Forecasting Stock Prices with Machine Learning and Probabilistic Models
Arihant Jaggi
NHSJS
National High School Journal of Science
is a free, online, peer-reviewed research journal for high school students. This manuscript has been submitted; the published version is coming soon.
ABSTRACT
Accurate modeling and forecasting of asset prices has been a long-sought objective in quantitative finance, driven by the persistent need for robust risk management and capital optimization. However, rigorous cross-sectional comparisons between deep/machine-learning and traditional stochastic mathematical models across varying market regimes and multiple tickers remain significantly limited. This study evaluates the … [view more]
Keywords: Stock Price Forecasting; LSTM; Geometric Brownian Motion; Decision Tree; Naive Persistence Baseline
Awards & Recognition
S.-T. Yau High School Awards
Research Submission
Submitted under the S.-T. Yau High School Science Award program. Publication in NHSJS forthcoming.
AP Research
Score of 5 · College Board
Earned a score of 5 on AP Research for this forecasting investigation.
AP Capstone Diploma
College Board
Awarded the AP Capstone Diploma in recognition of completing the Capstone program, including this AP Research project.