Trajan Capital
Modernization of financial services infused with deep learning A.I. systems.
Business re-engineering and tailored investment advisory solutions through the utilization of artificial intelligence tools and neural networks to provide precise data analytics to conduct our services.
Financial Services we offer
Asset management & risk management advisory services provide added value to our client’s investments and business.
High-end consulting services to assist streamline your business success and growth over the upcoming years.
Specialized industry solutions to help navigate through our constantly evolving and adapting global market.
Performance Driven:
Licenses & Certification
Clients Internationally
Client Retention
Assets Under Advisory
Trajan Capital was founded in 2019 in New York, NY USA with the scope to provide innovative added value services. We focuses on businesses re-engineering and value creation through the deployment of advanced mathematics & management strategies, and comprehensive adoption of artificial intelligence tools.
At Trajan Capital, our clients’ best interests always come first, and everything we do goes strictly by our values and professional business ethics. We conduct business following the highest industry standards to encourage integrity in the capital markets.
Where ever applicable we integrate today’s latest technologies and design them to provide optimized data analytics. The outcome result is a system that provides more precise data outputs which have been run through thousands of simulations and calculations. We are not a company based on fundamental analysis, but rather unbiased data-driven advisory solutions. We apply machine learning and deep learning algorithms within artificial dynamic neural networks which create the logic for our systems.
The artificial neuron, loosely modeled off of a neuron in the human brain, simply hosts the mathematical computations. Like our neurons, it triggers when it encounters sufficient stimuli. The neuron combines input from the data with a set of coefficients, or weights, that either amplify or dampen that input, which thereby assigns significance to inputs for the task the algorithm is trying to learn.
What identifies a Deep Neural Network from the more standard single-hidden-layer neural networks is the number of layers that compose its depth. More than three layers (including input and output) qualifies as “deep” learning. The further you advance into the neural net, the more complex features there are that can be recognized by your neurons, since they aggregate and recombine features from the previous layer. It makes deep-learning networks capable of handling very large, high-dimensional data sets with billions of parameters that pass through nonlinear functions.
Our Approach
Our advisory and consulting services are majorly based on data analytics through our Dynamic Neural Network systems to provide precise data and measurement for our clients to paint a clear picture of their assets performance.
Dynamic Neural Networks, dynamically adapt depending on their data inputs (price, volume, etc.) providing unbiased simulations of assets exposure to unnecessary risk and thereon formulate plans to manage and monitor accordingly.
Our main focus is to promote capital preservation with solutions to simultaneously stimulate wealth growth. Risk management is the key to survival in the capital markets, performance simply follows.
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