Spring 2025

Researcher

Hayt R. Haria

Faculty Advisor

Not specified in the PDF

Overview

This project develops HariaX, an intelligent multi-asset forecasting platform designed to help young investors make independent, data-driven financial decisions. Unlike traditional tools that focus on a single market, HariaX applies a broad forecasting approach across equities, mutual funds, real estate, forex, and commodities.

The system combines historical and live market data from platforms such as Yahoo Finance, TradingView, and Bloomberg Terminal. After testing traditional models like ARIMA, GARCH, and Linear Regression, the project shifted toward a more adaptive technical-analysis framework using RSI, Fibonacci retracements, EMA, MACD, and volume-based indicators.

The goal of HariaX is not only to forecast price behavior, but also to make investing more understandable, visual, and accessible for the next generation of investors.

Key Findings

1. Platform Validation.

  • The project successfully built a multi-asset forecasting framework that works across several financial markets instead of being limited to a single asset class.
  • The platform showed that modular, asset-specific forecasting strategies are more practical than a one-size-fits-all model.
  • Its visual and indicator-based design makes forecasting outputs easier for retail investors to interpret and use confidently.

2. Impact of Model Choice

  • Traditional models such as ARIMA, Linear Regression, and GARCH were useful as baselines but performed poorly in highly dynamic, nonlinear, and volatile market settings.
  • These models struggled with short-term responsiveness, regime shifts, and cross-asset adaptability.
  • The transition to technical indicators improved forecasting flexibility, interpretability, and responsiveness to real market behavior.

3. Forecasting Methodology

  • Equities: Fibonacci retracement and momentum indicators were applied to stocks such as Tesla and Nvidia to identify trend reversals, support/resistance zones, and entry/exit opportunities.
  • Mutual Funds: RSI and volume trend overlays were used to compare U.S. and Indian funds, revealing smoother momentum in U.S. funds and more aggressive swings in Indian funds.
  • Real Estate: Forecasting relied on yield-based estimation and regional ROI analysis, especially across the U.S., India, and UAE.
  • Forex and Commodities: The platform analyzed macroeconomic conditions, central bank policy, inflation, and geopolitical trends to forecast major currencies and commodity prices.

4. Comparative Insights

  • Adaptive technical indicators proved more effective than classical econometric models for the project’s goal of a real-time, scalable, and user-friendly forecasting engine.
  • HariaX demonstrated that visual forecasting tools can improve transparency and help non-technical users understand why a signal is generated.
  • The project evolved from a research experiment into the early foundation of a potential all-in-one investment product for young investors.

Conclusion

The HariaX framework shows that a modern forecasting engine for retail investors should be adaptive, modular, and visually interpretable. Traditional statistical models alone were not sufficient for the project’s broader objective, while technical indicators offered faster response, greater flexibility, and stronger usability across asset classes.

Future research should:

  • integrate machine learning enhancements
  • add ESG-based investment filters
  • improve mobile and web accessibility
  • strengthen educational features that explain signals in plain language
  • expand globally across more markets and user segments

Significance

This project is significant because it positions HariaX as more than a financial forecasting tool. It presents a vision for democratizing financial intelligence by giving younger investors access to interpretable, cross-asset, data-driven guidance.

By combining forecasting, visualization, and education, HariaX aims to help users build confidence, improve financial literacy, and make smarter long-term investment decisions independently.