Frequently Asked Questions (FAQ) on Performance, Regulation, and Transparency

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We understand that investing in a sophisticated tool like AISHE requires trust and clarity. The world of automated trading is filled with bold claims, and we believe in addressing critical questions head-on. This FAQ is designed to provide transparent answers to the tough but fair questions that any serious user should ask. Our answers are based on the fundamental nature of AISHE: it is not a financial service, investment fund, or brokerage, but a highly advanced software tool - an Applied AI - that you, the user, install and operate on your own computer under your full control and responsibility.

This software is strictly for personal, non-commercial use only. As a private-use tool, it falls under the EU AI Act Article 2(1)(c) exemption. Commercial or professional use is strictly prohibited. Users are solely responsible for all trading decisions and compliance with applicable laws. (alert-warning)

1. Independent Performance Verification

Q: Are there independent audits of your trading results by firms like Deloitte or PwC?

A: No, and this is by design. Audits by firms like Deloitte or PwC are conducted for investment funds, asset managers, and companies that manage client funds. AISHE is a software product, not a fund. We do not manage client money. The trading results are generated on the individual, private accounts of each user at their respective brokers. Since we have no access to or control over these private accounts, a centralized audit of "company" trading results is not applicable. Performance is individual to each user's setup, timing, and broker.

Q: Do you provide verified backtest results over multi-year periods?

A: Backtesting is a standard tool for simple, rule-based Expert Advisors (EAs). However, AISHE is a dynamic, learning KI system. A traditional backtest, which rigidly applies a static set of rules to historical data, cannot accurately replicate the adaptive, real-time decision-making process of AISHE's neural network, which analyzes the market's "hidden state" (Human, Structural, and Relational factors). While we conduct extensive internal historical simulations during development, we consider forward-testing on live accounts to be the only true measure of performance for an adaptive AI. We encourage new users to utilize the free trial period to observe AISHE's performance in the current, live market environment.

Q: Have your performance claims been validated by regulatory authorities?

A: Regulatory authorities do not "validate" the performance claims of software products. Their role is to supervise licensed financial service providers. As a software developer providing a tool for personal use, we do not fall under this category. Our performance discussions are based on developmental data and user-reported experiences, which should not be construed as a guarantee of future results.

2. Regulatory Compliance and Licensing

Q: Does AISHE hold official financial services licenses (e.g., as an asset manager or broker)?

A: No. AISHE is a software company providing a tool for self-directed traders. We are not a broker, we do not provide investment advice, and we do not manage client assets. Therefore, a financial services license is not required for our business model, just as a manufacturer of professional trading terminals or charting software does not require one. The user always maintains full control and legal ownership of their funds at their chosen, licensed broker.

Q: Does the system comply with algorithmic trading regulations like MiFID II?

A: Regulations like MiFID II apply primarily to investment firms, brokers, and trading venues. They govern how these regulated entities manage their algorithmic trading activities to prevent market disruption. As a software tool operated by a retail user on their own account, AISHE itself is not a regulated entity under these directives. The responsibility for complying with the broker's terms of service and any applicable local regulations regarding automated trading rests with the user. AISHE operates through standard, broker-provided platforms like MetaTrader 4, staying within the technical ecosystem permitted by the user's broker.

3. Technical Validation and Risk Management

Q: Have the AI algorithms been validated by independent experts?

A: The core AI model of AISHE, based on the proprietary "Knowledge Balance Sheet 2.0" theory, is the result of over a decade of research and development. The underlying concepts have been developed in academic discourse. While the specific, proprietary code of AISHE is a protected trade secret (our "intellectual capital"), its conceptual foundation is robust. We focus on performance and stability as the ultimate validation of our model's effectiveness.

Q: Is there a robust risk management system with verifiable pre-trade controls and kill switches?
A: Absolutely. Risk management is a core component of the AISHE client.

User-Defined Controls: The user sets key risk parameters within the AISHE client, such as maximum lot size, risk per trade, and overall drawdown limits, which act as pre-trade controls. AISHE will not exceed these user-defined boundaries.
Internal AI-Driven Risk Management: The AI itself has internal risk management protocols. For example, the "half-life" of its forecasts ensures it doesn't cling to outdated market assessments, and it is designed to reduce or halt activity in market conditions it identifies as unpredictable or irrational.
Kill Switches: The user maintains ultimate control. They can deactivate AISHE instantly within the software client or by simply closing the MetaTrader 4 platform, which immediately severs the connection and stops all automated activity.

4. Transparency of Business Operations

Q: Who are the founders and management team?

A: The founder and lead developer of the AISHE system is Sedat Özcelik. His work on the underlying "Knowledge Balance Sheet 2.0" theory, which forms the philosophical and strategic foundation of AISHE, dates back to 2008 in collaboration with academic partners. More information about our history can be found on our "About Us" page.

5. Institutional Partnerships and Endorsements

Q: Does AISHE work with established financial institutions or have verified broker partnerships?

A: AISHE is designed to be broker-independent and operates on the globally recognized MetaTrader 4 platform, which is offered by hundreds of licensed and regulated brokers worldwide. This independence is a key feature, giving users the freedom to choose the broker that best suits their needs. We do not have exclusive "partnerships" that would compromise this neutrality. Any user with an MT4 account from a reputable broker can use AISHE.

Q: Are there endorsements from recognized financial experts?

A: We believe the most powerful endorsement comes from the user community itself and the transparent logic of our system's design. We focus on providing a robust tool rather than seeking paid endorsements, which can often be misleading. We encourage prospective users to engage with our community and review independently shared experiences.

6. Long-term Performance and Stability

Q: How did the system perform during market crises (e.g., COVID-19 crash)?

A: The core models of AISHE have been developed and simulated over many years, covering numerous market cycles, including periods of extreme volatility like the 2008 financial crisis and the 2020 COVID-19 crash. The system's design, which analyzes the market's "hidden state" (including the "Human Factor" of fear and panic), is specifically intended to adapt to changing market conditions rather than relying on static models that fail in a crisis. Its internal risk management is designed to become more conservative during periods of extreme, unpredictable volatility.

7. User Community and Verifiable Testimonials

Q: Is there an active, verifiable user base and independent reviews?

A: Yes, we have a growing global community of users. We encourage open discussion and the sharing of experiences in designated forums and social media groups. While we showcase testimonials, we strongly advise prospective users to seek out independent discussions and reviews on neutral platforms. The most verifiable experience is your own; that is why we offer a free trial period, allowing you to see the system in action for yourself before making any commitment.

8. The AI Model and Methodology

Q: How does AISHE define and analyze the "hidden state" of the market?

A: The "hidden state" of the market refers to the complex web of underlying drivers that cause observable price and volume changes but are not directly measurable themselves. Traditional analysis sees the price; we see the forces behind the price. AISHE is built on our "Knowledge Balance Sheet" model, which defines this hidden state through three core components:

The Human Factor: This represents the collective psychology of the market - fear, greed, herd behavior, panic, and euphoria. We analyze this through patterns in volatility, order flow speed, and price action velocity that indicate emotional rather than logical decision-making.
The Structural Factor: This is the "logic" of the market - its rules, established support/resistance zones, algorithmic trading patterns, and reactions to scheduled economic events. It’s the predictable, systematic part of market behavior.
The Relational Factor: This covers the complex interdependencies between different assets and markets. For example, how a change in the bond market might influence a currency pair, or how an equity index reacts to shifts in commodity prices.
AISHE's neural network is trained to continuously estimate the current "weight" or dominance of each of these factors, thereby creating a multi-dimensional view of the market's true condition.

Q: How does the AI combine these three factors to make a decision?

A: The combination is a non-linear, dynamic process managed by the core AI in our Main System. It's not a simple checklist. The neural network creates a real-time, multi-dimensional model of the market. Based on incoming data, it determines the current "market regime" by identifying which factor (or combination of factors) is dominant. For example:

In a high Human Factor regime (e.g., a panic sell-off), the AI will prioritize short-term momentum and counter-trend opportunities, expecting irrational overreactions.
In a high Structural Factor regime (e.g., quiet trading before a major news release), the AI will give more weight to established price levels and statistical probabilities.
In a shifting Relational Factor regime (e.g., a currency suddenly decoupling from its usual correlation with an index), the AI identifies this as a potential paradigm shift and may adjust its entire strategy for that asset.
The final trading decision is the output of this complex, continuous analysis, resulting in a forecast with a calculated "half-life" reflecting the AI's confidence and the expected duration of the current market state.

Q: Why do you state that traditional backtests are unsuitable for AISHE?

A: Traditional backtesting is effective for static, rule-based systems (like most EAs). It answers the question: "What would have happened if I had applied this fixed set of rules to past data?" This approach has a fundamental flaw when applied to an adaptive AI like AISHE:

It Ignores Learning and Adaptation: A backtest cannot simulate AISHE's ability to learn and adapt its internal weightings based on evolving market conditions. It would be like testing a grandmaster chess player by forcing them to make the same moves in every game, regardless of what their opponent does.
It Misses the "Hidden State": Backtests only use price and volume data. They cannot replicate AISHE's core function of estimating the hidden Human, Structural, and Relational factors from that data. The context is lost.
It Creates a False Sense of Security: An over-optimized backtest on historical data can look perfect but often fails in live trading because the market conditions of the past never repeat exactly.

We believe the only true test for an adaptive AI is forward performance validation in a live, unpredictable market. This is why the trial period is a central part of our offering.

9. Security and User Control

Q: What technical safeguards protect my funds when I run AISHE locally on my computer?

A: This is a critical point. The security of your funds is ensured by a clear separation of duties and a robust architectural design:

AISHE Never Accesses Your Funds Directly: The AISHE software does not have your brokerage login credentials or API keys for withdrawal/deposit. It operates through the MetaTrader 4 (MT4) platform, which is designed to allow trading signals without enabling fund management functions like withdrawals.
Execution via the Broker's Platform: All trade orders generated by the AISHE client are sent to and executed by your broker via the secure MT4 terminal. The security of your account and funds is ultimately handled by your regulated broker, just like with any manual trade.
No Remote Control: The AISHE client on your PC operates autonomously based on data from our Main System, but neither we nor anyone else can remotely log in to your AISHE client to execute trades. The link is for data and strategic parameters, not for remote control.
You Are the Ultimate Gatekeeper: Your funds are only at risk from trading losses, not from unauthorized access through our software. You can sever all activity instantly by closing the AISHE client or your MT4 platform.

Q: How customizable are AISHE's risk and execution settings?

A: We believe that while the core AI provides the strategic intelligence, the user must always remain in ultimate control of their risk. The AISHE client provides a comprehensive but easy-to-use control panel where you, the user, define the hard limits for the AI's operation on your account. These settings include, but are not limited to:

Maximum Risk per Trade: Set a fixed lot size or, more dynamically, a percentage of your account balance that any single trade is allowed to risk.
Maximum Overall Drawdown: Define a "red line" for your account. If the total drawdown reaches this user-defined percentage, AISHE will automatically stop all new trading activity.
Trade Session Times: You can restrict AISHE's trading activity to specific hours or days of the week if you wish to avoid certain market sessions (e.g., high-volatility news events).
Symbol Selection: You choose which financial instruments you want AISHE to operate on from a list of supported symbols.

The AI will always operate within the strict boundaries you set. It will never override your core risk management directives.