What AlgoMart Is (and Isn’t)

AlgoMart is a platform for discovering, analysing, and subscribing to quantitative investment strategies supported by transparent data, historical simulations, and clearly structured performance metrics.

Each strategy on AlgoMart is presented with detailed analytics—including historical back-tested results, benchmark comparisons, risk metrics, allocations, and simulated trades—allowing users to independently evaluate how a strategy has behaved across different market conditions.

At the same time, it’s important to clearly understand what AlgoMart does not do. AlgoMart is not a fund manager, not a robo-advisor, and does not provide personalised investment advice.

This guide explains the difference in plain English.

Quick definition

AlgoMart is a quantitative investment strategy marketplace.

You subscribe to access investment strategies supported by analysis, including historical simulations, performance statistics, allocations, and rebalance information—so you can evaluate strategies independently and decide how (or whether) to apply them within your own investment framework.

Marketplace vs Fund vs Robo-Advisor

Many investors encounter different platforms that appear similar on the surface but operate very differently underneath. Understanding this distinction is essential.

AlgoMart:

• Provides access to structured quantitative investment strategies

• Displays historical performance, benchmarks, allocations, and risk metrics

• Does not hold capital

• Does not execute trades

• Leaves all decisions and execution under user control

Managed Fund:

• Pools investor capital

• Makes investment decisions on behalf of investors

• Executes trades directly

• Investors delegate control to the fund manager

Robo-Advisor:

• Typically collects investor profile information

• Automatically allocates and rebalances portfolios

• Executes trades on the user’s behalf

• Often provides model-driven portfolio recommendations

AlgoMart operates fundamentally differently: it provides strategies and analysis, not discretionary management.

What you get on AlgoMart

AlgoMart is built around clarity, transparency, and consistency in how investment strategies are presented. Depending on the strategy and subscription tier, users can typically access:

• Historical performance simulations based on long-term back-testing

• Strategy-specific benchmark comparisons (e.g. blended equity/bond benchmarks)

• Risk and performance metrics such as:

  • CAGR

  • Sharpe and Sortino ratios

  • Alpha and Beta

  • Volatility and maximum drawdown

• Strategy allocations and simulated trade history

• Rebalance information, typically on a monthly basis, with additional adjustments during specific market conditions

All data is generated by AlgoMart’s proprietary simulation and back-testing engine using a unified data source to ensure consistency across strategies.

What you don’t get (and why that matters)

1) AlgoMart does not hold your money:

AlgoMart does not custody or control client assets. Your capital remains entirely with your chosen broker or custodian.

2) AlgoMart does not trade for you:

AlgoMart does not place trades on your behalf. Strategy allocations and rebalance information are provided for transparency and analysis—not automatic execution.

3) AlgoMart does not provide personalised investment advice:

AlgoMart does not assess individual financial circumstances, objectives, or risk tolerance, and does not recommend strategies to specific users.

This distinction matters because AlgoMart should be used as a decision-support and strategy-evaluation platform, not as a managed investment product.

What “marketplace” means in practice

A marketplace model allows you to:

• Compare multiple quantitative strategies side-by-side

• Evaluate how different strategies behave across market regimes

• Understand the trade-offs between growth, volatility, and drawdowns

• Choose how (or if) a strategy fits within your own investment approach

The Knowledge Base exists to help translate strategy data into understanding—so users can engage with strategies confidently and responsibly.

A simple 10-minute starting checklist:

If you’re new to AlgoMart, this approach helps build confidence quickly:

1. Read the strategy concept to understand its objective and structure

2. Check the benchmark composition before comparing performance

3. Focus first on five key metrics:

   • CAGR

   • Maximum drawdown

   • Annual volatility

   • Sharpe ratio

   • Beta

4. Review how the strategy behaves during stress or defensive regimes

5. Only then review cumulative returns and long-term charts

This order helps avoid performance-first bias and supports more informed evaluation.

Important note (informational use):

All content on AlgoMart is provided for informational purposes only. It does not constitute investment advice, does not consider individual circumstances, and should not be interpreted as a recommendation to buy or sell any security or adopt any specific strategy.

Users are encouraged to conduct their own due diligence and consult qualified financial professionals before making investment decisions.