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Diversification means spreading your capital across different assets, which may help reduce risk and stabilize returns. Different asset classes often move in opposite directions: when one falls, another may rise. Diversification can take place both across asset classes (e.g., stocks and bonds) and within each class (different sectors or securities).

They are exchange-traded instruments with low costs that make market access easier.

• ETF (Exchange-Traded Fund): funds that track a stock or bond index, offering broad diversification.
• ETC (Exchange-Traded Commodity): instruments that allow you to invest in commodities (gold, oil, wheat), adding commodity exposure to the portfolio.

• Distributing ETFs: periodically pay dividends or bond coupons to investors.
• Accumulating ETFs: automatically reinvest profits within the fund, increasing the value of the shares.
• ETCs on commodities don't generate cash flows (like dividends or coupons), so they cannot distribute or reinvest proceeds.

PharosFolio® uses a simple model built on three asset classes: global equities, Eurozone government bonds, and gold. This combination balances growth, stability, and protection while keeping costs low and avoiding unnecessary complexity. Other asset classes, such as real estate or cryptocurrencies, were deliberately excluded, as they would increase costs and complexity without delivering clear benefits for most investors.

Accumulating ETFs automatically reinvest any distributions, which can make them an efficient solution for long-term growth in many cases, but the best choice depends on each investor's personal situation and local tax rules.

Rebalancing is a periodic adjustment that brings the portfolio back to its target asset allocation, which may help manage risk and returns.

• Classic rebalancing: assigns fixed percentages to each asset (e.g., 60% stocks, 35% bonds, 5% gold), without adapting to market changes. When you rebalance, you restore these exact percentages.
• Adaptive allocation (PharosFolio®): updates target allocations based on risk estimates and market conditions, which historically showed potential to reduce volatility during market stress.

With PharosFolio® you can simulate both approaches. Our adaptive allocation method uses a proprietary risk management model designed to explore the balance between risk and return.

The key difference is what each approach rebalances to:

• Fixed 60/40 Allocation: You choose a static mix (60% stocks, 40% bonds) and rebalance periodically to restore those exact percentages, regardless of market conditions.
• PharosFolio® Adaptive Allocation: The target allocation changes based on risk estimates from our proprietary model. During periods of higher market stress, the model historically adjusted to more conservative allocations; during calmer periods, it allowed for more growth-oriented positions.

Both portfolios rebalanced annually—the key difference is adaptive vs fixed target allocations.

Important: PharosFolio® adaptive allocation is not market timing. It doesn't try to predict short-term price movements or tell you when to buy or sell. Instead, it systematically adjusts the target portfolio mix based on quantitative risk estimates. Both approaches require staying invested and rebalancing periodically—the difference is in the systematic rule behind the allocation decision.

Many studies show that trying to time the market is difficult and can increase trading costs and stress. PharosFolio® is built around the idea of staying invested with a diversified portfolio and looking at periodic rebalancing in the simulations, rather than trying to guess short-term market movements.

The tool shows how different rebalancing choices would have behaved in past markets; it does not try to predict or time future moves, and it does not tell you when to buy or sell.

General-purpose chatbots generate broad market commentary. PharosFolio® simulations run on real market data and let you test allocations, rebalancing rules, and risk bands that match your goals. We surface analytics (returns, volatility, drawdown, user plan context) that a chatbot doesn't provide.

A backtest simulator helps test investment strategies without risking real money. It lets you explore how different asset allocations might have performed historically, compare risk and return profiles, and understand various approaches. PharosFolio® uses a proprietary risk management methodology applied to a three-asset model (global equities, Eurozone government bonds, and gold) across 3 predefined risk levels. The backtest simulator shows how these portfolios would have behaved in the past based on historical data, providing educational insights.

Simulations provide a theoretical reconstruction of how a portfolio would have behaved in the past under ideal conditions, based on historical data. In reality, portfolios may behave slightly differently due to factors such as price changes, transaction costs, or market liquidity. Results should therefore be viewed as qualitative guidelines, useful for exploring scenarios and understanding possible risk/return profiles.

PharosFolio® uses both fund data and index data to build longer histories.

When a fund has no data for older periods, the backtest simulator fills the gap using the index it tracks.

Index data are an "ideal" benchmark, so when you compare two funds on the same index, the more recent fund (with more index backfill in its history) can appear to have better simulated performance than the older one.

For cleaner comparisons, it is usually better to:

• compare different risk levels or allocations using the same funds, or
• start the simulation from a date when all selected funds have data available.

In the fund selector, each ETF/ETC is shown with the date from which data are available in the backtest simulator, so you can take this into account.

Portfolio risk is the possibility that a portfolio's value may decline, sometimes sharply. A key indicator is the maximum drawdown, which represents the largest loss recorded over a given period. It shows how much a portfolio could temporarily fall during market stress. To add perspective, PharosFolio® also displays rolling annual returns over 3, 5, and 10 years, illustrating how portfolios perform across different time horizons. Considering drawdown and rolling returns together helps you assess whether a portfolio matches your goals:

• A portfolio with deeper drawdowns may still be suitable for long-term investors (10+ years), since historical data show it can recover and deliver stronger long-term returns.
• Conversely, if your horizon is shorter (around 3 years), a portfolio with smaller drawdowns and steadier rolling returns may be more appropriate.

PharosFolio® lets you compare up to three portfolios simultaneously, helping you balance your tolerance for temporary losses with your time horizon and investment goals.

The Sharpe Ratio is a risk-adjusted performance metric that measures how much excess return above the risk-free rate a portfolio generates relative to the dispersion of its annual returns. In PharosFolio®, it is calculated on an annual basis using the 3-month Euribor rate as the risk-free reference.

Formula:

Sharpe Ratio = X̄ / √( (1/M) · Σ_y=1^M (X_y − X̄)² )

Where:

• X_y = R_y − R_f,y (the excess return for year y).
• X̄ = (1/M) · Σ_y=1^M X_y (the arithmetic mean of the annual excess returns).
• R_y = the portfolio's return for year y.
• R_f,y = the 3-month Euribor rate for year y.
• M = number of years in the period. The expression under the square root is the population standard deviation of the annual excess returns—same convention as the PCI.

Higher Sharpe Ratio values indicate better risk-adjusted performance, meaning the portfolio has generated a higher and more stable risk premium above the risk-free rate.

The PCI is a proprietary risk-adjusted performance metric that measures the consistency of a portfolio's long-term growth path. It evaluates how closely a portfolio's actual annual returns cluster around its long-term annualized growth rate (CAGR), providing a direct measure of the stability of the compounding process over time.

Formula:

PCI = CAGR / RMSE

RMSE = √( (1/M) · Σ_y=1^M (R_y − CAGR)² )

Where:

• CAGR = the portfolio's compounded annual growth rate over the entire period.
• R_y = the actual return achieved during calendar year y.
• M = number of years in the period.
• RMSE (Root Mean Square Error) = the dispersion of annual returns relative to the CAGR, measuring how far annual returns typically deviate from the portfolio's long-term compounded growth rate.

PCI values approaching or exceeding 1 indicate an exceptionally consistent growth trajectory, meaning an equity curve where annual returns stay tightly clustered around the long-term CAGR trend.

PharosFolio® uses monthly ETF/ETC data from their launch date. To extend the history back to 2002, we rely on publicly available reference data and indexes:

• Equity ETFs:
  • Global (developed+emerging): MSCI ACWI for funds tracking that index, and MSCI ACWI IMI for all others (differences with similar global indexes are minimal).
  • Global (developed): MSCI World for all funds (differences with similar global indexes are minimal).
  • US: S&P 500 and NASDAQ 100 for funds tracking those indexes.
• Bond ETFs → as a proxy, we use data from the Xtrackers II Eurozone Government Bond ETF (the oldest in its category, launched in May 2007), and extend the series with a synthetic index built from European Central Bank data, using maturity weights aligned with common market benchmarks.
• Gold ETC → gold spot price.

For equities and bonds, we use the total-return versions of the reference indexes (dividends/coupons reinvested) to mirror accumulating ETFs. This way, the most recent part of the simulations reflects actual ETF/ETC performance, while the extended history provides a consistent qualitative reconstruction. Together, they allow portfolios to be assessed over long horizons.

Official bond indexes require very expensive licenses, which would be unsustainable at this stage for a start-up like PharosFolio®. To keep simulations consistent over long periods, we use a synthetic total-return bond index—built from publicly available ECB data with benchmark-style maturity weights and coupon reinvestment—so it aligns with accumulating ETFs. This synthetic proxy applies only to the older part of the historical series, while the most recent years are always based directly on Xtrackers II Eurozone Government Bond ETF data. This ensures simulations remain closely aligned with real portfolio behavior.

Simulations are based on monthly historical data, used to estimate risk levels and to calculate the asset allocation through walk-forward analysis. Since they rely on month-end prices, they are not affected by intraday price delays.

Rebalancing events are never triggered by market conditions: they occur on a set schedule or when the user makes deposits or withdrawals. At each event, the latest available market prices are used to calculate how many units of each ETF/ETC would need to be bought or sold to align the portfolio with the current target allocation. Prices used by PharosFolio® are delayed, with delays that vary by exchange: actual prices at the time of execution may differ, and users should take this into account before placing orders through their own broker.

PharosFolio® is a software tool designed to support advanced investors in managing their portfolio autonomously. Its outputs do not constitute investment advice, and any decision to act on them rests with the user.

PharosFolio® uses a proprietary risk model from the Risk Budgeting family. The model is a correlation-aware version of the inverse-volatility approach, with each asset weight derived through a closed-form equation. Unlike classic Risk Budgeting, which requires solving a system of nonlinear equations at every step, the closed-form equation makes the weights fully deterministic and simulations virtually instantaneous. Model parameters are recalibrated through walk-forward analysis at each scheduled rebalancing event.

Walk-forward analysis is a validation technique that calibrates a strategy on an in-sample historical window and tests it on the subsequent out-of-sample period. Repeating this process across successive rolling windows shows how the strategy would have performed using only the data available at each point in time, without look-ahead bias. PharosFolio® applies it at two stages: in simulations, where each period's results are computed out-of-sample, and at each rebalancing event, where the model parameters are recalibrated on the most recent window of monthly data, reducing overfitting.

No. PharosFolio® is a software tool designed to support advanced investors in managing their portfolio autonomously. Target allocations and buy/sell amounts are calculated by a rules-based model from the parameters you select (assets, amounts, risk level), without assessing your personal, financial or tax circumstances. They are not personalized investment recommendations, and any decision to place orders rests with you.

PharosFolio®'s simulations can be especially useful when you want to explore different risk levels or check how a portfolio could behave over time. Many users prefer to run simulations once or twice a year, or when their personal situation changes, to compare scenarios in a structured way.

When you move from simulations to real trades, it is important to think about liquidity and market depth for the ETF you are trading.

• Liquidity and order book
  Liquidity is how easy it is to buy or sell an ETF without moving its price too much. The "order book" is the list of buy and sell orders at different prices. In ETFs with low trading volume or a thin order book, large orders can be harder to execute at the expected price.
• Larger orders
  With larger orders, there is a higher risk that the trade is only partially executed or not executed at all at your chosen price. For this reason, some investors prefer to split a large order into smaller trades, placed over time, to reduce the impact on the market and improve the chance of full execution.

PharosFolio® is designed for advanced investors in the Eurozone who want a simple, low-cost, and diversified way to explore portfolio strategies without active trading or complex products.