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Phoenix, a no-loss brokerage for active individual investors

Hacker News

Phoenix, a no-loss brokerage for active individual investors

Do you like actively trading? If you do, chances are you lose money. 85% of active individual investors lose money, for an aggregate loss of around $1trn per year. Several major causes of this are outside the control of investors: 1. Wall Street has a large informational edge. 2. Wrongdoing towards individual investors goes unpunished by the government and regulators, with a revolving door between these two and Wall Street. 3. Short-term frictional costs eat into a short-term trading style. 4. Brokerages now have a business model of selling customer trades to financial institutions. This is rife with conflicts of interest and abuse, with limited transparency. 5. Brokerages are incentivized to push a bad trading style on their clients and do so, in order to maximize their own revenue. Phoenix seeks to provide better financial outcomes for individuals actively trading markets, with no potential for trading losses for any participants, but a real chance for big gains. We aim to reduce the $1trn loss of active individual investors by 98% (we plan to take the last 2% as our revenue), and to build a new community and product for them that has the core focus of improving investor outcomes. Every other individual investor brokerage product we’ve reviewed ultimately has the goal of exploiting them more, or in a new way. We’re taking a radically different approach. How does this work? Our core product doesn’t involve any interaction with real financial markets or institutions. Instead, we simply ingest market data into our app, and all customer trades are virtual based on these real prices. This means that investors trade in exactly the same way as they would in a real brokerage, just with simpler liquidity, algorithmic derivative pricing, and no real consequences if things go wrong (like margin calls, taxes on unrealized gains, or debt from losses on margin). This also means there are no deposits or fees required to participate in Phoenix. Investors who do well don’t make trading profit, but instead earn rewards based on their ranking on our leaderboard in each day or week. We generate the money for these rewards by taking subscription revenue in exchange for a variety of premium features that we offer associated with our ecosystem. This revenue feeds the value of a crypto token, which then automatically distributes rewards based on the ranking charts. Want more information? Visit phoenix-trade.io/docs for more info We don’t offer an account-less demo as most of our features depend on referencing a specific user. If you want to trade please sign-up at the title url.

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Actual performance

3points
Did not reach leaderboard

Launch Intel predictions

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Indie HackersFits the IH revenue-focused audience · Strong signals: maximize · Missing: supports, reddit linkedin, podcasting
88%88% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
best fitHighest predicted score across all platforms for this description.
TrustMRRFits verified-revenue profile · Strong signals: trading, way · Missing: mobile apps, ios, personal
66%66% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Product HuntOn track for Day 1 leaderboard · Strong signals: model, user, new · Missing: mac, agents, macos
59%59% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
Hacker NewsStrong engagement from HN community · Strong signals: ide, io · Missing: https docs, excited, just released
52%52% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
AppSumoMay struggle as an AppSumo deal · Strong signals: calls · Missing: plus, platform, intuitive
47%47% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Strong signals: revenue, profit, margin · Missing: arr, mrr, saas
26%26% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
BetaListMay not resonate with beta-testers · Strong signals: crypto, reward · Missing: web3, chat, cryptocurrency
0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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