Top_Rank systematically allocates capital to the strongest assets across multiple asset classes by continuously ranking them based on relative strength. The strategy focuses on disciplined selection rather than market forecasts.

Top_Research represents the complete universe of rule-based trading strategies, which are systematically implemented within the GR_Strategies portfolios in both USD and EUR.

Date Top_Rank DAX SP500
27 Feb 2026 0.26 % -0.02 % -0.43 %
Feb 2026 4.00 % 3.04 % -0.87 %
2026 10.55 % 3.24 % 0.49 %
Start 2023 50.44 % 81.59 % 79.16 %
Ann. Return 13.44 % 20.23 % 19.73 %
Sharpe ratio 1.42 1.43 1.34

Strategy framework
Top_Rank operates on a cross-asset universe including equities, bonds, commodities, and defensive assets. All assets are evaluated using standardized, volatility-normalized returns to ensure comparability across fundamentally different market instruments. Allocation decisions are made strictly rule-based, without discretionary input.


Momentum-based selection
Asset selection is driven by relative momentum rankings calculated over multiple lookback horizons. Only the top-ranked assets with positive momentum are eligible for allocation, while assets with negative momentum are systematically excluded. This ensures capital is allocated exclusively to assets demonstrating persistent strength.


Risk normalization and control
To prevent unintended concentration and excessive volatility, returns are normalized using rolling volatility measures. Additionally, asset-specific return caps are applied to limit extreme exposures. This creates a more balanced and robust allocation across assets with differing risk profiles.

Signal aggregation
Multiple momentum horizons are evaluated in parallel and combined into a single allocation signal. This aggregation reduces noise, mitigates timing risk, and avoids overreliance on a single lookback period. The result is a smoother and more stable tactical allocation over time.


Objective
Top_Rank aims to capture medium-term market trends across asset classes while systematically controlling risk. The strategy seeks to adapt continuously to changing market leadership, providing diversification, responsiveness, and resilience across varying market environments.

Top_Rank – Monthly Allocation Weights

Top_Rank analysis since start

Performance table since start 2023 (USD):

Top_Rank: 50.44 %
Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Year
2023 5.1 -4.3 1 1.1 -1.4 0.1 2.7 -2.8 0.1 1.6 0.6 4.2 7.8 %
2024 -1.3 4.8 5.6 -2.6 -0.6 -0.8 2.5 2.7 2.9 0.4 1.9 -1.6 14.2 %
2025 2.4 0.0 -0.3 -4.2 0.1 2 0.1 2.2 5.6 1.9 0 0.6 10.5 %
2026 6.3 4.0 10.6 %

Performance and Risk Metrics for Top_Rank

Performance Metrics

Top_Rank
Cumulative Return (%) 50.44
Ann. Return (%) 13.90
Ann. Sharpe Ratio 1.45
MAR Ratio 1.60

Risk Metrics

Top_Rank
Ann. StdDev. (%) 9.60
SemiDeviation (%) 0.45
Max DrawDown (%) 8.71
Value-at-Risk (%) -1.01

Daily Metrics

daily metrics (%)
Av. Return (%) 0.05
Best Day (%) 2.35
Worst Day (%) -3.91
Av. Up-Day (%) 0.45
Av. Down-Day (%) -0.43
Pct Up-Days (%) 55.00
Pct Down-Days (%) 45.00

Monthly Metrics

monthly metrics (%)
Av. Return (%) 1.01
Best Month (%) 6.30
Worst Month (%) -4.31
Av. Up-Month (%) 2.12
Av. Down-Month (%) -2.01
Pct Up-Months (%) 73.00
Pct Down-Months (%) 27.00

Drawdown Analysis Top_Rank in Days

From To Depth Length
2025-02-21 2025-09-10 -8.71 % 139
2023-02-02 2023-12-13 -6.30 % 218
2026-01-30 2026-02-27 -4.83 % 20
2024-04-12 2024-08-21 -4.67 % 91
2025-10-09 2025-10-20 -3.93 % 8

Top_Rank vs Other Asset Classes since start | S&P 500

Top_Rank TLT VNQ UUP EFA DBC GLD DAX SPY
Annualized Return 13.4% 0.9% 8.7% 3.5% 19.2% 4.8% 38.2% 20.2% 19.7%
Annualized Std Dev 9.4% 14.6% 17.3% 6.8% 14.0% 15.2% 18.3% 14.2% 14.7%
Annualized Sharpe 1.42 0.06 0.50 0.52 1.37 0.31 2.08 1.43 1.34
Worst Drawdown 8.7% 22.4% 21.8% 10.1% 14.1% 13.8% 13.9% 16.0% 18.9%

Rolling Correlation of Top_Rank vs. DAX | S&P 500

Top_Rank DAX SP500
Top_Rank 1.000 0.244 0.385
DAX 0.244 1.000 0.530
SP500 0.385 0.530 1.000

More analysis for Top_Rank

Rolling 12-Month Window for Return & Stdv & Sharpe Ratio

Risk Analysis for Top_Rank vs. DAX | S&P 500

Top_Rank Return versus Other Asset Classes

Extended analysis dating back to 2014

Top_Rank TLT VNQ UUP EFA DBC GLD SPY DAX
Annualized Return 8.3% 1.7% 7.2% 3.3% 6.7% 1.2% 12.1% 11.1% 8.0%
Annualized Std Dev 8.8% 14.5% 19.6% 7.1% 16.6% 17.1% 15.3% 17.2% 18.6%
Annualized Sharpe 0.94 0.12 0.37 0.47 0.41 0.07 0.80 0.65 0.43
Worst Drawdown 15.0% 48.4% 42.4% 14.2% 34.2% 59.9% 24.5% 33.9% 38.8%

Longterm Return Table for Top_Rank starting 2014

Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Year
2014 0.5 -2.3 3.7 -2.1 2.9 2.8 0.9 6.5 %
2015 8 -1.8 -0.2 -0.9 -1.5 -4.1 1.4 -1.9 -0.7 -0.8 0.1 -3.1 -5.9 %
2016 -1.2 2.3 0.7 1.8 -1.1 1.1 1.6 -1.8 0.4 0 0.5 2.3 6.7 %
2017 0.1 2.7 1 0.6 2.8 -0.2 -0.7 0.2 -1.3 4.2 1.3 1.5 12.6 %
2018 9.2 -8.9 -0.5 0.8 2 0.2 -0.3 3.7 -1.9 -5.2 0.4 1.9 0.2 %
2019 1.7 -0.3 2.2 -0.2 -1.3 2.5 -0.6 5 -1.6 1.2 -0.9 5.6 13.8 %
2020 -2.7 -0.4 -0.5 1.1 0.9 0.3 4.3 1.7 -3.3 0.6 8.8 4.2 15.6 %
2021 3 4.8 0.7 3.8 1.3 1.3 1.6 1.2 -3.8 1.6 -2.9 1.7 14.9 %
2022 -2.9 1.7 3.7 1.9 -1.1 0 0.9 -1.4 -0.1 -0.1 -1.9 -2.2 -1.7 %
2023 5.1 -4.3 1 1.1 -1.4 0.1 2.7 -2.8 0.1 1.6 0.6 4.2 7.8 %
2024 -1.3 4.8 5.6 -2.6 -0.6 -0.8 2.5 2.7 2.9 0.4 1.9 -1.6 14.2 %
2025 2.4 0 -0.3 -4.2 0.1 2 0.1 2.2 5.6 1.9 0 0.6 10.5 %
2026 6.3 4 10.6 %
Some more information

My portfolio comprises:


  • Top_Dual & Top_Target momentum and accumulation strategies, are focusing on harnessing and leveraging market trends for consistent and sustainable growth.
  • Top_Switch, an Asset rotation strategy is dynamically reallocating capital across asset classes to optimize returns and mitigate risks.
  • Top_Vola strategy, is tailored to capitalize on both sudden and sustained market fluctuations, enhancing risk - adjusted returns.
  • Top_Switch, an Asset rotation strategy is dynamically reallocating capital across asset classes to optimize returns and mitigate risks.
  • Top_Rank, a cross-asset ranking and selection strategy that systematically allocates capital to the strongest assets based on relative performance and momentum, ensuring disciplined participation in prevailing market leadership.
  • Top_Trend (=CTA) strategy, which forms the backbone of diversification with a 30 % allocation. This strategy excels in capturing trends and providing stability during market
  • Additional advanced and highly specialized approaches, crafted to adapt seamlessly to complex and evolving market dynamics.

Together, these strategies create a robust and well - balanced portfolio framework. By blending simplicity with sophistication, the approach ensures adaptability, consistency, and long - term success, even in the face of unpredictable market conditions.

Uncorrelated Strategies


The cornerstone of success lies in the deliberate and precise integration of diverse, genuinely uncorrelated strategies, executed with unwavering discipline and emotional composure. My approach is devoid of the influence of greed or fear, guided instead by the principles of expertise and professionalism. Each decision is the product of meticulous analysis and a technically sound methodology, consciously avoiding impulsive or reactionary behavior. Furthermore, all decisions are grounded 100% in mathematical and statistical principles, ensuring objectivity and consistency. By consciously excluding any human influence, the process eliminates the risk of emotional bias or subjective judgment. This steadfast adherence to strategy allows me to navigate the complexities of the markets with confidence and consistency, maintaining an unyielding commitment to excellence.

Trading


The elegance of these strategies lies in their straightforward yet effective design. Each morning, data is carefully downloaded, and within 15 minutes, calculations ensure that theoretical models align seamlessly with practical execution. By evening, new orders are automatically dispatched to the exchange, just before the market closes. This approach is not a feat of magic, but rather a testament to disciplined craftsmanship. It guarantees that execution timing remains uninfluenced — an essential factor in maintaining the robustness and reliability of the strategy.

Data Used


Back-testing is often dismissed as mere theory or abstract mathematics. However, I recognize that the performance up to December 2022 reflects a combination of real - time trading outcomes and newly implemented systems. While historical achievements provide valuable insights, I find little satisfaction in endlessly revisiting past successes. My focus is clear and uncompromising—cutting through bureaucracy to channel my energy toward the present and future, where true progress is made.

Dedication


In collaboration with my dear friend and developer, Helmuth Vollmeier, in a fit of genius or maybe just sheer madness, we decided to hit the reset button on everything in 2022. It was like a software update for our lives — new and improved. Unfortunately, the joy of our new start was short-lived as Helmuth passed away suddenly in February 2023, leaving me deeply saddened. Despite facing phases of doubt and questioning the meaning of it all, I returned to my desk, immersing myself in learning once again, now without my dear friend Helmuth by my side! I dedicate this work to Helmuth Vollmeier, one of my best friends, my intellectual partner, my daily communicator, and companion!

GR_Strategies are diversified portfolios that combine multiple fully rule-based trading systems from Top_Research into a single systematic allocation, offered in USD and Euro.

Top_Research is the research and development layer where all underlying rule-based trading strategies are designed, tested, and maintained.