Goldnasdaqsimulation

C 62 completed
Cli Tool
unknown / python · tiny
19
Files
9,942
LOC
0
Frameworks
3
Languages

Pipeline State

completed
Run ID
#366960
Phase
done
Progress
1%
Started
Finished
2026-04-13 01:31:02
LLM tokens
0

Pipeline Metadata

Stage
Skipped
Decision
skip_scaffold_dup
Novelty
41.89
Framework unique
Isolation
Last stage change
2026-04-16 18:15:42
Deduplication group #47591
Member of a group with 1 similar repo(s) — canonical #65621 view group →
Top concepts (2)
Project DescriptionWeb Backend
Citation: Repobility (2026). State of AI-Generated Code. https://repobility.com/research/

AI Prompt

Create a Python script to simulate and backtest a 200% leveraged investment strategy combining NASDAQ100 (QQQ) and gold futures (BCOMGC). The tool should calculate the daily Net Asset Value (NAV) using a specific formula involving QQQ's JPY-converted daily return, the gold index's daily return, and an annual fee. I also need functionality to run future projections using both Bootstrap and Monte Carlo (GBM) methods, and the ability to generate various comparison charts like drawdown, Sharpe ratio, and final NAV distributions. The script should handle data fetching for QQQ, USD/JPY, and BCOMGC, and allow running the simulation for historical periods or projecting out to a specified number of future years.
python finance backtesting simulation quant monte-carlo nasdaq gold time-series
Generated by gemma4:latest

Catalog Information

Simulates and backtests a 200% leveraged strategy combining NASDAQ100 and gold futures, comparing results to an actual fund and projecting future performance.

Description

This tool performs a daily backtest of a 200‑percent leveraged strategy that blends the NASDAQ100 index (QQQ) with gold futures. It calculates the net asset value (NAV) using a custom return formula that incorporates currency conversion and management fees, then compares the simulated NAV to the actual fund’s NAV. Users can also generate probabilistic future projections for up to 30 years using bootstrap resampling or a geometric Brownian motion Monte‑Carlo model. The output includes detailed charts, statistical summaries, and performance metrics such as drawdowns and Sharpe ratios. It is designed for quantitative analysts and portfolio managers who need a rigorous, data‑driven assessment of leveraged equity‑gold strategies.

الوصف

يُجري هذا البرنامج محاكاة يومية لاستراتيجية ذات رافعة 200٪ تجمع بين مؤشر NASDAQ100 (QQQ) ومستقبل الذهب. يُحسب قيمة صافي الأصول (NAV) عبر صيغة عائد مخصصة تأخذ في الاعتبار تحويل العملة والرسوم السنوية، ثم يُقارن NAV المحاكاة مع NAV الفعلي للصندوق. يتيح البرنامج أيضًا إنشاء توقعات احتمالية للأداء المستقبلي حتى 30 سنة باستخدام طريقة البوتستراب أو نموذج مونت كارلو للانحراف الجبري. تُنتج النتائج مخططات تفصيلية، ملخصات إحصائية، ومقاييس أداء مثل الانخفاضات النسبية ومؤشر شارب. يستهدف البرنامج المحللين الكميين ومديري المحافظ الذين يحتاجون إلى تقييم دقيق وموثوق لاستراتيجيات الأسهم والذهب ذات الرافعة المالية.

Novelty

6/10

Tags

financial-simulation backtesting portfolio-analysis risk-modeling monte-carlo bootstrap leveraged-strategy performance-comparison

Technologies

matplotlib numpy pandas

Claude Models

claude-opus-4.6

Quality Score

C
61.9/100
Structure
53
Code Quality
90
Documentation
59
Testing
0
Practices
66
Security
100
Dependencies
60

Strengths

  • Consistent naming conventions (snake_case)
  • Good security practices \u2014 no major issues detected
  • Properly licensed project

Weaknesses

  • No tests found \u2014 high risk of regressions
  • No CI/CD configuration \u2014 manual testing and deployment

Recommendations

  • Add a test suite \u2014 start with critical path integration tests
  • Set up CI/CD (GitHub Actions recommended) to automate testing and deployment
  • Add a linter configuration to enforce code style consistency

Security & Health

4.1h
Tech Debt (A)
A
OWASP (100%)
PASS
Quality Gate
A
Risk (1)
About: code-quality intelligence by Repobility · https://repobility.com
MIT
License
2.5%
Duplication
Full Security Report AI Fix Prompts SARIF SBOM

Languages

python
88.4%
markdown
11.2%
text
0.4%

Frameworks

None detected

Concepts (2)

Repobility · code-quality intelligence · https://repobility.com
CategoryNameDescriptionConfidence
Repobility analyzer · published findings · https://repobility.com
auto_descriptionProject DescriptionTracers NASDAQ100ゴールドプラス(ファンドコード: 645133)の仮想基準価額シミュレーター。80%
auto_categoryWeb Backendweb-backend70%

Quality Timeline

1 quality score recorded.

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