Three practical reads from the Murravyn team. They are written for people who use (or are considering) automated trading, and they favour specific habits over grand theories. None of it is investment advice, and all of it applies regardless of which platform you trade on.
Common trading mistakes, and how to avoid them
Most trading mistakes are not exotic. They are ordinary human shortcuts applied to a market that punishes shortcuts, and they show up in the first months of almost every account we see. The good news is that each has a simple, mechanical fix, and none of them requires talent, only a small amount of discipline.
The first mistake is starting too big. When the first deposit equals everything a person is willing to invest in the idea, every percentage move feels decisive, attention turns obsessive and decisions turn emotional. The fix is to begin with the tier minimum, €250 on Basic, and to add only after a month of watching how your own temperament reacts to normal swings. You are learning two things at once: the market's behaviour and your own.
The second is confusing a bull market with skill. In a rising market, most positions pay, and confidence compounds faster than capital. The reality check is deliberate record-keeping: write down, per strategy, what you would have done in a falling market, and check it against what actually happens when one arrives. Strategies that only work when everything rises are not strategies; they are exposure.
The third is revenge trading: recovering a loss quickly by doubling exposure, which converts a bad day into a bad month. The mechanical fix is a personal circuit breaker, a rule written in advance that stops trading for the rest of the day after a set drawdown. Automated platforms make this easy to configure and impossible to argue with, which is the point.
The fourth is ignoring costs. A strategy that returns slightly less than the sum of its commissions and spreads is a hobby, not an investment. Check the cost breakdown in your reports monthly, and be sceptical of any setup whose costs are hard to find. On this platform every fee is shown before you confirm a transaction, so there is no excuse not to look.
Finally: not having an exit plan. Decide, in writing, under what conditions you would stop a strategy, take money off the table, or add to a position, and review that plan quarterly rather than in the moment. Decisions drafted calmly and executed under pressure beat decisions improvised under pressure, every time.
Manual trading versus automated trading
Manual trading means you find the opportunities, place the orders and manage the positions yourself. Automated trading means software does some or all of that according to rules you configure. Neither is inherently superior; they solve different problems, and understanding the trade-offs matters more than picking a side.
The strengths of manual trading are judgment and context. A person can read a news story, sense that the market has overreacted, and decide that today is a day to do nothing. The weaknesses are the mirror image: humans tire, get emotional, cannot watch markets overnight, and execute inconsistently when it matters most. The classic failure is having a plan and abandoning it at the worst moment because a position is underwater.
Automated trading's strengths are consistency and coverage. A strategy watches its instruments continuously, applies its rules identically at 3 a.m. and 3 p.m., and never hesitates because it had a bad sleep. For anyone with a job, a family or any other claim on their attention, that coverage is the entire appeal: the analysis and execution happen while you live your life, and the audit history shows exactly what was done and why.
The weaknesses of automation are rigidity and false comfort. A strategy applies its rules even when conditions have changed in a way its rules do not measure, and it will never knock on your screen to say "this no longer makes sense". That is why automation on this platform is supervised, not autonomous: you choose the strategies and their boundaries, volatility guardrails can pause activity when markets turn disorderly, and every action is logged for your review. The comfortable idea that software removes risk is exactly the idea to resist; what it removes is the need to be present for routine execution.
In practice, many experienced investors land on a hybrid: a core of automated strategies running quietly within strict limits, and a small amount of manual activity for the situations that reward human judgment. Whichever mix you choose, the discipline transfers: position sizing, written plans, cost awareness and honest record-keeping work identically in both modes. If you are starting from zero experience, automation with a personal manager reviewing settings with you is the gentler learning curve, precisely because the routine decisions are handled while you learn to supervise.
The psychology of trading
Markets are made of people responding to prices, which means markets are partly made of feelings. Fear, greed, regret and hope each have a signature on a chart, and the person who recognises them in themselves has an edge over the person who only recognises them in others. Trading psychology is not decoration around the numbers; it is half the game.
Loss aversion is the foundation. Losing €100 hurts roughly twice as much as gaining €100 feels good, so people hold losing positions hoping to break even and sell winners early to lock in relief. The result is a portfolio of the positions you regret and none of the ones serving you. The countermeasure is deciding exits in advance, when no money is at stake, and treating those decisions as contracts with yourself rather than suggestions.
FOMO, the fear of missing out, is loss aversion's sibling: watching an asset run away and buying late, at the top of enthusiasm, with the largest position of the whole cycle. The tell is that the urge intensifies the longer the move has already lasted. The countermeasure is a written allocation plan: fixed amounts, fixed conditions, and a rule that no asset gets a larger allocation because it is moving today. Automation helps here more than willpower ever did, because a configured strategy is immune to a chart that looks exciting.
Overconfidence arrives after a run of good results, which is why it is most dangerous exactly when you feel safest. The signature is position sizes creeping upward, risk rules quietly relaxed, and the phrase "this time is different" said without irony. The countermeasure is boring bookkeeping: log every decision, review the losses you would have taken at your original risk settings, and let a spreadsheet argue with your self-image. Quarterly reviews with your manager serve exactly this purpose.
The healthiest mental model we know is to treat trading as a long game played in small, survivable increments. Nothing that happens in one week should be able to change your month, and nothing in one month your year. People who size accordingly sleep well, review their reports with curiosity instead of dread, and make better decisions precisely because none of them felt urgent. That calm is not a personality trait; it is an architecture, built from allocation limits, written plans and a schedule for checking the screen that you actually keep.
If you recognise yourself struggling, act on the structure rather than the mood: reduce sizes, pause strategies, take a week away. The market will still be here when you return, and the account you protected by resting will thank you for it.