Cos'è Montbon Analytics?

Montbon Analytics è una piattaforma di analisi tecnica che combina onde di Elliott, Metodo Montbon e intelligenza artificiale per generare segnali di trading con score 0-100 e target di prezzo automatici.

Come funziona l'analisi con le onde di Elliott?

Il sistema identifica automaticamente i cicli di Elliott Wave su tutti i timeframe, calcola i livelli di Fibonacci, rileva divergenze e proietta i target di prezzo per ogni grado d'onda.

Cos'è il Metodo Montbon?

Il Metodo Montbon è un sistema proprietario di analisi tecnica che combina 4 pilastri: analisi tecnica classica, Elliott Wave, medie mobili multi-timeframe (MTF) e analisi fondamentale. Il risultato è uno score integrato 0-100 con livelli operativi automatici.

Sì, esiste un piano Free con 1 analisi gratuita senza login e 5 con account. I piani a pagamento partono da 1,99 EUR/mese (Basic, 30 analisi) fino a 24,99 EUR/mese (Elite, analisi illimitate).

I segnali di trading sono affidabili?

Montbon pubblica un track record verificabile di tutti i segnali generati, con win rate e rendimento medio storico consultabile nella sezione Track Record. I rendimenti passati non costituiscono un indicatore affidabile dei risultati futuri. Le analisi non costituiscono consulenza finanziaria.

How to Score a Stock Without Guesswork

A stock can look attractive for three completely different reasons - strong earnings, a clean chart, or simple hype. The problem is that mixed signals create hesitation. If you want to know how to score a stock, the goal is not to predict the future with certainty. It is to reduce noise, compare opportunities quickly, and turn scattered information into a structured decision.

Most retail investors already do some form of scoring, even if they do not call it that. They glance at revenue growth, check whether price is above a moving average, maybe look at valuation, and then make a judgment. The weakness is inconsistency. One day valuation matters most, the next day momentum takes over, and the process shifts with emotion. A real scoring method fixes that.

What it means to score a stock

Scoring a stock means assigning a repeatable rating to a company based on a set of defined inputs. Instead of asking, \"Do I like this name?\" you ask, \"How many of my conditions are aligned right now?\" That shift matters because markets punish vague conviction.

A useful stock score is not just a single number pulled from a black box. It should reflect a framework. In practice, that usually means combining multiple pillars such as trend, momentum, price structure, and fundamentals. The final score is less important than the logic behind it. If the score says 82 out of 100, you should know why it is high. If it says 41, you should know what is missing.

This is where many DIY approaches break down. Investors either build a spreadsheet so complex they stop using it, or they rely on one indicator that works only in certain market conditions. A score should simplify decisions, not create more friction.

How to score a stock with a repeatable framework

The cleanest way to do it is to separate the analysis into pillars, assign each pillar a weight, then total the result. You do not need fifty variables. You need a handful of factors that cover different dimensions of market behavior.

A practical framework usually includes four areas: technical trend, momentum and structure, fundamental quality, and trade risk. These cover the main question every investor is trying to answer. Is the business healthy, is the market confirming that view, and is the setup worth the risk?

1. Score the trend first

Start with price trend because it tells you whether the market is broadly rewarding or rejecting the stock. A stock trading above its 50-day and 200-day moving averages, with those averages sloping upward, deserves a higher score than one stuck below both.

This does not mean trend should dominate every decision. A great company can be in a temporary drawdown. But trend is still a strong filter because it captures behavior from thousands of market participants. If a stock has strong fundamentals but persistent technical weakness, your score should reflect that conflict.

A simple trend score might assign points for price above the 20-day, 50-day, and 200-day moving averages, and additional points if those averages are aligned in bullish order. That keeps the process measurable.

2. Measure momentum and price structure

Trend tells you direction. Momentum tells you quality. Two stocks can both be above the 200-day average, but one may be accelerating while the other is losing strength.

This is where relative strength, recent breakout behavior, support and resistance, and wave structure can help. If a stock is breaking above a major range on rising volume, the score should improve. If it is extended far above support and nearing overhead resistance, the score may still be decent, but risk rises and the setup becomes less attractive.

Momentum scoring is especially useful for swing traders and tactical investors because timing matters. A stock with solid long-term fundamentals but poor short-term structure may be worth owning later, not now. Scoring helps separate a good company from a good setup.

3. Add a fundamental layer

If you are scoring a stock rather than just trading price action, fundamentals belong in the model. The exact metrics depend on the type of stock. A mature large-cap should not be judged by the same standards as an early-stage growth name.

That said, some metrics are broadly useful: revenue growth, earnings growth, margins, debt load, free cash flow, return on equity, and valuation relative to peers. You do not need every metric to be perfect. You need enough evidence that the business is not fighting against the chart.

This is where nuance matters. A high-growth software company may deserve a good score even with a rich valuation if growth and margins are improving. A value stock may score well with slower growth if cash flow is stable and debt is under control. The point is not to reward one style. The point is to measure internal quality in a consistent way.

4. Score the risk, not just the upside

Many investors only score what they like. Fewer score what can go wrong. That is a mistake.

A stock with a strong chart and solid fundamentals can still be a poor trade if the stop loss is too wide, the entry is late, or the reward-to-risk ratio is weak. This is why a serious scoring model includes operational context. Where is support? Where would the trade be invalidated? Is there enough upside to justify the risk?

This part is often the difference between analysis and action. A stock might earn a favorable raw score but drop to a watchlist category if the setup is crowded or poorly positioned. Good scoring does not just say what is attractive. It says what is actionable now.

How to weight each factor

There is no universal formula, because time horizon changes everything. A swing trader may give more weight to trend and momentum. A long-term investor may lean harder on fundamentals. The key is to set the weights before looking at the stock.

For example, a tactical scoring model could assign 35% to trend, 25% to momentum, 25% to fundamentals, and 15% to risk structure. A longer-term model might reverse those priorities. Neither is inherently better. What matters is consistency.

Once the weights are set, score each category on the same scale, then combine them. That gives you a final number that can be compared across names. Over time, you can test whether certain thresholds actually lead to better outcomes.

What a useful stock score should tell you

A score should do more than rank names from best to worst. It should classify decision quality. In practice, that often means three buckets: opportunity, neutral, and risk.

An opportunity score means multiple pillars are aligned and the setup is operationally usable. Neutral means the case is mixed - maybe fundamentals are strong but trend is weak, or momentum is improving but valuation and risk are stretched. Risk means too many variables are working against the trade, even if one factor looks appealing.

That kind of classification is powerful because it removes false precision. The difference between a 76 and a 78 is rarely meaningful by itself. The difference between aligned and conflicted usually is.

Common mistakes when trying to score a stock

The first mistake is overfitting. If your model uses twenty indicators, it may look smart but become impossible to trust in live markets. Keep it tight enough that you can explain every input.

The second mistake is ignoring regime. In a strong bull market, trend and momentum may deserve extra weight. In a choppy or defensive environment, fundamentals and risk control may matter more. A scoring model should be disciplined, but not blind.

The third mistake is treating the score as a buy signal by itself. A score is a decision aid. It helps you organize evidence, not outsource judgment. If a stock scores high ahead of earnings, for example, event risk may still change the trade completely.

The fourth mistake is failing to review results. A model only improves if you track what happened after high scores, medium scores, and low scores. Public verification matters. Otherwise, a score is just branding.

A better way to make stock scoring practical

If you are building this process manually, the challenge is not understanding the logic. It is doing it fast enough to matter. Pulling charts, checking moving averages, reviewing fundamentals, mapping entries, and comparing risk/reward across multiple names can easily turn into a time drain.

That is why structured scoring tools are gaining traction. The best ones do not replace judgment. They compress the work into a readable system, show how the pillars align, and make the verdict transparent. A platform like Montbon, for example, is built around that idea: combine technical analysis, automated wave interpretation, multi-timeframe moving averages, and fundamentals into a single score with operational levels attached.

That approach is useful because it answers the real question most self-directed investors have: not just whether a stock looks good, but whether the setup is clear enough to act on.

If you want to know how to score a stock well, start by removing subjectivity where it hurts most. Define your pillars. Weight them deliberately. Let trend, fundamentals, and risk challenge each other instead of confirming your bias. A good score will not eliminate losing trades. It will help you avoid sloppy ones, and that alone can change your results over time.