My name is Aditya Singh. I am a Computer Engineering student. I like writing programs more than I like reading market commentary, which is how I ended up in quantitative finance as a side project. I did not spend years on a trading desk. I spent nights reading free explainers, a few papers, and Quantpedia’s strategy notes, then I tried to recode the smallest pieces I understood.
This website is the public notebook for that work. The research question is practical: how does a trading algorithm take in data and decide to act? I answered it with moving averages and RSI because those formulas are short, they have names in the literature, and I can show every step on one page (Wilder, 1978; Brock, Lakonishok, and LeBaron, 1992; Faber, 2007).
Methods, in one paragraph: I keep daily bars, compute indicators from closes, delay the trade by one bar so I do not trade on the same close I just used, and grow a cash account that earns nothing when the rule is out. Charts on the site use one illustrative series so the pictures, the equations, and the table all talk about the same object. When I cite Quantpedia, Fidelity, Investopedia, or StockCharts, I am pointing at the place I learned a definition or saw a figure, not claiming those sites endorse my test.
If you want the short version of the findings: a slow average-based long/cash rule cut the worst drop on my sample and also made less money than sitting still. A faster crossover traded more and looked worse. That is the shape I expected from the papers. It is not a reason to put real money on these lines.