Crypto, Fiat, and Assets Are Now Strategic Rivals

When discussing investments in specific asset classes, be it real estate, stocks, or crypto, it is important not to look at them in isolation. This is because they are all competing with each other for the same limited pool of capital and attention from the investing public.

As such, various financial markets should be seen as the complex result of the interactions between many factors influencing not just specific asset classes, but also the interplay between these asset classes.

Game theory is a branch of applied mathematics that can help explain better how this works. This analyzes situations in which parties, called players, make decisions that are interdependent, which causes each player to consider the other player’s possible decisions, or strategies, in formulating their strategy.

In a newly published scientific paper¹, two researchers at the University of Stavanger (Norway) use game theory to model the impact of cryptocurrencies on financial strategy. Their model covered the actions, strategies, and interplay between households, governments, central banks, firms, CeFi (Centralized Finance), and DeFi (Decentralized Finance).

They published their findings in the journal International Review of Financial Analysis, under the title “A game-theoretic model of cryptocurrencies, fiat currencies and assets”.

Using Game Theory For Crypto & Macroeconomics

While applicable to games like chess, the most important applications of game theory are in the fields of politics and economics. Game theory has been used to model and shape central bank policies, expectations of the public about inflation, international trade conflicts, and many other applications.

A key concept here is “utility”, which assigns a number to each player’s alternatives to convey their relative attractiveness. Maximizing someone’s expected utility automatically determines a player’s most preferred option.

It should be noted that utility is not the same as maximum gains. For example, sometimes, making sure some gain occurs can be considered optimal by a player, even if this means leaving some money on the table.

In its most advanced forms, game theory also introduces more complex elements, like information asymmetry (some actors know more than others), the effect of past behaviors on future expectations, and the understanding that multiple Nash equilibriums (an outcome in a non-cooperative game for two or more players in which no player’s expected outcome can be improved by changing one’s own strategy) can exist at the same time.

The model used in this study was deployed as a five-player “game”, representing respectively:

• Households, who choose consumption, labor, borrowing, and asset allocation.
• Governments, which choose taxes and penalties.
• Central banks, which choose fiat interest rates and money creation or withdrawal.
• Private firms, which choose wages and production conditions.
• CeFi and DeFi banks, which choose lending terms in fiat and crypto markets.

The idea is that the net returns from fiat, crypto, and other assets come from independent choices regarding all these factors.

“Readers can therefore understand the full model as an expanded version of a simpler mechanism: policy changes alter borrowing incentives, borrowing changes inflation and balance-sheet conditions, and those shifts feed back into portfolio choice and institutional payoffs.”

Building A Crypto Macroeconomics Game Theory

Setting Up The Stage

The model distinguishes traditional assets (e.g., fiat currencies, bonds, stocks) from cryptocurrencies.

Traditional assets, such as fiat currencies (including CBDCs), are centrally issued and controlled, subject to printing/withdrawal by central banks, inflation adjustments, and full taxation/penalties.

Cryptocurrencies, in contrast, are decentralized, with fixed or algorithmically limited supplies (e.g., Bitcoin’s cap), enabling new uses beyond traditional currencies:

• Programmable smart contracts for automated lending in DeFi.
• Tokenization of real-world assets (e.g., assets like NFTs as a distinct class).
• Borderless peer-to-peer transfers reduce transaction costs.

This makes both the model and real-life cryptocurrencies resilient to central manipulation. In this model, crypto’s innovation drives DeFi utility gains (including anonymity for certain assets), but volatility may deter traditional adoption for “normal” transactions.

However, to keep the model simple enough and stable, behavioral biases were not introduced (irrational action from an economic standpoint), and economic shocks or spikes in volatility were not included.

In this model, inflation, policy credibility, expected returns, volatility, taxation, adoption, and trust are all impacting the behavior around financial assets and the future return of cryptocurrencies and traditional asset classes. To capture this interplay, the researchers tracked 11 distinct asset classes, categorized by their economic function:

These 11 assets and the behavior + interactions of the 5 types of “players” were modeled into 26 derived equations, encompassing utility functions, constraints, inflation definitions, and equilibrium conditions.

Model Calibration With Different Countries

The authors calibrated their model to the US and Nigeria in order to relate the results to recognizable institutional and macroeconomic environments. For example, here are some of the changes made:

• The US is modeled as more consumption-driven.
• Nigeria’s model was modified to match its higher target inflation environment.
• The transaction cost parameter was lowered for the US to reflect more efficient digital banking and crypto exchange conditions and raised for Nigeria to reflect the informal economy, weaker infrastructure, and higher transaction frictions.

The same calibration could be done for many more countries and business environments. This method also lets the model equations show what would happen if some parameters were to change—for example, if new crypto regulations are adopted, if inflation rises, etc.

What Can the Game Theory Model Tell Us About Crypto?

What Did The Model Show?

When running the model, the researchers came to 12 different “formal propositions” on how crypto is affected by borrowing, inflation, portfolio substitution, wages, and utilities responding to changes in key household, monetary, and structural parameters. To make these findings easier to consume, they can be organized by their core financial dynamics:

Dynamics of Borrowing, Interest Rates & DeFi Utility

• Proposition 1: An increase in fiat borrowing attractiveness can raise fiat borrowing. In contrast, cryptocurrency borrowing and DeFi bank utility exhibit initial growth followed by contraction.
• Proposition 2: Higher perceived borrowing costs in both fiat and cryptocurrencies can still increase fiat borrowing when the induced inflation benefit outweighs the direct borrowing cost.
• Proposition 3: Fiat withdrawal can reduce fiat borrowing and CeFi bank utility, while still making decentralized finance relatively more attractive.
• Proposition 4: Higher policy rates can expand both fiat and cryptocurrency borrowing in the context of high inflationary expectations.
• Proposition 5: Cryptocurrency inflation can cause a portfolio reallocation that increases cryptocurrency borrowing and DeFi bank utility.
• Proposition 10: Fiat money printing asymmetrically crowds out cryptocurrency borrowing, as central bank fiat currency printing escalates fiat borrowing, inflation, and central finance utility.

Dynamics of Wages, Labor & Market Structure

• Proposition 6: Wage allocation to consumption increases with the utility of holding fiat currency.
• Proposition 7: Greater wage curvature (greater reduction in salary from high unemployment conditions) alters the fiat–crypto borrowing mix in ways that favor decentralized finance.
• Proposition 8: A higher population strengthens government utility, because larger household numbers expand the tax base and induce compensating borrowing and portfolio adjustments.
• Proposition 9: Higher employment rates can reduce nominal wages, yet improve both household and firm welfare.
• Proposition 11: More numerous companies raise household wages and consumption, and reduce borrowing and inflation.
• Proposition 12: Higher wages compress borrowing and inflation while hurting firms.

Policy Recommendations

Together, these propositions paint a complex picture of the interaction between crypto & DeFi and the rest of the economic system. This led the authors to make a few recommendations:

The first one is a warning that conventional monetary tools may not operate in hybrid fiat-cryptocurrency systems in the same way as in purely fiat economies. For example, such a hybrid system will react to tighter fiat conditions differently—in some condition sets boosting traditional finance, in some other sets doing the opposite.

A direct consequence is that tax policy and enforcement should be coordinated with financial regulation.

“This points toward balanced tax design, proportionate penalties, improved reporting standards, and better institutional coordination across tax authorities, financial supervisors, and central banks. Excessively harsh enforcement in one market segment may not eliminate risk, but merely relocate it.”

A third recommendation is that CBDCs (Central Bank Digital Currencies) should prioritize payment efficiency, low transaction costs, interoperability, and legal clarity.

In the same way, financial regulation should target resilience, not only suppression. A policy hostile to cryptocurrencies and reducing decentralized finance through tighter fiat conditions may fail or even backfire.

“A well-designed CBDC may therefore improve financial inclusion and transaction efficiency while limiting destabilizing shifts between centralized and decentralized finance.”

Lastly, wage compression or income insecurity may push households toward greater reliance on both fiat and crypto borrowing. Policies that stabilize household income may therefore support not only welfare, but also macro-financial resilience.

The context of the country also matters, with higher inflation and a stronger informal finance system having a massive impact on the use of fiat and cryptocurrencies.

Overall, this game theory macroeconomic model proves that central banks and policymakers need to update their mathematical and mental models for the existence of cryptocurrencies. What worked in the past might have completely opposite results now that a new parallel, and radically different type of currency exists and is accessible to the public.

“The central policy challenge in hybrid fiat-cryptocurrency economies is therefore to manage substitution, spillovers, and incentives across markets rather than to regulate each market in isolation.”