Methods for Statistical Analysis of Virtual Goods
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Unconventional Exchange: Methods for Statistical Analysis of Virtual Goods Oliver James Scholten∗, Peter Cowling∗, Kenneth A. Hawicky and James Alfred Walker∗, Senior Member, IEEE ∗Department of Computer Science, University of York, Heslington, York, YO10 5GE, UK Email: fojs524, peter.cowling, [email protected] yDepartment of Computer Science, University of Hull, Hull, HU6 7RX, UK Email: [email protected] Abstract—Hyperinflation and price volatility in virtual Virtual economies can be succinctly described as the emer- economies has the potential to reduce player satisfaction and gent phenomena of users generating, trading, and consuming decrease developer revenue. This paper describes intuitive ana- virtual goods [3]. This definition is supported by Nazir and lytical methods for monitoring volatility and inflation in virtual economies, with worked examples on the increasingly popular Lui’s comprehensive review [4] and Knowles and Castronova’s multiplayer game Old School Runescape. Analytical methods chapter [5] in the Handbook on the Economics of the Internet drawn from mainstream financial literature are outlined and [6]. These economies have been found to share many similari- applied in order to present a high level overview of virtual ties with real economies but with several important differences. economic activity of 3467 price series over 180 trading days. These can be summarized as a lack of regulatory oversight, Six-monthly volume data for the top 100 most traded items is also used both for monitoring and value estimation, giving no upper limit on the generation of new virtual assets, and a conservative estimate of exchange trading volume of over complete dependence for governance on the developer of £60m in real value. Our worked examples show results from virtual world. This freedom gives developers a rich landscape a well functioning virtual economy to act as a benchmark for to create impressive user experiences, with games like Old future work. This work contributes to the growing field of School Runescape offering an environment in which players virtual economics and game development, describing how data transformations and statistical tests can be used to improve can explore, trade, and increase their avatar’s abilities to virtual economic design and analysis, with applications in real- achieve greater feats. time monitoring systems. Virtual goods can be described as a rivalrous digital token Keywords: virtual economies, virtual goods, exchange, in a virtual world, this follows Hamari and Keronen’s work [7] statistical analysis. which investigates why people purchase these virtual goods. It should be noted that although the creation of the goods in I. INTRODUCTION the literal sense, as the data in the database of the developer, requires little effort, it is the creation of the goods under the Virtual hyperinflation reduces individuals ability to purchase rules of the virtual world that requires some amount of work items with the virtual currency they have, in effect altering (for example defeating some boss or travelling some distance). the rate of progression in games such that new players With virtual economies and virtual goods briefly introduced, will progress more slowly, and the relative value of existing we can discuss the phenomena they exhibit in a general sense, player’s items will decrease over time [1]. Hyperinflation specifically price behaviours caused by developers actions. causes in virtual economies include incorrect calibration of the As virtual goods themselves can be created and destroyed mechanisms of addition/deletion [2] of virtual currency and/or at will by the controller of the virtual economy, their supply items, duplication bugs in code, or external factors such as and demand is subject to several important effects. The in- gold farming activity - each increasing the amount of virtual troduction of a new virtual good to an existing system, in currency in circulation at a rate greater than the economy can arXiv:1905.06721v2 [q-fin.GN] 18 Jun 2019 the form of a game update or new release, is of primary comfortably handle. This paper explores analytical methods concern. Upon introduction a new virtual good may devalue which can be used on existing data sets to give virtual economy existing goods with which it shares similar function, it may controllers the ability to identify non-standard behaviour and grow itself in price given its relative lack of abundance, or it potentially damaging effects of actions like game updates or may not move in price at all should in-game vendors offer it at micro-transaction additions. We begin by introducing virtual a fixed and replenishable rate. It is these types of effects which economies, virtual goods, and the emergent economic phe- also contribute to virtual economic instability, increasing risks nomena found to take place in virtual worlds. of virtual hyperinflation and other undesirable behaviours like excessive gold farming by players. This work was supported by the EPSRC Centre for Doctoral Training in Intelligent Games & Games Intelligence (IGGI) [EP/L015846/1] and Research into virtual economies and their behaviour also has the Digital Creativity Labs (digitalcreativity.ac.uk), jointly funded by EP- wider effects than game design and player satisfaction. Work SRC/AHRC/Innovate UK under grant no. EP/M023265/1. by Castronova [8], Knowles [9], and Lehdonvirta [10], has investigated virtual worlds as the future of low-skilled work, 978-1-7281-1884-0/19/$31.00 c 2019 IEEE their origins and issues, and their regulation, respectively. consecutive days up to 09/12/2018. The time-zone indepen- These works all view virtual worlds through serious academic dence of the GE means six months of real time are represented and regulatory lenses to identify issues in their governance as weekends are not excluded. Data was gathered through and wider impact. This is especially relevant given the real- Jagex’ publicly accessible GE API, and items with zero price value of the currencies and goods existing in virtual worlds as movement over the entire length of the series were excluded presented in this paper. (109 items total), leaving 3358 series of interest. Finally, this paper may be outlined as follows: section II Volume data for the 100 most traded items was also gathered discusses the mechanics by which virtual goods are exchanged, through the Jagex GE webpage2. This is used in index con- and the data gathered as part of this work in Section III. struction and for estimating exchange trading volume. Volume We then discuss the data analysis methods used in Section data for the remaining 3258 items is not available through the IV, providing brief explanations and justifications for each. GE API so is not included. With data and methods defined, we present several preliminary findings which are available through pure observation in A. Transformations Section V. We then present the main results including figures describing each of the methods presented in Section VI. The In order to explore virtual goods price histories effectively discussion and conclusion then bring together the findings and a number of transforms may be applied, these allow slight summarize the contribution in Section VII, to be followed by variations of analytical interpretations from the original data a brief critique of our implementations and recommendations set, and allow a more complete analytical picture to be drawn. for further work in Section VIII. B II. VIRTUAL EXCHANGES I(c) = r c (1) Bv With virtual economies, goods, and emergent economic phenomena briefly introduced, we move to outline virtual Framing discussion of virtual items with respect to their economic exchanges - the vessel with which any economic real world value requires a formal mapping as shown in 1 - instability may be detected. a na¨ıve estimation of the real-world price of a virtual asset I With more than 100,000 concurrent players1 Old School given it’s virtual price c based on the real and virtual prices Runescapeis one of the largest multiplayer role-playing games of in-game bonds (Br and Bv). These are items redeemable globally, with over 250 million registered accounts. Gameplay for membership by players and can be traded on the GE. This revolves around increasing skills, gathering items, and social- equation may be generalized for any world by substituting izing with other players. Many of the items each player collects the bond prices for any virtual token officially sold by the may also be traded on the Grand Exchange (GE) - a limit order developer and it’s corresponding in-game price. Analytical exchange with few constraints other than an four-hourly buy insights drawn from real-value series following such transfor- volume limit which varies per item. This exchange is freely mation will not be inherently informative but can be used to accessible to all players with member (paid subscription) present findings on a more intuitive scale. Note that this may and non-member items combined. Bid-Ask spreads (charts be complicated further by the use of multiple virtual currencies showing how much other people are willing to offer/pay for within a world yet this addition only wraps the relationship in goods) on the GE are not visible to players and cannot be layers of conversions so is omitted. used either for trading or analysis. Transactions then occur Grey markets for real money trading is a further means to when buyer orders are matched with sellers, or trades are made buy and sell in-game currency [12], albeit explicitly against independently from the exchange. These direct trades are not the terms of use for many developers. Accounting for prices accounted for in the data gathered but represent an interesting in such markets remains difficult, hence interpretation of the avenue of further work. above equation as-is generalizes to ‘the price of item I equals The limited information the GE offers to those using it for the amount of real currency required to purchase it’s in-game trading applies a hard limit to the amount a given player can worth through official channels’ which may be inflated from know about the state of the system as a whole.