Mean Reversion Strategy
The Mean Reversion strategy is a type of statistical arbitrage approach in quantitative trading. It is based on the idea that asset prices tend to revert to their long-term average after short-term deviations. The core assumption is: when prices deviate significantly from their historical mean, they will eventually return to that mean. This strategy is…
Flash Crash Strategy
The “Flash Crash” strategy is a short-term trading approach inspired by the experiences and stories of Jesse Livermore, as described in the classic trading book Reminiscences of a Stock Operator. This autobiographical account of Livermore’s trading career is widely regarded as one of the most influential works in the field of stock trading. Core Idea…
The Turtle Trading Strategy: A Classic Trend-Following System
The Turtle Trading Strategy is a classic trend-following approach developed in the 1980s by Richard Dennis and William Eckhardt. This strategy identifies entry and exit points by tracking a market’s highest and lowest prices over a defined period. It is designed to capture long-term trends and profit from sustained price movements. The Origin of the…
How to Use Google Finance Data in Google Sheets
If you have years of experience in quantitative trading, you’re probably no stranger to the Google Finance API. It was once a very popular tool in the financial trading industry, offering numerous advantages over its competitors. The Google Finance API not only provided real-time stock market data but also allowed users to create and manage…
Python Quantitative Trading: How to Access Financial Market Data?
This article introduces how to use Python to call pre-packaged high-frequency data APIs. We’ll use Alltick’s tick data interface as an example. Here’s a sample code snippet. Requesting Candlestick Data In the code above, we use the Apple stock (AAPL.US) as an example to request minute-level K-line data. To request other K-line types, pass the…
Bollinger Bands Strategy
The Bollinger Bands strategy was developed by John Bollinger in the early 1980s. It is a highly popular technical analysis tool used to assess the price level and volatility of an asset. The Bollinger Bands consist of three lines: the middle line is an n-period moving average (typically a 20-day simple moving average), while the…
From Tick Data to Candlestick Charts
Candlestick charts are a widely used chart type in stock markets and financial trading, designed to display information such as the opening price, highest price, lowest price, and closing price over a specific time period. This article introduces how to convert real-time tick data into candlestick data of various timeframes and provides essential formulas and…
Dual Moving Average Strategy
The Dual Moving Average (Dual MA) strategy is a simple yet widely used technical analysis tool designed to identify trend changes in the market and generate trading signals. This strategy involves two moving averages—a short-term (fast) and a long-term (slow)—and uses the crossover points between them to determine the timing for buying or selling. Strategy…
R-Breaker Strategy
The R-Breaker strategy is a well-known trading strategy developed by American trader and programming expert Richard Saidenberg. It was made public in the early 1990s. This strategy is primarily used in the futures markets, where it has performed particularly well with S&P 500 index futures, but it can also be applied to other financial markets….
Forex Strategies in Python
The foreign exchange (forex) market, known for its high liquidity and 24-hour trading cycle, attracts a large number of traders. Quantitative trading strategies are also very popular in the forex market. Below are three classic forex trading strategies that can be implemented quantitatively. 1. Momentum Trading Strategy The momentum strategy is based on the assumption…
