These articles are not tutorials for the platform; your manager covers that on your first call. They are the ideas that decide whether trading goes well for someone, whichever tools they use, written the way we would explain them over coffee.
Common mistakes in trading, and the habits that prevent them
Most losing trades are not exotic failures; they are ordinary mistakes made in ordinary moments. The first is trading without a plan: entering because a price "looks cheap" with no entry reason, exit condition or size in mind. A plan does not need to be clever, it needs to exist before the trade, because during the trade your judgement is the least reliable instrument on your desk.
The second is position sizing that ignores the worst case. Risking a large slice of an account on one idea means a single bad week can end the whole experiment, and even a sound strategy cannot survive a sizing error. The third is moving the stop-loss: the little adjustment people make when a trade goes against them, converting a planned small loss into an unplanned large one. The whole value of a stop is that it was decided calmly in advance.
The fourth is revenge trading, the attempt to win back a loss immediately, usually at double size and half thought. Markets do not know what you lost and owe you nothing; the only rational response to a loss is to follow the plan more carefully, not more aggressively. The fifth is ignoring costs: commissions and spreads quietly consume under-sized, over-frequent trading, which is why our reporting shows them separately rather than burying them in a net figure.
The habits that prevent all five are unglamorous: write the plan, size for the worst week you can accept, treat stops as contracts with yourself, take a walk after a loss, and read your cost line every month. None of them requires talent, which is good news, because talent is not what trading rewards most. Discipline is.
Manual trading versus automated trading: an honest comparison
Manual trading means you watch the markets, decide, and click. Its great strength is adaptability: a human can read context, smell a news-driven spike, and exercise judgement no model has. Its great weakness is everything else: humans need sleep, get bored, get excited, and cannot watch six instruments across five exchanges at three in the morning. Manual trading is limited by your calendar and your nervous system.
Automated trading executes rules a human wrote, at machine speed, without fatigue and without mood. It never forgets a stop-loss because lunch was good, and never doubles a position because a forum sounded confident. What it cannot do is notice that the world has changed in a way its rules do not cover; a model is only as wise as the situations it has seen. That is why our engine pauses trading when conditions become excessively unstable rather than improvising.
The honest summary is that they solve different problems. Automation handles vigilance, consistency and execution, which are mechanical tasks where machines excel. Humans supply goals, tolerance for risk and the judgement of when a strategy no longer fits the market it trades, which is why our accounts pair the engine with a personal manager rather than pretending either is sufficient alone. The best arrangement we know is rules executed by machines, supervised by people who know your name.
For a beginner, the practical difference is simpler still: automation removes the requirement to become a screen-watcher before you can participate sensibly, while keeping every decision about what to risk and when to stop entirely in your hands.
The psychology of following a strategy
Ask experienced traders what finally made them consistent and few mention analysis; most mention behaviour. The core problem is that trading delivers feedback in a uniquely poisonous way: good decisions sometimes lose money, bad decisions sometimes win it, and the emotional system learns exactly the wrong lesson from both. A win taken early feels like confirmation; a loss held too long feels temporary. Both feelings lie.
Two biases do most of the damage. Loss aversion makes a paper loss feel unfinished, encouraging stops to be moved and dead positions to be nursed. Recency bias makes the last three days feel like the new permanent reality, so a strong week breeds overconfidence and a weak one breeds abandonment of a perfectly sound plan at the worst moment. Both biases whisper, and both are best answered with process rather than willpower.
The practical defences are structural. Decide when calm: entry, exit, size and the maximum loss are agreed before money moves, and written down where they cannot be quietly edited. Review on a schedule, not on impulse: a weekly look at the whole picture prevents daily mood from steering anything. Measure the decision, not just the outcome: a trade that followed the plan and lost is a good trade, and one that broke the plan and won is a bad habit with a reward attached. And automate what can be automated, which is precisely the discipline an execution engine provides for free: it does not move your stop, because it does not feel anything.
The last point deserves its own line: the goal is not to feel nothing, it is to arrange things so that feelings have nothing important to do. That is what a strategy is for, what a manager is for, and what the weekly report is for. Trading psychology, in the end, is mostly good plumbing.
Reading is the cheap part. These guides describe behaviour, not a promise of results, and every point in them applies to automated accounts too. The risk disclosure page covers what can go wrong; the getting started guide covers what to do next.