Strategies

Driven by Data, Executed by Algorithms

You’re interested to participate in the investment potential of digital assets, Novum Alpha can help.

Melding comprehensive data science tools with automated execution, Novum Alpha harnesses the unparalleled investment potential of digital assets. Leveraging sophisticated deep learning software, developed when digital asset markets were in their infancy, our algorithms have weathered countless digital asset market cycles and delivered consistent, market-agnostic returns for our clients.

Allocation Objective

Novum Alpha specializes in utilizing deep learning tools to filter out signal noise in digital asset markets, providing a market-agnostic means to participate in digital assets and deliver uncorrelated returns in all digital asset market conditions.

Risk is managed at the portfolio level using a suite of both automated portfolio management and monitoring tools, as well as regular managerial oversight.

Automated risk management algorithms are designed to stop out trades when preset risk parameters are exceeded and portfolio performance is managed 24/7 by risk management software.

Data Science

Data forms the core of our trading strategy and advantage.

Given the disparate data points and poor quality of datasets inherent in digital markets, deep learning tools enable us to filter out “signal noise” and ensure purity of data for the construction of quantitative tools and trading algorithms. These tools and algorithms are then overlaid to identify trading opportunities and active risk management ensures that automated trading algorithms are deployed tactically for maximum performance.

Better data ensures better results.

Risk Management

A keen eye on risk is at the very core of what we do. Leveraging automated risk management tools allows our portfolios to be monitored round-the-clock as digital asset markets never rest and algorithms actively search digital asset markets for trading opportunities.

Our risk management software actively analyzes trading-related risks both at the trade level as well as at the portfolio level, making regular, automated adjustments to exposure and maximizing performance.

Portfolio tools dynamically report on strategy type, performance and overall portfolio weightage to prevent trade concentration.

Preset trading stops and cut-outs ensure that automated algorithms efficiently exit trading positions when unforeseeable market externalities occur.

Minimizing risk is a key portion of maximizing profit.

1. IDEA GENERATION

▪ Utilizing a mosaic approach, disparate data points are collected and collated from various public and private sources and supplied to in-house deep learning tools.

▪ Trading and research infrastructure will utilize order books, social media monitoring, news and press releases, price data and other proprietary analytical tools.

▪ Market agnostic approach to develop absolute return in all cryptocurrency market conditions will leverage heavily on systematic arbitrage, statistical arbitrage, liquidity provision, market making and event-based trading strategies.

2. ASSET SELECTION

▪ Given the vast and disparate datapoints in the digital asset market, a keen attention to detail can generate significant alpha as digital asset markets tend to be inherently inefficient. Deep learning tools filter out market manipulation and signal noise to ensure clarity of data.

▪ We trade in only the most liquid and technologically sound digital assets, which ensures trading positions have accessible exit options.

▪ Disparate data is fed into deep learning tools and assessed using quantitative models, which generate actionable trade signals.

▪ Proprietary trading system overlays digital asset selection to determine maximum portfolio exposure for any particular digital asset trading pair.

3. RISK MANAGEMENT

▪ An actively traded digital asset portfolio should be fairly diversified to cater for underlying digital asset risk.

▪ Trades are automatically sized according to proprietary algorithms and frequency of trading is constrained to ensure systematic alpha.

▪ Portfolio monitor systems monitor overall portfolio risk and performance 24/7 to minimize trade concentration and exposure.

4. AUTOMATED TRADING

▪ Digital asset markets are 24/7, 365 days a year, providing ample opportunities for generating alpha through the systematic use of automated trading programs.

▪ Digital asset markets are 24/7, 365 days a year, providing ample opportunities for generating alpha through the systematic use of automated trading programs.

▪ Risk-managed automated algorithmic trading programs trade multiple short to mid-term strategies that have been designed to capture digital asset price movements using rules-based signal-generating logic.

▪ Multi-strategy, multi-timeframe and multi-input sets approach ensures significantly more stable performance, reduced risk and low correlation between instruments traded.