Signum Alpha envisions an entire financial ecosystem tailored to the needs of today as well as tomorrow. By putting the people in the center of this ecosystem, we were able to map all their financial needs, and propose services that would empower investors by delivering innovative algorithm-driven investment solutions.
Signum’s portfolio of services is comprised of a diverse set of FinTech initiatives, from easy access to quality investment vehicles, to simplified modeling tools, and financial education apps. We believe the future of financial decision-making and investment is going to be distanced even further from human opinions towards all sorts of algorithm-based processes where machines capable of analyzing massive amounts of financial data would make effective investment decisions efficiently.
Signum Alpha is the force behind Stash Up, your personalized investment robot. Stash Up helps investors determine their asset allocation (Bond, Cash, Equity) and select the right equity/bond strategy to trade. Quant analysts and developers of financial models evaluate and showcase their strategies via our back-end. Potential investors get to see the performance of those strategies, and choose ones that represent their investment style and preference. We will walk with you step by step, helping you define and track your investment goals, allocate capital in different asset classes, and trade the right strategy(s).
Determine whether you want to play the market, buy a new car, a new house, contribute to a college fund, save for your retirement or plan your dream vacation.
Choose the right mixture of equity, bonds and cash in your portfolio to ensure maximum returns on your investment with the approperiate amount of risk.
Choose your equity strategy from a pool of quality-tested quantitative strategies, based on your preferences and the strategy's historical performance.
Set us up with your portfolio manager or brokerage of choice, we send out your orders automatically and keep you informed on the progress made.
Comprehensive reports on historical performance of selected strategies as well as your portfolio's profit and loss are presented to you and updated daily.
Always ride with the best strategies available, grow your Stash Up by contributions and profits, meet your goals and reach financial greatness.
Robo Advising capability is a must have for traditional investment advisors, keeping the costs low and expanding their reach. We would provide software as a service, containing an ETF Packaging Module, a Client Onboarding Module, a Portfolio Management Module, plus customization and maintanance. Using our Open Platform Robo Advising services, every investment manager will be able to enjoy the advantages of these easy to use technological advancements.
To enable more people map their ideas and model stock behavior, we’ve designed Quantie, which is a simple to use strategy building tool. Quants can choose from a diverse set of filters and screen the stock market, looking for combinations of filters that successfully predict profitable trends. Quantie's back-end calculates each model’s performance metrics. These strategies if they pass Stash Up’s quality compliance criteria, will be published to our Strategy Market, creating income opportunities for our Quantie users.
Sophisticated machine learning algorithms work best when they are exposed to big and diverse sets of subjects to learn from. For such systems to be able to create better financial meta-models, we would need to feed them many basic quantitative algorithms, to combine, evaluate, and learn from. As more and more standardized quant strategies are submitted to our pool via Stash Up back-end as well as via project Quantie, we will become capable of implementing project Q, where deep learning algorithms would create and improve meta models that would become more and more capable of predicting market movements and stock behavior as time passes.
Next in our NPD funnel is our educational platform, project E-Tree. We believe in making educational tools and financial knowledge accessible to all people who are willing to take part in the investment process. E-Tree is based on a carefully designed tree of financial knowledge, covering areas ranging from general knowledge of major players in the industry, to financial concepts and definitions. We believe in gamification when it comes to education, so E-Tree is designed to be fun and engaging as well as an opportunity for growing our knowledge base. Users who finish the game are then expected to have clearer ideas about financial processes and major players in finance, and be able to make better-informed financial decisions.
We are a Vancouver based technology company, developing a Neo-Advising investment platform. Our goal is to make your investment process as transparent, convenient and competitive as possible. We evaluate investment strategies based on a very strict set of standards, and will publish only the quality-assured strategies for our investors to choose from.
We are dedicated to keeping you informed and will serve you to our best of capabilities, so you could lead your portfolio to greatness, meet your goals and achieve your dreams.
Stash Up Average
Our team's background and experience is in Finance, Economics, Mathematics, Computer Science, Theoretical Physics, and Business Administration. A multi-disciplinary team developing a multi-faceted investment service.
Experienced with system analysis and architectural design, financial modeling, PR and advertising, client psychology, business administration
Experienced with design and development of FinTech solutions, software engineering, financial modeling, Economics, tech start-ups, technology planning
Years of Trading Experience
The Standard subscription provides you with all the main features and functionalities of Stash Up eco-system, you won't miss anything essential for a convenient investment planning and execution. We kept the complexity and the clutter to a minimum here. The Pro subscription will let the finance savvy to delve deep and customize their investment approach even further.