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A simple way to estimate risks of DeFi projects

In the previous post (see [1]) we considered a simple way to determine a ROI on a lock-up period for a DeFi project. In our analysis of different projects we had assumed that they have the same level of risks.

In this post we consider a simple way to estimate risks for different DeFi projects using as a quantitative measure a probability of losses of our investments in DeFi projects.

In one of the previous posts (see [2]) we considered a simple way to make probabilistic forecasts using objective historical data or subjective experts estimations.

We use the same approach to make estimations of different risks in DeFi projects. We classify all risks on three groups: hardware related, software related, and human related.

Hardware related risks are risks of failure in computers and/or networks hardware on which blockchains are running.

Software related risks are risk of failure in software. Main components of this group are: blockchains, virtual machines, smart contracts, bridges, dApps (liquidity pools, automatic market makers, brokers, etc.). A blockchain is a distributed ledger where all transactions are recorded. Virtual machines are software that emulate work of real computers. Smart contracts are small programs executed on the virtual machines and simulate real contracts. Bridges are small programs that connect different blockchains. dApps (distributed applications) are big programs executed on the virtual machines. DeFi (decentralized finance) is a collection of dApps that simulate traditional financial institutions. For example, automatic market makers (AMMs) simulate market makers on financial markets, liquidity pools (LiPs) simulate traditional lending institutions (banks, credit unions, etc.), distributed exchanges (DEXs) simulate traditional stocks, bonds, commodities, currency, derivative exchanges.

The big advantage of DeFi is costs reduction on commissions to intermediaries and salaries to humans. For this reason ROIs and APYs in DeFi are significantly higher than in traditional financial institutions.

The big disadvantage of DefI is inability to recover losses via legal systems (courts, negotiations, etc.), because all functions are performed by dApps, not by humans. Therefore, investors in DeFi projects should be prepared that investment losses are final and are not recovered.

Human related risks are risks of losses due to human adverse actions. They may be developers, hackers, thieves, etc.

We use a simple free tool (risks assessments checklist) available at

This tool estimates the total probability of losses per year PrLY from a DeFi project based on estimations of probabilities of losses per year for each component, which can be estimated using objective data or subjective estimations.

We enter the estimated values for each component into the input text boxes and then click on the button “Estimate PrLY!”. The final result will be shown below the button, on the right side.



To interpret probabilities, it is useful to imagine that we can participate in a project 100 times. Then a number of cases when we have losses will be the estimated probability of losses in percentages

To compare risks for different projects we need to convert PrLY to a probability of loss on a lock-up period (PrLLP). To do this we use a free tool Pcalc available at:

For example, if we have PrLY=9.5% and a lock-up period is one month then we can with this tool to calculate that a probability of a loss on the lock-up period PrLLP is equal to 0.83%.




If we invest all our crypto into DeFi projects with positive PrLY we can receive ROI if there will not be losses, or we can lose all our investments. In this case (we lost all) we can not invest more and receive positive ROIs. The idea is that we keep one part of our investments in safe wallets/accounts and the second part we keep in high APYs DeFi projects. In the long run we will lose in some cases, but will have profits in other cases. If we find an optimal allocation of our cryptos between the safe and risky parts we may receive positive ROI on the whole portfolio (two parts) in the long run. Such problems (how to allocate assets/resources in optimal ways) are studied in optimal assets allocation theories.

In the next post we consider a simple way to find such optimal allocation structures for DeFi projects. Also we will show that for small investors, allocations of assets between two groups (risky and safe) is the most optimal solution, in the long term, if the risky group has the highest risk adjusted ROI.

Allocations between three and more groups are not optimal. Big investors use such allocations because they can not allocate big amounts of assets in only two groups, due to limits on amounts possible to invest in a single group. Therefore, small investors have better ROIs on their assets than big investors in the long run, if they have the same opportunities of investments in DeFi or other high APYs projects.


In the next post we consider a simple way to optimize your crypto yield farming and high APY investments.



[1] A simple way to convert a DeFi project APY to a ROI on a lock up period

[2] Simple ways to make probabilistic forecasts.


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I_g_o_r is an author of several books available on

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