Evrydiki

Evrydiki is a systematic trading firm using algorithmic models and strict risk controls to trade global multi-asset markets and compound capital steadily over time.

We’ve built and backtested our core strategies, integrated them with Interactive Brokers’ API, and are moving from paper trading to live trading with proprietary and seed capital while assembling a technical and investment team.

Evrydiki focuses on investors and institutions who think in risk-first, data-driven, and systematic terms. This includes:
High-Net-Worth Individuals
Portfolio Managers & Asset Management Professionals
Hedge Funds
Insurance Investment Teams

Evrydiki operates in a large and expanding global market driven by demand for systematic and risk-aware strategies.
The Total Addressable Market (TAM) is approximately $5.5 trillion, comprised of hedge funds, CTAs, quant investors, and alternative allocators.
The Serviceable Available Market (SAM) — focused on Europe, Middle East, and investors using Interactive Brokers — is approximately $3.6 trillion.
Evrydiki’s Serviceable Obtainable Market (SOM) within 3–5 years is estimated at $350M–$450M, reflecting highly targeted outreach to HNWIs, family offices, hedge funds, boutique asset managers, and insurance investment teams who value systematic, transparent, risk-first trading.

Traditional investing is emotional, opaque and inconsistent. Most investors don’t have access to disciplined, data-driven strategies with clear, predefined risk and drawdown limits.

Evrydiki uses algorithmic, rule-based models and strict risk controls to trade multi-asset futures systematically, executing via APIs so decisions are consistent, transparent and free from emotion.

Competitors and Existing Alternatives
Evrydiki operates in a space where several types of players already serve parts of our target market. We don’t claim the space is empty; instead, we position ourselves clearly among these alternatives.
1. Quant Hedge Funds & CTAs
Large quantitative hedge funds and CTAs (Commodity Trading Advisors) already offer systematic futures strategies to institutional clients.
Strengths: Deep teams, long track records, institutional processes.
Limitations for our target clients:
Very high minimum tickets
Limited access for smaller HNW investors
Black-box strategies with minimal transparency
Often designed for “average” market assumptions, not explicitly for fat-tailed, mis-behaved regimes


2. Discretionary Portfolio Managers & Wealth Managers
Traditional wealth managers and portfolio managers often offer multi-asset portfolios with some exposure to derivatives or funds.
Strengths: Relationship-based, holistic wealth view.
Limitations:
Human, discretionary decision-making
Inconsistent reaction to volatility and crises
Limited systematic futures overlays
Risk rules often implicit, not algorithmically enforced

3. Robo-Advisors & Model Portfolios
Robo-advisors and banks’ model portfolios offer automated, rules-based investing in ETFs and mutual funds.
Strengths: Low cost, automation, simple UX.

Limitations:
Mostly long-only ETF allocation
Limited use of derivatives / futures
Built on modern portfolio theory with near-normal assumptions
Weak response to truly extreme market moves

Evrydiki’s contrast: focuses on futures and derivatives, not only cash markets; designed around Mandelbrot-style “wild markets,” not purely normal distributions.

4. Retail Algorithmic Platforms (DIY Quant)

Platforms like retail algotrading frameworks, signal platforms, and marketplaces allow users to run their own systems.
Strengths: Flexibility, access for retail traders, educational value.
Limitations:
User must design, test, and maintain strategies themselves
No unified risk framework or capital-protection philosophy
Quality and robustness of strategies vary widely

Evrydiki’s contrast:
We provide a coherent, integrated framework: research → risk model → execution → monitoring, not a tool for random strategies. The philosophy (wild markets, capital preservation, rules before emotion) is built into the system from day one.

5. Single-Strategy Signal Sellers / Copy Trading
There are services selling trading signals or offering copy-trading in FX, CFDs, or futures.
Strengths: Easy to start, no need to code.
Limitations:
Often opaque performance reporting
Little formal risk management
Strategies can be short-lived and marketing-driven
Evrydiki’s contrast:
We do not sell random signals; we build a principles-driven systematic trading business, with clear documentation, risk metrics, and a focus on long-term survivability.
Short positioning sentence (for forms / slides)

Advantages & Differentiators
Evrydiki stands apart fr om traditional investment approaches, signal providers, and conventional quant strategies through a combination of philosophy, engineering discipline, and risk-first design. Our competitive edge is grounded in how we model markets and how we manage risk.

1. Built Explicitly for Mis-Behaved Markets

Most investment strategies assume markets are “normal” or mean-reverting.
Evrydiki begins with the opposite assumption:
markets are wild, irregular, fat-tailed, and prone to extreme events.

This foundational belief drives:

shock-resistant position sizing
stress-tested risk parameters
resilience during turbulence

This market philosophy is a major differentiator because most existing products are not engineered with extreme events as a baseline assumption.

2. Risk-First Architecture (Not Return-First)

Wh ere most managers focus on maximizing returns and “optimizing performance,” Evrydiki is built around drawdown control, capital preservation, and risk absorption.

Our risk stack includes:

fractional sizing
max drawdown brackets
contract caps per instrument
scenario testing in chaotic conditions

This structure puts risk before opportunity, leading to long-term durability — a core concern for HNWIs, hedge funds, and insurers.

3. Fully Systematic, Principles-Based Execution

No emotions.
No news reactions.
No “this time it’s different” thinking.

Every decision is made through:

algorithmic rules
quantitative signals
daily updates
automated execution via API

This ensures consistency and eliminates the human weaknesses that often destroy performance.

4. Multi-Session, Global Futures Strategy

Evrydiki is engineered to operate across the natural market cycle:

Asia → Europe → United States

This gives several advantages:

diversified opportunity set
natural smoothing of volatility
exposure to global liquidity flows
reduced dependence on any single market

Trading globally reduces concentration risk and increases strategy robustness.

5. Transparent, Auditable, API-Driven Execution

Unlike discretionary managers or opaque hedge funds, Evrydiki’s execution is:

logged
automated
rules-based
fully reproducible

This builds trust with:

portfolio managers
insurance companies
HNWIs
regulated institutions

Because they can easily audit the logic and the performance drivers.

6. Boutique, Accessible Model

Large quant funds require:

€5M+ minimum tickets
complex subscription structures
long lock-ups
limited transparency

Evrydiki aims to provide a professional systematic strategy, making it:

accessible
transparent
easy to integrate
compliant for non-institutional investors

This accessibility is a major competitive advantage.

7. High Scalability with Low Operational Overhead

Because the system is algorithmic and API-based:

scaling up does not require more human labor
execution is automated
infrastructure overhead is low
scaling to high AUM is operationally efficient

This makes Evrydiki structurally advantaged compared to discretionary or hybrid funds.

8. Unique Intellectual Blend:

Evrydiki’s philosophy is uncommon in the investment world:

markets are fractal, volatile, fat-tailed
clarity, rules, principles
API-driven engineering → modern execution and automation

This combination differentiates Evrydiki intellectually, strategically, and operationally.

Propriatary trading, conslting ,monthly subscriptions

We manage client accounts or get licenced as a fund and charge a combination of management/licensing and performance fees, with future revenue from bespoke systematic mandates, strategy licensing and technology partnerships.

Evrydiki will allocate funds across team development (35%), infrastructure (25%), proprietary trading capital (25%), promotions (10%), and contingency (5%). This balanced allocation allows us to build the system, test it live, and establish early investor traction.

Investors contributing €500,000 receive a hybrid benefit package, including:
(1) equity participation (approx. 10%),
(2) preferential trading terms (reduced management fee and reduced performance fees), or
(3) a small ongoing revenue share from future strategy licensing or technology partnerships.

Although Evrydiki is designed with a risk-first philosophy, no trading strategy or financial business is without risk. The following risks outline the key challenges and limitations inherent in systematic trading and in the development of Evrydiki.

1. Market Risk (Unpredictable Price Movements)

Financial markets are inherently volatile and can behave in unpredictable ways.
Even though Evrydiki is engineered for mis-behaved markets, sudden price gaps, extreme volatility spikes, or correlated market shocks can result in losses.

Mitigations:
conservative fractional Kelly position sizing
volatility-adjusted exposure
predefined loss and drawdown limits
diversified futures universe

2. Model Risk (Model Behaviour vs Real Markets)

No model can fully capture real market dynamics.
Backtested performance may not reflect live results due to:

structural changes in markets
regime shifts
new forms of volatility
model assumptions that no longer hold

Mitigations:

continuous model monitoring
stress-testing under extreme scenarios
incremental, controlled deployment of risk

3. Execution Risk (API, Slippage, Latency)

The strategy depends on accurate and timely execution via broker APIs
Potential issues include:

API downtime
slippage during fast markets
delayed fills
rejected orders
network failures

Mitigations:

fallback execution logic
monitoring of order confirmations
robust infrastructure design
limited order size to reduce liquidity impact

4. Liquidity Risk

Certain futures contracts or intra-session periods may experience reduced liquidity, leading to:

wider spreads
worse fills
slippage
difficulty scaling

Mitigations:

focus on highly liquid futures
pretrade liquidity checks
micro contracts to improve fill quality

5. Operational Risk

Operational issues may arise from:

server failure
data feed errors
incorrect parameter configurations
software bugs
human error in oversight or deployment

Mitigations:

logging and audit trails
sandbox testing environments
strict change management
daily integrity checks

6. Regulatory & Compliance Risk

Future phases may require:

licensing
compliance frameworks
audit procedures
adherence to investor protection rules

Changes in financial regulation may affect:

how services can be offered
who can invest
operational costs
Mitigations:

early alignment with MiFID / CySEC guidelines
phased rollout (proprietary → seed → managed accounts)
professional legal oversight

7. Behavioural Risk (Investor Misalignment)

Some investors may:

misunderstand the strategy
have unrealistic return expectations
become uncomfortable during inevitable drawdowns
This can lead to premature withdrawal or pressure to deviate fr om the model.

Mitigations:

clear communication
setting expectations upfront
transparent reporting
adherence to systematic discipline

8. Technology Risk

Evrydiki relies on:

automation
data processing
local infrastructure

Any failure may disrupt trading or introduce errors.

Mitigations:

redundant systems
version-controlled deployments
backups of configuration/state
quality assurance processes

9. Concentration Risk

If the strategy is overly allocated to specific assets, regions, or volatility regimes, it may behave poorly in certain environments.

Mitigations:

diversification across global markets
multiple uncorrelated models (future expansion)
regime-aware exposure

10. Business & Scaling Risk

Building a systematic trading firm requires:
capital
talent
infrastructure
regulatory compliance
investor trust

Failure in any of these can lim it growth or delay development.

Mitigations:
lean operational model
scalable API-based execution
staged rollout (proprietary → seed → managed account)
partnerships with investors and quant professionals

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