Momentum Investing in Quant Trading - A 365-Day Capital Gain Strategy

In this article, I would like to share a quant trading strategy, which can get capital gains by leveraging and riding the stock pricing wave. It’s a 365-day strategy, which can be implemented through intraday trading or short-term momentum trading. Momentum investing in quant trading is extremely popular, which can help you maintain a sustainable positive cash flow, much like working for a company, rather than waiting a long time compared to long-term investing.

To whom:

• People who are beginners in quant trading
• People who are using AI to analyze potential investment opportunities

Table of Contents: Momentum Investing in Quant Trading - A 365-Day Capital Gain Strategy

• What is momentum investing?
• Why momentum investing can be extremely popular in getting capital gains
• How to leverage momentum investing in quant trading
• Momentum trading downside
• AI Prompt Components to analyse investment opportunities using the momentum trading
• AI Prompt sample and momentum investing strategy python script

What is the momentum investing in quant trading?

Momentum investing in quantitative (quant) trading is a strategy that seeks to capitalize on the continuation of existing market trends. The core idea is that assets that have performed well in the past will likely continue to perform well in the short term, and vice versa for poor performers as well in the short term.

Momentum investing in quant trading works with several core components, which are as follows:

• Relative strength index - In general, the RSI that is lower than 40 is a signal to buy in, or that is higher than 60 is a signal to sell out.
• Moving Average Convergence Divergence - The MACD lookback days have a couple of very common options. They are 20, 50, 80, 120, 200
• Trading volume and volatility - Both are must-have elements to run momentum investing strategy in quant trading on the target stock tickers

Why momentum investing can be extremely popular in getting capital gains

Compared to long-term investing, value investing, or growth investing, the cycle of momentum investing is much shorter than other investing strategies. momentum upward or downward trend can occur in intraday trading, or the lookback period can be a 3, 6, 9, and 12-month. That implies that as long as you can detect the signal of buy-in or sell-out, it can be a daily routine and a regular trading schedule to get capital gains. It takes less time to wait compared to value investing.

Momentum is a price-based signal trading strategy, which sets up a quant trading algorithm to buy assets that have had relative positive returns over some time (e.g., past 3, 6, or 12 months). Or people can rank assets by performance and buy the top performers, short the bottom performers

Unlike mean-reversion strategies, which bet on prices returning to average, momentum assumes trends do not require prices returning to average, and it can persist over short to medium-term horizons. That implies it takes less time to wait for a new round of capital gains as long as the opportunity signal occurs. As long as the trading volume of a ticker is sufficient and the volatility is enough, investors would consider momentum strategies to monetise the wave

How to leverage momentum investing in quant trading

First things first, people need to prepare a list of target stock tickers with a historical price dataset down to the day at least. They can be from an index, a standalone company stock ticker, or an ETF, and so on. The stock pricing dataset is the fundamental to get the momentum trend and analyze the opportunity signal. So it can calculate the up and down price gap over a period. Based on the upward or downward trend, people can calculate the average capital gains from every single signal of buy-in and sell-out based on the up and down

Second, people need to identify the signal of buying-in and selling-out, although it has already shaped an upward or downward trend. So people need the relative strength index and also consider the MACD lookback period to further ensure if the signal is solid.

Lastly, people need to set a target price for both stop-loss and target price to get capital gains. This price would be used in the quant trading that works with RSI and MACD to finally determine the buy-in or sell-out price point and take actions.

Momentum investing downside

As you might be aware, momentum investing is a kind of relying on technical analysis and price signals, which are based on a historical dataset over a period. The downside of momentum investing is that it’s more on a micro perspective to determine and take actions, where basically it ignores the fundamentals, macroeconomic, political events, and sector performance.

Historical dataset represents the past performance, which is not a 100% correct indicator to predict the future, and the future will not happen as well as what past did. In particular, the modern investment environment is more dynamic than ever, and it has more factors that can affect the final result. So if the dataset people are using is out of date, it can severely distort the picture of what people should understand.

For relieving the impact from momentum investing downside, people get used to integrating with more macroeconomic metrics, index price performance and industry events, and political incidents to get the signal detection in a more precise way

AI Prompt Components to analyse investment opportunities using the momentum trading

If you use generative AI to analyse investment opportunities, in terms of momentum investing, here is a list of components you need to consider and include in the AI prompt as follows:

• Target stock price dataset
• Up and down performance analysis over a period
• Average capital gain over a period
• Relative strength index analysis
• MACD performance compared to the latest close price
• Other factors: macroeconomic indicators (interest rate, CPI, etc), index price performance dataset, political events, industry events, and news

AI Prompt sample and momentum investing strategy python script

def momemtum_investing(ticker):
    # Define a list of stocks to analyze
    # Fetch price data and calculate momentum metrics
    momentum_stocks = []
    tickerPricing = ""
    df = get_up_or_down(tickerPricing)
    df2 = df.reset_index()
    overbought_oversold_investing1 = overbought_oversold_investing(df2, 14)
    df2['RSI'] = overbought_oversold_investing1['rsi'].tolist()
    df2['50D MA'] = df2['Close'].rolling(window=50).mean()
    df2['200D MA'] = df2['Close'].rolling(window=200).mean()
    # Define momentum criteria (example: RSI > 50, Price > 50D MA, Price > 200D MA)
    latest_rsi = df2['RSI'].iloc[-1]
    latest_close = df2['Close'].iloc[-1]
    latest_50d_ma = df2['50D MA'].iloc[-1]
    latest_200d_ma = df2['200D MA'].iloc[-1]
    if latest_rsi > 50 and latest_close > latest_50d_ma and latest_close > latest_200d_ma:
        momentum_stocks.append({
            "Ticker": ticker,
            "RSI": latest_rsi,
            "Price": latest_close,
            "50D MA": latest_50d_ma,
            "200D MA": latest_200d_ma,
            "Momentum_qualification": "Verified"
        })
    else:
        momentum_stocks.append({
            "Ticker": ticker,
            "RSI": latest_rsi,
            "Price": latest_close,
            "50D MA": latest_50d_ma,
            "200D MA": latest_200d_ma,
            "Momentum_qualification": "Not Verified"
        })
    return momentum_stocks

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