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Visão geral da estratégia selecionada

NOKBUSDT

Instrumento de ações · execução via Binance
NOKB 0 +7078.16% 1TRAD-XCS0
Recomendado pela DevioLab · Core 1 iRecomendação principal da DevioLab: perfil mais protegido, suave e estável, focado no controle de risco e drawdown.
Recomendado pela DevioLab · Core 2 iRecomendação mais agressiva da DevioLab: aceita maior risco e drawdowns mais profundos em troca de retornos potencialmente maiores.
28Operações
92.9%Taxa de acerto
+18.82%Operação média
+136.75%Melhor operação
-8.86%Pior operação
+527.1%Anualizado
Perfil analítico da estratégia · dd81ca5bf9518cc4

Systematic Analysis of the Algorithmic Strategy for NOK · Nokia Oyj

An analytical study of the top-ranked algorithmic trading model for Nokia Oyj (NOK) equity on the 15-minute timeframe. The strategy achieves a high win rate of 92.86%, a cumulative historical return of +7078.16%, and a strictly controlled maximum drawdown of 8.86% across nearly seven years of evaluated history.

Ler análise completa

Strategy profile

This algorithmic trading model was engineered for trading Nokia Oyj shares (ticker symbol NOK) on the stock market using a 15-minute chart interval. According to the internal DevioLab ranking system, this specific setup holds the number one rank for this asset with an overall analytical score of 86.98. The strategy belongs to the class of highly selective, low-frequency quantitative models that seek substantial market moves while filtering out structural noise. Over the full historical evaluation window from September 16, 2019, to August 20, 2026 (spanning 6.93 years), the strategy registered only 28 completed trades, confirming its patient position-taking methodology.

Trading rhythm and position duration

The execution rhythm of the algorithm is marked by extreme selectivity, executing an average of just 4.04 trades per year. In the provided dataset, specific numerical values for average and median holding hours, as well as the exact spacing between trade exits, are not specified, which precludes precise measurement of intraday holding periods. However, the low annual trade count demonstrates that this strategy is far from scalping; it operates as an opportunistic swing mechanism waiting for high-probability setups on the 15-minute timeframe.

Quality of historical results

The quality of closed historical trades shows strong statistical edge. Out of 28 completed positions, 26 were profitable, yielding a win rate of 92.86%. Total historical net profit across the dataset reached +7078.16%, supported by a robust profit factor of 5.31. The average return per trade stands at +19.13%, while the median return per trade is +10.35%. The single best trade achieved a gain of +136.75%. Notably, the top three winning trades generated 49% of the total gross profit, pointing to significant reliance on large outlier winning moves.

Risk, drawdown and losing behavior

Risk preservation is a standout feature of this quantitative model. The maximum historical peak-to-trough equity drawdown was kept to 8.86%, which is unusually low for a strategy producing a multi-thousand percent cumulative return. Across the entire 6.93-year backtest, the algorithm experienced only 2 losing trades in total, with the single worst trade losing -8.86%. The maximum consecutive losing streak was capped at 1 trade, whereas the maximum winning streak reached 15 consecutive winning trades.

Behavior through time and yearly stability

Evaluating the strategy over extended timeframes reveals a model designed to maintain capital preservation during unfavorable market regimes. Although detailed year-by-year statistical breakdowns are not provided in the primary dataset, the ability to sustain a 15-trade winning streak indicates strong capital expansion during trending phases. Generating roughly 4.04 trades per year demonstrates that the logic avoids forcing transactions when market conditions fail to meet its parameters.

Strengths and limitations

The primary strengths of this model include its outstanding win rate of 92.86%, a high profit factor of 5.31, minimal historical drawdown of 8.86%, and impressive total return of +7078.16%. The main limitation lies in the small sample size of 28 completed trades over nearly 7 years, which limits broader statistical confidence. Furthermore, 49% of gross profits came from the top 3 trades, and extended periods without trading activity require strict investor discipline.

DevioLab analytical conclusion

The NOK 15-minute algorithmic model presents an exceptional balance between downside protection and upside capture. Holding rank 1 for Nokia Oyj on DevioLab with a score of 86.98, the model stands out for its minimal drawdown profile and high win consistency. However, prospective observers must keep in mind the small trade sample size and low execution frequency. This evaluation represents a historical simulation research report and does not constitute financial or investment advice.

Data scope and methodology

This analysis is derived from simulated historical closed trade data for Nokia Oyj (NOK) between September 16, 2019, and August 20, 2026. All percentage metrics reflect hypothetical backtested performance. They do not represent live brokerage account returns, do not account for individual execution slippage or platform fee structures, and offer no guarantee of future trading performance.

Análise completa da estratégia