Fractional Ownership: A New Way to Invest

In recent years, technology has changed how we invest. Now, you can own a piece of things that used to be out of reach, like fine wines, art pieces, or luxury cars. This is called fractional ownership. Instead of buying an entire item, you buy a share, kind of like how everyone chips in for that fancy pizza. But here’s the catch: these shares can sometimes be tricky to sell later, just like when you try to sell a half-eaten pizza slice at a party.

#The Problem with Liquidity

Liquidity in finance means how easily you can buy or sell something without causing a big price change. If a market is liquid, it’s easy to trade. If it’s illiquid, you might be stuck holding that pizza slice way longer than you expected. In our new world of fractional ownership, markets can be quite illiquid. This means it can be hard to find someone to buy your share when you want to sell it. That’s where the research comes in-we want to figure out how to make these markets work better.

#Research Goals

The goal of this research was to simulate what happens in these markets using a method called agent-based modeling (ABM). Imagine if you had little virtual investors (agents) who buy and sell these fractional shares. By watching how they interact, we can learn about liquidity-like how to get more people to buy your pizza slice!

#How the Model Works

The agents in our model have a few different roles:

1. Pure Buyer (PB): These folks only want to buy shares. Think of them as pizza lovers waiting for the slice they want to come up at the right price.

2. Pure Seller (PS): These agents only sell shares. They’re like the people who, if they have an extra pizza slice, want to get rid of it for the best price possible.

3. Buyer Seller (BS): These agents can both buy and sell. They’re the pizza enthusiasts who are willing to trade their slice for another one they find more appealing.

#The Market Setup

Our model is based on real data from a FinTech startup that deals with fractional ownership. In this setup, investors can buy shares of assets worth €50 each. These assets can then be traded on a secondary market.

The market works like this:

• Trading Days: The market is open for trading at least once a month. It's like having a monthly pizza party where everyone brings their favorite slice to share.

• Trading Rules: Sellers can list their shares with prices set within certain limits of their asset's value. If your price is too high or too low, you won't sell much.

• Order Matching: Buy and sell offers are matched based on who gets there first, just like who grabs the last slice of pizza!

#Important Factors

Liquidity is influenced by several factors:

1. Number of Shares: The more shares available, the easier it is to sell. But if everyone wants to sell at once, it can become a problem.

2. Pricing: How the assets are valued matters too. If everyone thinks a slice of pizza is worth €2 when others think it’s worth €1, deals will be tough to make.

3. Market Rules: Each platform has its own set of rules that can affect how easily people can buy and sell.

#The Simulation Framework

We use ABM because it lets us simulate complex interactions between agents. Each agent has its own strategies for buying and selling. They act based on their budget and the rules of the market.

Agents can behave in simple or complex ways. Some are random, while others try to learn from the environment like that smart friend who knows exactly when to grab a slice of pizza before it’s gone!

#Agent Behavior

#Pure Sellers

Pure Sellers are the ones putting their slices up for grabs based on a shock that makes them want to sell. They decide how much to sell based on their current ownership and the market price. If they’re feeling generous, they might price their slices a bit lower to attract buyers.

#Pure Buyers

Pure Buyers are driven by the desire to own more than what they could buy directly. They browse through the offer book and are more likely to buy lower-priced shares. But let’s be honest; they might just pick a slice because it looks delicious!

#Buyer Sellers

Buyer Sellers have the ability to both buy and sell slices. They set their prices based on what they think other agents might want. They’re like that friend who knows all the secret pizza places and finds the best deals.

#Market Dynamics

The market goes through two phases: the pre-trading phase where sellers list their offers, and the trading phase where buyers can swoop in and make purchases. The model allows us to see how these interactions play out over time.

#Data Gathering

The data for this simulation comes from trading activities on a real platform, which helps us build a more accurate model. We collected information about trades, prices, and how many people were involved.

The stats show that many offers are not settled-think of it as many people wanting pizza, but not necessarily finding a buddy to share with.

#Results and Analysis

We compared the simulated market results to the real-world data. Surprisingly, the simulation could replicate the real market dynamics quite well. The main metric we looked at was the liquidity ratio.

What is the liquidity ratio? It’s the number of trades that actually happen compared to the number of offers made. If you had a pizza party with 10 slices and only 2 got eaten, that’s not very liquid!

#Sensitivity Analysis

We tested how changes in the agents’ behavior would impact liquidity. Here are some fun findings:

• More Sellers: If more sellers enter the market, they might make things less liquid because everyone is trying to get the best deal. It’s like having too many people fighting for the last slice!

• Buyer Activity: When buyers are more active, the liquidity ratio goes up. This means more people want to buy than sell; it’s a pizza party success!

• Price Range: Tweaking the price range for offers had different effects based on whether we were looking at sellers or buyers.

#Conclusion

In short, this research shows us how to better understand and simulate illiquid markets, particularly with fractional ownership. By modeling these agents and their behaviors, we can find new ways to improve liquidity.

The findings highlight that while some things in the market are predictable, others can be quite surprising. Just like that pizza party, you never know who will show up or how many slices will actually be eaten!

#Future Directions

Looking ahead, we want to make our agents even more diverse. We also plan to explore how changes in market rules might maximize liquidity.

So, the next time you think about fractional ownership, remember-just like in a pizza party, it’s all about sharing the right slices and keeping things flowing smoothly!