10 Common Statistical Models You Should Know
Here presents the 10 most commonly used statistical models/algorithms every Quants and AI developers should know. Linear Regression Logistic Regression Decision Tree ...
Here presents the 10 most commonly used statistical models/algorithms every Quants and AI developers should know. Linear Regression Logistic Regression Decision Tree ...
What is Relative Strength Index? The relative strength index (RSI) is a technical indicator for financial market analysis. By measuring the magnitude of recent price changes, it evaluates the over-bought or over-sold conditions of ...
Hello, I've been backtesting many different ideas and i have been talking with a friend about this topic and we conclude that there's no a general ...
I attended a seminar recently. The speaker said people no longer use simple Black-Scholes setting in Wall Street. They add in different volatility models to capture the irregular up and downs of ...
Introduction The Hurst exponent, denoted as H , is a measure of the long-term memory of time series data. Originally developed to analyze hydrological data, it has gained prominence in financial ma ...
I am a newbie for quant trading, and I am very interested to start a career in this field. Appreciate if anyone can share some good reference books here. ...
What is an Autoregressive Model? An autoregressive (AR) model predicts future behavior based on past results. It is used for forecasting when there is some correlation between values in a time series and the values that precede an ...
I recently struggle on creating good trading strategy... Just wanna to know what is your workflow for developing and testing new trading algorithms? From idea generat ...
In a simple setup, let's say (w 1 , w 2 ) are weights invested in assets 1 and 2. I only saw discussions when w 1 +w 2 =1, even if short selling is allowed. ...
How are you integrating machine learning into your trading algorithms? What models or techniques have proven most effective for predictive analysis in your experience? Let's share insights and tips on ...
Hi all, i am new to algo-trading. So far I built an algo that seems to work for 1 year. How far should I backtest? The longer the better, or does it depend on the timeframe used? ...
I run a regression of a hedge fund's returns vs Fama French 3 factors. If I want to look at the distribution of idiosyncratic returns of a hedge fund, should I only use the residuals or the residuals+ ...
By performing the Singular Spectrum Analysis (SSA) or Singular Value Decomposition (SVD) on moving average helps improve the sensitivity of the model to pivot points and rebounces. SSA is often use The aim of SSA is to decompose a time series into smaller components to better interpret its trends. SSA takes the chracteristic difference between a sliding window as the major contributing signal ...
Hello algogene team, I am really appreciate your powerful backtest and trading engine which provides lot of datasets to work with. It would be even great if the system can further support pe ...
Risk management is important and necessary for long terms investment. A good risk management mechanism helps keep your account safe from unexpected events and unlucky times, and makes you distingui ...
What is Average True Range? The Average True Range is a technical analysis indicator, originally developed by J. Welles Wilder. ATR does not provide indication about price trend. Instead, it measures the market volatility for ...
As titled, from you guys experience, what would be the best extrapolation method suggested for future price prediction? ...
What is Sharpe Ratio? The Sharpe ratio was developed by William F. Sharpe, a Nobel laureate, to help investors understand the return on an investment in relation to its risk. The ratio measures the return earned in exce ...
As title, how can I statistically test whether a given price series is random or not? Appreciated if anyone can share some reference/ programming code. PS: I don ...
Given n stock time series X 1 , X 2 , ... X n , I want to measure how much they have dispersed over time. For example, are they moving "more together" this year co If there are only 2 time series, then I can just calculate the correlation of X 1 and X 2 . ...
Let X 1 , X 2 , ... be independent, identically distributed random variable with P ( X j = 1 ) = q, P ( X j = -1 ) = 1-q Let S 0 = 0 and for n >= 1, S n = X 1 + X 2 + ... + X n . Let Y n = e S n ...