Currently I have purchased 15 of this item to experiment with, and for some reason volatility is only slightly lower although prices have hit 1mo highs. I should note there was one occurrence of negative slippage. (-0.05 USD). I have been rigging the Bid rate at 0.10 USD so if you plan to research this Time series please note that.

http://steamcommunity.com/market/listings/753/274940-Get%20Over%20Here%21

I would like to add that a noticeable effect has been made in the manipulation of prices, as average price is slowly increasing. I will plan on cornering the market in order to get a general idea of total copies of a specific item in circulation. This could be useful when rigging supply and demand for the purpose of studying it's effects on the market.

I found a video game market (steam community market) which allows for trading of in game items between users, most items are <0.25 USD each, and market capitalization appears to be maybe $5-$10 USD on some items. Something to be noted is the transaction fee is 15% which does limit the possibilities a bit.

One example item: http://steamcommunity.com/market/listings/753/274940-Get%20Over%20Here%21

Some discoveries that should be taken into account:

Many items appear to have very consistent supply and demand, thus leaving them in a sort equilibrium thus the drift in price is very low.

One thing I did find while manually market making is occasionally a user will sell an item at a price lower than the bid, effectively making spreads go negative. In that case, the highest bidder then receives the item. This occurs on average about 1 out of 15 times a trade is cleared, but will go as long as 100 trades between opportunities on occasion. I created a program that provides constantly re-lists bid and offer quotes at the same price as soon as they are filled. By clearing very high volumes (over 1k items a day) I managed to turn $1 into $14 within 3 weeks. This isn't as good as it sound given the returns capped at about 5 bucks invested and I even got blocked from accessing the server after making 8k+ requests in an hour.

Given some less popular items have capitalizations of less than 5 USD it is possible for a dealer to accumulate almost all copies of the item in existence, allowing for the fixing of prices, perhaps useful for reducing volatility.

There is a one week holding period before the in game item is delivered to your inventory, this was implemented into the market before I attempted arbitrage based on negative spreads, and was why I stopped my high volume strategy. A one week delivery means a very large open interest is required in order provide liquidity 24/7.

Another thing, I have discovered is certain items are pretty much identical, but the amount they have been used in the game creates a spread in the value, this could be used for correlation based stat-arb perhaps?

Modeling the market: For an item in equilibrium, the price will not drift much so the time series can be assumed as stationary.

Since It is easy to accumulate a massive open interest, at least compared to volume, one can assume for the sake of the model that there is unlimited buying and selling potential on behalf of the liquidity provider, and I will assume no one else is providing liquidity to the market and all other bids/offers are individuals seeking the utility of the item, rather than to make gains trading it.

$b$ will represent the dealers bid

$o$ will represent the dealers offer

$B_t$ will represent a process for the given item's market bid rate defined as $>= b$ with an unknown distribution.

$O_t$ will represent a process for the given item's market offer rate defined as $<= o$

$S_t$ can be defined as $O_t-B_t$

One Hypothesis I have, is that $B_t-b$ and $o-O_t$ are perhaps log normal distributed.

A method I propose for verifying the distribution is to sample the percent of negative spread arbitrage opportunities and compare them to the expected amount of opportunities a given distribution expects for the Process $S_t$ which could be used for fitting a distribution.

My question:

Can any research done into this in-game market be applied to real market making for financial markets, or is there factors not accounted for?

I found a video game market (steam community market) which allows for trading of in game items between users, most items are <0.25 USD each, and market capitalization appears to be maybe $5-$10 USD on some items. Something to be noted is the transaction fee is 15% which does limit the possibilities a bit.

One example item: http://steamcommunity.com/market/listings/753/274940-Get%20Over%20Here%21

Some discoveries that should be taken into account:

Many items appear to have very consistent supply and demand, thus leaving them in a sort equilibrium thus the drift in price is very low.

One thing I did find while manually market making is occasionally a user will sell an item at a price lower than the bid, effectively making spreads go negative. In that case, the highest bidder then receives the item. This occurs on average about 1 out of 15 times a trade is cleared, but will go as long as 100 trades between opportunities on occasion. I created a program that provides constantly re-lists bid and offer quotes at the same price as soon as they are filled. By clearing very high volumes (over 1k items a day) I managed to turn $1 into $14 USD within 3 weeks. This isn't as good as it sound given the returns capped at about 5 bucks invested and I even got blocked from accessing the server after making 8k+ requests in an hour.

Given some less popular items have capitalizations of less than 5 USD it is possible for a dealer to accumulate almost all copies of the item in existence, allowing for the fixing of prices, perhaps useful for reducing volatility.

There is a one week holding period before the in game item is delivered to your inventory, this was implemented into the market before I attempted arbitrage based on negative spreads, and was why I stopped my high volume strategy. A one week delivery means a very large open interest is required in order provide liquidity 24/7.

Another thing, I have discovered is certain items are pretty much identical, but the amount they have been used in the game affects the value of the item and creates a spread, this could be used for correlation based stat-arb perhaps?

Modeling the market: For an item in equilibrium, the price will not drift much so the time series can be assumed as stationary.

Since It is easy to accumulate a massive open interest, at least compared to volume, one can assume for the sake of the model that there is unlimited buying and selling potential on behalf of the liquidity provider, and I will assume no one else is providing liquidity to the market and all other bids/offers are individuals seeking the utility of the item, rather than to make gains trading it.

$b$ will represent the dealers bid

$o$ will represent the dealers offer

$B_t$ will represent a process for the given item's market bid rate defined as $>= b$ with an unknown distribution.

$O_t$ will represent a process for the given item's market offer rate defined as $<= o$

$S_t$ can be defined as $O_t-B_t$

One Hypothesis I have, is that $B_t-b$ and $o-O_t$ are perhaps log normal distributed.

A method I propose for verifying the distribution is to sample the percent of negative spread arbitrage opportunities and compare them to the expected amount of opportunities a given distribution expects for the Process $S_t$ which could be used for fitting a distribution.

My question:

Can any research done into this in-game market be applied to real market making for financial markets, or is there factors not accounted for?