ProgramsGraduate Consulting Experience (Summer 2025)ProjectsSageFusion AI - Analyzing Statistical Distributions of the stock ma...

Project Title: SageFusion AI - Analyzing Statistical Distributions of the stock market assuming a non-normal distribution

SageFusion

Details
Project Title SageFusion AI - Analyzing Statistical Distributions of the stock market assuming a non-normal distribution
Project Topics Data Management Entrepreneurship Information Technology (IT) Research, Analysis, Evaluation
Skills & Expertise Emerging Tech
Project Synopsis: Challenge/Opportunity
Well, I own three companies: www.investmentscy.com, www.sagefusion.co, and https://www.therapharma.consulting/
Project Synopsis: Activities/Actions Required
Action Items:
  1. Market Data Analysis and Statistical Distributions
    • Gather publicly available financial data on historical stock market trends.
    • Analyze year-over-year changes in statistical distributions for specific ticker symbols.
    • Compare assumptions of normal distribution versus actual data.
  2. Algorithmic Risk Model Enhancement
    • Develop new AI-driven risk modeling techniques based on real-world distribution patterns.
    • Test different machine learning approaches to improve forecasting.
    • Identify potential trading strategies derived from data-driven insights.
  3. Data Licensing and Thought Leadership
    • Assess the commercial value of refined investment models for licensing.
    • Explore opportunities for publishing white papers and research on financial risk modeling.
    • Identify potential clients and partners in the financial services and government sectors.
  4. Implementation & Testing
    • Conduct backtesting using historical data to measure the effectiveness of new models.
    • Optimize algorithms based on test results and stakeholder feedback.
    • Provide strategic recommendations on integrating findings into Sage Fusion’s treasury management platform.
Project Synopsis: Expected Results
Measuring Success:
  • Identification of inaccuracies in traditional risk modeling assumptions.
  • Development of AI-enhanced models that improve investment decision-making.
  • Backtested performance improvements in risk assessment accuracy.
  • Potential revenue opportunities from data licensing and consulting.
  • Published findings and reports demonstrating insights for financial professionals.
Milestones & Deliverables
Milestone 1: Market Data Collection & Distribution Analysis
  • Goal: Examine financial market data to challenge traditional normal distribution assumptions.
  • Guiding Questions:
    • How do stock price distributions evolve over time?
    • What statistical anomalies exist in current risk models?
    • How can we visualize year-over-year changes in market data?
    • What are the implications of non-normal distribution for risk modeling?
    • How do AI models improve accuracy in detecting these changes?
  • Suggested Deliverable:Market distribution analysis report with visualized trends.
Milestone 2: Development of AI-Driven Risk Models
  • Goal: Enhance traditional risk models using AI and advanced statistical techniques.
  • Guiding Questions:
    • What machine learning methods are most effective for risk prediction?
    • How can non-normal distributions be incorporated into trading algorithms?
    • What are the limitations of existing financial risk models?
    • How can AI improve dynamic portfolio management?
    • How do proposed models compare in performance to industry standards?
  • Suggested Deliverable:Prototype AI model with initial backtesting results.
Milestone 3: Commercial Feasibility & Data Licensing Strategy
  • Goal: Explore monetization opportunities through data licensing and financial research applications.
  • Guiding Questions:
    • Which institutions could benefit from access to refined risk models?
    • How can Sage Fusion monetize proprietary financial insights?
    • What pricing structures exist for data licensing in financial markets?
    • How do regulatory considerations impact commercial adoption?
    • What marketing strategies will position Sage Fusion as a leader in investment science?
  • Suggested Deliverable:Business case and go-to-market strategy for data licensing.
Milestone 4: Final Testing & Integration with Sage Fusion
  • Goal: Validate models through real-world testing and prepare for integration into Sage Fusion’s treasury management platform.
  • Guiding Questions:
    • How do backtested results compare to traditional risk modeling?
    • What refinements are needed before implementation?
    • How will integration impact Sage Fusion’s overall product offering?
    • What client feedback can be gathered for further optimization?
    • What long-term research directions should be pursued based on project findings?
  • Suggested Deliverable:Final AI risk model, backtesting validation report, and integration plan.
Suggested Resources from Sage Fusion
  • Historical investment models and previous research attempts.
  • Proprietary market datasets for back testing AI-driven risk models.
    • Access to Sage Fusion’s treasury management platform for integration testing.
  • Past reports and financial statements relevant to risk modeling.

Project Timeline

SageFusion - SageFusion AI - Analyzing Statistical Distributions of the stock market assuming a non-normal distribution
Due Date
Activities
Deliverables
Status
Action
Wed, 04/17/24
12:00 AM UTC
Applications Closed for Students
No Deliverables
No deliverables are required for this action item.
Location: Virtual
CapSource Platform
Fri, 05/10/24
12:00 AM UTC
Teams Finalized, Projects Assigned
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Location: In Person
CapSource
Fri, 05/10/24
12:00 AM US/Eastern (UTC-04:00)
Students Upload Signed "Fordham Unpaid Internship Agreement"
Required Deliverable
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Deliverable submission is required.
Location: In Person
CapSource
Fri, 05/10/24
12:00 AM UTC
Students Upload Resume
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View Calendar
Fri, 05/17/24
12:00 AM UTC
Industry Partners to Provide Each Offer Letter to Each Student
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Location: In Person
CapSource
Fri, 05/24/24
12:00 AM US/Eastern (UTC-04:00)
Kickoff Eval
Required Evaluation
Evaluation submission is required.
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Fri, 05/31/24
12:00 AM UTC
Goal Date for CPT Approval
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Location: In Person
CapSource
Mon, 06/03/24
12:00 AM UTC
Projects Launch!
Schedule time to launch projects with each team member and project manager
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Guiding Questions:
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Location: In Person
Virtual
Wed, 06/12/24
12:00 AM UTC
Temp Check
Required Evaluation
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Fri, 06/28/24
12:00 AM UTC
Temp Check
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Wed, 07/10/24
12:00 AM UTC
Temp Check
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Fri, 07/26/24
12:00 AM UTC
Projects End
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Location: In Person
Virtual
Fri, 07/26/24
12:00 PM UTC
End of Project Self Reflection
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