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NEW ARTICLE

Lognormal Distribution: Neither Thin- nor Fat-Tailed

https://quantatrisk.com/2024/11/05/lognormal-distribution-thin-nor-fat/

Lognormal Distribution: Neither Thin- nor Fat-Tailed | Øuant at Risk In probability and statistics, distributions are often classified as either "thin-tailed" or "fat-tailed," a distinction that reflects the likelihood of

NEW ARTICLE

Understanding the Invisible Tail of a Power Law
https://quantatrisk.com/2024/10/29/invisible-tail-of-a-power-law/

Did you know that... Peaks Over Threshold (POT) is a statistical method used in extreme value theory to analyse the distribution of values exceeding a certain high threshold. Instead of focusing on the entire dataset, POT hones in on extreme events (the "peaks") that cross this threshold, modeling their frequency and magnitude separately. This approach is well-suited for assets like cryptocurrencies, where price movements can be highly volatile and exhibit extreme "tail" behaviour, such as sudden price spikes or crashes.

Applying POT to crypto risk modeling has several advantages:

1. Focus on Tail Events: POT emphasizes large deviations, which are especially important in crypto markets known for extreme highs and lows. It captures the behavior of rare, significant price movements that drive substantial risk.

2. Flexible Threshold Setting: POT allows analysts to choose a threshold level based on the asset's unique characteristics. This flexibility is valuable in crypto, where the frequency and size of extreme events can vary widely between coins.

3. Improved Risk Assessment: By focusing on extreme losses or gains, POT can provide more accurate estimates for metrics like Value at Risk ( ) and Expected Shortfall ( ), helping investors and risk managers to better understand and prepare for rare but impactful market events.

Pump & Dump in -Markets

Emerging often fall victim to “pump and dump” schemes, largely due to their low liquidity and limited regulation. Unlike established assets, new coins typically have fewer buyers and sellers, making their prices more susceptible to manipulation. In a typical pump and dump, a group of traders will artificially inflate the price by purchasing large quantities, creating an illusion of growing demand. This spike generates hype, attracting uninformed investors who jump in, hoping to profit from the rise.

As the price peaks, the original buyers—those who orchestrated the pump—start selling off their holdings, often all at once. This sudden mass sell-off, or "dump," causes the price to plummet, leaving late investors holding devalued assets. These schemes exploit new coins' lack of established trading patterns, making them particularly vulnerable to abrupt price swings. Without a strong regulatory framework, emerging cryptocurrencies remain an attractive target for such manipulative tactics, reinforcing the importance of thorough research before investing in new or lesser-known coins.

The following code illustrates a typical "pump and dump" process:

One of the most least understood topic in of the sample. Learn something new:

Quantitative Analysis of a Sample Drawn from the Unknown Continuous Population | Øuant at Risk In quantitative finance, we very often deal with a sample mean and sample standard deviation being derived given a vector or a time-series or any other