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The impact of Bitcoin hacking incidents in the crypto market

Republished by Plato

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In the 2013–2017 period, 29 hacks occurred in the Bitcoin market where a total of 1.1 million Bitcoin were stolen. Noting that the average price for Bitcoin (BTC) in December 2020 exceeded $20,000, the corresponding monetary equivalent of losses is more than $22 billion, which strongly highlights the societal impact of this criminal activity. 

What did crypto exchanges do to address this problem? Nowadays, about 90% of exchanges use some kind of cold storage system, which means that digital assets are stored offline. Keeping Bitcoin offline considerably reduces the threat from hacking attacks.

Related: Roundup of crypto hacks, exploits and heists in 2020

Nevertheless, Jean Baptiste Su, principal analyst and technology futurist at Atherton Technology Research, highlights that in 2019, hackers stole over $4 billion, which was more than twice as much as in 2018. In fact, cyberattacks are a very serious issue that cast doubts on the security of modern blockchain-based applications in the financial industry. Of course, one can argue that thefts also occur when using traditional payment methods, such as credit cards. For instance, the Annual Fraud Statistics released by The Nilson Report documents that credit card fraud losses worldwide reached $27.85 billion in 2018.

Related: Crypto exchange hacks in review

I think it is important to point out that fraud in the market for credit cards as opposed to fraud in the cryptocurrency market are difficult to compare for at least four reasons:

  • First, many more people use credit cards as opposed to cryptocurrency.
  • Second, although the frequency of fraud in the market for credit cards is considerably higher, the average amount of stolen monetary equivalent per fraud is dramatically lower.
  • Third, it is much more likely that credit card owners are insured by the credit card company, whereas Bitcoin users typically do not have such insurance.
  • Finally, it is much more probable that the police have some chances of successfully dealing with credit card losses compared to Bitcoin thefts in cyberspace.

Hacking effects on the crypto market

To explore the question of how Bitcoin hacking incidents affect uncertainty in the overall Bitcoin market, I conducted an empirical study where I analyzed how the volatility — which is in financial economics a measure of an asset’s uncertainty — responds to hacking incidents. To do so, I used a so-called Exponential Generalized Autoregressive Conditional Heteroskedasticity model where I included binary dummy variables in the variance equation. The dummy variables measured the impact on the volatility up to five days after a hacking incident in the Bitcoin market.

In my study, I found that Bitcoin’s uncertainty in terms of volatility significantly increases. Surprisingly, I found two effects — a contemporaneous effect and a delayed effect. The volatility increases on the day of the hacking incident and then drops down to normal levels again. There is no effect between day one and day four. Then, on the fifth day after the hacking, the volatility substantially increases again. Since there are no other events that took place, the effect is most likely caused by the same hacking incident.

A possible explanation for the delayed effect could be that hacking incidents are more likely to occur at small exchanges that probably exhibit a lower level of security standards compared to larger exchanges. As a consequence, information diffusion occurs more slowly.

Another interesting finding of the study is that even other cryptocurrencies, such as Ether (ETH), do respond to hacks in the Bitcoin market. Interestingly, the volatility of Ether exhibits only a delayed effect. There is no contemporaneous effect. However, the delayed increase in volatility on day five is virtually the same as we observed for Bitcoin’s volatility.

A possible explanation for this finding could be that exchanges trade multiple cryptocurrencies at the same time, and if an exchange was hacked, thieves could steal both Bitcoin and Ether, which could be a possible explanation for volatility spillovers found in my study. Another possible explanation for this phenomenon could be that thieves are using one cryptocurrency to cash out on their theft of the other, thus shifting the demand for cryptocurrencies from Bitcoin to Ether, for instance.

What is the risk of a cyberattack in terms of the U.S. dollar?

To explore this issue, I collaborated with colleagues from the Finance Research Group and the Mathematics Research Group at the University of Vaasa. Together with Niranjan Sapkota and Josephine Dufitinema, we collected 53 hacking incidents in the Bitcoin market totaling in the 2011–2018 period corresponding to 1.7 million stolen Bitcoin. We argue that naïve risk management may dramatically underestimate the risk of those hacking incidents and that naïve risk management may dramatically underestimate the risk of those hackings incidents.

In the study, we show that the distribution of hacking incidents is extremely fat-tailed. This means that Black-Swan-like events are more likely to occur. We found that the probability distribution of hacking incidents does not have a theoretical mean, which implies that the mean of the loss distribution is infinite. To compute an estimate of the risk due to cyberattacks in the Bitcoin market, we then employed recently proposed tools from extreme value theory, or EVT.

We showed that the shadow mean of the expected risk of cyberattacks is $59.70 million, which is definitely larger (almost two times) than the corresponding sample tail mean of $30.92 million. More specifically, the shadow mean is computed by an application of ETV and corresponds in our research context to the expected risk of cyberattacks above a certain threshold. In our study, we chose as a threshold a loss of $1 million. That means all losses due to cyberattacks that are above $1 million are treated as extreme values.

The next step in our calculation was to combine the shadow mean with the expectation of the loss distribution where we collected all losses due to cyberattacks that are less than $1 million. Combining our shadow mean with the sample mean below our chosen threshold, we calculated an overall expected loss of $24.89 million instead of $12.36 million, which is the naïve sample mean of the hacking incident data.

Our findings have significant implications. For instance, our results show that standard tools used in traditional risk management can perhaps not be relied upon for making decisions.

The views, thoughts and opinions expressed here are the author’s alone and do not necessarily reflect or represent the views and opinions of Cointelegraph.

Klaus Grobys is a docent in financial economics at the University of Jyväskyla and an assistant professor of finance at the University of Vaasa. Grobys is also affiliated with the research platform InnoLab at the University of Vaasa. His recent studies investigate the opportunities and risks associated with new innovative digital financial markets. His recent research was, among others, covered by U.S. business magazine Forbes.

Source: https://cointelegraph.com/news/the-impact-of-bitcoin-hacking-incidents-in-the-crypto-market

Blockchain

Polkadot Gears Up for Parachains Launch: Unveils ‘Common Good’ Parachains

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Polkadot, the interoperable blockchain protocol spearheaded by Ethereum co-founder Gavin Wood, has announced its forthcoming parachain launch.

Parachains – application-specific blockchains that connect to the main network and benefit from its security and computing capacity – are viewed as the building block of Polkadot’s ecosystem. Initially, the plan was for 100 parachain slots, with an auction process determining who gets to ‘lease’ parachains for defined time periods.

However, according to a blog post published by the team on February 25, some slots will be made available for ‘governance-allocated parachains,’ also known as common good parachains. These common good parachains have been conceived to address the so-called “free rider” problem, wherein parachains can forgo contributing to elements (such as bridges) that may benefit the ecosystem as a whole.

Solving the Free-rider Problem

The free-rider problem is best understood with reference to an analogy. Supposing a levy is imposed on car manufacturers to offset pollution: in turn, vehicles’ cost is increased, and all drivers are forced to pay extra.

Although everyone will subsequently benefit from a less toxic atmosphere, only those who actually buy a car will have contributed: the others (cyclists, for example) are considered free riders.

Polkadot’s governance process will essentially earmark parachain slots for consideration outwith the auction process, with a Council and Technical Committee representing passive stakeholders and supplying technical guidance. Both groups will then decide whether to accept or reject the direct registration of certain parachains.

According to the blog post, both system-level chains and public-utility chains may emerge as blockchain categories that qualify as common good chains.

Any parachain, in other words, that the Polkadot team deem beneficial for the overall ecosystem – bridges, identity projects, and smart contract platforms and governance would all theoretically be under consideration.

Chains that help remove transactions from the Relay Chain and enable more efficient parachain processing seem the likeliest to be considered ‘common good.’

As noted in Polkadot’s blogpost:

“By allocating a subset of parachain slots to common good chains, the entire network can realize the benefit of valuable parachains that would otherwise be underfunded due to the free-rider problem.

Polkadot’s governance system is on the bleeding edge of social coordination and it will be exciting to see how it helps the network evolve to meet the needs of its constituent parachains and stakeholders.”

Polkadot Gears Up for Parachain Launch

The Polkadot team recently published a roadmap noting that all upcoming parachains will be tested on regular parachain testnets, like Rococo and on Kusama Network. The latter being Polkadot’s canary network.

Kusama is a proving ground for parachains, allowing developers to build and deploy them and experiment with Polkadot’s governance, staking, nomination, and validation functionality.

Once parachains are live, community members will have their say on which additional features and network upgrades should be incorporated over time.

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Source: https://cryptopotato.com/polkadot-gears-up-for-parachains-launch-unveils-common-good-parachains/

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Blockchain

Cardano Price Analysis: 28 February

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While a majority of the assets are still trying to recover from the recent price drop, Cardano managed to record a new all-time high over the past week. Clocking in a value of $1.48 yesterday, Cardano is currently one of the top three assets in the world and while the asset has registered a 10% drop over the past few hours, it has maintained its 3rd position with a market cap of $38 billion.

Cardano 6-hour chart

Source: ADA/USD on Trading View

The 6-hour chart of Cardano continued to indicate a rising price but the asset was moving within the trendlines of an ascending channel. With a couple of higher highs witnessed, the asset has dipped over the past 24-hours, and the correction may go even further in the charts. A bearish breakout should allow the asset to recover its position at a previously held range before addressing the higher range again in the future.

At press time, the 50-day Moving Average has continued to act as underlying support but a possible move below $1.12 is likely.

According to the VPVR range, the support range at $0.90-$0.95 could be tested since the trading volume at the price point has been significant over the past few weeks.

Market Indicators

Source: ADA/USD on Trading View

Market Indicators appeared a little on the neutral side at press time but considering the pattern was bearish, the indicators may head in the same direction.

Relative Strength Index or RSI is currently holding a position above 50 but the indicator suggested an increasing selling pressure in the chart. Stochastic RSI is exhibiting a bearish pullback at press time, with the signal line hovering the bullish line.

MACD appeared bullish at press time, but a potential trend reversal is in the charts, with the MACD line converging towards the bearish line.

Important levels to watch out for

Resistance: $1.48
Support: $1.30, $0.92-$0.90
Entry Position for Short: $1.325
Stop-Loss: $1.48
Take Profit: $0.90-$0.92
Risk/Reward Ratio: 2.43x

Conclusion 

Cardano’s price action has been within the ascending channel formation and a bearish breakout in the coming week should not be discounted.


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Source: https://ambcrypto.com/cardano-price-analysis-28-february

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Blockchain

Bitcoin Cash, Uniswap, Zcash Price Analysis: 28 February

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Bitcoin Cash looked uncertain to flip its press time resistance as the indicators gave mixed signals regarding its future trajectory. Uniswap could move southbound from its descending triangle pattern as momentum rose on the selling side. Zcash showed some indecision in its market as the price continued to trade within a range, with a breakout unlikely over the coming sessions.

Bitcoin Cash [BCH]

Source: BCH/USD, TradingView

With weekly losses of over 33%, Bitcoin Cash slipped to the 12th position on the crypto-rankings with a market cap of $8.6 billion. On the 4-hour timeframe, the price slipped below $464 support but the bulls eyed a comeback on the charts. The RSI avoided the oversold territory but pointed lower from the 35-mark at the time of writing. The MACD was bullish-neutral as the fast-moving line floated just above the Signal line.

It was doubtful whether the aforementioned resistance mark could be flipped over the next few sessions as trading volumes and buying activity remained muted.

Uniswap [UNI]

Source: UNI/USD, TradingView

A descending triangle formed on Uniswap’s 4-hour chart after the price formed lower highs post record levels. Prices usually tend to break downwards from this pattern on low trading volumes. The Awesome Oscillator showed that momentum rested with the selling side as the red bars rose below the half-line. A fall below the lower trendline could see UNI move towards the $15 mark.

The Stochastic RSI disagreed with the AO and suggested that UNI could be up for some gains after a bullish crossover in the oversold zone. However, a move above the upper trendline was unlikely considering the state of the broader market.

Zcash [ZEC]

Source: ZEC/USD, TradingView

Zcash continued to move within a fixed channel on the 4-hour chart as equilibrium was maintained between the buyers and sellers. The Bollinger Bands also reflected the consolidation as volatility remained low in the market. The MACD line was superimposed on the signal line, reflecting the indecision in the market.

However, a sharp move in either direction could see the market tilt strongly in the favor of the side that enforces the breakout. A bullish scenario could see ZEC move towards the next resistance mark at $138.4. Conversely, a fall could see the price move towards $98.1 support.


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Source: https://ambcrypto.com/bitcoin-cash-uniswap-zcash-price-analysis-28-february

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