The digital currency in the eyes of economists – risk articles: the wind

Digital Currency in the Eyes of Economists: Series Preface

The digital currency in the eyes of economists – Classification: Bitcoin with no place for souls

The digital currency in the eyes of economists – market articles: will there be no leek in the currency circle?

The Digital Currency in the Eyes of Economists – The Exchange: The Glory of the King

The digital currency in the eyes of economists – price articles: ups and downs in the bubble

[Editor's note] Faced with the new challenges of digital currency, economists are divided into two categories, one is scornful, and it is not worth mentioning that digital currency is a speculative bubble ; the other is cautiously accepted and begins cutting-edge exploration. As the digital currency grows, more and more economists join the second camp. For this reason, Kay unveiled a series of articles on “Digital Currency in the Eyes of Economists” , which is the most comprehensive review of digital currency literature. In the six aspects of classification, market, exchange, price, risk, and supervision, the global economists' research on the frontier theory of digital currency is summarized , which provides a useful reference for interested researchers. This article is the fifth risk article in the series, the next one is the last supervision article, so stay tuned.

In the British "Financial Times" November 30, 2017 titled "Bitcoin turned from a bull market to a bear market and changed back to a bull market in one day", one paragraph was written as follows: "At Lehman Brothers in September 2008 After the fall, the US stock market spent 24 days, fell 20% and then went to the bear market; and Bitcoin, the new era of cryptocurrency, has been breaking the bull market's highest record, breaking the bull market again in just 6 hours on Wednesday. record of."

Risk and volatility research

High risk and strong volatility are characteristics of digital currency . Whether it is from the intuitive feelings on the historical price chart or from the public financial media reports, we can clearly perceive the characteristics of digital currency, which is different from traditional financial assets.

And the academic research on the risk and volatility of digital currency, especially bitcoin, is mainly concentrated in several directions: First, study the returns, volatility and speculative nature of Bitcoin, and compare other assets, such as gold, dollars and securities. Used to understand the classification and role of Bitcoin. The second is to explore effective ways to study the volatility of Bitcoin. Third, bitcoin volatility trends over time, as well as differences in volatility from short- and long-term, low-frequency and high-frequency perspectives. The fourth is the relationship between other types of digital currency and bitcoin in terms of volatility . The fifth is to use the Random Walk and Borwnian motion theory to study the long-term memory (Long memory) and continuous volatility of Bitcoin volatility.

Asset allocation is essential

Is there any practical application to study the risks and volatility of digital currencies? Not only is it significant, but digital currency is likely to be an indispensable portfolio for asset allocation.

Looking back at the taxonomy in the series "Digital Currency in the Eyes of Economists", we mentioned that many researchers classify bitcoin as an asset rather than a currency. In addition, some scholars believe that bitcoin belongs to commodities, and scholars simply put Bitcoin is recognized as a new hybrid asset (see the Classification section for details). Grinberg (2011) questioned the classification of bitcoin as securities, investment contracts, commodities or currencies, and believed that the road to legalization of Bitcoin would not be smooth, which would cause its price volatility to be large.

Because the distinctive characteristics of digital currency make it difficult to classify, it makes it suitable for the role of alternative assets in asset allocation, in line with the principle of diversified investment.

Dyhrberg (2016a) believes that Bitcoin has a role in the financial system and investment portfolio. Katsiampa (2017) also holds a similar view. He believes that studying the volatility of Bitcoin is important because the market value of Bitcoin is growing rapidly and its position in the financial market is becoming more prominent.

In order to study the volatility of Bitcoin and other digital currencies in more depth, we need to find the most suitable models and methods. Dyhrberg (2016a) used the GARCH model to study bitcoin volatility and found that bitcoin volatility became higher with observation time and exhibited non-stationarity. He found evidence of Enders (2010). Enders said that the most noteworthy feature of Bitcoin is the volatility of volatility, which is extremely high in some periods and low in others. Through Engle's Lagrange Multiplier Test, the residual value of the bitcoin price logarithm shows a strong ARCH effect, which confirms the variation of bitcoin volatility. Katsiampa (2017) goes one step further on this. He uses a variety of GARCH models to test the volatility of Bitcoin and compare the results to find the best model for bitcoin research. He found through research that the AR-CGARCH model is the best model, and at the same time, in the study of bitcoin volatility, special attention should be paid to the medium- and long-term and short-term components of Conditional Variance. However, Klein et al. (2018) found that bitcoin returns showed asymmetry in the market shock, so FIAPARCH was considered to be the best model for studying the conditional volatility of Bitcoin.

Cheah and Fry (2015) argue that Bitcoin is a highly speculative and volatile market, full of speculative bubbles, and that the value of Bitcoin is uncertain and close to zero. Blau (2017) did not agree. He believes that after the first large price fluctuations in Bitcoin in 2013, it can be concluded that the high volatility of Bitcoin is not caused by speculative trading. His reasons are: during the period of high volatility, speculative trading volume is not high; speculative trading volume and bitcoin volatility are not positively correlated, but negatively correlated; using Newey and West (1987) to label the difference control variable The univariate and multivariate tests of the GMM model yielded the same conclusion as above: the use of a probabilistic regression model to measure the extremes of bitcoin price extremes and the level of speculative trading is negatively correlated.

From another perspective, there are more than 2,000 digital currencies on the market, and their volatility is not the same. Understanding their risk characteristics, ie volatility, helps with investment and risk management. Gkillas and Katsiampa (2018) use the latest five mainstream currencies (bitcoin, Ethereum, Ripple, Bitcoin Cash and Litecoin) using the principle of extremum (Extreme Value Theory) to study the characteristics of the tail region of its return. Their research found that bitcoin has the highest cash risk, while bitcoin and light currency are the least risky.

Internal and external risk management and hedging

Bitcoin risk management and hedging can be viewed both internally and externally: internally, using Bitcoin derivatives, such as Bitcoin futures, to hedge against the risk of price fluctuations in Bitcoin or other digital currencies, which requires understanding Bitcoin derivatives. The intrinsic link between goods and all digital currencies and the effectiveness of hedging; external refers to the risk of investing in bitcoin to reduce the investment of other asset classes, that is, using the characteristics of weak correlation between bitcoin and other types of assets to diversify investment. The aspect is more concerned with the dynamic relationship between Bitcoin and the overall market, and not limited to the relationship between Bitcoin and certain types of investment products. At present, academics pay more attention to external risk management and hedging. There are few researches on internal risk management. It may be that Bitcoin derivatives have just come out, and it will take some time for them to play their role.

Internal risk management and hedging are mainly based on whether the bitcoin futures that began trading in December 2017 can actually be used to hedge the risk of other digital currencies other than Bitcoin, also known as Cross Hedging. To test the effectiveness of cross-hedging, we used the Minimum Variance Hedge Ratio, which assumes that the price is normally distributed. The minimum volatility hedge ratio h calculated by this model is a percentage of the entire asset that can be hedged by Bitcoin futures.

The reason why h is called the minimum volatility hedge ratio is because even if you use another method, you can no longer use the hedging method to reduce the risk of the entire portfolio. In this way, it can be calculated that the Ripple h is 0.612, the Ethereum is 0.483, and the Dodge is 0,861. Taking Ripple as an example, 0.612 means that if you hold Ripple, you can use the short bitcoin futures to cover the risk of 61.2% Ripple. In the same way, it can cover the risk of 48.3% in Ethereum and 86.1% in Dodge. In other words, using the same bitcoin futures to hedge, the risk efficiency used to hedge Dodge coins is higher than that of Ripple, and the efficiency of hedged Ethereum is the lowest. Because 13.3% of Dodge coins are exposed to risk, and Ethereum is still 51.7% exposed to risk.

These minimum volatility hedge ratios represent systemic risks in digital currencies, that is, the risks that all digital currencies face together. On the other hand, the part of the minimum fluctuation hedge ratio that is not covered, such as 13.9% or 51.7%, is an independent risk. This type of risk has nothing to do with bitcoin. As can be seen from the data, most digital currencies are not related to each other. We can only say that Bitcoin futures and other derivatives of Bitcoin can effectively hedge the risk of Bitcoin, but the risk management of other digital currencies is not very effective.

However, from the historical perspective of the development of the digital currency industry, the correlation and hedging ratio between digital currencies will become smaller and smaller. The main reason is that the underlying technology of digital currency has evolved very rapidly. When Bitcoin appeared, it occupied the majority of the digital money market at that time. Most other digital currencies in the same period were derived from the bitcoin system, using the same proof of work mechanism (Proof-of- Work), we call it the first generation of digital currency. Later Ethereum and the subsequent emergence of a large number of alternative currencies were based on the Smart Contract mechanism, which we call the second generation of digital currency. Recently, EOS has developed rapidly, based on the Proof-of-Stake, which we call the third generation digital currency. As various types of digital currencies have emerged, these different types of digital currencies are based on different underlying technologies and principles, which inevitably result in smaller linkages and hedging ratios.

External risk management and hedging , using digital currency to reduce risks in traditional financial investment and asset management has always been a hot topic of research. Baur et al. (2018) found that the return of Bitcoin is very different from other traditional assets – securities, foreign exchange, commodities, etc. The correlation between them is extremely low, so Bitcoin has become a good tool for risk divergence in both normal and volatile market environments. Baur also found that one-third of Bitcoin is held by investors, so the function of Bitcoin's exchange media intermediary is weak relative to other assets. However, as more people accept and use Bitcoin, fluctuations in Bitcoin can affect the stability of the financial and monetary systems. However, from now on, especially from the low correlation of Bitcoin and other assets, we still think that Bitcoin is a good risk diversification investment tool, but we are also cautious because of the risk to Bitcoin. The nature of doing all-round analysis and research is still only at a very early stage.

Baur and Lucey (2010) define the use of hedging assets, Diversifiers and Safe Haven. Hedged assets refer to assets that are irrelevant or negatively related to the return of the hedged assets; risk-distributed assets refer to assets that are positively correlated with the hedged assets but are not absolutely related; safe assets refer to the market turmoil , assets that are negatively correlated or unrelated to hedged assets.

Scholars used these hedging definitions as standards and found some interesting conclusions using dynamic correlation methods.

Bouri et al. (2017) used the Dynamic Conditional Correlation (DCC) model to detect bitcoin and global major stock indices, bonds, oil, gold, commodity indices and the US dollar index to distinguish bitcoin from hedging assets and risk diversification assets. Still a safe asset. The study shows that bitcoin reflects more of risk-spreading asset attributes rather than hedging asset attributes. However, Bitcoin reflects the security asset attributes when Asian stocks plunged . This study shows that bitcoin's hedging, risk diversification, and security attributes change over time. Other scholars have reached the same conclusion at different time points.

Another study uses the same methods and models as Bouri, but the target is not a large class of financial assets, but a major currency. Urquhart et al. (2018) studied whether bitcoin can be used as a hedge or safe asset in the mainstream currency on an hourly basis, based on its daily high volatility. The study used the Asymmetric Dynamic Conditional Correlation (ADCC) model to analyze and find that Bitcoin can become a hedge asset for Swiss Franc CHF, Euro EUR, GBP GBP, and become Australian Dollar AUD, CAD CAD and Japanese Yen. JPY's risk diversification assets. The study also applied the non-temporal Hansen (2000) test model to conclude that Bitcoin could become a safe asset for CAD CAD, CHF CHF and GBP GBP in an extremely volatile market environment.

Bouri and Urquhart's research shows that bitcoin is not a hedge fund, and that it is normally a risk diversified asset and a safe asset. At the same time, we can infer that the function of bitcoin's hedging risk can be better realized at high frequencies.

Klein et al. (2018) argued that bitcoin and gold are vastly different from the perspective of the bitcoin's hedging function . In times of market turmoil, gold has long been considered a good place to avoid risks, while bitcoin is different, and bitcoin is as volatile as the market. Klein studied the fluctuations of bitcoin and stock indices and commodity indices by using dynamic correlation analysis and compared them with gold. In the comparison, the portfolio analysis method is used to emphasize the performance of gold and bitcoin in the market turmoil. The BEKK-GARCH model is used to measure the time-Varying Conditional Correlations of gold and bitcoin. The results show that gold and silver have similar fluctuation characteristics. However, from the perspective of asset portfolio, Bitcoin does not have the property of a safe asset like gold. Using the portfolio (Portfolio-Based) as a benchmark to measure the bitcoin's ability to hedge against the S&P 500, gold, and MSCI global stock indices, gold's hedging function dominates and averages 36.98% of assets. The hedging effect can reach up to 90%. In contrast, Bitcoin can only have a 3% to 4% hedging function. The chart below shows a comparison of the hedging functions of gold and bitcoin in portfolio risk management in the Klein report. It is clear that Bitcoin's hedging function is far less than gold.


However, early Dyhrberg (2016a) also used the asymmetric GARCH model to study the hedging properties of bitcoin and gold, but reached a different conclusion. Dyhrberg proved that Bitcoin can hedge against the Financial Times Stock Exchange Index, while Bitcoin can also hedge the US dollar index in the short term. Bitcoin has similar hedging power to gold in multiple dimensions, so the study suggests that Bitcoin can be used as a good risk management tool like gold.

Why do you come to different conclusions in the same way? We saw that Dyhrberg used the data for two years earlier than the article by Klein et al., so it may be inferred that bitcoin volatility itself has changed a lot after two years. Interestingly, even the same author has a different view of bitcoin volatility and hedging. Dyhrberg published two research articles in 2016. Dyhrberg (2015a) believes that Bitcoin's hedging is between gold and US dollars. Dyhrberg (2015b) believes that Bitcoin's hedging is higher than originally estimated and can be used to hedge UK. Stock and dollars.

Different researchers, even the same researcher, have different views on the bitcoin's hedging function at different times, which is not uncommon in the digital currency world, because digital currency is a new field of rapid change. This can be seen in the research of many scholars who study the structural break of digital currency. Among them, Thiesa (2018) used the Bayesian Change Point (BCP) method to study the average return and fluctuation of Bitcoin, and found that the structural changes of Bitcoin were very frequent.

From these economists' research on the risk volatility and hedging properties of Bitcoin in different periods, we can think that although Bitcoin is not a versatile hedge asset, it can be targeted for a certain period of time and efficiency. Some mainstream currencies reflect good hedging. At the same time, most studies like to compare bitcoin with gold because they play a similar role in risk management of other types of assets. The conclusions of these studies generally agree that Bitcoin and gold have similarities, but Bitcoin's risk management and hedging functions are not as good as gold.

End of risk, the next article of supervision – keep up with the times, so stay tuned.

=== References: ====

· Dyhrberg, AH, (2016a). Bitcoin, gold and the dollar – A GARCH volatility analysis, Finance Research Letters, Volume 16, 2016, Pages 85-92, ISSN 1544-6123,

· Katsiampa, P., (2017). Volatility estimation for bitcoin: A comparison of GARCH models. Economics Letters, Volume 158, 2017, Pages 3-6, ISSN 0165-1765, .econlet.2017.06.023

· Enders, W., (2010). Applied Econometric Time Series. Wiley.

· Cheah, ET, Fry, J., (2015). Speculative bubbles in Bitcoin markets? An empirical investigation into the fundamental value of Bitcoin. Economics Letters, Volume 130, 2015, Pages 32–36. ISSN 0165-1765, https: //

· Blau, BM, 2017. Price dynamics and speculative trading in Bitcoin. Res. Int. Bus.Financ. 41, 493–499.

· Baur, DG & Dimpfl, T. & Kuck, K. (2018). Bitcoin, gold and the US dollar – A replication and extension, Finance Research Letters, Volume 25, 2018, Pages 103-110, ISSN 1544-6123, Https://

· Bouri, Elie & Molnár, Peter & Azzi, Georges & Roubaud, David & Hagfors, Lars Ivar (2017). On the hedge and safe haven properties of Bitcoin: Is it really more than a diversifier?, Finance Research Letters, Volume 20 , 2017, Pages 192-198, ISSN 1544-6123,

· Urquhart, Andrew and Zhang, Hanxiong (2019). Is Bitcoin a Hedge or Safe-Haven for Currencies? An Intraday Analysis. International Review of Financial Analysis, Volume 63, 2019, Pages 49-57, ISSN 1057-5219, https: //

· Klein, T. & Thu, HP & Walther, T., (2018) Bitcoin is not the New Gold – A comparison of volatility, correlation, and portfolio performance, International Review of Financial Analysis, Volume 59, 2018, Pages 105- 116, ISSN 1057-5219,

· Thiesa, Sven and Molnár, Peter (2018). Bayesian change point analysis of Bitcoin returns. Finance Research Letters. Volume 27, pp. 223-227.