B-TIER technique
Fast Fourier Transform — decomposing NVDA price into frequency signals
100k ft — What is this?
Fast Fourier Transform — decomposing NVDA price into frequency signals
50k ft — Why care?
Applies FFT to NVDA price action to decompose it into frequency components, separating noise from dominant cycles. Shows how to identify the strongest periodic signals in price data.
10k ft — Key takeaways
• FFT separates noise from dominant market cycles
• Identifies strongest periodic signals in price data
• Foundation for frequency-based trading strategies
5k ft — Tools & techniques
(no tools tagged)
Fast Fourier Transform, Frequency Decomposition, Spectral Analysis, algorithmic trading
1k ft — Deep-dive / try it
Stop trading the noise. Start seeing the signal. 📉📈
Financial markets are noisy. By applying the Fast Fourier Transform (FFT), we can decompose a stock's price action (like NVDA here) into different frequencies.
Grab the full script repo, comment "FFT" to build this for your own portfolio. 💻
The top chart overlays the smoothed "Signal" (low-frequency trend) against the raw, jagged price action. The bottom chart isolates the "High-Frequency Noise"—the erratic movements that often trick traders into bad entries.
Math doesn't lie; it just clarifies.
rahzyey
23w
Is this applied on rolling window?
Transcript excerpt
(no speech detected)
More from @quant.dhawan
- B-TIER Heston Model — stochastic volatility for realistic options pricing
- B-TIER Cox Process — doubly stochastic Poisson for bursty market events
- A-TIER Hidden Markov Models — detecting market regime shifts automatically
- B-TIER Avellaneda-Stoikov — optimal spread calculation for market makers
- A-TIER Ornstein-Uhlenbeck Process — mean reversion for pairs trading