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WE BOARD MANAGEMENTS; Apologies for inconvenience shutdown database ecosystem services... We're here to notify you all that, our company went offline is because it's under maintenance passing through upgrades!!! So feel free to enjoy you investment trade with massive income bonus profit which will going to reflected and add up to you trade account balance as a profit bonus!

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The traditional way of trading

📢Trading on cryptocurrency exchanges is strenuous. Traders monitor the markets continuously not to miss out a good chance for a trade. They make decisions based on experience and intuition. Only few people become skilled traders and achieve real positive returns in the long term.
Visualization of the market trends by charts and indicators aid finding the right timings for placing orders. Many traditional trading strategies base buy and sell decisions on certain conditions on these technical indicators. Sometimes, traders also use additional information like news reports which might not always be reliable.
Technical indicators are all formed from the same data, such as market prices and volumes. That means, the different indicators do not contain any new or distinct information. The underlying data they are computed from already contain the complete information. Indicators are simply ways to visualize the data differently to aid the trader getting clues on hidden patterns.

🚸Automation of trading

In case of cryptocurrencies the 📣markets are open for trading 24h per day, 7 days a week. It becomes impossible for a human trader to monitor the market all the time. Moreover, these markets have a high volatility and manipulation through fake order books and volumes, such as wash trading or pump-and-dump schemes, is commonplace. In addition, many fake news surrounding cryptocurrencies make it difficult for anyone but the most professional traders to take rational decisions.

🛗Therefore, bot based trading became more and more popular in the recent years. Established providers like Cryptohopper, 3Commas or Trade Santa offer the automatic execution of standard and user-defined trading strategies. Backtesting functions, which compute the simulated performance of the strategies on historic market data, aid the trader finding a profitable strategy.

📶Beyond empirical strategies

The aforementioned trading strategies are qualitative methods that rely on the expertise of human traders. Whether automated by a bot or executed manually, they rely on many subjective factors. Only professional traders are able to achieve high returns. But even they have to optimize their strategies empirically which can be very time-consuming. Many traders learn hard lessons and loose money until they find a working strategy. Some bot providers offer simple pre-configured standard strategies that might be moderately profitable even for novice traders. However, their performance falls far behind the strategies of pro traders.
Institutional investors with sufficient resources started to explore quantitative methods for trading. These are based on the computational analysis of massive amounts of data to strip complex patterns of behavior into numbers. Statistical models fitted to data from many sources returned more profits. But how do we know, these models are already the best possible ones?

The next level of bot performance

Artificial intelligence (AI) takes cryptocurrency trading to the next level of optimization. The underlying mathematical models are universal in some sense, so they can adapt to the data. They provide not merely a pre-defined strategy with optimal parameters, but even the underlying model itself adapts to be optimal for the problem at hand. Moreover, if set up properly, the whole process of finding the best trading strategy with the best parameters can be executed completely automatically. Cloud-based cryptocurrency trading bots as provided by companies like profitmodule.net, ecosystem database server or B-Cubes are executing these strategies reliably.

Challenges and solutions

The drawbacks are that in-depth knowledge of machine learning as well as massive computational resources and huge amounts of data are required for the design and training of successful trading algorithms. As pointed out by Janny Kul from Credium, naiv approaches to AI based trading frequently fail. We need to address signal performance, risk and order execution as well as data quality and generalization.
Fortunately, new companies are emerging with highly spezialized and renowned experts and high-performance computing resources. They ensure that all these complex issues are taken care of in a professional way. They have researchers continously working on ever better methods and algorithms to find the optimal level of profitability. This yields sophistication that was only available to institutional investors in the recent past. Companies like profitmodule.net,.make AI cryptocurrency trading bots now accessible for every crypto-investor. No need to have in-depth know
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