Trading Truth Exposed aggregates and publishes documented evidence of fraudulent trading advice, including failed predictions, pump‑and‑dump schemes, and false insider claims. The platform presents detailed timestamps, screenshots, and impact analyses for each case, quantifying follower losses such as the $2.3 M from Michael Sikand’s predictions. Users can also submit their own evidence to help build a comprehensive record that warns investors and deters future scams.
Funding
Funding not disclosed
Founders
Product
Problem
Retail investors are frequently misled by self‑styled trading gurus who share unverified predictions and false insider claims, leading to significant financial losses. There is no centralized, verifiable record of these fraudulent activities, making it difficult for investors to assess risk and avoid scams.
Solution
Trading Truth Exposed creates a publicly accessible database that aggregates verifiable evidence of fraudulent trading advice, including failed predictions, pump‑and‑dump schemes, and false insider claims. Each entry includes timestamps, screenshots, and impact analysis to demonstrate the real‑world consequences of the advice. The platform also provides a crowdsourced submission portal, allowing users to contribute additional proof while protecting their anonymity. By consolidating this information, the service enables investors to research a guru’s track record before following any recommendations, thereby reducing exposure to deceptive practices.
Target Audience
Primary users are retail investors and financial consumers who evaluate trading advice, as well as consumer protection organizations monitoring market misconduct.
Features
- Structured evidence catalog with categories such as Failed Predictions, Pump & Dump Schemes, Options Fraud, and Misinformation
- Detailed documentation for each case, including timestamps, screenshots, and quantified follower losses
- Searchable database and filter options to investigate specific individuals or types of fraud
- User‑driven evidence submission form with guidelines for providing verifiable data while keeping submitter identity confidential
- Impact analysis that aggregates total financial losses attributed to each fraudulent activity
- Regularly updated statistics summarizing overall fraud metrics (e.g., total failed predictions, cumulative follower losses)