Examining on Post Earnings Announcement Drift (PEAD), we deliver a long-short strategy generating 9.96% alpha with -0.45 S&P 500 beta. … Continue Reading GPR Report – Behavioral Finance [慣性盈餘]
STOCK TRADING via A.I. & MACHINE LEARNING WORKSHOP Saturday, February 9 and 16, 2019 | 9:30 a.m. to 1:30 p.m. … Continue Reading Dr. Peter Lin at Columbia University MACHINE LEARNING WORKSHOP
Using Leading Indicator, we deliver a stable, less volatile strategy in Taiwan Market with 5.2% annualized return. [中文] 策略專注於捕捉市場「失常」的時機點。 利用總體經濟指標，搭配統計方法設定合理市場價格範圍。
There is no excerpt because this is a protected post.
Autocorrelation We often need to characterize time series autocorrelation, , which is defined as When the sequence is weakly stationary, … Continue Reading AMRA Model and Kalman Filter (01)
OHLC from Tick Data This post shows you how to process tick data and generate Open-High-Low-Close (OHLC) price statistics. Tick … Continue Reading Tick Data and Charting for NBBO
Our previous article on Kalman filter gave us a simple linear regression output. The model is designed to handle noisy … Continue Reading Kalman Filter (02) – S&P 500 and Dow Jones Pairs Trading
Linear Regression Let’s get some Kalman filter basics and start playing around with it. There is a long history about … Continue Reading Kalman Filter (01) – S&P 500 and Dow Jones Linear Regression