Machine Learning to identify & develop predictive models for returns
Database includes more than 10,000 global equities and 500+ unique factors. Factor data includes both absolute values and respective rates of change. Common fundamental factors such as unemployment, GDP, CPI, LIBOR, PPI and many more plus technical factors such as Exponential Moving Average (EMA), Stochastic, Bollinger© Bands and others can be incorporated into portfolio models.
In addition, we track more esoteric data sources, such as news sentiment, social media sentiment, insider buying and selling, supply logistics and more. This data is analyzed to find and validate predictive models which inform tailored strategies to achieve the specific performance goals of our clients.
Lucena® delivers powerful quantitative analysis to hedge funds, investment advisors and other sophisticated investors. Our Artificial Intelligence-based decision support technology enables investment professionals to find market opportunities and to reduce risk in their portfolio. Our software is powered by Machine Learning algorithms utilizing multiple orthogonal big data sources to provide predictive forecasting in an easy to use actionable user interface. Lucena® offers subscription-based access to its cloud platform, QuantDesk®. In addition, we deliver highly researched investment strategies in the form of model portfolios.
Lucena® incorporates data from multiple, orthogonal Big Data sources including fundamental, technical, macroeconomic, and esoteric sources. Our data covers every security in every major exchange in the world and includes historical trends going back decades. The ability to filter multiple data points and distinguish insights from random noise can only be enabled by powerful technology and scalable hardware infrastructure. Lucena® provides our customers with actionable, scientific recommendations when it is appropriate or applicable. QuantDesk® automatically adjusts to changing market conditions and refines its analysis using only data factors relevant to a given circumstance.
Value Proposition for Wealth Advisors and Hedge Fund Managers:
- Enjoy the capabilities of in-house skilled quantitative analysts at a significantly lower price point.
- Leverage a scientific approach to investing.
- Explore portfolio studies/backtesting strategy validation and recommendations.
- Integrate with EMS/OMS Systems.
- On-demand Quants for special projects and research assignments.
QuantDesk® is the only platform that enables a non-technical portfolio manager to construct, validate and deploy a profitable investment strategy without writing a single line of code.
Value Proposition for White Label Resellers and Active Traders:
- Access to technology normally available only to large and proprietary hedge funds.
- Hedge fund performance without hedge funds fees.
- Powerful algorithms able to leverage the investor’s insight and preferences.
- Differentiate yourself by empowering your clients with advanced and hard-to-replicate technology.
Lucena® is uniquely positioned to enable a fund manager or data scientist the means to apply a full cycle of Machine Learning and quant based research to investment strategies!
Market Opportunities: More than 80% of actively managed funds underperform each year. In response several trillion dollars of capital has been reallocated away from active management and into passive products like index funds and ETFs with no end to this trend in sight. In today’s dynamic investment environment and the proliferation of big data adoption, macroeconomic and behavioral forces can overwhelm the performance of fundamental-based static portfolios. Many believe that this ubiquitous access to information, in real-time, is the main drive to this growing phenomenon, resulting in volatility and swings and at times unpredictable results. All told, the future for active management is very challenging especially if the current dynamics continue.
Our software combats these challenges by augmenting a portfolio manager’s skill with deep, but easy to use quantitative tools based on Statistical Machine Learning. An astute investment professional’s insight, combined with Lucena®’s decision support algorithms, enable portfolio managers to cut through the clutter of billions of data points and identify scientifically backed relationships that can be exploited for improved performance. Lucena®’s solutions amplify discretionary investment professionals’ their skill. Because Lucena® applies Statistical Machine Learning, our systems are able to self adjust and adapt automatically to evolving market conditions.
Specifically our technology delivers the following features:
Price Forecasting: Machine-learning algorithms forecast future trends using fundamental, technical, and proprietary data feeds.
Hedge Finding: Given a client’s holdings, our proprietary algorithm finds an optimal basket of securities to provide a hedge that reduces risk, yet still maintains return.
Portfolio Optimization: Given a portfolio find an optimal allocation of holdings for a given risk profile.
Event Analysis: Based on historical performance following an event (technical, corporate action or geo political), discover the characteristics of securities most like to react similarly should this event repeat.
Back Testing: Enables a client to evaluate the efficacy of a trading strategy by rolling back time and simulating trades as if they were done in the past not knowing what the future holds.
Alpha Vector Data Feeds: Subscription to data feeds providing equity scoring based on our Machine Learning algorithms.
Premium Strategies: Lucena® offers, for success-based compensation, model portfolio trades based on sophisticated and significantly researched proprietary trading algorithms developed by Lucena®’s quants.
Quant for Hire: Professional services including market research and portfolio analysis.
Subscribers can access Lucena®’s technology through a monthly subscription to our SaaS (software as a service or cloud) infrastructure. Because we are completely web based, there is no need to download special software onto a client’s local machine. Users can be up and running immediately upon sign-up.
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