By: Matej Ujevic, CEO

Josip Krapac (PhD.), Artificial Intelligence Lead Scientist

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Since our inception in 2015, we have been fascinated by the exponential growth of digital assets in terms of value, market volume, and trading opportunities. As emphasized in recent our We Have a History blog post, at that time there were only a few digital assets and exchanges available. Handling assets and making trades was relatively easy.

Over the last 24 hours bitcoin trading volume has surpassed $3 billion. Bitcoin alone holds nearly 50% of the entire cryptocurrency market with all other digital assets totaling around $3 billion in trading volume. We are now talking about $6 billion of daily traded digital assets after about 8 years.

Considering that the number of cryptocurrencies available has also grown during this time from less than 20 to over 1.000 tradable digital assets, and with the number of exchanges increasing to well over 100, it’s becoming nearly impossible to manually track trading opportunities, digital assets, or make reasonable trading decisions and have risk control mechanism implemented. These complexities and the number of trading opportunities can lead to numerous missed trading opportunities, and for most traders and investors, deprivation of sleep and time. We strongly believe that investment and trading is a rules based game, where one should omit subjectivity and stick to a game plan. Without algorithms it’s extremely difficult and time consuming to scan digital assets trading opportunities, devise trading strategies, backtest them, and stick to a defined game plan all at the same time. Thus, we will enable our platform and its building blocks to allow traders and investors to devise strategies and investments that will have automated algorithmic strategies. This will omit all subjectivity from trading and investing. By having access to a platform that offers automated strategies and investments, stakeholders stand to benefit over the rest of the market.

Making exponential returns was relatively easy while the digital assets market was still growing. Markets are bound to eventually turn, and when they do, it’s likely that it will be drastic (by more than 50%). Many of the digital assets (48% of dotcom companies did not survive a dot com bubble burst) may not be able to sustain in the aftermath of such a drop. We believe that traders and investors that follow their predefined algorithmic strategies and make their decisions without subjective judgement will also stand to have an upper hand or even benefit in such an event.

The security trading industry has had tremendous growth in algorithmic trading percentage. We expect even faster adoption of algorithmic trading within digital assets, and as such, will not only provide platform services, but also integrate third party building blocks as a service, giving stakeholders an upper hand over the rest of the market.

Another significant factor that should be noted,is the rise of Artificial Intelligence. We believe that with such a complex number of signals (technical, news, sentiment, fundamental) autonomous agents empowered by reinforced learning (a machine learning technique that learns action selection policy) and with access to the right amount of data (perceived world state) can select an action (buy or sell signal, portfolio optimisation) based on the perceived world state. State-of-the-art deep learning techniques have recently been used to learn the policy.

The state of the environment is usually represented by historical prices (both trades and order books), but can also be time-stamped information from reports, blogs,news and social network feeds requiring attention to Salient parts of that content (e.g. particular news article or tweet) so this information can be used to additionally guide selection of optimal action.

Since the market is a highly dynamic system, in order to adapt to changes in the market state (e.g. volatility, buy/sell signals), policy should be learned and adapted online. Additionally, “static agents” that learn policy offline do not take into account the influence of their actions (e.g. buy/sell signals) on the environment (e.g. latest price). This is not yet a very well researched area, but a crucial one for intelligent agents that operate in highly dynamic environments.

Future research into autonomous agents and reinforced learning within specific field of strategy development and asset management will over time, beat human developed strategies. The age of traditional investment advisors and asset managers is coming to a close as algorithms and software agents will make most of the decisions in the future. DIgital Assets Power Play will research and implement such techniques within its Operational Wallet.

In summary, complexities within digital assets trading and investing are on the rise, and will continue to do so. Digital Assets Power Play will provide necessary services and building blocks that will enable developers and investors to strategically boost their returns and introduce algorithmic rules to their investments.