Introduction

Anyone first venturing into the world of trading and investing is quickly confronted with an overwhelming number of opinions, methods, and supposed recipes for success. In forums—and especially on social media—the promise of quick, low-risk profits is often held out, provided you subscribe to a signals group on Telegram for a monthly fee or pay several thousand Euros for the “ultimate trading course.”

Unfortunately, the idea of taking the time to deeply understand the subject yourself and to develop a personalized investment strategy often falls by the wayside. This article shows why systematic action—whether in active trading or long-term investing—is crucial for sustained investment success. We analyze typical beginner mistakes, introduce proven trading approaches, and explain how to structure and test your own strategy.

What happens without a Strategy?

Those who enter the market without a clear strategy often leave their decisions to spontaneous impulses—with sobering results. Beginners in particular are swayed by short-term price movements, emotions, or outside influences. The result is ill-considered trades, inconsistent or absent risk management, and ultimately unsatisfactory outcomes.

Typical sources of error include: [1, 2, 3]

• Fear and Greed: Greed tempts you to take excessive risks, while fear often causes positions to be closed too early—worried about losing already-realized gains. Even more problematic is holding losing trades too long in hopes of a rebound.

• Herd Behavior: This describes the tendency of investors to follow others’ decisions, especially in uncertain situations. It can lead to overvalued markets and speculative bubbles. Studies show that social influences can have a strong effect on investment behavior.

• Loss Aversion: Losses are felt much more intensely than equivalent gains, leading to the quick realization of profits and the prolonged holding of losses.

• Home Bias: The tendency to invest predominantly in domestic financial products, neglecting the fundamental concept of diversification.

Understanding these behavioral patterns and consistently applying a clear, rule-based strategy can help investors avoid emotional mistakes and achieve long-term success.

Trading or Investing - Which suits you?

Before developing a concrete strategy, some fundamental questions must be answered, since the right approach depends heavily on your individual risk capacity and time horizon. Do you sell in a panic when prices drop by 20 %, or can you weather a crash calmly? Ask yourself whether you’ll need your invested capital back in the short term, or whether you can leave it invested for several years.

Depending on your answers, you can choose between investing and trading, as each approach carries different requirements and risks:

Investing focuses on long-term wealth accumulation. Investors rely on fundamental analyses and hold positions for years. Long-term studies show that passive investment strategies generally outperform active funds—especially after fees. [4, 5]

Trading targets short-term price movements, with positions often held for only days or weeks. This approach demands greater risk tolerance and closer market monitoring. Day trading is an extreme form, opening and closing positions within minutes. [6]

Only a small subset of disciplined traders and active fund managers can outperform the market—usually through systematic methods and consistent strategy application. The choice between these approaches should realistically reflect both your financial ability to absorb losses and your psychological readiness to handle market volatility.

What makes a good Strategy

Whether you trade actively or invest for the long term, a successful strategy requires more than just an idea—it must be well thought-out, rule-based, and consistently executable. Random impulses or spur-of-the-moment gut decisions may succeed occasionally, but they are no reliable foundation for long-term success.

Clear Rules instead of Intuition

A good strategy defines, in advance, clear criteria for entry, exit, and position sizing. For investors, this might be a valuation model based on key fundamental metrics; for traders, a technical trigger such as a trend break or a volatility signal. Clear rules help avoid emotional decisions.

Fit to Person and Market Environment

A strategy must suit both the market conditions and the person using it. If you tolerate temporary losses and have time on your side, long-term value or dividend strategies may be appropriate. If you prefer active engagement and reacting to short-term signals, you need precise rules to curb overreactions. Adopting someone else’s strategy without checking whether it fits your risk tolerance or lifestyle is a common mistake.

Measurability and Testability

A good strategy can be tested and produces measurable results. In trading, this is done via backtesting—simulating the strategy on historical data.

On www.gravitrade.at, you can backtest your strategies over multiple years to see metrics like hold ratio, number of orders, profit factor, maximum drawdown, performance, and a comparison to buy-and-hold.

As an example the following figures show simulation results from an EHang trading strategy over a period of five years

A backtest is not a reliable guarantee of future performance, but it helps assess whether a trading idea is fundamentally viable and consistent.

Realistic Expectations

No strategy wins every time. The key is generating more winners than losers over many trades or investments. While you can “fine-tune” models with extra indicators and parameter optimization, overly complex models often only work in hindsight and fail in live markets. Simple, transparent, rule-based strategies with realistic expectations have proven more robust long term.

Choice of Trading Style

The timeframe also matters. Even automated strategies that generate buy and sell signals increase workload and costs (fees and spreads) with each trade. Generally, three styles are distinguished by timeframe:

  • Scalping: Extremely short-term trades on a minute- or second-basis, high frequency, small targets.
  • Day Trading: All positions opened and closed within one trading day to avoid overnight risk.
  • Swing Trading: Positions held for days to weeks to capture larger market moves.

Independent of the trading style chosen, similar strategy concepts can be applied - some of which will be introduced in the following chapter.

In active trading, the goal is to profit from short- to medium-term price movements. The following approaches rank among the most commonly used strategies by traders. These trading strategies can be executed manually.

At www.gravitrade.at you have an easy way to create these rule-based approaches - often called “trading bots” - to test them and receive automated, ongoing evaluations, saving you valuable time.

Trend Following

In a trend-following strategy, positions are opened in the direction of the prevailing market trend. Technical tools—such as moving averages or trend channels—are used to identify suitable entry and exit points.

  • Pros: High hit rate in clear trends
  • Cons: Poor performance in sideways markets

To determine the direction and strength of a trend, the Directional Movement Index (DMI) indicator is often used in conjunction with the Average Directional Index (ADX).

A rising ADX above a threshold—e.g., 25—signals a well-established trend. When the +DI line crosses the –DI line from below, this can be a long signal; conversely, the opposite crossover may indicate a short setup.

The chart shown below illustrates that the DAX exhibited clear trends during periods of strong ADX (for example, October 2024 and March 2025), whereas when the ADX was flat, there were hardly any sustained movements—typical challenges for trend‐following strategies in sideways market phases.Mean Reversion (Reversal Strategies)

A further popular trend-following indicator is the MACD (Moving Average Convergence Divergence). It’s based on the difference between two exponential moving averages (typically the 12- and 26-day EMAs) and generates potential buy or sell signals when it crosses its signal line. The accompanying histogram visualizes the strength of the divergence between the MACD line and the signal line—the larger the histogram, the stronger the trend momentum.

The chart below shows the MACD applied to the DAX equity index. On January 8, 2025, the MACD line (126.4) crossed the signal line (124.5) from below—a classic bullish signal. At the same time, the histogram turned slightly positive (1.86), indicating the start of upward trend momentum. This buy signal is confirmed by the subsequent price rally in the DAX.

You can use these two indicators, as well as many others, for automatic detection and signal generation in trend-following strategies in the strategy editor on www.gravitrade.at. There, in the Academy, you’ll also find additional helpful and more detailed tips on using these indicators to build your own automated trading strategies.

Mean Reversion Strategy

Based on the assumption that prices tend to revert to their mean after extreme moves. Extremes are identified with indicators like RSI or Bollinger Bands.

  • Pros: Works well in calm, non-trending markets
  • Cons: Risky when strong momentum or trend breaks occur

A practical example is illustrated by the following backtest of a simple strategy on the DAX. Two RSI indicators were used to generate signals. Buy signals occur when the RSI breaks back upward out of oversold zones (a threshold of 30 was applied here)—indicating a potential return to the mean. Conversely, sell signals are generated when the RSI falls back from overbought zones, which in this example were defined as values above 70.

In several instances - notably in August 2024, January 2025, and April 2025 - these RSI signals reliably identified price reversals, effectively supporting the mean-reversion approach during calm market phases. Over the test period, the strategy delivered a return of 26.2 %, slightly outperforming the buy-and-hold return of 22.1 % over the same timeframe.

Breakout Trading

Breakout traders act on price breakouts above resistance or below support, often triggered by news or volume spikes.

  • Pros: Strong momentum when true breakouts occur
  • Frequent false breakouts ("fakeouts")

Entry criteria for a simple breakout strategy might include:

  • The daily closing price breaks above the high of the closing prices from the past week, and
  • The momentum indicator is positive (indicating strength after the breakout).

An exit criterion for a complete trading strategy could be a 3 % trailing stop-loss or, alternatively, a take-profit target.

If you’d like to replicate and test this strategy on www.gravitrade.at, the following illustration shows the corresponding setup in the editor.

Besides these approaches, there are many other methods - such as momentum or range-trading models. Which strategy suits you best depends on your personality, time horizon, and the prevailing market conditions.

If you prefer to focus more on long-term, passive wealth accumulation, proven investment strategies are available; some of these will be introduced in the next section.

Those aiming to build wealth over the long term often adopt a passive or semi-active approach. The following strategies rely on fundamental data, broad diversification, or proven models to capture corporate earnings and economic growth over years or decades.

Buy and Hold

Buy-and-hold is probably the simplest and most well-known investment strategy: investors commit a lump sum or contribute at regular intervals—such as through a savings plan—into a broadly diversified portfolio, often comprised of stocks, bonds, or index ETFs. The investments are held for many years, regardless of short-term market fluctuations or investor sentiment.

• Pros: Easy to implement, low transaction costs, and historically high success rates when applied consistently. Using monthly savings plans also mitigates the risk of poor entry timing through cost averaging.

• Cons: Requires discipline and the ability to endure volatile market phases. Moreover, a broadly diversified buy-and-hold strategy typically only achieves average market returns, making outperformance impossible.

Value Investing

Value investing aims to purchase shares of companies whose current market price is below their intrinsic value. The analysis is based on classical valuation metrics such as the price-to-earnings ratio (P/E), book value, or free cash flow.

Although the efficient-market hypothesis assumes that all available information is already reflected in prices, value investors like Warren Buffett believe that markets are often—but not always—efficient. Emotions, herd behavior, or fundamental misjudgments can lead to mispricings that can be exploited rationally.

• Pros: The opportunity to acquire undervalued companies with a solid risk-reward profile

• Cons: Requires detailed fundamental analysis and patience, since market inefficiencies often take long periods to correct.

If you’d like to try your hand at fundamental analysis, the Market Overview on www.gravitrade.at offers a wide selection of valuation metrics and fundamental data for numerous companies.

Dividend Strategy

In the Dividend Strategy, the focus is on companies that pay regular, stable dividends. Investors thereby earn ongoing income in addition to any share-price appreciation. This income can either be used as passive cash flow or reinvested to benefit from compounding.

Selection criteria for dividend stocks include a long history of stable payouts, solid earnings, and a healthy balance sheet with manageable debt. During volatile market phases, dividend stocks can bring stability to a portfolio and reduce emotional stress.

• Pros: Ongoing income regardless of price swings

• Cons: A strong focus on dividend yield may lead to overlooking high-growth companies, potentially limiting long-term total returns

To cover all living expenses from monthly dividend payments—and thus achieve financial independence - typically requires invested capital in the high six-figure range. Even so, covering smaller expenses (for example, a monthly streaming subscription) with dividends can be highly motivating.

Quantitative Approaches

Quantitative investment strategies rely on systematically evaluating stocks against objective metrics. Unlike classical value investing - which also weighs qualitative factors like management quality - quantitative approaches assess companies solely via predetermined numeric models, for instance based on return on equity, earnings growth, or relative price performance.

A well-known example is Susan Levermann’s Levermann Strategy, which translates various fundamental and market indicators into a point-scoring system; the higher a company’s total score, the more attractive its stock.

Quantitative models offer a structured, emotion-free decision framework but demand disciplined rule application and ongoing model review.

• Pros: Transparent, rule-based criteria minimize emotional errors and support consistent stock selection

• Cons: Success hinges on data quality, user discipline, and the ability to adapt models to evolving market conditions

Tip: You can find all the necessary metrics to evaluate companies according to the Levermann method - or other quantitative models - in the Market Overview on www.gravitrade.at.

Conclusion

Without a clear strategy, success in the markets is left to chance. Whether you pursue active trading or long-term investing, the key is to choose an approach aligned with your goals, risk tolerance, and time horizon.

Quick profits via signal groups or expensive “secret” courses may seem tempting, but real, sustainable success comes from personal understanding, systematic action, and disciplined execution.

With the strategy concepts presented here, you have a solid foundation to carve out your own path - whether as an active trader or a long-term investor.

If you’re ready to get started and build and test your own strategies, you’ll find all the tools you need at www.gravitrade.at!

References

  • [1] C. Ankele, Behavioral Finance und das Phänomen der Spekulationsblasen, Klagenfurt, 2017.
  • [2] D. Woschitz, Massenpsychologische Phänomene in der Finanzwirtschaft, Graz, 2011.
  • [3] M. Grunewald und M. Möller, Sieben typische Fehler bei der Geldanlage - Lösungsansätze der Behavioral Finance, Köln: Institut der deutschen Wirtschaft Köln, 2017.
  • [4] B. Armour, R. Jackson, E. Gorbatikov und H. Kim, Morningstar’s US Active/Passive Barometer, 2024.
  • [5] A. R. Ganti, T. Edwards, D. Di Gioia, F. Chapman und N. Didio, SPIVA U.S. Scorecard, 2024.
  • [6] E. F. Fama und K. R. French, „Luck versus Skill in the Cross-Section of Mutual Fund Returns,“ The Journal of Finance, Bd. LXV, Nr. 5, pp. 1915-1947, 2010.