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No. The models are more for timing by looking at predicted inflection points and not for predicting price targets.

Yes, here is a least squares fit with a 9th degree polynomial. Corn to the Moon!:)

It's hard to overfit (model noise) on typical asset prices with a parabola and three cosine waves. If I used a few more cosines ... Now there is a fit that would have made Jean-Baptiste Joseph Fourier proud!:)

I did some trend and cycle analysis of the CORN ETF by fitting 10 curves to the most recent 123 calendar days of close prices with prices (20210125 through 20210527) and then extrapolating the curves for 21 calendar days. The models for the curves are: y = 16.7131156921387 -...

The original article for the strategy was for SPY, so it's probably valid to test it with SPY as long as entries on ex-dividend dates account for the dividend or all the close and open prices are adjusted for dividends for the test...

The mean price for the 10 models on 20210514 (end of input data) was 1,835.57391357422. The mean price for the 10 models on 20210528 was 1,825.53142089844 (10.0424926757798 lower than the mean for 20210514).

Using data from yahoo finance for Gold Jun 21 https://finance.yahoo.com/quote/GC=F/history?p=GC=F For 123 calendar days ending 20210416 (starting point 20201215), 10 fitting functions generated were: y = 1891.65246582031 - 2.29241752624512 * x + 0.00931525230407715 * x * x +...

The code calculates the slope by dividing the fixed $2 increase of a stock that starts out at $100 and outputs the day index, old price, price increase from the previous day, slope from the previous day to the current day, and the current price. So after 1 day, the slope was 2/100, and the...

A fixed increase means the slope is decreasing. For example, perl -e 'use warnings; use strict; my $curPrice = 100; my $incr = 2; for (my $i = 1; $i <= 10; ++$i) { my $slope = $incr / $curPrice; my $nextPrice = $curPrice + $incr; print "i $i curPrice $curPrice incr $incr slope...

Here is an article that has examples of multi-step LSTM forecasting. https://machinelearningmastery.com/how-to-develop-lstm-models-for-time-series-forecasting/ And another by the same author that mentions other ways to do multi-step forecasting...

Portland is still Portland too. https://www.oregonlive.com/portland/2021/05/portland-police-declare-riot-as-marchers-break-windows-on-anniversary-of-george-floyds-murder.html

The attached orderbook.pdf has some screenshots from the video.

This might help. https://tradingrush.net/i-tested-rsi-adx-trading-strategy-100-times-and-you-should/

I don't know who the shooter was, of course. But I'm guessing the perp was someone local to the area who interacted with someone else from the area near George Floyd Square. Who doesn't like a little gunfighting now and then?:)...

That's true without looking at the context, but immediately after is So his conclusion is China could have stopped the spread of COVID-19 to the rest of the world like they did inside China.

Nope. Never.:)

Here are how the locals remembered George Floyd's death one year later.

I was thinking of a play on words like "Time of the Sines" (already used by a band from your neighborhood:)) or something to confuse other machine learning enthusiasts like "Least Squares Time Machine (LSTM)," but I just call it GaCurveFitter.

I wrote it in C++ and opencl (so most of the calculations are done on a GPU) with controlling code in perl and shell (bash). The graphs are from gnuplot. A model (e.g., for GLD) bwould be something like y = 178.67431640625 - 0.552311420440674 * x + 0.0044319755397737 * x * x +...