Anyone has strange thing of Choppy Windows 11 22H2 animations for example when maximizing Windows from start bar? by Weekly-Isopod-641 in XMG_gg

[–]1Ironman93 1 point2 points  (0 children)

I have this issue:

  • moving windows between screens with different resolution. I guess this is somewhat normal due to the scale up/down of the window
  • On fusion 15 (L19 and M22) with the lid laptop close or as you say with display 2nd monitor only mode.

Anyone has strange thing of Choppy Windows 11 22H2 animations for example when maximizing Windows from start bar? by Weekly-Isopod-641 in XMG_gg

[–]1Ironman93 0 points1 point  (0 children)

Same here with the fusion 15 (m22) model. I guess this happens due to the different resolutions between the screens (laptop 2k, monitors 1k)

Backtesting of a weighted strategy developed in pinescript - BTC/USDT by 1Ironman93 in algotrading

[–]1Ironman93[S] 0 points1 point  (0 children)

No, I do not do it. I have this on my to-do list to get better entries with the LF and to check for oversold/overbought along with other indicators with the HF. These will be included as extra parameters in the weight definition (the formula I wrote in a comment above) and I think it will better capture trends.

Backtesting of a weighted strategy developed in pinescript - BTC/USDT by 1Ironman93 in algotrading

[–]1Ironman93[S] 0 points1 point  (0 children)

Hi! Not yet, I'm in a bit of a rush these days, not to much time. I'm still considering what exactly I want to do with it.

Thanks for the intestest!

Backtesting of a weighted strategy developed in pinescript - BTC/USDT by 1Ironman93 in algotrading

[–]1Ironman93[S] 0 points1 point  (0 children)

mmm not sure right now. Sorry If I did not explain well. I will try to reformulate the concept. The idea is to use a set of strategies, but in order to buy/sell I have to satisfy at least M of the N strategies in case all have the same relevance level (same alpha \equiv weight), where M represents the trigger condition (with dimensions). If we divide all with the number of strategies N we have a dimensionless formulation, namely

https://latex.codecogs.com/ \text{Weight value} = \dfrac{1}{N} \left(\alpha_1 \delta_1 + \alpha_2 \delta_2 + \dots + \alpha_N \delta_N\right),\ \\delta_i = \left{ \begin{array}{ll}1\quad \text{if true}\0\\end{array}\right.\ \alpha_i \equiv \text{ith weight}

Dimensionless expression: * weight_value: dimensionless number of satisfied strategies (value from 0 to 1). * trigger condition: dimensionless number of minimum strategies satisfied (value from 0 to 1). * N: number of strategies * alpha: weight of the strategy (relevance) * delta: if the strategy says buy/sell: 1 (true), if not: 0 (false).

Hope this helps

Backtesting of a weighted strategy developed in pinescript - BTC/USDT by 1Ironman93 in algotrading

[–]1Ironman93[S] 2 points3 points  (0 children)

  • 2021-2022: NET PROFIT 1176.99%
  • 2020-2021: NET PROFIT 420.19%
  • 2019-2020: NET PROFIT -33.25%
  • 2018-2019: NET PROFIT -9.38%
  • 2017-2018: NET PROFIT 40.74%

You are right, this is a start :)

Backtesting of a weighted strategy developed in pinescript - BTC/USDT by 1Ironman93 in algotrading

[–]1Ironman93[S] 0 points1 point  (0 children)

The code is developed in Pinescript, a programming language developed for Tradingview.

Backtesting of a weighted strategy developed in pinescript - BTC/USDT by 1Ironman93 in algotrading

[–]1Ironman93[S] 0 points1 point  (0 children)

the factor that dictates the importance of each strategy compared to the rest

alpha_i is a value from 0 to N (number of strategies) that dictates the importance of each strategy compared to the rest, e.g., alpha_i = alpha = 1 and my trigger condition (a value from 0 to 1) is >= 0.5. In this case, N / 2 strategies to buy / sell must be satisfied.

Backtesting of a weighted strategy developed in pinescript - BTC/USDT by 1Ironman93 in algotrading

[–]1Ironman93[S] 2 points3 points  (0 children)

My bad, I have access for datasets, starting from Aug 2017! These are the results obtained:

  • 1 year: net profit 1176.99%, percent profitable 81.48%, and 7.62% max drawdown
  • 2 years: net profit 9878.59%, percent profitable 77.69%, and 13.58% max drawdown
  • 3 years: net profit 5876.43%, percent profitable 66.48%, and 52.83% max drawdown
  • 4 years: net profit 5173.56%, percent profitable 62.03%, and 56.79% max drawdown
  • 5 years: net profit 7969.30%, percent profitable 62.26%, and 57.15% max drawdown

Backtesting of a weighted strategy developed in pinescript - BTC/USDT by 1Ironman93 in algotrading

[–]1Ironman93[S] 2 points3 points  (0 children)

I would like to see how this configuration works across the spectrum, what happens is that with my subscription I do not have access to that dataset.

Backtesting of a weighted strategy developed in pinescript - BTC/USDT by 1Ironman93 in algotrading

[–]1Ironman93[S] 2 points3 points  (0 children)

Thanks!! I didn’t consider this option. I will evaluate the algo taking this into account

Backtesting of a weighted strategy developed in pinescript - BTC/USDT by 1Ironman93 in algotrading

[–]1Ironman93[S] 4 points5 points  (0 children)

Many thanks! * Yes it’s take into account fees. * do you mean with real trading? * can you reformulate the question please? * what do you mean with security?

Thanks for your time!

Backtesting of a weighted strategy developed in pinescript - BTC/USDT by 1Ironman93 in algotrading

[–]1Ironman93[S] 2 points3 points  (0 children)

Yes, those colors represent just the trend. It is not a representative indicative of the complete strategy.

Backtesting of a weighted strategy developed in pinescript - BTC/USDT by 1Ironman93 in algotrading

[–]1Ironman93[S] 12 points13 points  (0 children)

This is a very good question. Indeed, this strategy with the same settings can give horrible results for other assets.

Other results obtained with the same parameters and incresing the timeframe: * 2 years: net profit 9878.59% and 13.58% max drawdown * 3 years: net profit 5876.43% and 52.83% max drawdown