OUR APPROACH AND TRACK RECORD
Crypto Fragility Model
The challenges for crypto investors have never been so great. The lack of adequate tools to deal with this new market has caused great losses.
Traditional models, such as fundamentals and technical analysis, are not suitable to manage risk exposure in crypto assets, contrary to the premise of these traditional models, cryptocurrencies’ price distribution does not revert to the mean but rather have a fat-tailed distribution. The main characteristic of Fat-tail distribution’s is the occurrence of extreme events and different from historical patterns, which makes models based on past behavior highly inadequate for future predictions.
To properly deal with this new asset class, Convex Research has developed a unique Antifragility model. Drawing from Nassim Taleb’s antifragility framework. The Crypto Antifragility Model is the appropriate tool to manage risk in cryptocurrencies, because it measures the fragility of an asset and prepares for extreme events (of the black swan type) One does not need know the history, but rather the current state of the system, which is, its level of fragility.
In using Convex Research’s solution, investors will have the right tool for a professional and disciplined investment strategy to properly manage their exposure to cryptocurrencies.
Advantages of Crypto Fragility Model
It's the adequate method to perform in the crypto-coins market, far more appropriate than traditional fundamental, technical analysis and other approaches based on "guesses" and "hype".
A research product that is based on actual data to develop a very complex analytical method, but whose results are presented in a very simple and easy to digest format.
Timing is key. You will able to identify moments of fragility and antifragility, when volatility and uncertainty can play to your advantage.
Preservation of capital
We do not want to beat the market, but to dodge its worst blows to enjoy the returns that it offers.
Understand the Model
In the real world we have two classes of event probability distribution. One in which events occur close to the mean (e.g. thin tails). The other in which a small number of observations create the largest effect (e.g. fat tails) and the sample size always insufficient to determine even its average.
While in the thin-tail domain, the losses come from the collective effect of many events, and no single event alone can be strong enough to affect the aggregate, in fat tails distributions, losses come from large isolated events, as in the case of crypto-coins, where significant daily variations are routine.
In the fat tail domain, statistical properties are not in the sample, but outside of it, and therefore using time series for predictions is incompatible with rigorous statistical inference, since historical performance is highly insufficient to formulate any prediction.
Accordingly the fragility model is the appropriate tool does investors and managers to use daily in volatile markets under fat-tailed domain, such as the crypto-coin markets, since this model does not depend on historical data. To measure fragility and prepare for rare and random events we do not need to know the historical track record, but rather must know the current state of the system, that is, its current level of fragility.
The Crypto Fragility Model collects thousands of relevant date of the crypto-coin ecosystem, such as volume, hash rate, transaction cost, spread between exchanges, number of active portfolios, unconfirmed transactions, google trends, and apply these factors to calculate in real time the level of fragility
Fragility can be defined as an sensitivity to shocks, since its antonym is not robust, but the Antifragile, something that benefits and improves as resists shocks.
When the level of fragility is high, this means that a small deterioration in the ecosystem will produce a great negative impact on prices. Reversely, a negative fragility level (Antifragility) will produce a situation of convexity, where by a small improvement in the ecosystem will produce a significant increase in prices. The mathematician Benoit Mandelbrot recognized these abrupt changes and discontinuities in prices as a pattern within the irregularity of the markets and called this the “Noah Effect, after the biblical character. The Crypto Fragility Model alerts us in advance when we are on the verge of a Noah effect.