How Crypto Assets and Financial Markets Are Connected: A Simple Guide

Do you know how crypto assets, such as Bitcoin, Ethereum, or Dogecoin, are related to other financial markets? Learn the concept of spillovers

How Crypto Assets and Financial Markets Are Connected: A Simple Guide
Photo by fabio / Unsplash

Have you ever wondered how crypto assets, such as Bitcoin, Ethereum, or Dogecoin, are related to other financial markets, such as stocks, bonds, or commodities?

Do they move together or apart?
Do they influence each other or are they independent?
And why does it matter?

In this blog post, I will explain the concept of spillovers, which measures the degree of interconnection between different assets. I will also show you some interesting findings from a recent study by the International Monetary Fund (IMF)  titled "New Evidence on Spillovers Between Crypto Assets and Financial Markets" analyzes the spillovers between crypto assets and financial markets.

What are spillovers?

Spillovers are the transmission of shocks or movements from one asset to another. For example, if positive news about Bitcoin causes its price to rise, this may also affect the prices of other crypto assets or financial assets that are linked to Bitcoin. Similarly, if a negative event in the stock market causes investors to sell their stocks, this may also affect the demand and prices of crypto assets or other financial assets.

  • Spillovers can be measured in terms of returns and volatilities. Returns are the changes in prices over time, while volatilities are the fluctuations or risks in prices.
  • Spillovers can be positive or negative, depending on whether the movements are in the same or opposite direction.
  • Spillovers can also be direct or indirect, depending on whether the transmission is through a common factor or through a chain of effects.

To illustrate, let’s use an imaginary example. Suppose there are three assets: A, B, and C.

Asset A is a crypto asset,

asset B is a stock index, and

asset C is a bond index.

Suppose that one day, there is a piece of positive news about asset A that causes its price to increase by 10%. This is a shock to asset A that may have spillover effects on assets B and C.

One possible spillover effect is that some investors who own asset A may decide to sell some of their holdings and use the profits to buy more of asset B, which they think is undervalued. This would increase the demand and price of asset B, creating a positive return spillover from asset A to asset B.

This is a direct spillover effect.

Another possible spillover effect is that some investors who do not own asset A may become more interested in crypto assets after seeing the news and the price increase. They may decide to buy some of asset A or other crypto assets, using some of their funds that were invested in asset C. This would reduce the demand and price of asset C, creating a negative return spillover from asset A to asset C.

This is an indirect spillover effect.

A third possible spillover effect is that the increase in price and volatility of asset A may make some investors more cautious and risk-averse. They may decide to reduce their exposure to risky assets such as asset B and increase their holdings of safe assets such as asset C. This would decrease the demand and price of asset B and increase the demand and price of asset C, creating negative and positive volatility spillovers from asset A to assets B and C respectively.

This is also an indirect spillover effect.

As you can see, spillovers can be complex and dynamic, depending on various factors such as investor preferences, expectations, behaviour, information, market conditions, etc.

Spillovers can also vary over time and across different assets.

How do we measure spillovers?

To measure spillovers between different assets, we need to use some statistical tools that can capture the relationships between them. One such tool is called vector autoregression (VAR), which is a mathematical model that describes how each variable (asset) depends on its own past values and on the past values of other variables (assets).

Using VAR models, we can calculate how much each variable contributes to the forecast error variance of another variable. The forecast error variance is the difference between the actual value and the predicted value of a variable at a given time horizon. The contribution measures how much each variable explains or influences the uncertainty or risk of another variable.

Using these contributions, we can construct a table (matrix) that shows the spillover effects between different variables (assets). Each cell in the table shows how much variable j contributes to the forecast error variance of variable i. The diagonal cells show how much each variable depends on its own past values (own variance), while the off-diagonal cells show how much each variable depends on other variables (cross-variance).

What are the main findings from the IMF study?

The IMF study uses the spillover approach described above to analyze the relationship between crypto assets and financial markets. The study uses daily data on 23 crypto assets and 15 financial variables, covering the period from 2014 to 2023. The study also examines how spillovers change over time and during periods of stress or turbulence.

The main findings from the study are:

  • Crypto assets and financial markets are moderately connected, with spillovers increasing over time and during periods of uncertainty or shocks.
  • Crypto assets tend to transmit more spillovers to financial markets than vice versa, although reversals can occur during periods of financial stress.
  • Crypto assets are more connected with global equities, the VIX index, and gold, while less connected with bond indices, the US dollar, and other commodities.
  • Crypto assets may not serve as effective diversifiers or safe havens for investors, as they tend to become more correlated with financial markets during risk-off episodes.
  • Crypto assets could pose potential risks to financial stability, as they could act as sources or amplifiers of shocks across financial markets.

The study provides a comprehensive and rigorous analysis of the interconnections between crypto assets and financial markets, using a state-of-the-art methodology. The study also contributes to the policy debate on how to regulate and supervise crypto assets, given their potential implications for financial stability.

Here are the main points to remember:

  • Spillovers are the transmission of shocks or movements from one asset to another.
  • Spillovers can be measured in terms of returns and volatilities, using VAR models and forecast error variance decompositions.
  • Crypto assets and financial markets are moderately connected, with spillovers increasing over time and during periods of uncertainty or shocks.
  • Crypto assets tend to transmit more spillovers to financial markets than vice versa, although reversals can occur during periods of financial stress.
  • Crypto assets may not serve as effective diversifiers or safe havens for investors, as they tend to become more correlated with financial markets during risk-off episodes.
  • Crypto assets could pose potential risks to financial stability, as they could act as sources or amplifiers of shocks across financial markets.
Disclaimer: The views expressed in this blog are not necessarily those of the blog writer and his affiliations and are for informational purposes only.

Be the one who brings valuable insights to the table by sharing this post.

Want to be part of a community of informed and engaged individuals? Follow us on social media @Facebook, @Linkedin and @Twitter  

Subscribe on LinkedIn

Don’t be left behind! Sign up for FinFormed and start growing!