Dump it Here

[Skate]

Surely the whole point of a technical approach is exactly that: 'timing'.

Market Timing
This signal aspect, “market timing,” is one of the elements that affect profitability, which can be improved by including the “PercentageUp Buy Filter” as an indicator of a buy condition. As the “PercentageUp Buy Filter” represents the percentage increase in the market, this indicator essentially identifies whether the market is bullish or bearish.

The “PercentageUp Buy Filter”
This filter allows buy signals to be generated when the advancing constituents of the XAO index are above 56%, which denotes a bullish market. Conversely, the method will time the exits of existing positions when the filter falls below 25%, indicating a bearish market. The “PercentageUp Filter” is a useful tool that enables the strategy to adapt to shifting market conditions.

@ducati916 quote nails it. With trading, it’s all about timing, and this is where a “buy timing filter” is one such method that indicates the optimal time when signals can be produced.

Skate.

 

[Skate]

Hi, I've seen some discussion on the value of AI. I put a question into chatgpt and this is the code generated. I just thought it was an interesting exercise, as I had seen ChatGPT being discussed in another thread.

https://www.aussiestockforums.com/threads/dump-it-here.34425/post-1221944

ChatGPT Experiment
@CNHTractor made a post asking ChatGPT to reproduce the Amibroker code to replicate the “PercentageUp Buy Filter.”

I’m Impressed
I had previously made a series of posts about the idea of incorporating a “PercentageUp Buy Filter” into a buy condition. I’m impressed that ChatGPT was able to code my idea of a “Buy Filter.” That said, ChatGPT does make a lot of mistakes when coding in AFL and doesn’t grasp array processing all that well. However, it is improving over time.

ChatGPT reproduce some code
The code produced by ChatGPT does almost the same job as my “PercentageUp” buy filter. To be fair, ChatGPT did calculate and plot the percentage of stocks that closed higher than they opened. However, ChatGPT didn’t include the extra check on the overall market index, and it uses a “user-defined filter” value instead of fixed thresholds.

In My Humble Opinion
You would need to add these missing parts to the ChatGPT-generated code to make the "buy timing filter" efficient and effective. Otherwise, the code that ChatGPT produced should work for calculating and plotting only the percentage of up days, which would be limited in achieving the desired results of a true buy filter.

Skate.

 

[Skate]

Simple trading strategy testers are very misleading, and causes novices to have a false sense of security that are doing systematic trading. This appears to be one of them. It's missing really quite crucial systematic trading/backtesting capabilities.

@Richard Dale if I gave you a strategy would you Backtest it and do a forum post with your unbiased results

Now that would be super interesting/helpful to see!
A comparison of biased vs Richards unbiased.

@Richard Dale, I appreciate your detailed explanation of systematic trading. While I’m disappointed by your response, I understand your reasons and respect your perspective. I’ll continue developing a more comprehensive understanding of systematic trading.

Over the years, I’ve been fortunate to use this thread to share my knowledge which has significantly aided in my trading. By suggesting new ways of thinking about the markets, I’ve posted numerous ideas and concepts, even if they haven’t always been perfect. For those who crave basic ideas to kickstart their trading journey, this thread serves as a starting point.

The danger, in my opinion, is if a new trader thinks that it's easy to develop a system like this that works consistently in all market conditions, then they may get themselves into trouble.

I offered @Richard Dale one of my TradingView strategies to have it backtested correctly. While I understand and appreciate his reluctance, I believe there is still value in sharing ongoing results.

The strategy in question started paper trading on the 1st of July 2024, to coincide with the beginning of the new financial year. Unfortunately, July and early August haven’t been favourable for the strategy.

Skate.

 

[Skate]

Skate.

 

[DaveTrade]

View attachment 182464

Skate.

Quote of the Day

“The elements of a good trader are:​

(1), (2) and (3) being able to cut losses.

If you can follow these three rules, you are better than most.”​

 

[Skate]

Skate.

 

[shivahit]

I get all the positivity about cutting losses, but isn't profit also a part of a good trader? A much important part?

 

[shivahit]

View attachment 182540

Skate.

Isn't it stake?
Edit: I didn't realise it was your name Skate, I thought you wanted to say the quote was about the stakes. And also I don't know why I didn't see this before posting the above post

 

[Skate]

I get all the positivity about cutting losses, but isn't profit also a part of a good trader? A much important part?

@shivahit, you’re right. While cutting losses is crucial to protect your capital and manage risk, making profits is indeed a fundamental goal for any trader. A good trading strategy balances both aspects of minimising losses and maximising gains. A successful trader finds the right balance between the two.

Skate.

 

[LeFeek]

I get all the positivity about cutting losses, but isn't profit also a part of a good trader? A much important part?

Profit is indeed a crucial part of being a good trader. Cutting losses is important, but it's equally important to know when to hold and nurture profitable trades.

 

[Skate]

Skate.

 

[Skate]

Skate.

 

[Skate]

Explanation
This is a theoretical investment exercise comparing the stock selections of expert fund manager Dr. Don Hamson and Google (AI) Gemini. Both have provided their top 5 growth and income stocks for the ASX over the next 12 months.

Results after 30 weeks
1st Place $7,303: Google Gemini (AI) - RED line on the equity chart (5 winning positions)
2nd Place $5,2760: Dr. Don Hamson (Expert) - BLUE line on the equity chart (3 winning positions)






Skate.

 

[TimeISmoney]

Holyheck, this pick is the power house.

 

[Skate]

Explanation
This is a theoretical investment exercise comparing the stock selections of expert fund manager Dr. Don Hamson and Google (AI) Gemini. Both have provided their top 5 growth and income stocks for the ASX over the next 12 months.

Results after 31 weeks
1st Place $6,425: Google Gemini (AI) - RED line on the equity chart (4 winning positions)
2nd Place $4,765: Dr. Don Hamson (Expert) - BLUE line on the equity chart (3 winning positions)






Skate.

 

[frugal.rock]

I'm gunning for the Doc.

AI can go shove it's stupid head up it's coders backside

 

[Richard Dale]

LLMs are as presented are non-repeatable.

This is a meaningless set of testing. Despite the interesting metrics/graphics presented, this has no statiscal signifiance.

Good luck attributing any sort of trading strategy intelligence to LLMs.

Back to simian darts again it appears, Skate.

But it's quite entertaining as to your failures in methodology.

 

[Skate]

LLMs are as presented are non-repeatable.
This is a meaningless set of testing. Despite the interesting metrics/graphics presented, this has no statiscal signifiance?
Good luck attributing any sort of trading strategy intelligence to LLMs.
Back to simian darts again it appears, Skate.
But it's quite entertaining as to your failures in methodology.

@Richard Dale, thank you for your input. It’s always valuable to have diverse perspectives, even if we don’t always agree.

The article by Chris Conway of Livewire Markets, which inspired this exercise, highlights the evolving capabilities of (AI) in stock picking. As (AI) technology continues to improve, it will be interesting to see how it compares to humans in the field of finance.

The exercise comparing Dr. Don Hamson’s stock selections with Google Gemini (AI) is theoretical and meant to spark discussion and interest. While you may find the methodology lacking in “statistical significance,” it’s important to note that this experiment is ongoing. The aim is to observe and learn from the results over 12 months rather than draw immediate conclusions.

For those interested in following the progress of this experiment, here are the links to the relevant articles:

#1. Fundie vs AI: Who is the better “Income” stock picker? - You can view that wire below:

Fundie vs AI: Who is the better stock picker? (and 10 ASX stock ideas for your trouble)

AI is getting better, faster, & stronger. Will it ever be able to pick stocks like a human? We take a step towards answering that question.

www.livewiremarkets.com

#2. Fundie vs AI: Who is the better “Growth” stock picker? - You can view that wire below:

Fundie vs AI: The best ASX growth stocks for the next 12 months

We've seen the income stocks, now we're looking at growth stocks in this edition of "Fundie vs AI: Who is the better stock picker?"

www.livewiremarkets.com

Skate.

 

[Skate]

The article by Chris Conway of Livewire Markets, which inspired this exercise, highlights the evolving capabilities of (AI) in stock picking. As (AI) technology continues to improve, it will be interesting to see how it compares to humans in the field of finance.

Explanation - Fundie vs AI: The best ASX "Growth" stocks for the next 12 months
This is a theoretical investment exercise pitting Google's (AI) Gemini against Tobias Yao from Wilson Asset Management in selecting five "Growth" stocks for the next 12 months.

Fundie vs AI: The best ASX growth stocks for the next 12 months

We've seen the income stocks, now we're looking at growth stocks in this edition of "Fundie vs AI: Who is the better stock picker?"

www.livewiremarkets.com

Results after 31 weeks
We recognise that this is nothing more than a fun, but nonetheless important, thought experiment. Ultimately, (AI) will likely become a tool that all use to make more informed decisions, across a broad range of topics.



Skate.

 

[TimeISmoney]