, this is such an extreme approach, it’s hard to recommend it as a general practice for anyone but the most stalwart intellectual and contrarian.

If you read any financial press, or listen to AM radio, you likely have heard a much more common refrain about a hedge against crists:  Gold.

Gold has historically been pitched as the ultimate hedge against inflation and crisis.  You can literally find websites that explain how to not only buy gold bullion, but how to effectively bury it in your yard in such a way that it won’t come up on satellite photos (in case the US Government chooses to confiscate it again, like FDR did in 1933.)  I’m not kidding.

Because fascination with gold goes back basically as long as recorded history, it’s rare to find new information on the topic.

This article in Seeking Alpha, however, caught my eye, as a rare piece that had something new to say about investing in Gold.

July 9: A Golden Hedge Against The Dreaded Dollar

This article highlights a well known point – that recently, when the market collapsed, gold actually collapsed with it.  In fact, if you look at the charts, in the past decade, gold and the market look like their moving together.  This makes it a terrible hedge, because good hedges are supposed to be decoupled.

In truth, GLD does appear to be a venerable contender for a portion of a well-diversified portfolio. Yet in a “black swan/perfect storm catastrophe” like the 3 month, systemic breakdown of 2008 (September through November), GLD dropped an astonishing -30%.  PowerShares DB U.S. Dollar Bullish (UUP) soared 20%.

What’s interesting, however, is that in these periods, a very surprising asset has done well: The US Dollar.  The author goes on to advocate for a split between the US Dollar Bullish ETF and Gold.

The article shows this chart, which tracks gold and the US dollar over the past two years:

The insight here is not that you should split your “crisis” holdings between Gold and the Dollar.  Most Americans are already heavily weighted in dollar holdings.   The insight is simply that gold actually doesn’t cover you in all crises, despite the protestations of the gold bugs.

Indeed, I would like to see this relationship going back over the past century, to see what possible approaches might make sense:

• A balanced approach?
• A reciprocal trade where you sell into strength of one, and buy the other?
• Relationships between various mixes of gold & dollar to hedge a stock portfolio?

My guess is that a dollar-denominated fixed income allocation (Treasuries) would look similar to dollar bullish, and would fit a more traditional view of asset allocation.

Zynga launched a great promotion this weekend called “Sweet Seeds”, and I thought it deserved at least a little direct attention.  So yes, this is “yet another Farmville post” (YAFP).

For quick reference, here are the links to my first five Farmville posts:

• The Personal Economics of Farmville
• The Personal Economics of Farmville, Part 2
• More Farmville Economics
• Farmville Economics: What Price Experience?
• Farmville Economics: Risk Adjusted Crop Profitability

A brief description from Farmville Village:

Zynga has just launched “Sweet Seeds for Haiti” a special FarmCash crop you can buy with 50% of the proceeds going to charity. These plants are unique in that they never wither and give maximum experience points, with a special gift in your gift box for you, too!

My first reaction to this announcement was “Genius!”   Not to be cynical, but Zynga seemed to have a pattern of rolling out crops with superior economics and rapid turnarounds to help drive huge activity spikes.  (The Super Berries in August, for example, were well timed with a surge over 10M daily active users.)

By rolling out a super-charged crop for charity, they could get the benefit of increased activity and funnel money to a deserving cause.  Win-win.  It seemed like a brilliant approach to match up business & altruistic goals, and set forward a powerful concept of buying virtual goods as a mechanism for charitable fundraising.

In fact, at first, the only thing that surprised me a bit was that only 50% of the money was going to charity.  I suppose there might be some costs associated with payment processing and handling the operational surge of activity.  Typically, however, if you are going for a charity, you tend to absorb those costs to avoid the appearance of profiting from people who are looking to donate to a good cause.

Then I actually looked at the economics for Sweet Potatoes.  And I was left scratching my head.

The stats for Sweet Potatoes are as follows:

• 3 XP
• 10 coins to plant
• 125 coins at harvest

By itself, these statistics would make Sweet Potatoes truly a super crop, except for one detail:

• 1 day to grow

115 Coins of profit per day puts Sweet Potatoes between Broccoli & Cabbage for daily profit, #16 on the table I published last week.  Really not very super.  Super Berries had huge numbers because they could be harvested every 2 hours.  But a full day?  You’d do better on experience and profit planting almost any of the 8 hour (or faster growing) crops.

3XP (+1XP for plowing) does compare favorably with all daily crops, except for Peas.  Peas offer:

• 3 XP
• 176 coins of profit / day

As far as I can tell, there is absolutely no reason you would plant Sweet Potatoes if you already have Peas.  None.  And it certainly wouldn’t be worth $5 (25 FV) to do so.  True, this crop doesn’t whither… but that just makes the activity goal even more unlikely.

All this would be different if the crop took 4 hours to grow instead of a day.  But with the current numbers, planting Sweet Potatoes just doesn’t make any sense.

I’m going to hazard a few guesses as to why Zynga set these numbers here:

• Theory 1: They didn’t care about people at higher levels.  Of my 50 neighbors, only one is at a level where they can buy Peas. So these numbers would look good to at least 98% of the audience.
• Theory 2: The target market is sensitive to time.  The 1 day cycle and removal of withering suggests that they were targeting a segment of users that don’t want to spend all day planting & harvesting.
• Theory 3: The load generated by Farmville has been so high on Zynga given it’s phenomenal success, they decided last minute to extend the growing time to a day, to minimize activity for a period of time.  In a way, the Sweet Potatoes are Bizarro Super Berries, working to diminish activity, instead of encourage it.
• Theory 4: They didn’t run the numbers on the economics.  (I find this impossible to believe.)

I still believe the concept behind the Sweet Seeds announcement incredibly sharp.  Plenty of time and opportunity for Zynga to tune these type of events going forward.

Almost genius.  Almost.

Update:  Here are additional posts on Farmville Economics, published after this one:

• Farmville Economics: Flowers & Updated Tables
• Farmville Economics: Cranberries, Pattypan Squash, Acorn Squash

Too much fun.  Tonight, we revealed the identity of Fake Leonard Speiser to, well, the real Leonard Speiser.

The key to obfuscation was simple: there was no one Fake Leonard Speiser.  A group of people who have worked with Leonard before all had access to account.  Consider it a form of “Twitter Improv”.

Yes, this is the kind of fun we have in Silicon Valley.  It’s because we’re geeks.

See below for the kickoff email.  We had fun with this all weekend.  I hope Leonard (and fans) did too.  I’d like to think that even though Fake Leonard was just around for a few days, he was starting to develop a real personality.

Goodbye, Fake Leonard.

From: Adam Nash
To: Elliot Shmukler, Chris Yeh, Bart Munro, Ben Foster, Shri Mahesh, Michael Dearing, Kenny Pate
Subject: Welcome to the Fake Leonard Conspiracy
Date: Fri, 25 Sep 2009 11:10:37 -0700

Merely by reading this email, you have been inducted into the Fake Leonard Speiser conspiracy.

Yesteday, Leonard made the mistake of issuing this tweet:
http://twitter.com/leonardspeiser/status/4350181575

Clearly, this was a desperate cry for a prank.  We will oblige him.

Behold, Fake Leonard Speiser:
http://www.twitter.com/fakeleonard

Instead of just one of us making up fake lines from Leonard, we are *all* going to contribute.  Kind of like a live, Twitter improv.

Here is the commitment:
For the next few days, every one of us will make *at least* one tweet from the Fake Leonard account.  Don’t worry about being consistent with the tone of everyone else too much – just shoot out lines that you can imagine Leonard saying.

Follow @fakeleonard, and tweet/respond/retweet his posts, to help get his followers up.  If someone wants to run around and follow a broad swath of his social network, all the better.

This is all in good fun, so nothing too personal or offensive. 

The account password is:
********

Please try to make your first tweets today… I got mine in.

Email me with questions.
Adam

Update: I’ve been reminded that this is the second online gag I’ve played on Leonard Speiser… in the first, the co-conspirator was GoldenPalace.com.

It’s clear that my addiction to spreadsheets and Farmville knows no bounds, so as predicted, here is my fifth post on the topic.

Here are the quick links to my first four posts:

• The Personal Economics of Farmville
• The Personal Economics of Farmville, Part 2
• More Farmville Economics
• Farmville Economics: What Price Experience?

The wizards at Zynga have been busy, and with regular updates every week (or even more frequently), a large number of new crops have been introduced.  As the comments on my other posts have become quite demanding, here are two of my original tables, updated for all the new crops (as of September 20, 2009):

Assumptions: All numbers are normalized for one planting square per day, and assume a “perfect” farmer who can operate all 24 hours of a single day.  It’s assumed that you will need to harvest, plow, and plant every cycle for a given crop.

As it turns out, many times players are optimizing for experience per day, rather than for profit.  As a result, here is an updated table that shows experience per crop, with the same assumptions:

It’s fairly obvious from the numbers above that crops that can be planted and harvested multiple times per day have a significant advantage. This advantage is largely due to the +1 XP you get from plowing a square, and the multiple turns per day. While the longer duration crops have higher experience, they don’t generate enough experience to match the multiple cycles of crops like the berries, or the 8-hour crops like Tomatoes.  Of course, this ignores the time value of money, the primary topic of my first blog post on Farmville Economics.

It seems as if Zynga has been doing their homework when building out their technology tree with additional crops.  Using my 15 coin / XP estimate, the table combining the value by coins and experience is dominated by the new crops:

The title of this blog post, however, is Risk Adjusted Crop Profitability.  One of my orginal concerns was that measures of profitability were not properly taking into account the amount of risk that each crop incorporated.

When you plant a crop in Farmville, it grows for an allotted time.  During that time, you cannot harvest the crop, nor can you recover your capital.  It’s completely illiquid.  After that time period, you have an equivalent time period (100% of the growing time) to harvest the crop.  At that point, your investment is liquid and recoverable.  After the harvest time has expired, over the next equivalent time period (between 100% and 200% of the growing time), your crops will wither square-by-square, until none are left.

As a result, a crop that yields a few more coins of profit, but that involves an up-front investment of fifty coins, may not actually be worth the risk of withering.

In case you think I’m being melodramatic, it’s a very common problem.  People invest all of the wealth into planting crops, get distracted or misunderstand the rules, and then end up with withered crops and no money left over to re-plant.  They have to depend on “lotteries” and “helping neighbors” to recapitalize.  (In fact many don’t, which may be a problem Zynga needs to monitor.)

So how do we model risk-adjusted profitability?

In typical financial modeling, you would have a “cost of capital” – namely a borrowing rate that would be your cost of money over a period of time.  However, for this analysis, it didn’t seem appropriate – maybe I’ll revisit sometime in the future.

To model the Farmville risk, I tried to literally focus on the following facts:

1. How much capital (coins) up front you risk by planting one square?
2. What is the risk that you won’t be available during the harvest time?
3. Probability of harvest + Probability of wither = 100%
4. Multiply the profits per cycle with the probability of harvest
5. Normalize to a risk-adjusted profit per day

In order to model #2, I’ve used the following assumption: you are expected to check Farmville once every 24 hours.  You can replace this with your own number, but given that Farmville has 15M+ active daily users, this assumption seems fair.

So, assuming any hour is the same as any other (on average), there is a 1/24 probability that you will be able to check Farmville in a given hour.  24 * 1/24 = 100%

I’m also assuming that your ability to check on a crop in any given hour is independent of the ability to check any other hour.  This keeps the probability calculations simple.

This means that for shorter lived crops, there is real default risk:

• There is a 23/24 chance in any hour that you will not check on the crop.
• This means, for a 4-hour crop, there is a 23^4/24^4 = 279841 / 331776 = 84.3% chance that you’ll miss checking on the crop during harvest time for full profit.
• This means, for a 4-hour crop, there is an 84.3% chance you’ll miss the withering time, where you’ll receive partial profit.  (I’m assuming a linear decay rate)
• This results in a default rate of 71.1% on a four-hour crop.

Using calculations similar to those above, I generated an expected profit per cycle.  I’ve regenerated the table (ignoring experience) for the crops, and ranked them by risk-adjusted profitability:

Now, I’ve made quite a few simplifying assumptions here, so don’t confuse this with a PhD thesis in Farmville Economics. But it’s amazing to me how this list of crops, more than any other table, best reflects my own internal preferences on what to plant. Maybe that’s because the “once a day” estimate of average availability best fits my own time table during the week.

Another way of revising this estimate is to look at the “risk of complete default” as highly correlated with the “stress level” you feel when you plant a given crop.  Super Berries are awesome, but there is no question that when I plant them, I am hyper-aware of the need to check on them within a 2 hour window to harvest my profits.

Definitely an interesting lens on the topic of profitability.  Please feel free to share alternative views on how to evaluate the risk-adjusted profitability of Farmville crops here in the comments.

Update:  Here are additional posts on Farmville Economics, published after this one:

• Farmville Economics: Sweet Seeds are *Almost* Genius
• Farmville Economics: Flowers & Updated Tables
• Farmville Economics: Cranberries, Pattypan Squash, Acorn Squash

Despite the fact that some people find my recent preoccupation with Farmville amusing, the traffic to my original series of blog posts on the Personal Economics of Farmville has been extremely high.  This isn’t surprising given the incoming links from the Zynga Blog and the Wall Street Journal.

Here are the quick links to my first three posts:

• The Personal Economics of Farmville
• The Personal Economics of Farmville, Part 2
• More Farmville Economics

Well everyone knows that bloggers can’t resist traffic, so as a result, I thought I’d add a fourth post to the series, highlighting some of the insights into the economic value of Farmville experience points.

It all started with the analysis I presented in the second post, which modified the profitability matrix for each Farmville crop by adding an economic value for Experience.  Here is a snippet:

The question is, how do you blend the value of experience and coins? The truth is, the function for valuing experience is probably too complicated to get right.

However, I did find a simplistic proxy.  1 experience point = 15 coins.

Why? Well, it turns out you can just sit there, plow a square for 15 coins, and get 1 experience point.  You can then delete the square and do it again.  So at least, in theory, you can “buy” an infinite supply of experience points for 15 coins each.

Boy, did that start a firestorm.  It turns out, there is a well-worn analysis that says that Farmville experience is actually worth 10 coins.  Why?  If you plow a square of land (-15 coins, +1 XP) and plant soybeans (-15 coins, +2 XP) and then delete, you spend a total of 30 coins, and you get +3 XP.  Thus 30/3 = 10 coins / XP.

It’s a more complicated series, and it ignores the liquidity issue of requiring the purchase of 3 XP at a time, not 1 XP, but it’s a pretty good proxy for the “cheapest” way to buy experience.

The more I thought about this, however, the more dissatisfied I became with the answer.  The reason?  It ignores the incredible time cost of those set of actions:

• Click the plow tool.
• Click the square.
• Click the market tool
• Navigate dialog, click soybeans.
• Click the square
• Click delete tool
• Click the square
• Select “Accept” from the “Are you sure” dialog

Ugh.  For 3XP.  Can you imagine trying to get 4500 XP this way?  I can’t.

As a result, I’m even going to invalidate my original 15 coin / XP assumption.  In fact, you’ll notice that for truly painless actions, like buying a building, the number of XP gained is typically 1/100 the price of the item.  For example, when you pay 250,000 coins for a log cabin, you also get 2500 XP.

I think this effectively bounds the range of the value of XP.  Clearly, it’s worth more than 1/100 of a coin, because you ALSO get the log cabin, which is a pretty snazzy farm improvement.  It’s also clearly more than 1/10, because the time cost of that process is clearly extracting value beyond the coins.

So, value of XP is:

0.01 coins < 1 XP < 0.1 coins

I’m guessing the value of XP is close to 20 coins.  A haybale is only 100 coins, and it gives you 5 XP.  Since a haybale is a pretty negligible improvement, you can assume that most of the price is actually for XP.  So, that would bound the range even tighter:

0.2 coins < 1 XP < 0.1 coins

Now, I know what you are going to say: “You can sell the haybale for 5 coins, making it even cheaper!”.  The problem there is that now you have to go through the delete process, with the confirmation dialog.  Ugh.   I’m trying to avoid that work.

In fact, my analysis is still missing a “cost” for the implicit clutter a haybale creates on your farm.  You have a limited amount of space, so the “price” of a haybale is really:

Cost of haybale = 100 coins + MIN((time cost to delete haybale – 5 coins), opportunity cost of lost 1/16 of a square of land)

Maybe in a future post I’ll explore the opportunity cost of clutter in more detail.  It’s certainly the thing that would prevent you from literally filling your field with haybales to buy experience.  (Interestingly, Farmville just rolled out an improvement today that lets you buy haybales continuously!)

Finally, I have to share a tip that was posted on one of my earlier articles that has represented the single largest improvement in my Farmville quality of life:

If you “fence in” your farmer, then Farmville will harvest, plow, seed a square immediately, without waiting for the farmer to walk to it.

I was skeptical of this advice at first, but I tried it this weekend, and it speeds planting a large farm by AT LEAST 50%.  I use ducks to “fence in my farmer”.  I keep several in a box at the edge of my farm, and first thing I do is walk the farmer into the box.  I then move one duck to close the trap, and boom, 15 minutes added back to my life. 

Your mileage may vary.  Enjoy.

Update: I’ve posted the following new articles on Farmville Economics:

• Farmville Economics: Risk Adjusted Crop Profitability
• Farmville Economics: Sweet Seeds are *Almost* Genius
• Farmville Economics: Flowers & Updated Tables
• Farmville Economics: Cranberries, Pattypan Squash, Acorn Squash

This is actually old news, but I picked it up in a few searches I was doing on Palladium.

It seems that in early April, Max Baucus (Sentator from Montana) put forward a bill (S. 758) to authorize the US Mint to produce a 1 ounce Palladium coin, similar to the very successful 2009 Ultra High Relief gold coin.

CoinNews.net: Palladium Ultra High Relief Coins Come Back, S. 758

History, however, provides insights. Senators Max Baucus [D-MT] and Jon Tester [D-MT] sponsored S. 758 and they also introduced S. 2924 for the same purpose last year. That bill was similar to an earlier and unanimously passed House version, H.R. 5614. The Senate failed to take action on either before the new year, and both died with the end of the 110th congress.

The previous bills would have authorized one-ounce proof and uncirculated palladium coins that were digital reproductions of the famed Augustus Saint-Gaudens’ designed 1907 $20 Double Eagle — often described as the most beautiful coin ever minted in the U.S.

Buyers of the gold 2009 Ultra High Relief $20 Double Eagles can attest to the beauty and detail of that 1907 design. During the first day of Ultra High Relief sales alone, the US Mint sold 28,173. Despite the over $1200 price tag for one, the latest Mint sales figures show 56,527 have been purchased.

You might be wondering why Max Baucus, who is point on driving health care reform in the Senate, would concern himself with coinage.

It turns out that the only mine in the United States that produces Palladium is in Montana, and with the auto industry hurting, it’s a serious jobs issue for the State.

Commodity speculators may be on the outs with regulators in Washington right now, but it seems if you take a commodity and turn it into a coin to spark collector/speculator interest, well, that’s just OK.

In any case, I would love to see this happen.  Buying Palladium right now is incredibly difficult.  2005 & 2006 Canadian Maple Leafs are hard to find without a huge (30%+) markup over the metal.  Ironically, this crash of the auto marketplace is a perfect opportunity to invest in Palladium.  Not surprisingly, however, the lack of demand for the metal also seems to translate into a lack of vehicles to invest in it.

Such is the life of a contrarian coin investor.

Let’s hope Max can take a day off from the health care push and get this one passed.  Given it’s bi-partisan support, maybe it can help revive some form of bi-partisan cooperation in Washington…

Thought I’d take a break from posting about pretend farming, and add my annual post on my real life farming efforts.

Those of you who know me, or who have been reading this blog for a while, know that I love to garden.  Despite having a tiny amount of plantable land (I have two 3×3 foot garden boxes, and one 3×6 that I use for tomatoes), I do my best.

I try to balance color and variety each year with my tomato picks.  I only have room for four plants (technically, if I gave them proper space, two plants), so I try to mix demonstrated produces with at least one tomato that I’ve never grown before.

For 2009, I planted:

• Sweet 100 (Red Cherry)
• Sungold (Small orange)
• Lemon Boy (Medium yellow)
• Green Zebra (Medium Green/Yellow striped)

As usual, I do nothing fancy for my garden boxes.  They have reliable watering through soaker hose on a timer, and I fill each box with new compost every spring.

For volume, Sungold really stole the show this year.  Normally, the Sweet 100 cherry tomatoes are the big producer, but not this year.  The Sungold plant went nuts.  The bush overgrew my 4-foot cage and spilled over the entire box:

Gorgeous fruit, with bountiful bunches of bright orange tomatoes.  Very sweet.  I’m being conservative by saying that we’ve harvested over 200 tomatoes off this one plant already this season, and we’re harvesting another 50+ daily right now.

The clear champion of this summer, however, was the experimental variety, the Green Zebra. The Green Zebra, it turns out, is not an heirloom tomato (although I thought it was when I bought it.)

The plant has been an incredible grower, and has produced several dozen fruits already.  They are a beautiful green striped, medium-sized tomato that turn yellow at the top when they are ripe.

They grow in beautiful clusters, and the vine has been producing several ripe tomatoes every day through August.

They taste delicious, like a slightly acidic version of a typical salad tomato, but with beautiful color.  Fantastic addition to any garden.

So, the 2009 award for best tomato (in my garden) goes to: Green Zebra.

Maybe I can get Zynga to add it to Farmville as a “Super” crop? 

Wow.  The traffic from the first two blog posts on Farmville has been high.  In fact, the Zynga blog even picked up the two articles.  Very flattering.

I was all set to write a post tonight on the economics of trees in Farmville… but then I caught Pablo’s post on “Treeconomics”.

Brilliant.  Leveraging some of the work I had done, he does a evaluation of a 16-square of trees in terms of “yield” vs. crops.  Very interesting, confirming that a 16-square of Date trees can compare very favorably to almost everything.

I’m going to have to think about this a bit more – I want to build a model where I incorporate a few additional factors:

• The “down payment” for trees.
• The freedom to never have to “plow” or “plant” again. (value of time)
• The freedom from working capital for seeds on an ongoing basis.
• The removal of “withering risk”.  Crops wither after 20% of their growing time, yielding a complete loss of the capital to plow & plant.  Trees never wither.
• The lack of experience points from trees
• Incorporate the data from all the trees, not just the ones you can buy.

I’ll still write a follow up here, but tonight there is no need.  Check out this table from Pablo as  sample:

And this one:

Too cool.

Now go read it.

Updates: I’ve now posted additional articles on Farmville Economics:

• Farmville Economics: What Price Experience?
• Farmville Economics: Risk Adjusted Crop Profitability
• Farmville Economics: Sweet Seeds are *Almost* Genius
• Farmville Economics: Flowers & Updated Tables
• Farmville Economics: Cranberries, Pattypan Squash, Acorn Squash

Yesterday, I wrote a fairly popular post about the personal economics of Farmville, the extremely popular Facebook game by Zynga.  There were enough comments and emails about the original post, I decided to write a quick follow-up to cover some of the most common ideas and concerns.

I was also able to get the data on Red Wheat and Yellow Mellon, which were missing from my original post.  Also, this weekend saw the (temporary?) advent of “Super Berries”.  I’ve updated my original table here, showing the rank of all Farmville crops based on net profit per day per square.  Let’s just say there is a reason Super Berries are, well, super:

The most interesting questions and comments came from Abhi Kumar, product manager for Farmville at Zynga.  Needless to say, it was extremely flattering to have Abhi interested in my post, and to hear his thoughts on the topic.

The first point Abhi raised was interesting.  The question was, how would I factor experience into these calculations.  Clearly, experience is crucial to the game in several regards:

• It’s crucial for rising in the technology tree, to get access to new crops, tools, and other beneficial items.
• It’s a basic game mechanic that drives people to see their “score” rise.
• It’s public to your neighbors.  As a social game, this adds an additional game mechanic, similar to a leaderboard, that encourages you to boost your score.

In order to calculate the experience for each crop, I took the experience that each crop delivers per cycle, added one experience point per cycle for re-plowing, and then normalized the values for a single day (24 hours) and a single square.

Not surprisingly, the quick cycle-time of the berries dominates this table.

The question is, how do you blend the value of experience and coins? The truth is, the function for valuing experience is probably too complicated to get right.

However, I did find a simplistic proxy.  1 experience point = 15 coins.

Why? Well, it turns out you can just sit there, plow a square for 15 coins, and get 1 experience point.  You can then delete the square and do it again.  So at least, in theory, you can “buy” an infinite supply of experience points for 15 coins each.

When you include experience at this price, the rank of the crops changes significantly from the original “coins only” version of the most profitable crops:

In many ways, this final table is a more satisfying answer on what to plant, since it gives a fairly balanced view across coins (which are needed to buy seeds, tools, and other items) and experience (which is also needed to raise your level to buy seeds, tools, and other items).

Clearly, this analysis is very sensitive to the value of an experience point. The more value you ascribe to experience, the more the compound table begins to resemble the experience-only version.

As part of my original post, I had run some analysis that suggested that if you value the time that it requires to check on your crops, harvest them, and re-plow & plant, then you might get a different order.  I’ve now updated the chart to include the three crops that I didn’t have yesterday.

click to see the enlarged chart graphic

Based on the addition of the new crops, the top five crops in terms of their value in $ US / hour are:

1. Yellow Mellon
2. Broccoli
3. Red Wheat
4. Corn
5. Watermelon

All of the values are still well below $1 / hour.

I re-ran these numbers utilizing the experience points.  While they did shift the numbers to the right, they didn’t alter the ranking significantly.  This is likely because the cost in time (15 minutes) for each cycle and the high conversion rate (1500 coins / $1 US) means that the time cost of checking dwarfs the incremental value of the experience per cycle.

That’s why you can see that one wacky line, Super Berries, which starts so high it’s off the chart, but crashes down under the weight of 12 cycle refreshes per day.

A couple people specifically wanted to see this analysis taking into account the new Tractor, which speeds plowing by up to 4x (although you need to buy fuel).  Since I don’t have a Tractor yet (working on it), I estimated what would happen if a cycle plow/plant took only 5 minutes instead of 15.  Here is the updated chart:

click to see the enlarged chart graphic

For those of you playing at home, sorry to disappoint.  It turns out that dropping the time it takes does shift the value per hour out almost linearly.  You’ll note that in this chart, now the equivalent value for Yellow Mellon is over $2.62 / hour.  The order of the most valuable crops, however, does not change, because even five minutes dominates with such a high US $ to Farmville coin exchange rate.

Abhi did make one last point that I agree with completely.  The primary value of the game is not the coins you make.  (In fact, since you can’t really convert coins back to dollars, they are arguably worthless.)  The value is the fun and enjoyment you get from the time spent.

In fact, I could theorize that if you normally bill $50/hour for your time, the delta between your normal rate and the amount you are making with Farmville crops shows just how much you value playing Farmville.

Hope this post was as interesting to folks as the last.  I’ve got to go harvest some Super Berries…

Updates: I’ve now posted additional articles on Farmville Economics:

• More Farmville Economics
• Farmville Economics: What Price Experience?
• Farmville Economics: Risk Adjusted Crop Profitability
• Farmville Economics: Sweet Seeds are *Almost* Genius
• Farmville Economics: Flowers & Updated Tables
• Farmville Economics: Cranberries, Pattypan Squash, Acorn Squash

I’ve been playing Farmville, a social video game by Zynga, over the past week, and I have to say that I’m extremely impressed.  It’s a very simple simulation game, with well integrated social aspects to promote virality, a good technology tree, and clever virtual goods integration.

If you’ve played the game (and at this point, approximately 9 million people have), then you are likely already familiar with the primary economics of the game.  As a farmer, you have a certain number of plots.  It costs money (coins) to plow a plot and plant seeds.  Different crops take different amounts of time to grow, and are worth different amounts at harvest.  Quite simply, the question is:

Which crops should you plant?

Since I do love an excuse to crack open Excel, I built a simple model that tells you what crops are the “most valuable” to plant.  My model was simple:

• Revenue is just the value of the crop at harvest
• Cost is the cost of the seeds + the cost to plow the square

In order to compare crops, I had to normalize the values:

• Normalized all revenue and costs to “one square”
• Normalized all revenue and costs to “one day”, namely 24 hours

Thus a crop like Strawberries, which takes 4 hours to grow, can be theoretically planted 6 times in a single day.  Eggplant, which takes 2 days to grow, can be planted 0.5 times in a single day.

This model gives you the following simple table as output, ranked by “coins per square per day”:

(Note: I still haven’t gotten the revenue and cycle time for the new crops, Red Wheat and Yellow Mellon)

Most of the strategy guides that I’ve found across the web have basically gone just this far.

The problem with this model, however, is pretty obvious:

It assumes that your time has no value!

Listen, Raspberries might be #6 on this list, but you have to actually harvest and replant 12 times per day! (It’s a two-hour crop).  That only seems reasonable if you truly value your time at $0.  Theoretically, we should give some non-zero value to the time it takes to replant, and see how it affects the rankings.

To do this, I changed the model based on the following assumptions:

• It takes roughly 15 minutes to replant your farm with a crop
• 1500 Farmville coins are worth $1 (which is what Zynga charges to buy coins with PayPal or your credit card).

I then graphed out the ranking of the crops on a spectrum from $0.00 / hour value for your time, all the way to $1.00 / hour.

As you can tell from the range, the bad news is that even the best crop flips to being “negative value” per day at a monetary value of approximately $0.70 / hour.

click the image to see enlarged verson

This graph paints a very different picture.  If you rank crops by what hourly wage “zeroes them out” in value, you find that actually, your top three crops should be:

1. Broccoli ($0.69 / hour)
2. Corn ($0.57 / hour)
3. Watermelon ($0.54 / hour)

If you accept the idea that 1500 Farmville coins is worth $1 (which is a bit of a stretch since you can’t convert back to dollars…), then these are the crops that pay you the best “hourly wage” for your time.

There are a few things I’ve left out here:

• Trees / Animals. I haven’t run these numbers for trees or animals, but it would be trivial to do so.
• Working capital. These crops require different amounts of liquid cash in your Farmville account.  That capital theoretically has a cost, but I didn’t model it.
• Experience. Some people are playing for experience points, not coins.  Ignored here.
• Capital Risk. The different crops have different windows of time to harvest before your revenue goes to zero and your crops wither.  This analysis assumes a “perfect farmer”.

If you find this model interesting or useful, would love to see links back here from anyone who pursues any of these different issues.

Of course, that assumes that there is someone else out there twisted enough to spend time analyzing the personal economics of Farmville…

Updates: I’ve now posted several follow-on posts about Farmville Economics:

• The Personal Economics of Farmville, Part 2
• More Farmville Economics
• Farmville Economics: What Price Experience?
• Farmville Economics: Risk Adjusted Crop Profitability
• Farmville Economics: Sweet Seeds are *Almost* Genius
• Farmville Economics: Flowers & Updated Tables
• Farmville Economics: Cranberries, Pattypan Squash, Acorn Squash

Last Friday, I had a chance to write a good, solid piece about LinkedIn Recommendations for the official LinkedIn blog.  In case you missed it, the article is here:

LinkedIn Blog: LinkedIn Recommendations & The Reputation Economy

I spent a good bit of time on this post, and even took a half hour to discuss some of the fundamental driving concepts behind it with Reid Hoffman, to help stitch together my thoughts with some of the underlying premises behind LinkedIn.  I’m pretty happy with the result.

Here’s a quick snippet:

Whether or not we realize it, we all live and work in a networked world.  Reputations matter.  Relationships matter.  Information is bombarding us from a rapidly swelling variety of sources, with increasing frequency and variability in terms of quality.  Interestingly, people are managing this incredible increase in complexity with habits and business practices that date back decades, if not centuries.

They consider the source.  They consider the context.

Fortunately, in the 21st century, with the birth of the social web, we have tools at our disposal that are orders of magnitude more powerful than we have ever had as individuals or as a society.  To quote David Weinberger from his recent talk at PDF09, Transparency is the New Objectivity:

What we used to believe because we thought the author was objective we now believe because we can see through the author’s writings to the sources and values that brought her to that position. Transparency gives the reader information by which she can undo some of the unintended effects of the ever-present biases. Transparency brings us to reliability the way objectivity used to.

This change is, well, epochal.

David is talking about journalism, but his insights are at the heart of why LinkedIn is such a powerful concept.  On LinkedIn, the skills that you’ve spent your career obtaining, the experience that you’ve earned, the trusted relationships that you’ve formed – they are all made largely transparent.  Your professional reputation and relationships matter – and not just to you.  That value extends far beyond your profile itself – it carries over to every interaction, every message, and every piece of contributed content.

It’s always rewarding when you write a post like this to get positive feedback.  Here is a flattering quote from Neal Schaffer:

I think the most brilliant blog post to come out of reaction to Jeremiah’s is the one on the official LinkedIn Blog entitled “Recommendations and the Reputation Economy” and written by LinkedIn’s own Product Director Adam Nash.  He went further to talk about how transparency is the new objectivity and that not only are recommendations often mutual, but that requesting recommendations is absolutely normal.  In fact, he ends his post asking you to write three recommendations for people unsolicited.  Exactly!  That line could have been taken out of my upcoming book!

Normally I don’t flag every post I make to the corporate blog here on my personal site, but if you’re interested, do check out the piece.

No, that’s not a typo.  I have seen the future.  And in the future, a burgeoning virtual goods economy that has been building over the past few years will lead to the next great financial bubble and crash.

Far-fetched?  Read on.

In some ways, virtual goods are almost as old as role-playing games.  Experience and special weapons are time consuming to earn, so a light grey market to “cheat” by purchasing equipment or characters has always existed.

This ecosystem exploded with popularity of massively multiplayer games, like World of Warcraft, and virtual worlds, like Second Life.  For the first time, cottage industries of real human beings sprang up to devote full time effort to investing time and resources into accumulating virtual wealth.

While typical Silicon Valley chit-chat turned to the impressive revenues that virtual goods firms began generating in 2008 & 2009, it wasn’t until Zynga IPO’ed in 2010 with eye-popping revenues of more than a quarter billion real dollars that the concept of virtual economies really became mainstream.  Major players from across the entertainment and technology domains raced to enter the market, and to leverage the powerful virality of social platforms combined with the fundamental addictiveness of gaming.  Add the final magic ingredient – pure monetary greed, and you had all the animal spirits needed to create the great virtual goods boom.

Unfortunately, as described in Devil Take the Hindmost, almost all great booms and busts are created through a combination of financial innovation in products that create leverage combined with a technology innovation that drives wildly optimistic views of future value.

Virtual goods and virtual economies had all the right elements to boom.  Initially, the conversion from real world stores of value into virtual stores was highly controlled.  Some of these economies allowed for the transfer of goods and virtual wealth, and some didn’t.  Quickly, however, competition forced a basic truth – people like obtaining virtual wealth in the form of virtual goods.   They like seeing that value multiply and grow.  More and more innovative services and economies were built, and increasingly they enabled mechanisms to convert those virtual stores of value into other virtual stores.  They also enabled players to compound their virtual wealth.  In fact, some even enabled the conversion back into real money.

Thus the vicious cycle was born.  Converting real money into virtual goods, and then taking advantage of the ability to compound that virtual value at unrealistic rates, set off a true boom.  The rate of return on virtual investments was so high compared to the anemic returns offered by the still moribund real economy, that early adopters looked like geniuses.  In 2014, the meme began to spread that everyone should have a portion of their portfolio allocated to “virtual assets”, which were not highly correlated to traditional stores of value.   Funds sprang up to allow the average individual without the time or inclination to invest and build virtual wealth to access the market.

The companies providing these ecosystems had no reason to dampen this enthusiasm.  Their systems, like those of investment bankers or market makers of yore, ensured a percentage of all transactions as revenues.   They made money as people converted real currency to virtual currency, and technically, as they converted it back.  Like central bankers with no fear of inflation, they juiced their economies to juice their own revenues.  Fortunately, the higher the internal rates of return in the virtual worlds, the less people were incented to take their virtual goods out and convert to real money.  Everyone effectively let their money ride, watching their virtual wealth grow.

By 2015, the notional value of virtual goods exceeded $1 Trillion for the first time.  Government bureaucrats began to explore the possibility of taxing these virtual economies to help cover increasing deficits.  Lobby groups sprang up to protect this “new economy” from destruction.  Pundits debated this nightly on all major cable networks.  People borrowed real money at relatively low rates in the real world to invest in virtual goods, because the returns were so much higher.  Real debt grew, savings dropped, but virtual assets grew faster.

Then, in 2016, one of the more flagrant virtual worlds began to see withdrawals rise.  Not significantly at first, but it turned out they had allowed virtual wealth of their members to grow high enough that people began to “retire”.  Everyone was in the game, so new entrants with smaller balances could match the asset loss.  Suddenly, the bear arguments, which had been discussed for years (beginning with a famous blog post from 2009) began to make more sense.

No one had the real money to cover these virtual “liabilities” the companies implicitly had to their members.  There was no virtual FDIC to cover accounts.  There was no regulation to ensure that these accounts would be paid.  The first “run” on a virtual economy had begun.

Suddenly, it became clear that these virtual economies were linked, even if owned by different giant companies.  People who lost money in one virtual economy, began pulling real money out of others.  One virtual world froze conversion, like a panicked 20th century third world nation.  Then the run really began.

Virtual asset values plummeted.  But the real debts did not.  Suddenly it turned out that more companies had their fingers in the virtual pie than most people thought.  Asset management firms.  Insurance firms.  Hedge funds.  Large banks.  Tech giants.

And that’s how virtual goods caused the market crash of 2016.

Do I believe that it will really happen?  No.  Do I believe that conceptually, virtual goods and economies could lead us into uncharted waters economically if we are not careful?  Yes.

I’ve read quite a bit in the past decade about the history of market bubbles and panics, and the patterns of each.  In every case, financial innovation creates some new way for people to assume liabilities in a highly leveraged way, outside of existing regulation or norms.  In combination, some technology offers the world hope of a much larger economic future.  Given the new found ability to invest heavily in that future, and radically different perceptions of that future, people invest, creating a virtuous cycle of high returns and increased investment that sucks almost all the air out of the system… and then keels over.

A fun mental exercise for a Thursday night.

Still I wonder. Since it’s only 2009, I feel like I don’t own enough stock in these companies.  It’s going to be quite a ride.