Fredo_Whitefox 9 minutes reading from Bitcoin

Crypto Valuation: Shifting Risk Factors

Crypto Valuations: Shifting risk factors

An exploration of crypto risk factor relevance to price and multifaceted nature for the crypto market. Looking at BTC ETH and XRP for overlap and differences in impact of social, tech and macro-economic factors.

*Disclaimer* This is rough draft of an idea that should be a research paper. I most likely need years of data that maybe difficult to currently aggregate without learning how to code. Feed back is welcomed.

The methodology for valuations has evolved with the ever increasing complexity of financial transactions. For small businesses or private business sales there are a number of different accounting based methods.

Book Value, Liquidation value, Discounted cash Flow (DCF) and earnings multiplier (EM) are popular and straight forward enough that they were used historically to be done by hand. The "Book" was literal for much of history when using these valuations.

Today these valuations are still used as a measure for credit worthiness for business looking for loans. Certain methods are better for different types of transactions. EX. a business sale using liquidation value may benefit the buyer more than EM if the Debt/Asset ratio is high

As our understanding of Markets and Tech expanded there was a need for a new type of valuation model. Capital Asset Pricing Model (Capm) was developed in the early 1960s. It describes the relationship between systemic risk and expect returns for stocks.

Capm moved us from the valuation of the company financials via accounting to the comparison of the company risk(Beta) versus the risk free rate (10Yr T-bill). Time value of money + the investment risk =Expected return for investor.

Capm makes two assumptions that leads to longer term variations to actual price. 1) Markets are competitive and efficient(everyone has the same information at the same time) 2) Markets are made up of rational and risk adverse people.

Over the next few decades there was an explosion of development in financial economics and mathematical finance. Arbitrage Pricing Theory (APT) and later Stochastic modeling.

Capm only looked at 1 variable versus return, APT looked at multiple variables but required research to establish the impact of the variable to price. Stochastic modeling uses random variables in an ever evolving trade analysis that provides a probability of outcomes.

The crypto valuation model I looked at yesterday was built using a stochastic discount factor, a time-dependent random variable. As we explored this was also made up of multiple variable taken into consideration by their statistical relevance.

Now we can discuss how the risk factors: Macro: Ukraine, Gas prices, Inflation, Decades of QE. Crypto has yet to break away from the Stock market and other Risk assets as we can see the correlation between the S&P and BTC.

Bitcoin's Correlation to S&P 500 Hits 17-Month HighBitcoin's Correlation to S&P 500 Hits 17-Month High

The factors I believe shift over time in Crypto making it harder to price are the social and Tech based factors. In social we have the holder communities, crypto specific influencers (TA, news, and FOMO), Developers (Of all sizes building and attracting others to the space).

In Tech, we have the code base for the different DLT/ Blockchain projects themselves. These networks are living evolving things as nodes and updates are rolled out over time. These tech changes have fundamental changes in the price of the native token.

First let's take a look at social: BTC and the Elon Effect. Elon could move the market with tweets and over time that has diminished. This is an example of how a risk factor goes from being significant to just another aspect of the ecosystem.

The Elon Effect: How Musk’s Tweets Move Crypto MarketsThe Elon Effect: How Musk’s Tweets Move Crypto Markets

Tech: Miner fee's as a function of the blockchain. Eth and BTC both reward miners. As economic activity, this should provide value to the network.

On April 30th was the highest gas day, the price came down.

Bored Ape Yacht Club caused Ethereum fees to soar to astronomical levelsBored Ape Yacht Club caused Ethereum fees to soar to astronomical levels

This would suggest that Gas is a function of price but does not contribute to it directly. Instead gas (network Fees) is really just paid to the minors for securing the network. This value is either already priced in or reached the point of diminishing returns.

Tech: High arbitrage opportunity, this applies to many crypto currencies but it was easiest for me to see it with XRP as I follow the space so much. The high number of Dex and CEX options allow for the creation of automatic trading bots for anyone willing to put in the work.

This leads to markets that are far more efficient than stocks. In this case efficient is used to denote who has access to data and can make trades if they are willing. The many arbitrage opportunities provide for the opportunity of realized risk free profit.

Example, The Solo Dex shows a price .02 cents lower than a Korean CEX. a bot set up to trade USDT to XRP then back to XRP to USDT on the exchange could trade a number of times in a min as the price normalizes. I am sure it normalizes fairly fast but these events happen everyday

The longer the settlement time the greater the profit opportunity for arbitrage trades. Historically long distances and risk provided traders with large profits. XRP itself is capable of being used as a arbitrage tool within FX.

Ripple's liquidity hub even looks like an arbitrage bot that consolidates findings for the best price instead of profiting the spread. A arbitrage focused business would just need the selling ability but could also provide liquidity to Ripplenet.

XRP is correlated to BTC, that we know for sure. The BTC price affects every coin, sometimes a few will break out but I have yet to see a coin break out long term and sustain it. If anything it is more common to see a step up to new levels and then they find a new % correlation.

In conclusion: I am still compiling the data to prove this but it seems that the XRPL's Tech efficiency coupled with the SEC lawsuit, negative market sentiment (Slowly shifting) and native arbitrage opportunities all conspire to enable a low price.

XRP and other efficient chains will have a harder time with price appreciation until they reach a watershed moment in usage, adoption or tech change. A lack of regulatory clarity is hurting price but long term the XRPL has a lot of room for onboarding new use cases, per the price

@threadreaderapp unroll

This post is based on this twitter thread.


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