Innovative crypto investments strategies

Our vision is a pioneering approach that marries classic conservative investment strategies with the nuanced demands of the crypto realm. We are reconciling traditional portfolio management theory and practice with the emergence of a new asset class driven by different valuations, technical or subjective factors.

Our three Pillars

At Crypto United Partners, our investment framework is currently built on three core, stand-alone strategies that also could serve as building blocks. Each strategy is underpinned by robust proprietary and secondary research, state-of-the-art investment tools, and rigorous oversight. Our weekly investment committee ensure continuous alignment with our commitment to operational and investment management excellence.

Swiss Neutral Strategy

A strategy which turns the inherent volatility of crypto markets into steady and predictable income streams, disregarding the market phase.

What it is

A structured approach that captures yield from market inefficiencies (e.g., funding rate differentials) while neutralizing directional price risk.

Key point

Earning an attractive, fixed income like return-without enduring unpredictable swings in valuations.

Grow & Multiply Strategy

Our GMS is a long-only, systematic crypto asset allocation strategy inspired by classic finance portfolio models. It combines market equilibrium returns with our own forward-looking views derived from multiple proprietary signals such as on-chain activity, macro liquidity or technical momentum

What it is

Respond swiftly to changing market conditions using real-time data.

Key point

Optimal portfolio construction and rule-based rebalancing are the main performance drivers.

Long-Only Digital Asset Basket Strategy

Our investment committee conducts weekly reviews, applying both fundamental and technical insights (including our proprietary signals). This ensures that your portfolio remains aligned with market developments while focusing on sustainable returns.

What it is

A curated selection of leading cryptocurrencies, rebalanced weekly using traditional finance principles alongside unique on-chain signals.

Key point

An individualized service that integrates your specific constraints, whether that means daily liquidity, operational expense coverage, or specialized risk thresholds.

Asset selection

Firstly, the investment universe is defined according to the methodology and rules of well-established benchmarks and data providers. All components from our investable universe, hence constitutes a pool of digital assets screened on their liquidity metrics, tradability statistics on vetted exchanges and availability with vetted custodians.

While circumscribing the investment universe and portfolio size , the second objective is also to manage a “manageable” universe and a deep comprehension of our exposures at the expense of broad and superficial understanding.

Ratings and Rankings

In the absence of commonly accepted valuation methods in the industry, the valuation of a crypto-asset fundamentally depends on its nature, the key distinction being whether the subject asset grants its holder the right to a stream of future cash flows or not and while being contingent to the token type such as security tokens, utility token and cryptocurrencies.

Constituents of the investment portfolio are hence selected and integrated on a discretionary qualitative research-based relying on predefined rating criteria with importance being placed on the business risk profile (funding, revenues, utility, adoption), technology risk (code, speed, efficiency, smart contracts, scaling), legal risk and governance (documentation, testing, oracles, admin controls), security (incidents, audit, coverage, fixings) or more monetary-like parameters such as tokenomics (supply, incentives, vesting period).

Our proprietary evaluation is compared pari-passu to ratings opinions of other experienced professionals, established research platforms to form a consistent investment opinion and converge to a final project evaluation scoring.

Sentiment and psychology

In highly connected global markets and omnipresent social media, there has been increasing interest and success, to varying degrees, in applying data-driven and computational modeling approaches relying on sentiment indicators- Market sentiment triggered by legitimate (verified news) or unidentified (rumors) sources can trigger abnormal returns decoupled from fundamentals or valuations.

In Crypto assets, herd behavior” or socially de-engineered trends (influencer, online forums and communities) can be overwhelming as no fair-value benchmarks or references can reveal price movements drifting several standard deviations from a “fair level” as mentioned above. Practically, the fear and greed index or similarly engineered aggregates expressing a shifting attention on specific thematics can be combined with indicators to produce triggers and signals on price series. The application of overlay sentiment indicators offers the advantage of

Cut through the noise and render the portfolio asset allocation more precise
“Deflate” aggregated market valuations to reveal “noiseless” or cleaner target levels.
Help to manage volatility while deciphering “real” or persistent risks from temporary dislocation episodes based on emotions or temporary hypes.
Sentiment aggregates work as forward-looking indicators, helping to manage exposures before any volatility or repricing gets reflected in valuations.

Indicators and signals

As an extension of a sentiments-based approach, technical analysis plays a central role in crypto in connection with the algorithmic analysis of historical price, trading volume and other statistical market data in order to identify trading opportunities.

Our scope is to optimize trading strategies (potential entry or exit points for trades) involving a systematic approach to analyzing market data and pattern

In our domain, indicators are decision tools, not the decision itself and believe that there lies more value or alpha potential generation in taking complex decisions based on simple indicators rather than taking a simple decision based on complex indicators. With this mindset, we essentially apply indicators to extract value from the idiosyncrasies and inefficiencies of the crypto markets and filter relevant signals according to the language and properties of each indicators, namely:

Forward vs. backward-looking indicators
Complementary indicators or mutually confirming indicators
Momentum vs. trend vs. volatility vs. volume

The perfect combination of indicators isn’t the one always pointing in the same direction and Each indicator should be dedicated to a specific purpose, not telling you the same thing two different ways. Our methodology applies complementary indicators to filter trades aimed at improving the trading system's performance.

Testing and back-testing

We can automate the process of portfolio optimization, the resulting strategies should be thoroughly back tested using out-of-sample data before considering real-world deployment. This process will help ensure that the strategy is robust and can handle different market conditions. We hence developed our backtesting tool designed specifically for the dynamic world of cryptocurrency.

Key Features:

Integrated Analysis: Combine fundamental and technical indicators to create robust trading strategies. Our tool integrates diverse data sources, ranging from prices to on-chain activity, to provide a detailed picture of the particular cryptocurrency.
Responsive to Market Changes: Adapt seamlessly to different market phases, whether during periods of high volatility, a bullish trend, or navigating through shifting Bitcoin dominance. Our tool adapts to choose the best strategy, ensuring the selection of the most suitable approach in a changing environment.
Ongoing Strategy Evaluation: Continuously monitor and assess the effectiveness of our strategies in real-time. This constant evaluation allows for timely adjustments, ensuring our approach evolves in sync with market dynamics.

Portfolio construction, optimization and risks

Intuitively, portfolio construction and subsequent optimization should reflect for a given time interval, the best combination of selected crypto assets from our investment universe from an expected risk/return perspective. While modern portfolio theory (Markowitz 1952) remains conceptually a reference and served well in the financial industry, it suffers several disadvantages in the crypto space, namely:

Key Features:

Highly volatile and skewed cryptocurrencies returns, have a greater chance of causing estimation error maximization, which will lead to extreme portfolio allocations and materially reduce diversification effects.
Optimization methods can be extremely time frame dependent. For instance Transitioning to a two-week strategy might strike a balance between agility and stability, capturing unfolding trends while extending to a four-week strategy enables investors to conduct a deeper analysis of performance and risk management.
In other instances, kurtosis minimization might be better appropriate than a traditional sharpe maximization due to fast transients and extreme returns of crypto assets.

Our optimization structure approaches transcending traditional optimization models while 1) seeking to match not the mean-variance weights, but also the risk associated with each weight according to an array of risk parameters; 2) Short-term high-frequency data dynamic portfolio rebalancing schemes consistent with mid-term fundamental /sector target weight and 3) the application of LSTM methodology (Long Short-Term Memory) in order to capture complex time-related patterns and enhance predictive power in prices developments.

Putting all the pieces together: A beam to spotlight investment decisions

A multidisciplinary approach, combining different types of analytical methods constitutes the quintessence of the investment process. This is aimed at enhancing the decision making process while shedding different beams of light on the same object in order to achieve a maximum of clarity on investment decisions or opportunities, and reduce shadow areas to the minimum.

In clear, we will just posed the analysis of objective/subjective factors (data/facts, vs. rumors/sentiment), qualitative and quantitative models (judgment/research base vs. modeling), short-time market movements vs. long-term trends to name a few.