A comparison of cryptocurrency volatility-benchmarking new and mature asset classes Financial Innovation Full Text

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Although more pronounced for cryptocurrencies, such an effect is shared among the two asset classes for the time period considered. The literature relevant to this study bifurcates into two distinct yet interconnected domains. The first is the foundational body of work on volatility modeling in finance, which has been a key topic in financial econometrics. Bollerslev et al. (2006); Barndorff-Nielsen et al. (2008); Chen and Ghysels (2011) highlights the effect of negative https://www.xcritical.com/ equity returns on increasing future volatility.

Low Liquidity (relative to other markets)

The crypto world is dynamic, and success lies in your ability to adapt, respond, and stay resolute in the face of ever-shifting market conditions. To profit from this dynamic landscape successfully, long-term investors diversify their portfolios, employ prudent risk management, and maintain unwavering faith in blockchain technology’s transformative potential. In the ever-evolving crypto realm, volatility becomes a catalyst for growth, a fundamental consideration for those committed to the crypto volatility trading long-term vision. The speculative nature of cryptocurrency markets amplifies their volatility.

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Includes the results of the empirical analysis, from the model estimation using panel data to the robustness check by repeatedly fitting the same model specification over a different time window. In addition, we carry out the individual estimation of the same model for every entity in the cryptocurrency cross-section to disentangle the aggregate results and validate them. Then discusses the key findings and the implications of our results for the cryptocurrency ecosystem and provides the takeaways from the volatility analysis.

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The WLS estimation is based on a preliminary Ordinary Least Squares (OLS) estimation, which is necessary to construct weights as the inverse of the fitted residual from such an OLS model. When estimating the panel regressions, we adopt the Newey-West Heteroskedasticity and Autocorrelation Consistent (HAC) estimators. This approach is particularly useful for addressing the potential issues of autocorrelation and heteroskedasticity in panel data, which are common in financial time series data. The Newey-West HAC estimators allow us to produce standard errors that are robust to these issues, thereby ensuring that our inference is more reliable.

Examining day-to-day crypto volatility and why it’s important

Various technical analysis tools can assist in identifying patterns, trends, and potential price movements. A low liquidity market – such as the cryptocurrency market – is easily susceptible to sudden and aggressive fluctuations in prices, since a single large order can move the markets and send the price soaring or crash in an instant. This is because there is an insufficient number of market participants and orders in the market to buffer against potentially large orders that can move the markets.

How Does Leverage in Crypto Impact Volatility?

Such an effect contrasts the notion of the asymmetric impact of returns on the realized variance and points to an inverted asymmetry inherent in the cryptocurrency data. The presence of the leverage effect in a financial return series is often motivated by the market participants’ response to adverse shocks. The increased volatility due to negative returns can start a self-reinforcing mechanism that leads to sudden asset “firesales”, exacerbating the uncertainty even further. Given the novelty of cryptocurrencies as an asset class, it is essential to determine if the asymmetric effect of volatility, commonly seen in mature markets, is also present here. Some previous work tested the asymmetric effect of cryptocurrency returns at daily frequency (Phillip et al. 2018; Baur and Dimpfl 2018; Brini and Lenz 2022) on a more or less comprehensive cross-section of cryptocurrencies. The results at the daily level detect the absence of a statistically significant leverage effect in such a market, showing an inversion of the asymmetric effect of returns.

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Understanding and harnessing volatility is a key aspect of successful trading. In the world of trading, volatility isn’t just a random term; it’s a category of indicators that serve to measure the price’s fluctuation within a specific time frame. One of the reasons why the pandemic had such a strong effect on the crypto sector is because it appeared a lot more secure than cash. These and other avenues carry some promise to address day-to-day volatility and make cryptocurrencies more viable for everyday use.

Understanding market volatility

Then, we present the collected data outlining descriptive statistics of the universe of the two asset classes, cryptocurrency, and equity. The final part of the Section describes the model specifications employed and the estimation techniques to gain insights into the drivers of future volatility. After analyzing the cryptocurrency ecosystem at the macro level, we analyze the data in our universe at the micro level by individually estimating each model’s specifications for each entity.

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The overlooked feature of this, however, is that price swings communicate important information to founders and investors, and builds previously unseen levels of transparency into the system. Moreover, we observe less persistence and volatility memory in cryptocurrency than in traditional equity markets. This finding motivates a deeper investigation into the underlying factors that contribute to these distinctive volatility patterns.

• This complexity can sometimes be averaged out in panel estimations but might cause problems in individual time series estimations.
• Typically, historical volatility is calculated over a specific period in the past, such as the past day, month, or year.
• Moreover, staying informed about external events and market sentiment drivers is equally vital.
• Which is nonzero only when the daily return of the asset under study is negative.
• Lastly, the period covered by our dataset, from 2020 to 2022, allows us to appreciate the significance of our selected volatility drives under the latest bullish and bearish market regimes that characterize the cryptocurrency market.
• The standard deviation of daily returns for the preceding 30- and 60-day windows.

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All the model specifications are estimated in-sample since our scope is to obtain insights regarding the driving factor of the volatility process. The forecasting problem is not treated in this study, although the results can be beneficial to improve modeling for that purpose. Understanding the different types of volatility in crypto is important for investors and traders who want to manage risk and make informed decisions about buying, selling, or holding cryptocurrencies. By monitoring historical, implied, and realised volatility, investors can gain a better understanding of how the crypto market is likely to behave in the future and adjust their strategies accordingly. Realised volatility is a measure of how much a cryptocurrency’s price has actually fluctuated over a given period of time. It is calculated by taking the standard deviation of the logarithmic returns of a crypto over the given time period.

The most significant subtlety of volatility lies in its manipulation of human nature and weaknesses. Very sharp price swings strongly impact the emotions of traders and investors. They can evoke intense feelings, both pleasant (euphoria) and negative (fear).

Further to this, ChatGPT’s role in cryptocurrency analysis is significant, offering real-time updates, market sentiment analysis, technical analysis, and educational support. It can answer queries, assess risks, aid in portfolio management, and suggest trading strategies. Its insights should be combined with extensive research and diverse information sources. Cryptocurrency trading involves substantial risks due to the market’s extreme volatility and speculative nature.

Volatile trading can sound scary, but there are several ways to take advantage of these speedy price movements. If one digital asset experiences a decline, the overall impact on the investment portfolio is lessened due to the presence of other cryptocurrencies. This helps to reduce the overall risk for the investment portfolio and protect investments from volatility. Volatility creates uncertainty across any market, making investment planning much more challenging. Constant price swings often hinder investors from deciding on investment assets and determining budgets for such investments. It’s important to note that none of these methods allow for a 100% confident assessment of how volatile stocks or digital assets are.

Moreover, staying informed about external events and market sentiment drivers is equally vital. News or expectations about events can significantly influence market volatility, creating either bullish or bearish sentiment. Traders must be well-versed in key events in the financial world, concerning both crypto and traditional markets, to anticipate and prepare for the shifts in market dynamics. It’s crucial to remember that cryptocurrency market volatility can lead not only to gains but also to substantial losses.

Traders often make decisions based on expectations rather than intrinsic value, leading to sudden price fluctuations. High-frequency trading, margin trading, and the prevalence of trading bots also contribute to rapid changes in price. The dynamic and 24/7 nature of cryptocurrency markets further intensifies the frequency and speed of trading, adding to the volatility.

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