TONUSD: A Bearish Rollercoaster – Are You Ready for the RideTelegram CEO Pavel Durov Arrested in France
Pavel Durov, the CEO and founder of the popular messaging app Telegram, was arrested on Saturday evening at Le Bourget Airport in France while exiting his private jet. The arrest is linked to an ongoing police investigation in France, which is reportedly focused on Telegram's lack of content moderation, allowing criminal activity to persist on the platform.
Charges and Potential Penalties
Durov, a Russian-French billionaire, faces serious charges related to offenses allegedly facilitated through Telegram, including complicity in drug trafficking, crimes against children, and fraud. If found guilty, he could face fines and up to 20 years in prison, depending on the specific laws under which he is charged and the severity of the alleged offenses.
Impact on Toncoin and TON Ecosystem
The arrest of Telegram's CEO has had a significant impact on the cryptocurrency market, particularly on Toncoin (TON), which is closely tied to Telegram. Toncoin experienced a sharp decline of over 19%, dropping from around $6.75 to under $5.50 in less than 12 hours following the news. The TON ecosystem as a whole has been affected, with concerns raised about the future of the blockchain and its relationship with Telegram.
Reactions from the Tech Community and Supporters
The tech community has expressed various reactions to Pavel Durov's arrest, with concerns raised over privacy, security, and the balance between these aspects and government oversight. Elon Musk, CEO of SpaceX and Tesla, took to Twitter to show his support for Durov, using the hashtag #FreePavel and sharing a theoretical idea about people being executed for liking a meme. The TON community has also issued a statement expressing its firm support for Durov and emphasizing that the operation and mission of the community will not be affected by this incident.
Now let's have a look at the technical context behind the TONUSD and what I'm looking for to get positioned into shorts on hourly timeframes by relying on probabilities.
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