Very interesting stuff. I'd like to try and test this in Amibroker but not sure how to start. Can you please do a post on each of the steps for "Question 3: Can you predict whether NASDAQ 100 INDEX will outperform the Russell 2000 Index in the short term" Thank you for an enlightening post (very rare thing in these boards lol).
I tried a variation of this idea with the daily low prices of iShares Russell 2000 Value ETF (IWN) divided by the daily low prices of Invesco QQQ Trust (QQQ) then multiplied by 100. For the relative performance I fitted a curve to this ratio for rolling 4 month periods. The curves had a parabola (y = a + b * x + c * x^2) added to a cosine wave that might be skewed for right or left translation. The fitted curve rises when IWN is performing better than QQQ and vice versa. For example, here is an example of ratio values, parabola trend, and fitted curve for 123 calendar days starting 20121123 and ending 20130325. Here is the skewed cosine wave alone which is right-translated (falls faster than it rises). The curve formula for this example is Code: y = 100.706581115723 + 0.164993017911911 * x - 0.000613634416367859 * x^2 + 0.475093841552734 * skewed_cos(twopi / 45.5548653679802, 1.6029417514801, -0.509737253189087, x, 100) where skewed_cos(freq, phase, skew, x, iter) = cos(freq * x + phase) when iter == 0 skewed_cos(freq, phase, skew, x, iter) = cos(freq * x + phase + skew * skewed_cos(freq, phase, skew, x, iter - 1)) when iter > 0 X values are calendar days since the beginning of the 123 calendar day input period. I ran a long-only test with price data adjusted for splits and dividends from 20000728 through 20220414 using 4-months (123 calendar days) for each fitted curve (data was linearly-interpreted for non-trading days). If the skewed cosine wave was rising, a potential simulated trade would buy IWN at the next day close and sell IWN at the close on the day the skewed cosine wave was predicted to peak. If the buy and/or sell dates occurred on non-trading days, one or both would be moved to the next trading day. Also, simulated trades would only be entered if the overall fitted curve was predicted to go up for the potential trade duration. The result was 1807 simulated trades with a mean result of +0.98%, median result of +1.06%, and 1161 simulated trades (64.25%) profitable (results not adjusted for slippage and commissions). So, I conclude trading on style rotation with price ratios of two different assets can be profitable.
Well done! Most academic researchers also use daily pricing data even though some also include more data such as gold, interest rates, commodities, and FX pricing. However, my research shows that intraday data has much richer information, and therefore can improve the performance significantly. I mainly use 1-hour data and 2-hour data in modelling, and map into higher frequency in actual trading. I will show more details over the weekend! If anyone wants to read more research papers, search "style rotation" on this website: https://www.ssrn.com/index.cfm/en/
I use daily data because it seems good enough for the swing trading I do. I look forward to seeing more details.
I also like the pair of QQQ (TQQQ, SQQQ)-IWM(TNA, TZA) given that I can trade the pair in the retirement accounts which don't allow short. There are also e-mini, micro e-mini futures for automatic day trading.
Another big down day! A good day for the long/short strategy based on style rotation and factor timing. The attached simple chart shows how I do the modelling.
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while predicting the directions of the market is very hard, I do manage to come up with the day trading tool to trade ES, gaining average 30 points in April.