Finandy News

Important Notice from Finandy We have identified a security incident involving the compromise of a Finandy server-side transit wallet used to process user withdrawals. The compromise was not detected immediately. As a result of unauthorized access, funds were withdrawn from the wallet. This wallet was deployed and used exclusively for the operational processing of withdrawals. At the time of the incident, it held a portion of the remaining funds left after the closure of Finandy’s brokerage infrastructure. The compromised wallet has been taken out of service. We are currently conducting a full review of our infrastructure and investigating the cause of the compromise. The unauthorized withdrawal of funds has been confirmed. The exact amount of losses and the list of affected users are currently being determined as part of the reconciliation process. Once the review is complete, we will publish confirmed information regarding the consequences of the incident and separately provide details on how the situation will be resolved for affected users. ‼️IMPORTANT‼️ The incident does not affect API trading or user funds held on connected external exchanges. It relates exclusively to the remaining funds held in Finandy wallets deployed to process withdrawals after the closure of the brokerage infrastructure.

✏️ How Comparing Your P&L to Others’ Distorts Your Own Plan In trading, it’s easy to start evaluating yourself not based on your own system, but on other people’s results. When someone shows a big profit, impressive stats, or a successful entry, you immediately get the feeling that you’re not doing enough. The problem is that someone else’s P&L almost never shows the full picture. It may be based on a different account balance, a different risk level, a different leverage ratio, a different strategy, and a completely different drawdown level. When a trader starts comparing themselves to someone else’s numbers, they gradually lose touch with their own plan. The urge arises to trade more aggressively, enter the market more often, or take trades that previously didn’t fit the system 😬 As a result, decisions are made not based on logic, but on the desire to “keep up.” But the market doesn’t reward you for trying to catch up to someone else’s results. It punishes you for losing control of your own trading 🧠 Someone else’s P&L can be motivating, but it shouldn’t become the benchmark for your risk, pace, or decisions. In trading, what matters isn’t looking successful compared to others, but consistently sticking to your own plan.

🤖 What Is AI Token Scoring and What Are Its Weaknesses AI token scoring is the evaluation of a project using artificial intelligence. The system analyzes various data points: market capitalization, trading volume, team activity, social media, on-chain metrics, tokenomics, listings, and holder behavior. As a result, the token receives a relative rating indicating how strong, risky, or promising it appears to be. This is convenient because AI can quickly process a volume of information that would take a long time to analyze manually 🔍 But this approach has a weakness: AI evaluates data, not the future. If a project looks good based on metrics, that doesn’t necessarily mean it will deliver growth. Some data may be inflated, social media activity may be artificial, and trading volumes may not reflect real interest. Furthermore, AI may not understand the context. For example, why the market is currently ignoring a particular sector, why investors don’t trust the team, or why a good project has ended up in the wrong phase of the cycle 🧩 Therefore, AI scoring is useful as a filter but dangerous as a ready-made answer. It helps to quickly weed out weak options and identify points for analysis, but the final decision must still take into account the market, risks, and common sense.

📊 Weekly Recap The week saw a cautious recovery. Bitcoin managed to climb above $61,000 following weak U.S. labor market data: market participants once again began pricing in a more dovish stance from the Fed, which supported demand for risk assets 💵 However, the overall backdrop remains challenging. Citi lowered its forecasts for BTC and ETH, citing weak ETF inflows, slow progress on crypto regulation in the U.S., and investor caution. Strategy received particular attention. The company announced a financial restructuring, including a liquidity reserve and the possibility of selling a portion of its BTC holdings to support its obligations and buyback program. This is an important signal for the market: even the largest holders are beginning to manage risk more actively. At the same time, capital continues to shift toward the AI sector. This creates competition for investors’ attention: crypto now needs more strong drivers to restore a steady inflow of funds. The main takeaway of the week: there’s no panic, but there’s no clear trend either. The market is trying to recover, but major players are still acting cautiously. In this phase, it’s more important to look not at the rebound itself, but at whether the price can hold after it 👀

🏦 Why the RWA Sector Has Become a Topic of Its Own for Traders RWA stands for the tokenization of real-world assets: bonds, real estate, funds, commodities, and other instruments that exist outside the crypto market. Interest in this sector is growing because it bridges the gap between crypto and traditional finance. This is an important step for the market: tokens are no longer just speculative ventures but are beginning to be tied to real assets 🧱 For traders, RWA is interesting not only as a long-term trend but also as a separate sector to monitor. When capital flows into this sector, related tokens, infrastructure projects, and platforms that work with tokenization begin to grow. That said, it’s important not to confuse hype with real value. Not every project labeled “RWA” automatically becomes a strong one. You need to look at what exactly is being tokenized, whether there’s demand, who the project’s partners are, and how transparent the model is 🔍 RWA has become a distinct topic because the market is increasingly looking not just for a cool idea, but for a connection to the real economy. And if this sector continues to develop, it could become one of the bridges between crypto and large institutional capital.

🔍 How Traders Can Verify AI Conclusions Without Turning Them Into Trading Signals AI can quickly analyze news, compare scenarios, and highlight risks. But its conclusion isn’t a trading signal - it’s material for analysis. The main mistake is to treat the neural network’s response as a ready-made solution: “The AI said so, so it must be okay to enter.” In reality, it may not take into account current liquidity, chart context, commissions, trade risk, or important events that change the picture 🤖 Therefore, AI conclusions should be tested as hypotheses. What data did it use? What might it have overlooked? Is there an alternative scenario? Does the idea align with your risk management and trading plan? A good approach is to ask the AI not only for arguments “for” but also for arguments “against.” This helps you avoid getting too attached to a single idea and spot weaknesses in the logic more quickly 🧩 AI is useful when it helps you think more broadly. But it becomes dangerous when a trader starts shifting the responsibility for entry onto it. Use AI as an analyst, not as a button to execute a trade. The decision still has to go through your system, risk management, and understanding of the market 🛡️

⏳ How Options Affect Spot Price Movements Before Expiration As options approach expiration, the market often begins to behave differently. The price may “stick” near certain levels, move more sharply than usual, or, conversely, become too calm. The reason is that large market participants have open positions in options, and as the expiration date approaches, they have to manage their risk. They hedge their positions through the spot or futures market, and this affects the price of the underlying asset 🧮 For example, if there is a concentration of option interest near the current price, the market may gravitate toward these zones or linger near them for a long time. Sometimes it looks as if the price is “magnetically drawn” to a certain level. But after expiration, the situation can change dramatically. Some of the pressure disappears, hedges are closed out, and the market gains more freedom to move in a new direction 🧲 That’s why, ahead of major expirations, it’s important to look not only at the chart but also at option levels, open interest, and areas where significant risk may be concentrated. Options do not directly control the market, but they often alter its behavior at the most critical moments.

🧠 Why Traders Confuse Access to Information with an Edge Today, traders have access to almost everything: news, charts, on-chain data, reports, analytics, expert opinions, and AI tools. It seems that the more information there is, the higher the chance of making the right decision. But access to data in and of itself is not an edge. The problem is that thousands of market participants see the same information. If a news story has already hit the feed, a report has already been analyzed, and a chart is already being discussed in chat rooms, that information is no longer unique 📰 The real advantage lies not in the moment the information is received, but in how the trader interprets it: what they filter out, what risk they’re willing to take, which scenarios they compare, and whether they can avoid reacting emotionally. Sometimes an excess of data can even be a hindrance: it leads to more doubts, more conflicting signals, and the urge to constantly double-check oneself. That’s why the winner isn’t the one with the most tabs open, but the one who can quickly separate the important from the noise and make decisions based on a system, not on the flow of information.

🧮 What Is a Basis Trade and Why Do Major Players Use It? A basis trade is a strategy that exploits the difference between the spot price of an asset and the futures price of the same asset. For example, if Bitcoin is cheaper on the spot market but its futures are trading at a higher price, a trader can buy BTC on the spot market and simultaneously open a short position in the futures market. In this case, the trader’s goal is not to profit from a rise or fall in BTC’s price, but rather from the narrowing of this spread. This is attractive to major players because such a trade is less dependent on the market’s direction. They don’t need to predict where the price will go. What matters more is that the spread between the spot and futures prices converges over time. Funds and professional traders actively use these strategies, especially when there is high demand for leverage in the market, futures are trading at a premium, and funding rates or price differentials become attractive. But a basis trade is not a “risk-free button.” There are risks related to liquidity, fees, changes in funding rates, sharp price movements, and execution issues 🧩 That’s why this strategy is most often used by those with access to capital, infrastructure, and precise risk management. To put it simply: a basis trade isn’t a bet on the market’s direction, but an attempt to profit from the difference between its various layers.

🧩 Why Traders Need Their Own Set of Prompts for Market Analysis AI can be a useful tool, but the results depend heavily on how the question is phrased. A general request like “analyze the market” will almost always yield a response that’s too superficial. That’s why traders need their own set of prompts for different tasks: analyzing news, testing trading ideas, assessing risks, identifying weaknesses in a scenario, and preparing a brief summary of an asset 🧠 Such a set helps you avoid starting from scratch every time. Instead of chaotic questions, a structure emerges: what to check, what data to consider, which scenarios to compare, and where errors might lie. This is especially important when the market is moving quickly. A good prompt helps not just to get an answer, but to quickly organize your thoughts 🔍 But prompts shouldn’t turn into ready-made signals. Their purpose is to help with analysis, not to make decisions for the trader. Essentially, a set of prompts is a working tool - like a checklist, but for AI-driven analysis. The more precise the questions, the more useful the answers.

💻 How AI Agents Can Transform a Trader’s Work AI agents aren’t just chatbots that answer questions. They are systems capable of performing a sequence of tasks: gathering data, analyzing the situation, comparing scenarios, identifying risks, and drawing conclusions. For a trader, this can significantly change their workflow. Instead of manually checking news, reports, on-chain data, the events calendar, and asset behavior, part of this routine can be delegated to an AI agent 🧠 For example, the agent can compile a daily market summary, track important changes, send reminders about events, review the trading plan, or identify weaknesses in a trading idea before entering a trade. But here’s the key point: an AI agent shouldn’t become a “place a trade for me” button. Its task is not to replace the trader’s thinking, but to filter out unnecessary noise and help make more structured decisions faster 🛠️ The main advantage of such tools is speed and consistency. They don’t get tired, they never forget to check important factors, and they can handle large volumes of information. However, the responsibility still lies with the human. An AI agent can prepare data and highlight risks, but the final decision must be made by the trader. This is precisely where the future of trading may lie: not humans versus AI, but humans working with AI against market chaos.

🤖 How Exchanges Are Integrating AI Into Their Products Today AI on exchanges is no longer “the technology of the future,” but rather a part of their actual infrastructure. It’s used not only for visually appealing features in the user interface, but also for tasks that directly impact the security and performance of the platforms. One of the main use cases is anti-fraud and monitoring of suspicious activity. Exchanges use AI to more quickly detect unusual account behavior, suspicious withdrawals, fraudulent schemes, and attempts to circumvent rules. For example, Binance.US explicitly states that it uses a combination of human expertise and artificial intelligence in its AML processes, while Bybit has reported using an AI risk framework to intercept scam-related withdrawals 🛡️ The second area is personalization. AI helps select relevant tools more quickly, explain features, simplify support, and make the interface more intuitive for different types of users. Coinbase is already moving toward AI-powered advisors and agentic trading, where AI becomes not just an assistant but an integral part of the user experience 🧠 The third area is risk management. AI can analyze user behavior, volatility, and market activity to flag situations in advance where risk is higher than usual. But it’s important to understand: AI on an exchange isn’t a “make money” button. It’s a technology that makes the platform faster, safer, and smarter. The decisions still rest with the trader.

🧠 Can AI Help Control Emotions in Trading? AI doesn’t completely eliminate emotions from trading. But it can help you recognize when decisions start to be made not according to plan, but under pressure. For example, a trader can use AI to analyze their trading journal: after which trades does haste tend to set in, where does excessive risk begin, and at what moments are rules most often broken? 🔍 This helps identify recurring behavioral patterns that usually go unnoticed in the heat of the moment. AI can also be useful as an “external filter”: before entering a trade, you can quickly check the idea, the risk, and the pros and cons. Sometimes simply structuring a trade reduces the emotionality of the decision 🧩 But it’s important to understand: AI is no substitute for discipline. It can highlight a problem, ask the right questions, and help analyze mistakes, but it’s still a person who presses the button. Therefore, the best approach is to use AI not as an “buy or sell” advisor, but as a tool for self-control. It won’t automatically make a trader calm, but it can help them notice sooner when emotions start to take over their trading.

📅 Weekly Recommendations for Traders The market is starting the week on a cautious note: Bitcoin has once again fallen below $60,000 amid ETF outflows and escalating geopolitical tensions. This is putting additional pressure on the entire crypto market and dampening risk appetite 💸 The main focus right now is not to try to catch the bottom, but to watch how the market behaves near key levels. If rallies quickly fizzle out and buyers fail to hold those levels, it looks more like a weak recovery than the start of a reversal. This week, keep an eye on ETF flows, BTC’s reaction near $60,000, news from the Middle East, and U.S. macroeconomic data. Pay special attention to the labor market: fresh data could influence rate expectations and overall risk appetite 🏦 The strategy for the week is simple: don’t increase leverage after sharp moves, don’t enter pullbacks without confirmation, and take profits quickly during weak momentum. The market remains volatile right now, so it’s more important to maintain control over risk than to try to catch every move 🛡️ *This post is for informational purposes only and does not constitute personalized investment advice.

👀 How to Identify a Market Where It’s Better to Watch Than to Trade Not every market is suited for active trading. Sometimes the best approach isn’t to look for an entry point, but to wait. One of the main signs is a lack of consistency. The price constantly changes direction, breakouts are quickly reversed, and neither buyers nor sellers can maintain the upper hand for long. Another signal is a weak reaction to key levels and news. It would seem that the market should move, but instead it remains range-bound or produces chaotic spikes. During such a phase, the number of false signals usually increases sharply. Even good ideas stop working as expected. It is precisely during these periods that the urge arises to “squeeze” a trade out of the market at any cost. But more often than not, this leads only to unnecessary entries and avoidable losses. Sometimes the most professional trade is the one you didn’t make. The ability to wait for the moment when the market becomes clear again is just as important a skill as the ability to enter a position at the right time 🧠

🚀 What happens when the price outpaces fundamentals? Sometimes an asset’s price rises much faster than its actual performance. The company hasn’t increased its profits yet, the technology hasn’t been widely adopted, but the price has already risen severalfold 📈 This means the market is beginning to price in expectations for the future rather than the current state of affairs. This happens when investors believe the asset will become significantly more valuable in a few months or even years. The higher the expectations, the faster the price can outpace fundamental factors 💭 The problem arises when reality fails to keep up with these expectations. Even good news may stop supporting growth because the market has already priced it in. This is precisely why a period of rapid growth is often followed by a prolonged consolidation or correction. Not because the asset has become bad, but because the price needs to “catch up” to the fundamentals. ⚖️ It’s important to remember in the market: in the long run, fundamentals and price tend to converge. The only question is which will move faster—the business or the price 🧩

🧠 Why Good Decisions Often Seem Wrong In trading, the right decision doesn’t always feel comfortable. Sometimes a good trade seems too risky, closing a position feels premature, and deciding not to enter a trade feels like a missed opportunity 😬 This happens because the brain evaluates a decision based on the emotions of the moment, rather than on the quality of the process. For example, closing a losing trade according to plan is unpleasant. But it may be the right decision if the scenario has broken down and the risk has gone out of bounds ⛔️ Similarly, missing a move may seem like a mistake, although in reality it’s a sign of discipline if the setup didn’t meet the rules. Good decisions often look wrong before the result becomes clear. That’s why in trading, it’s important to evaluate not only the outcome of the trade but also how well the decision aligned with the system. This is precisely what distinguishes a systematic process from randomness.

📊 Weekly Recap It was a week marked by market pressure: crypto once again moved in tandem with the broader flight from risk. Bitcoin remained below $60,000, with ETF outflows and caution among major players exacerbating the weakness 💸 The main backdrop of the week was a sell-off in the tech sector. Shares of chip and AI companies fell sharply, and along with them, appetite for risky assets deteriorated. This is an important signal for crypto: the market is reacting more and more strongly not only to internal news but also to sentiment on the Nasdaq and in the tech sector. Separately, market participants kept a close eye on oil, the dollar, and inflation expectations. Oil prices fell as supply concerns eased, while gold, on the other hand, found support as a safe-haven asset. Within the crypto market, the main problem remains the same: there is price movement, but little confidence in it. Any rally is quickly met with profit-taking, and buyers have yet to demonstrate firm control. The week’s conclusion is simple: the market isn’t in a panic, but it’s in defensive mode. As long as large capital remains cautious, it’s better to focus not on individual price spikes, but on the price’s ability to hold its levels after a move 👀

🔄 Why the Market Loves to Return to Old Ideas There’s an interesting pattern you often see in the market: topics that seemed to have been forgotten end up back in the spotlight after some time. At one point, it was meme coins; then, NFTs; and later, artificial intelligence. After a while, interest wanes, but then the market starts discussing the same ideas all over again 💬 The reason is simple: market participants are constantly looking for clear narratives they can believe in. If a topic has already attracted capital and attention once, the likelihood of its return remains high. But the market rarely repeats the exact same scenario. It’s not the story itself that returns, but the interest in it. New conditions, different valuations, and shifting market sentiment can completely change the outcome 🧠 That’s exactly why experienced traders keep an eye not only on new trends but also on those the market has already “been through.” Sometimes the most interesting opportunities arise not where a new idea is born, but where an old one gets a second life ➕

📈 How Price Movements Form When There Is a Shortage of Sellers Many people believe that a strong influx of buyers is essential for market growth. But sometimes prices rise for a different reason—simply because there are too few sellers. Imagine this scenario: there are almost no sellers willing to actively sell, while demand remains at least at its usual level. At such a moment, even small purchases begin to gradually push the price upward 🔼 Interestingly, such price movements often appear calm. There are no huge volumes, no frenzy, and no sense that the market is about to explode. On the contrary, the rise can be slow and even boring. But at the same time, every attempt at a decline ends quickly because there simply aren’t enough sellers to sustain the drop. That’s exactly why strong movements sometimes begin not with an influx of new buyers, but with the disappearance of the desire to sell. For traders, this is an important reminder: price doesn’t move solely because of demand. Sometimes, a shortage of supply becomes the main factor 🧩 The market rises not when everyone wants to buy, but when there are fewer sellers than needed to maintain the current price 🚀