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Dump it Here

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# Disclaimer - This is a theoretical investment exercise
In this exercise, we put "Google (AI) Gemini" head-to-head with seasoned fund manager Dr. Don Hamson from Plato Investment Management. Both were tasked with providing their "top five growth and income stocks" for the next 12 months on the ASX.

First Place - $6,010
# Google Gemini (AI) - RED line on the equity chart

Second Place - $2,400
# Dr. Don Hamson (Expert) - BLUE line on the equity chart

Third Place - $1,707
# Skate - BROWN line on the equity chart






Skate.
 
Hi Skate,
I also have a concentrated portfolio, even if I am mostly in cash for the moment. I recently entered into APA Group (last month) and ALX (this month), mostly for the current and growing dividend, as well as playing the coming reversal of the rate cycle, these two stocks being kind of bond proxies. I was just curious whether you looked at these two stocks and if you did what your analysis was (you might not as your 5 stocks are cyclical, but these 2 are defensive). Just fishing for analysis on my picks, whether aligned or contrarian, not promoting them at all.
Yann
 
welcome to ASF

a tip for the new members @Skate will get his attention earlier ( for most members ) that @ in front creates a hyperlink

i would normally debate APA and ALX as 'bond proxies ' in the current interest rate scenario , but REITs are a nightmare/minefield , so i won't go there until the economic climate changes

can those two stocks grow dividends if interest rates spike once again ? ( rates might start rising by year end or they may not )

cash ready and available is probably a wise choice , but so is a 'shopping list ' in case we have a 20% (plus ) retraction , they are fairly common , so be ready ( not panicking )


these are interesting times , and they may actually be different this time

good luck
 
Jan81 said:
Hi Skate,
(a) I recently entered into APA Group (last month) and ALX (this month), mostly for the current and growing dividend, as well as playing the coming reversal of the rate cycle, these two stocks being kind of bond proxies.
Click to expand...

@Jan8, a warm welcome to our community!

Thank you for sharing your first post in the "Dump it here" thread. Your investment strategy is founded on a robust logic, that I have "no doubt" will lead to a successful outcome for you.

For a bit of background, I've been a mechanical system trader since 2015. On the 11th of December 2023, I made a switch to investing even though it was a snap decision, I had been thinking about the switch for a while.

I'm currently running a "real 12-month experiment" with "real money on the line" to explore the feasibility of deriving a sustainable income from a portfolio of five investments, based on three key principles: (1) Dividends, (2) Franking Credits, and long-term (3) Capital Gains that you can follow if interested.


My reasoning for selecting these particular companies was straightforward. I wanted to invest in businesses that I understood and that had a strong presence in the Australian and New Zealand markets. ANZ and CBA are the two largest banks in their respective countries, and BHP and FMG are leaders in the mining industry. WDS was a bit of a wildcard, but I believe they offered significant value and have the potential for strong capital gains.

I based my investment decisions on three key principles
1. Dividends - I wanted to invest in companies that offer consistent and attractive dividends, providing me with a steady income stream.
2. Franking Credits - I looked for companies that offer franking credits, which can increase my overall returns.
3. Capital Gains - I also considered the potential for capital growth (secondary consideration), investing in companies with a strong track record of increasing their share price over time.

Skate.
 
Jan81 said:
I recently entered into APA Group (last month) and ALX (this month), mostly for the current and growing dividend,
Click to expand...

@Jan81, I wanted to follow up on my previous post and clarify that my decision to invest was a "snap decision" but I had been thinking about investing in these stocks for some time before that.

I purchased them on Monday, the 11th of December 2023, at the opening price. My primary concern was finding companies that had a consistent track record of paying dividends and offering franking credits, as these factors were crucial to my investment strategy. Capital gains were a "bonus".

I was looking to invest around $400k to $500k in each position, and I wanted to ensure that each investment wouldn't significantly impact the market price. I carefully evaluated several stocks that met my criteria and ultimately decided on the five stocks I mentioned previously.

Skate.
 
Jan81 said:
I was just curious whether you looked at these two stocks and if you did what your analysis
Click to expand...

@Jan81, I never considered the two companies you mentioned as I was more narrow-focused on my research. Below there are two-coloured charts of the two companies in question (APA and ALX).

The charts below are weekly charts that I use for timing. Reading the chart is as simple as it gets. Buy when the price bars are "AQUA" and don't buy when the price bars are "RED".

With investing the entry is less critical than trading. Trading is all about "timing the market", investing is all about the "time in the market"

Jan81 said:
I recently entered into (a) APA Group (last month) and (b) ALX (this month),
Click to expand...

(a) APA Group (last month)
Dividend yield 6.8% with "NO" franking credits




(b) ALX (this month)
Dividend yield 5.7% with "NO" franking credits



Skate.
 
another angle for you to consider for new investments is 'franking credits ( essentially pre-paid tax on your dividends , not very useful to some investors , but may benefit you )

also you could ask @DrBourse for his assessments of your stocks , he often posts a detailed guide to a stock's fundamentals when asked
 
I've done the same thing, might dabble here and there in a few swing trades but that's it. If I can beat bank term deposits I'll be ahead in any case.

Ended up with almost similar stocks, but my wild horse is BOQ.
NAB
ANZ
FMG

Hope it all goes well for you skate.
 


Not a great week
The objective of this 12-month real live experiment is to explore the feasibility of deriving a sustainable income from a portfolio of five investments, based on three key principles: (1) Dividends, (2) Franking Credits, and long-term (3) Capital Gains.

After 14 weeks of this experiment
# Dividends and Franking credits = $0.00
# Capital Gains = $6,223
# Weekly Average = $445






Skate.
 
Ahoy there, My dear Old Friend Skates on Ice

The Secret in Great Ship Design is to offer " NO DIVIDENDS"
How many of the US Magnificent Seven Pay a Meaningful dividend
I think META dished out its First Bunch of Carrots last month WOW!

If you saw one of my last posts a week or so ago
They were talking about some ETFs being designed with " No DIVIDENDS "
Crikey! I have doing it all my Like

I just sell a few shares now and again when I need some Ready
I don't need to wait for their miserly Handouts and then watch the shares fall

That IMHO Dividends is "The Greatest Scam on Earth"

Salute and Stay Well
 
Captain_Chaza said:
That IMHO Dividends is "The Greatest Scam on Earth"
Click to expand...

@Captain_Chaza, the whole point of this 12-month real-live experiment is to explore the feasibility of deriving a sustainable income from

(1) Dividends
(2) Franking Credits
(3) Capital Gains

Skate said:
Not a great week
Click to expand...

Admittedly, it has been a disappointing week but "market fluctuations" are normal, and short-term factors often influence weekly movements. It pays to remember, investing is typically for the long term, and it’s crucial not to make hasty decisions based on short-term market movements. It’s often the long-term trends that more significantly impact your portfolio’s performance.

Skate.
 


# Disclaimer - This is a theoretical investment exercise
In this exercise, we put "Google (AI) Gemini" head-to-head with seasoned fund manager Dr. Don Hamson from Plato Investment Management. Both were tasked with providing their "top five growth and income stocks" for the next 12 months on the ASX.

First Place - $5,375
# Google Gemini (AI) - RED line on the equity chart

Second Place - $2,334
# Dr. Don Hamson (Expert) - BLUE line on the equity chart

Third Place - ( -$2,539 )
# Skate - BROWN line on the equity chart






Skate.
 
peter2 said:
My weekly XAO up count is only 35%, so that's a caution for next week. Yes, I'm using my version of the @Skate weekly up count indicator.
Click to expand...

@peter2 referenced my 'percentage up' filter which is the catalysis for the next series of posts. While our results may differ due to the methodology of our calculations, the 'percentage up' buy filter is a useful tool for identifying potential buying opportunities in a bullish market. If the average percentage change is greater than the threshold, the filter generates a buy signal.

The 'percentage up' filter calculates the percentage change of stocks in a watchlist over a specified period and then applies a threshold to determine whether the overall market sentiment is bullish or bearish. If the average percentage change is less than or equal to the threshold, the filter generates a buy signal.

The advantages of using a 'percentage up" buy filter include:
1. It helps identify potential buying opportunities in a bullish market.
2. It provides a clear and objective way to determine market sentiment.
3. It can be customised to suit individual trading strategies and risk tolerance.
4. It can be applied to a wide range of markets and time frames.

Overall, the 'percentage up' calculates the percentage of bullish stocks in a watchlist that also provides a visual representation of the market sentiment using a 'percentage up' ribbon. The clever feature of this buy filter is that the bullish and bearish thresholds can be adjusted to customise the filter's sensitivity to market conditions. As an example, I've recently increased the buy threshold to 56%.



Skate.
 
More technical information
The 'percentage up' buy filter is a straightforward concept, but its construction requires an explanation. I decided to create this filter to establish a more intelligent way of determining whether to take a position based on the current market sentiment.

I must emphasise that, in my opinion, Artificial Intelligence (AI) lacks the proficiency to code in Amibroker AFL and cannot develop a profitable trading strategy. The reason for this is that (AI) tends to fabricate responses on the go, prioritising expediency over accuracy. As a result, the accuracy of the code is not a primary concern for (AI).

Skate.
 
Evaluation and analytics are a different matter for (AI)
To better understand the 'percentage up' buy timing filter, I ask (AI) to explain it to an interested person. For instance, what specific criteria does the 'percentage up' filter use to determine whether a stock is a buy, and how does it factor in market sentiment?

Initialization of (AI) response
The 'percentage up' code starts with the _SECTION_BEGIN("Percentage Mode Parameters") directive, which defines the beginning of a section for the filter. It also initializes variables such as wlnum, List, Up, Total, and NoM.

Loop for Percentage Calculation
The code checks if it is the first iteration of the loop using the Status("stocknum") == 0 condition. It then enters a loop to calculate the percentage change for each symbol in the watchlist.

Procedures
It retrieves the symbols in the watchlist using CategoryGetSymbols(categoryWatchlist, wlnum).
For each symbol, it sets the symbol as the foreign symbol using SetForeign(symbol, 0).
It calculates the number of bars where the close price is greater than the open price using Up += Nz(Close / Open > 1).
It counts the number of valid bars for the symbol using NoM += NOT IsNull(C).
It restores the price arrays for the symbol using RestorePriceArrays().
The loop saves the calculated values of Up and NoM in static variables using StaticVarSet() for future use.

Retrieving Stored Values
After the loop ends, the code retrieves the stored values of Up and NoM using StaticVarGet() and assigns them back to the respective variables.

Percentage Calculation
The code calculates the percentage of bullish stocks in the watchlist using the formula: PercentWatchlistUp = round(100 * (Up / NoM)).

Threshold Parameters
The code defines two threshold parameters using the Param() function:

Bullish Threshold
This represents the minimum percentage required for the market sentiment to be considered bullish. The default value is 56%, and it can be adjusted between 0 and 100%.

Bearish Threshold
This represents the maximum percentage allowed for the market sentiment to be considered bearish. The default value is 25%, and it can be adjusted between 0 and 100%.

Bullish and Bearish Conditions
The 'percentage up' code sets two conditions based on the calculated percentage:

Percentage Bullish
This evaluates to true if the PercentWatchlistUp is greater than the BullishThreshold.

Percentage Bearish
This evaluates to true if the PercentWatchlistUp is less than the BearishThreshold.

Percentage Up Ribbon Plotting
If there is an additional condition PercentageUpFilter (not shown in the provided code snippet), the code plots a ribbon using the Plot() function. The ribbon color (RibbonColor) is determined based on the PercentageBullish condition. If it is true, the color is set to colorGreen; otherwise, it is set to colorRed.

Section End
The code ends the section using the _SECTION_END() directive.

Overall, this AFL code calculates the percentage of bullish stocks in a watchlist and provides a visual representation of the market sentiment using a buy timing filter and a corresponding visual lower ribbon. The bullish and bearish thresholds can be adjusted to customize the filter's sensitivity to market conditions.

Skate.
 
Captain_Chaza said:
I don't need to wait for their miserly Handouts and then watch the shares fall. That IMHO Dividends is "The Greatest Scam on Earth"
Click to expand...

Trading versus my investment experiment
I must admit, I miss the thrill of trading. Trading is like being in the driver's seat, constantly making decisions and adjusting my strategy to maximise my returns. With trading, I have more control over my actions and can react quickly to market movements.

However, I've found that trading also comes with its own set of challenges. For instance, I've struggled to get decent dollar value into individual companies without creating slippage. It's like trying to get a drop of water into a glass that's already full - it's difficult to make a significant impact.

On the other hand, investing in blue chip stocks or the top 20 companies has been a much smoother experience. There's less drama and volatility, and the returns are more predictable. Plus, I don't have to constantly monitor the market to make trades.

Trading is a more lucrative option for me
With my investment experiment, I'm only receiving two dividend payments a year, and one corresponding franking credit from the ATO. It's like waiting for a bus that's running on a fixed schedule - I know it'll arrive eventually, but I have to be patient.

In contrast, trading allows me to be more active and flexible. I can make trades whenever I want, and adjust my strategy to take advantage of market fluctuations. It's like driving a car with a manual transmission - I have more control over the vehicle and can shift gears to suit my needs.

Skate.
 
I'm now wondering
I'm now curious about how my trading strategy would have performed since the beginning of the year. While I could conduct a backtest and analyse the results, that would only provide a rough indication. My trading systems are designed to ensure that the value of each investment is never exceeded when buying a position at the opening price. However, the backtest and actual results can differ significantly depending on the method used. Therefore, I'll need to carefully evaluate the performance of my strategy using both backtesting and real-world data to gain a comprehensive understanding of its effectiveness.

A quick peek at the backtest results
The backtest results aren't too shabby for 15 trades

Statistics
All trades
Initial capital100,000
Ending capital117,000.74
Net Profit17,000.74
Net Profit %17.00%
Exposure %56.13%
Net Risk-Adjusted Return %30.29%
Annual Return %119.25%
Risk-Adjusted Return %212.47%
Transaction costs479.7
All trades15
Avg. Profit/Loss1133.38
Avg. Profit/Loss %11.35%
Avg. Bars Held5.6
Winners12 (80.00 %)
Total Profit19,616.78
Avg. Profit1,634.73
Avg. Profit %16.37%
Avg. Bars Held5.67
Max. Consecutive7
Largest win7209.12
# bars in largest win5
Losers3 (20.00 %)
Total Loss-2,616.04
Avg. Loss-872.01
Avg. Loss %-8.72%
Avg. Bars Held5.33
Max. Consecutive1
Largest loss-1,931.97
# bars in the largest loss4
Max. trade drawdown-1,931.97
Max. trade % drawdown-19.29
Max. system drawdown-1,341.23
Max. system % drawdown-1.30%
Recovery Factor12.68
CAR/MaxDD91.76
RAR/MaxDD163.49
Profit Factor7.5
Payoff Ratio1.87
Standard Error3339.01
Risk-Reward Ratio31.55
Ulcer Index0.38
Ulcer Performance Index303.47
Sharpe Ratio of trades1.83
K-Ratio0.52
Profit Take Trades1
Avg. Take Profit P&L1,441.82
% Avg. Take Profit P&L14.42%
Trailing Stop Trades2
Avg. Trailing Stop P&L-90.28
% Avg. Trailing Stop P&L-0.90%
Stale Stop Trades2
Avg. Stale Stop P&L67.56
% Avg. Stale Stop P&L0.68%
P&L for Closed Trades17,000.74
Number of Closed Trades5
Standard Deviation of Closed Trades3,460.8
Number of Open Positions10
Capital in Open Positions10,9903
Expectancy ($)1,133.38
Expectancy (per $100 inv.)4.73

Skate.
 
An English explanation of the backtest statistics from (AI)
The initial capital was $100,000, and the ending capital was $117,000.74, resulting in a net profit of $17,000.74. This represents a net profit percentage of 17.00%. The exposure percentage is calculated to be 56.13%, indicating the portion of the capital that was at risk during the trades.

The net risk-adjusted return percentage is 30.29%, which takes into account the level of risk involved in the trades. The annual return percentage is quite impressive but misleading at 119.25%, suggesting a high return on investment over a year but in reality, it was only a small sample of 15 trades.

Out of the 15 trades, 12 were winners, accounting for 80.00% of the total trades and very high for this style of trading. The total profit from the winning trades was $19,616.78, with an average profit of $1,634.73 per winning trade of a total investment of $10k per trade. The average profit percentage for the winners was 16.37%. There were 3 losing trades, representing 20.00% of the total trades. The total loss from these trades was -$2,616.04, with an average loss of -$872.01 per losing trade. The average loss percentage for the losers was -8.72%.

The largest win recorded during the trades was $7,209.12, achieved in 5 bars. The largest loss was -$1,931.97, occurring over 4 bars. The maximum trade drawdown was -$1,931.97, and the maximum trade percentage drawdown was -19.29%. The maximum system drawdown, representing the largest overall capital decrease, was -$1,341.23, with a maximum system percentage drawdown of -1.30%.

Additionally, there was one profit-take trade, with an average take profit P&L of $1,441.82 and a percentage of average take profit P&L of 14.42%. There were 2 trailing stop trades with an average trailing stop P&L of -$90.28 and a percentage of average trailing stop P&L of -0.90%.

Lastly, there were 10 open positions at the end of the trades, with a capital of $109,903. The expectancy, calculated as the average profit per trade, is $1,133.38, or $4.73 per $100 investment.

Overall, the trades resulted in a net profit of $17,000.74, with a solid net profit percentage of 17.00%. The annual return percentage of 119.25% and risk-adjusted return percentage of 212.47% indicate a highly profitable trading strategy.

Footnote
To conduct a more accurate result I would need to calculate the number of shares purchased at the opening price. An exercise I'm trying to avoid.

Skate.
 
For those interested in the trading performance and signals of this strategy
The trade signals for the period spanning from January 1st, 2024, to March 15th, 2024, are shown below. @peter2 may be particularly interested in these positions and the corresponding trade results, which demonstrate the effectiveness of system trading in generating profits. In my opinion, this approach has proven to be reliable and successful for me.





Skate.
 
Hi Skate I have had this indicator programmed, in several different variations, as close as possible to your many explanations. But there is lot of ambiguity in how its calculated and even though on surface it sounds simple it really is not. Two questions, 1: What lookback period are you using for the bars to calculate the combined market to get the average % ? 2: you are using weekly bars for the strategy, but are you using daily bars to calculate the % of bullish bars, within the weekly bar or weekly bars ? FYI there is a chance that something has been misunderstood by me, but I have not been able to program this indicator and see any positive use as a filter in the US markets, i do know you only trade Australia, but would be interesting if anyone else is actually able to replicate this indicator. Have anyone ? I have spent a considerable amount of money having very reputable afl developers to do it trying to interpret your posts here, but result have been not promising. But somehow you seem to have it working for you and thats great.
 
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