 Hi everybody. Thank you so much for joining today's Protocol Labs Research Seminar. Today we're joined by me. I'm going to be the one presenting the research today, very excited about it. And we're going to be talking about what influences NFT secondary pricing markets. To give you a bit of background on what I do, I am the marketing lead for the network goods team, which is formerly the Protocol Labs Research Team. And before I joined PL, I was a research associate at Cornell University and also the smart contract research forum, focusing on consumer economics as well as game theory and other things that impact crypto economics. So thank you so much for having me today Protocol Labs. And I'm going to be presenting my research titled Influencing NFT Pricing on Secondary Markets, a case study of vPunks. And I originally presented this at the Crypto Assets and Digital Asset Investment Conference, which was in Wren on April 7th. So a big shout out to Brian Lucy, who was the one who coordinated that conference. And I'm really excited to present this again here today. So with that, this research was independently done by me. This is not done by Protocol Labs. And so any of the NFT projects or companies or anything like that that I bring up in this presentation is solely meant to describe the research. It's not meant to be an endorsement of any type of PL or anybody at Protocol Labs. So quickly, we're going to introduce what we're going on about today. And really, the background and literature review of NFTs is pretty slim at best. So as many of us know, NFTs allow for immutable and permanent proof of origin for digital assets. So this could be, for example, a photo or music or assets in player and video games, for example. And there's a whole lot of other assets that are starting to be used for NFTs. But those are really kind of the bread and butter that we've been seeing recently. And surprisingly, even though this is a huge industry at the moment, there has been hardly any research that has typically been done that looks into what influences actual sales of NFTs or what impacts the prices of NFT sales. Now, this is kind of growing. There's been a few more conferences this year and a few more journals that have been asking for this type of research, but right now it's really limited. So what we wanted to do was more of a basic study, and we're going to get into the details of that later. But to kind of get this into perspective, NFT sales are obviously a growing multi-billion dollar industry. We've seen this for people who have been paying attention that this has grown from a couple million a few years ago, so billions just last summer alone. Now, the market's kind of cooling down because people are a little less excited in a bear market, more or less, to be buying NFTs. But it's still very popular. In an example, what we're seeing are websites like OpenSea, LooksRare, or Rareable, are kind of your top three NFT markets at the moment. Now, remember, NFTs can allow artists more direct access to buyers, and they also can potentially receive more money in secondary sales. So for example, on OpenSea, one of the things that people can do is when they mint NFTs or when an artist mints NFTs, they receive the initial payment when people mint them. But then also when that NFT is sold a second time, like a secondary sale, that artist receives more or less a royalty for every sale. Now, that's different than traditional artwork. Whereas if I went and bought a painting from an artist, and then I wouldn't sold that painting, I'm more than likely going to keep all of the money that I sold that painting for the second time, right? And that artist doesn't get anything. So that's a big benefit or a big potential benefit for artists who want to work with NFTs. And so there have only really been two major studies that have looked at anything related to NFT prices. And that was before I wrote this paper and this presentation. There might be more now. But at the time of writing, there were only two and they're both done by Michael Dowling, one who's looking at the land NFT and DeFi land and found that it was pretty inefficiently priced. But the prices increased rapidly. And that was pretty dependent on how many users were using the game and how many people were playing. And then also NFT prices have been shown to be independent of Bitcoin and Ethereum prices, right? So if Bitcoin goes up or Ethereum goes up, the NFT prices in terms of Ethereum and Bitcoin don't necessarily go up as well. So those are some things to keep in mind. So our research questions we're taking a look at today, there are three main ones. And the TLDR of what we're looking at is what are some of the influences that impact secondary NFTs, okay? But the three main questions we're looking at, number one is, does the ability to sort by active sales and auctions or sorry, does the ability to sort active sales and auctions by price and or attributes impact the NFT's final sale price? Question two is, does the existence of a roadmap impact the secondary sales price of NFTs? And three is, does the size of an NFT specific community impact that NFT's secondary sales price? Okay, so these are three things that artists or community managers or NFT sales platforms, for example, OpenSea looks where all those may want to know to be able to maximize NFT sales moving forward or maximize price or increase the speed of NFT sales. All of these questions may have something to do with those. And for those of you who are impatient and you just want to know the answer, yeah, all three of these things do impact NFT secondary sales prices. So we're going to dive into what that actually means and how they actually impact prices. But to be clear, all three of those questions are resounding. Yes, they do impact prices. What we're using today are called V-Punks. I'm going to explain what those are. We're just using this as a case study. And the reason why we're using it as a case study is because it gave us a very unique opportunity to study a marketplace both before and after auction sorting features, before and after a large community was formed, and before and after a roadmap was published. So this is a very unique case study where a lot of other NFTs don't have that type of opportunity to take a look at those before and after situations. So what are these? V-Punks, more or less, think of crypto-punks that we see on the Ethereum blockchain. This is very popular. It's about 10,000 unique 24 by 24 pixel algorithmically generated images. And the way that these were minted actually was pretty interesting. So the first 1,000 V-Punks only cost 390 vets while our VET, which is the ticker symbol for the V-Chain token. And then the final 9,000 to 10,000 V-Punks that were minted cost 3,900 vets. So it increased for every 1,000 that were minted, the minting price increased as well. So for those who got it really early, the minting price was cheaper compared to those who got it pretty late. Now, V-Punks are stored on what's called the V-Chain Thor blockchain. So for those who don't know, this uses a dual token model. So VET is the ticker symbol for V-Chain. And basically, what you do is you hold the bet in your wallet, and then that generates V-Thor. So that's a V-T-HR, if I'm recalling correctly, for the ticker symbol. And if you think of this in terms of Ethereum, when you're doing transactions on the Ethereum blockchain, you need to burn gas, which you're burning Ethereum for each transaction. Whereas with the V-Chain blockchain, what you're doing is you're doing transactions typically priced in VET. However, you're burning V-Thor. V-Thor is like the gas token. So you're generating that gas token by holding that in your wallet, and you're burning V-Thor. So just to give you a little bit of background there. Now, the V-Punks had created its own auction house for secondary sales and also just fermenting as well. The reason why is because the NFT marketplaces on the V-Chain blockchain and platform didn't really exist at the time when V-Punks launched. There wasn't like an open sea. There wasn't a looks rare. There wasn't anything like that. But when you want to go inside, okay, I'm going to go buy V-Punks second on a secondary sale on this website. And so the team who made V-Punks actually had to make their own auction house and their own website to be able to do auctions. So to give you some important dates, on July 25th, 2021, the initial minting of V-Punks began. Then on July 30th, the official V-Punk telegram channel was created. So this is interesting, right? Like they didn't have a telegram channel before they started minting. Whereas now what we see with a lot of NFT mints or drops, we're seeing telegrams or discords being formed beforehand. And they're using that to kind of hype up the mint. So this is an interesting case study here that they didn't do that before. And then finally, on August 5th, the 10,000th V-Punk was minted. So it took a couple of days for these to fully mint out. Where we're seeing other PFP NFT projects that have like 10,000 images. Some of them are minting out in the day. Some of them never minted out. This one, they fully minted all 10,000 of them. Took about, I don't know, two-ish weeks or less for the full mint. So really quickly, this is what they look like. The one on the top here on the screen is that's one of the ones that I own personally. So these are kind of what they look like. We've got four examples here. So there are many different character traits they can have. Each V-Punk has a corresponding rarity score. They are aliens, apes, and zombies. Those are the rarest type of like humanoid forms that they represent just over 1% of the total supply. And then they could have up to six attributes for the max and a minimum of one attribute. So they all look different. None of them are the same. And based on a combination of different attributes, they all have different rarity scores. And in theory, and what people postulate for these types of NFTs, is that the higher the rarity score, the more expensive that these NFTs will be on secondary sales. And so we're going to take a look at that as well in a second. But the data methodology that we have today comes from a few different places. So we have the V-Punk secondary sales. So we have on-chain secondary sales provided by the V-Punks team, specifically the community management team of them. And what we got from that data was the cost and vet for every single secondary sale, the rarity score for the V-Punk that was sold at the time, each individual characteristic of each V-Punk that was sold, and then the time of sale. And we also received the number of Telegram users provided by the V-Punk community management team. And so what that means is we took a look at the Telegram once it was launched, about five days after the initial minting period started. And we took a look at the number of Telegram users up until about one minute before every single sale. So if we were looking, for example, for sales today, what's today's date? May 24th. So if we were looking at a sale that happened at 12.13 right now, we'd look at the number of Telegram users up until 12.12 of today. And we would use that for our data point. So a couple of important dates that we need to take a look at here. Remember when I said that the V-Punks team needed to create their own auction house? Well, when they did that, the auction house was very, very bones. It didn't have a whole lot of features that what we're seeing today in some of these more mature auction houses like OpenSea, Luxury, Rarible, et cetera, et cetera, right? So on August 11th, they added a sort by price feature. On August 15th, they added a sort by rarity. And then on August 25th, they published a roadmap. So remember, it started minting on July 25th. And then if someone minted one of the V-Punks in the beginning, they wanted to sell a secondary, they could list it for sale, but no one could sort by price. They couldn't sort it by rarity. And so to do that, what you needed to do was basically click through each individual page to find whatever V-Punk you wanted. You couldn't sort them until August 11th and 15th. So that's a very interesting concept to take a look at and how this auction house evolved and how that potentially impacted the NFP sales later down the line. So what does our data look like? We have 7,272 sales that we take a look at. The start date for our data set is July 29th, 2021. And the reason why we don't start on July 25th, which is when minting started, is because we wanted to take a look at only secondary sales. We're not looking at minting data at all. So if something minted, or if there's a sale that happened for the 29th, we don't take a look at that as only 29th and afterwards. And it goes in from July 29th until September 6th. So about a little over one month more or less. So the average sales prices in vet was 9,328 vet. And unfortunately, I don't remember what that average sales price was in dollars. We can go back and take a look at the historical information on the coin tracker or multiple different websites. And then you can also take, we have 69% sales were post price sorting. So 69% of our 7,272 sales points that we're taking a look at was after August 11th. Then 42% were post the roadmap. So that's after August 25th. 62% were post the rarity sorting. So that's after August 15th. And then at the time at the end of the data set at the end of September 6th, we had 1,616 telegram users in total. So that kind of gives you an idea of what our data looks like. So here's our methodology. I quite frankly hate these types of slides, but I know we always have to talk about them. So these are our two base models that we have. And how we take a look at this is our dependent variable is going to be the log value of the sales price in the vet. And the reason why we don't just simply use the continuous variable of sales price instead of we take the log value of it is that the floor continuously rose throughout our time period throughout our data set. And we need to take that into consideration. So when I mean the floor, I mean the minimum sales price per NFT that was being sold on the secondary market, we take into account that the floor was rising to be able to really take a look at what these individual variables did to these secondary sales prices. So we take the log price of that at the time of sale. And then we have two different models here that we're looking at. And each one of these actually has three different equations. So on the right side of the screen, you'll see one, three, and five, and then two, four, and six. Those are different equations that we're going to take a look at later in the results slide. But basically, we're taking a look at how the sort by price function, the sort by rarity function and the published roadmap impacted sale secondary sales prices. And these are both binary variables. So if it has a one for sort by price, that means the sale took place after sort by price was implemented into the auction house. If it has one for rarity, it means that sale took place after sort by rarity was added to zero means it was done before. For that top equation, we have rarity score, and we also have the number of kilogram users as independent variables. And rarity score again is going to be more or less a combination of the different attributes that each feedback has. And what we wanted to do also is make sure that that rarity score had what we were to expect some correlation between these individual attributes that these view punks could have. So then that's why we had the second equation on the bottom. Again, the beginning is the same. We're using the log sales price event. We're also using the binary variables for sort by price, sort by rarity, and published roadmap. But instead of a rarity score, we instead have a variable that accounts for the number of attributes. Again, it could be between one and six. And then we also have the humanoid form, which means it was either a male, female, zombie, or an ape. And we're comparing those four types of humanoid forms to the alien form, specifically, because that has the lowest number of V punks that are alien human oids. And we also have the number of telegram users. So when we take a look at all this long story short, this should tell us, in theory, if any of these variables have an impact on the secondary sales price in terms of vent. All right. So that's that. Those are the models there. So let's take a look at it. Is there any impact? And if there is, what are these impacts? Now, again, this is one of those other slides for economics that I really hate showing, because there's a bunch of numbers. But it's very important to take a look at anyway. So the big things that we find here are once the auction house had features such as sort by price and sort by rarity, the actual secondary sales price for these NFTs decreased. And you notice those have three little aspects that's next to it. That means it was significant at a 1% level. Very important. We also found that project features and community grow, such as having a roadmap published and having more telegram users, both of those significantly increased the log value of these secondary sales for these V punks. So what does this really mean? Basically, sort by price and sort by rarity, which makes it easier for people to use the auction house actually decreased the secondary sales prices of these V punks, whereas adding a roadmap, publishing a roadmap. And in this one, for example, for V punks, they published the idea of creating what was called the VPU or the V punks utility token. So they actually launched the run cryptocurrency that is meant to be used in future play to earn games that will be featuring V punks. And so once that roadmap was published, the price of any NFT secondary sale in theory increased afterwards. And we can see that at a 1% level. And then also we see more telegram users as well also increase the secondary sales prices for V punks. And something that I don't really have on the left-hand side there, but I do want to address is that the rarity scores, the higher the rarity store, we see the higher the secondary sales price for these V punks. So that's rarity score. That's the fourth one down on the left-hand side. And then we also see for the more attributes that we have for V punks, the higher the secondary sales price. And then we also see that when we compare to aliens, apes, zombies, female and male humanoid forms all have a lower sales price than what aliens would have, comparative, right? And that makes sense because aliens have the smallest supply, followed by apes, followed by zombies, followed by females and males have the highest supply in this specific NFT drop. And so what we see is those have a pretty consistent impact on price where the ones with the lowest supply have the higher prices and the highest supplies have the lowest prices. That's not surprising, but it's something that we did confirm. And it's important to take a look at that as well. At the end of the day, what does this actually mean? And why is this important for anybody? Who's going to use this? First off, there needs to be, and I know this is really fast presentation, but that's okay. So we have time for questions at the end. First off, there needs to be a lot more research done that looks at the behavioral economics of NFT buyers. There's not really anything out there right now that looks at why people make certain decisions, what makes them want to buy one NFT over another, what makes one type of drop more exciting or the type of artwork that people want to buy. There's not a whole lot of research about any of preferences or any type of behavioral economic research for buyers. So that's one thing that we need to take a look at. We also should expand this study to include significantly more different types of NFTs, right? This is just a one NFT drop that we're studying here, and there's a million of them out there with datasets that are relatively easy to get if you just take on-chain data, download it, and you can put it into models. And so we can do that. We can take a look at if these results hold across other NFTs as well, or if this is a one-time thing. And then also, we would like to see more studies that will look at NFT sales across different established platforms, such as OpenSea, Variable, or the newer one looks rare, because, like I said, these sales were all done on an auction house that was brand new and was built specifically for V-Punks, right? Whereas these other larger websites like OpenSea, people know them. People go and buy stuff there all the time. They have huge volumes, and so studying how some sales are done there and velocity of sale and whatnot may be a very interesting thing for future researchers to take a look at. However, what our findings today mean, and who can these findings be used for is also super important, right? So really, this research is meant for people who are looking to enter the NFT market, so artists who maybe want to launch their own NFT line, and also for companies who are using their platforms as a place for secondary sales or auctions to take place for NFTs. And what we found is that community is super important. At the end of the day, when you run the numbers, we found that for every one new Telegram user that joined the V-Pump Telegram that increased the secondary sales price by 0.2%. Now, that sounds relatively small for an individual person, but I mean, if you think about that, five new people, that's 1%, that's compounding, right? So if you're able to get a ton of people, the large community, very excited about it, then you may be able to increase your price as an NFT artist. And that's not necessarily surprising, right? If you have a higher community demand for your product, for your NFT, maybe higher, if demand's higher in theory, we would expect prices to go up as well. Now, what we also found is that roadmaps were important. And I do want to flag that for a discussion at the very, very end here. But what we found in this specific study was that after the roadmap was published, the secondary sales prices of V-Punks actually shot up at roughly 33%, almost immediately. And it was pretty consistent for the days that followed the roadmap publication. So if you're an artist and you're able to build value and show there's a future in the product and the NFT that you're minting and putting out to the world, people may get more excited about it. They may be willing to pay more for the NFT if they believe in that roadmap and they see value down the line. So that's something that artists should consider potentially doing. Also, we found that the higher the rarity score and the lower supply of certain characteristics, the higher the NFT sales price, again, that's not surprising. But what that does mean is that if artists do want to maximize some of these secondary NFT sales, they do want to maximize hype around certain drops, they may want to increase these very hyper rare traits where maybe one of every 1,000 or something like that are a certain color or something like that. And having that higher rarity for certain types of NFT projects could potentially increase these secondary sales prices. And then we find that the sort by rarity and sort by price, when both of those functions were added to the auction house, we found that the prices, the secondary sales prices actually decreased and it was relatively significant. Now, I do want to just give my theory as to why that is. And again, this is just a theory, this is why more research should be done with this. But if you recall, when the auction houses were originally built for the V-Punks community, none of this, none of these sort features were there. So you had to go through and click every single page. And at times, that would be hundreds of pages of options for people to click through. And if they wanted to find a deal, they wanted to find one that was cheap, they had to keep spending a ton of time and just clicking, clicking, clicking, clicking, clicking, clicking. And eventually, they might have gotten higher. They might have gotten lazy and just bought one that they liked. They didn't really care about the price necessarily. So they didn't buy the cheapest one. They just bought one that they liked. But if you add these sort by rarity features or these sort by price features, then in theory, you can just sort by price lowest to highest or highest to lowest. And then buy the cheapest one and you immediately have one of these NFTs. It makes your job much easier as a consumer to just buy the cheapest thing on the market. And this is anecdotal. And I didn't, I don't have any proof on it with the data, but I did run a couple of tests. And we did see that after these sort by price and sort by rarity features were added, what we found was that those NFTs that were kind of selling in between the maximum price and the lowest price, those in between middle priced NFTs were not selling very much. It was typically the ones that were priced the highest or the ones that were priced the lowest that were selling. And those ones priced in between basically had to wait until the NFT price floor increased to get to their price. All right. So those are some of those things of big take home things. And I didn't say I wanted to flag road maps. After this study was conducted, there was another study that was done that looked at multiple different NFT collections on OpenSEA and used huge amounts of data, taking a look at secondary sales there. And what they found is that actually projects without roadmaps typically reached a higher at the height in terms of ETH for secondary sales than projects with roadmaps. So that's a very interesting concept, right? That's a very different finding than what this study found. And something that I think is very important to take into consideration with both of these is that this is a brand new area of research and we need a lot more research done that looks into pricing of NFT sales and how roadmaps impact them. Maybe something that should be looked at more because we are getting some conflicting data or conflicting results, my apologies, with different research papers and people that are publishing them. So that really concludes the main part of it. Here's my information for those who are looking at it. So thank you everybody for coming today. We really appreciate it. My cat me looks really wants to be in the video apparently. And we look forward to seeing you guys next time.