Tag: SPL Quantitative Trading Practice Series

Usually, the rise of stock market will create an upward trend. If one is able to capture the trend, they will get handsome benefits. This essay will introduce the commonly used Trend Trading Strategy. First, let’s look at some related concepts before introducing the trading strategy: 1. The latest trough: the stock price lower than that over the N trading days before and after the date when it occurs. 2. The crest before the trough: The stock price that is higher than that over the N trading days before and after the day and that appears before the latest trough.

The trading strategy is like this: 1. Set “up or not” as the target (target). If the closing price is higher than that of the previous date, assign 1 as the target value, otherwise assign -1 to it. 2. Add two metrics – highest closing price minus lowest closing price (max_dif) and closing price minus opening price (co_dif). 3. Suppose we need to predict the stock prices in the year 2023. Compute distance between the two metrics (max_dif and co_dif) on the current date and those on each of the previous 660 trading dates, find the 95 dates with the

The MACD (Moving Average Convergence Divergence), derived from the Exponential Moving Average (EMA), is highly effective for capturing trending market conditions. Its top (bearish) and bottom (bullish) divergences serve as a proven method for “buying the dip and selling the peak”, making it a key consideration for many medium- to long-term investors in real-world trading. In this essay, we will implement the MACD divergence strategy using SPL (Structured Process Language) and conduct backtesting to evaluate its performance. Before offering the SPL code, we need to look at how to compute MACD: 1. Short-term EMA: The short-term exponential moving average. The