Dollar cost average on TQQQ vs QQQ [Simulation]

This post runs a simple simulation on using the Dollar-Cost-Average strategy to invest in QQQ vs. TQQQ, its 3x-leveraged ETF.

In the simulation, QQQ will plunge 34% after 20 rounds. One round is a small up-and-down cycle – the index first moves up 1% then 3% down, until 34% down from the top. After reaching the bottom, I simulate another 42 rounds such that QQQ can almost crawl back to its previous top. This time, within each round, the index first moves up 2% then 1% down. In each round, we invest two times using a fixed amount of money, one after the up and one after the down. 

I simulate the same process for TQQQ. The only difference is that in each round, the up and downs are 3x as those in QQQ. 

The script and result can be found below. We can see that DCA in TQQQ will still give us better return. Also, as we expect, when QQQ has almost reached back to its former price (99.94), TQQQ is still not yet back to the peak (88.07). However, that does not contradict with the fact that the DCA earns more on TQQQ than QQQ overall.

DOWN_ROUNDS = 20
UP_ROUNDS = 42
stock_price = 100
amounts = 0
DAC = 100
SCALE = 1  # 1 for QQQ and 3 for TQQQ
for i in range(DOWN_ROUNDS):
    amounts += DAC / stock_price
    stock_price = stock_price * (1 + 0.01 * SCALE)
    print(f"round={i}, amount: {amounts}, price={stock_price}")
    amounts += DAC / stock_price
    stock_price = stock_price * (1 - 0.03 * SCALE)
    print(f"round={i}, amount: {amounts}, price={stock_price}")

for i in range(UP_ROUNDS):
    amounts += DAC / stock_price
    stock_price = stock_price * (1 + 0.02 * SCALE)
    print(f"round={i}, amount: {amounts}, price={stock_price}")
    amounts += DAC / stock_price
    stock_price = stock_price * (1 - 0.01 * SCALE)
    print(f"round={i}, amount: {amounts}, price={stock_price}")

print(f"final value={amounts * stock_price}")

# QQQ (scale=1) final value=15197.210360810055
# The last print: round=41, amount: 152.06046946267062, price=99.9418876879163

# TQQQ (scale=3) final value=22578.30484235393
# The last print: round=41, amount: 256.36563654519176, price=88.07071472846891