Dump it Here

[ducati916]

Apropos of nothing, I just want to say that here in Aust we have by far the worst trading products and services in the developed world. And highest brokerage.
Very strange that no one has taken up the opportunity to provide a decent, fully featured brokerage + platform here.

IB is really the only option but I don't like it for various reasons.

I agree.

It also tremendously limits the strategies, opportunities, liquidity, leverage and risk management that can be employed.

To date, it would be impossible for me to trade in the way that I do in Australia or NZ. Because of that I shifted to the US 23yrs ago when I started trading.

The time zone can be an issue for some, but with the level of automation on platforms, it's really not an issue.

Mr Skate had some issues with liquidity for $20K positions. SPY trades an average of 100 million shares/day. More importantly, the volume in the Options market is high. Of course if you want futures, no issues.

Wasn't TastyTrade on its way to Aus. at some point? Actually here it is: https://www.tastyworks.com.au/
I hadn't realised it had finally made it over. Now that I found it, I'll switch my account over. Their platforms are pretty damn good.

Of course probably only of any use if you want to trade the US.

jog on
duc

 

[Gringotts Bank]

I agree.

It also tremendously limits the strategies, opportunities, liquidity, leverage and risk management that can be employed.

To date, it would be impossible for me to trade in the way that I do in Australia or NZ. Because of that I shifted to the US 23yrs ago when I started trading.

The time zone can be an issue for some, but with the level of automation on platforms, it's really not an issue.

Mr Skate had some issues with liquidity for $20K positions. SPY trades an average of 100 million shares/day. More importantly, the volume in the Options market is high. Of course if you want futures, no issues.

Wasn't TastyTrade on its way to Aus. at some point? Actually here it is: https://www.tastyworks.com.au/
I hadn't realised it had finally made it over. Now that I found it, I'll switch my account over. Their platforms are pretty damn good.

Of course probably only of any use if you want to trade the US.

jog on
duc

I was looking at Tasty only a few days ago. Something put me off, but I can't remember now what it was. I think because it wasn't integrated with TV. $1.50 one-way for futures is pretty good though.

 

[wasp]

Afternoon all. I struggle to effectively navigate the interactive brokers "help" pages, I thought I might have more luck asking here. Does anyone know- let's say I have an account balance of $10,000. I then sell short $8,000 of stock XYZ. Is my buying power (ie, my capacity to go long) now $18,000? Or is it $2,000? Or something else?

 

[Skate]

Afternoon all. I struggle to effectively navigate the interactive brokers "help" pages, I thought I might have more luck asking here. Does anyone know- let's say I have an account balance of $10,000. I then sell short $8,000 of stock XYZ. Is my buying power (ie, my capacity to go long) now $18,000? Or is it $2,000? Or something else?

Short Summary
Without more information about your account and the margin requirements for the stock you are trading, it's difficult to provide an exact answer. However, in general, shorting a stock will "reduce your buying power" since you have already used a portion of your account balance to open the short position.

Your buying power after shorting $8,000 of stock XYZ will depend on the margin requirements of your broker and the specific stock you are trading. When you short a stock, you are essentially borrowing shares from your broker to sell them on the market, with the expectation of buying them back at a lower price to make a profit.

Interactive Brokers calculates buying power using a complex algorithm that takes into account various factors, including the margin requirements of the exchange where the stock is listed, the volatility of the stock, and your account's margin settings and equity. In general, shorting a stock will "reduce your buying power" since you have already used a portion of your account balance to open the short position.

Suggestion
To get a more accurate estimate of your buying power after shorting $8,000 of stock XYZ, you can check the margin requirements for that stock on Interactive Brokers' website or trading platform, and use their margin calculator tool to determine the impact on your buying power. Additionally, you can contact Interactive Brokers' customer support for assistance in calculating your buying power after opening a short position.

Assuming that the margin requirement for the stock is 50%, meaning that you are required to maintain at least 50% of the value of the short position in your account, your buying power would be reduced by $4,000 ($8,000 x 50%), leaving you with $6,000 in buying power ($10,000 - $4,000). This means that you would be able to go long up to $6,000 worth of stocks or other securities.

Again
It's important to note that the actual impact on your buying power may vary depending on your broker's margin requirements and the specific stock you are trading. I would recommend checking with your broker or using their margin calculator tool to get a more precise estimate of your buying power after opening a short position.

Skate.

 

[wasp]

Short Summary
Without more information about your account and the margin requirements for the stock you are trading, it's difficult to provide an exact answer. However, in general, shorting a stock will "reduce your buying power" since you have already used a portion of your account balance to open the short position.

Your buying power after shorting $8,000 of stock XYZ will depend on the margin requirements of your broker and the specific stock you are trading. When you short a stock, you are essentially borrowing shares from your broker to sell them on the market, with the expectation of buying them back at a lower price to make a profit.

Interactive Brokers calculates buying power using a complex algorithm that takes into account various factors, including the margin requirements of the exchange where the stock is listed, the volatility of the stock, and your account's margin settings and equity. In general, shorting a stock will "reduce your buying power" since you have already used a portion of your account balance to open the short position.

Suggestion
To get a more accurate estimate of your buying power after shorting $8,000 of stock XYZ, you can check the margin requirements for that stock on Interactive Brokers' website or trading platform, and use their margin calculator tool to determine the impact on your buying power. Additionally, you can contact Interactive Brokers' customer support for assistance in calculating your buying power after opening a short position.

Assuming that the margin requirement for the stock is 50%, meaning that you are required to maintain at least 50% of the value of the short position in your account, your buying power would be reduced by $4,000 ($8,000 x 50%), leaving you with $6,000 in buying power ($10,000 - $4,000). This means that you would be able to go long up to $6,000 worth of stocks or other securities.

Again
It's important to note that the actual impact on your buying power may vary depending on your broker's margin requirements and the specific stock you are trading. I would recommend checking with your broker or using their margin calculator tool to get a more precise estimate of your buying power after opening a short position.

Skate.

Thanks Skate! Your reply was super quick and helpful

 

[Skate]

I had an unusual conversation yesterday - I was asked three questions.
(1) Why do you concentrate on beginners?
(2) Why do you trade complicated trading systems when everyone knows they need to be simple?
(3) Can you tell me something about backtesting that I may not know?

The three questions provided a useful opportunity to clarify my perspectives on trading strategies. So the post isn't one lengthy read, I'll post my response to the questions in three individual posts.

(1) Why are my posts slighted towards beginners?
There are a few good reasons for this. First, beginners are more open-minded and receptive to new ideas. Those just starting out in trading are still forming their trading styles and strategies. They have yet to develop many hard and fast rules or become set in their ways. This makes them like "sponges" who soak up useful information and advice.

Seasoned traders, on the other hand, tend to be more set in their approach. After years of trading, they have developed strategies and systems that have worked for them in the past. They may be less willing to consider alternative perspectives or new trading ideas. While experience is valuable, it can also breed a false sense of confidence and an unwillingness to adapt.

Second, beginners make the most progress early on. Those just getting started in trading have the most to gain from good advice. Implementing good trading strategies and risk management from the beginning sets them up for future success. Seasoned traders, however, may have already ingrained habits that are harder to change.

Finally, as someone still learning and improving my own trading skills, I prefer to think of myself as a beginner. I try to post my experiences and trading ideas from that perspective, sharing what has helped me along the way. My aim is to give others something useful to consider, not assert that my way is the "right" way to trade. I always welcome alternate viewpoints to help expand my own knowledge.

In summary, my focus is on beginners not because their questions are easier to answer, but because they stand to benefit the most from useful advice at this phase. Their open minds and lack of ingrained habits make them primed for learning. While all traders can benefit from reading new trading ideas or simply new perspectives on old ideas, those just starting out are in the best position to implement changes that will impact their long-term success.

Skate.

 

[Skate]

(2) Why do you trade complicated trading systems when everyone knows they need to be simple?

(2) Regarding backtesting and "complicated" trading systems
It's true that most successful trading systems tend to be relatively simple and straightforward. Overly complex strategies can be difficult to implement consistently and profitably in real-time. I realised an explanation could benefit others giving me an opportunity to clarify my perspective on trading strategies.

However, complexity in backtesting does not necessarily translate to complexity in live trading but you need to get to this starting point. I believe rigorous backtesting involves simulating a wide range of possible indicators, filters, and conditions to start off the process.

An "optimized" system may seem complicated on paper but there is a purpose of testing many alternatives, including "overoptimized" strategies, is to discover the key success factors that drive performance. Backtesting is invaluable for exploring different possibilities before implementing it live. But while live trading demands simplicity, rigorous backtesting justifies some complexity.

The aim of testing various iterations is to discover what really drives performance, the one or two factors most correlated with profits. Then in live trading, you can pare down to a simple system that capitalises on these key success factors.This approach through backtesting many possibilities helps hone in on the simplest, most robust system for live trading. The optimized system on paper serves as a guide to refining a basic approach you can reliably follow over the long term.

So in summary, while I advocate for keeping live trading systems relatively simple, I do not see an issue with testing more complex strategies in backtesting. The goal is to discover what really matters through a rigorous process, then distill that knowledge into the most essential, easy-to-follow system for the realities of live trading.

Skate.

 

[Skate]

(3) Can you tell me something about backtesting that I may not know?

(3) Sure, you may not know about "edge case errors" when backtesting a refined strategy
Edge case errors are one area of backtesting that is normally overlooked. Missing this important step can cause grief down the track when live trading and the strategy fails to work as intended due to unusual or unexpected market conditions.

Backtesting the normal way has a few hidden flaws as they only test "normal" market scenarios, but not extreme or abnormal events as outlier data points. These outlier data points are the points not explicitly tested. Edge case errors often only reveal themselves "in the wild" when a strategy is live-traded with real market data, not just backtested data.

Once a strategy has gone through all the standard backtesting procedures consider one additional backtest step and backtest the strategy with extreme or abnormal scenarios that might occur in real markets. To identify and fix edge case issues explicitly test the strategy's logic with outlier data points. For example, data with very small/large indicator values, periods of high/low volatility, and data that have sudden spikes/drops in price or volume.

Edge case handling involves anticipating and testing unexpected scenarios that occur at the "edges" of normal usage. Good edge case handling makes your system more reliable and robust by anticipating and gracefully handling unpredictable scenarios that fall outside typical usage. However, you can never anticipate all edge cases, so your system still needs to be resilient to the unexpected.

In summary, by combining multiple indicators and filters from different approaches, and applying an "edge case" level of backtesting to the SAP Strategy "should" provide robust, lower-risk signals with multiple confirmations. The use of volatility, market sentiment, and risk metrics helps strengthen the signal.

Skate.

 

[Skate]

(2) Why do you trade complicated trading systems?

I'm the first to put up my hand when complex systems are mentioned
Simplicity sometimes doesn't equate to safety. When developing a trading strategy I do have my pet indicators, filters, and parameter that have been tested over many years but there are a few general hints I can pass on. Overall, I think that a balance between complexity and simplicity is key and that a deep understanding of the underlying principles driving the system is crucial for successful trading.

# Refining Your Trading Strategy
As traders progress beyond the beginner stage, focusing on refining their trading strategy becomes increasingly important. With experience comes a better understanding of what works and what doesn't, allowing traders to extract more value from their strategies.

# Identify Redundancies and Inefficiencies
Review your existing strategy and carefully analyse each section of code. Look for, (a) Duplicate or redundant calculations (b) Unused or unreferenced variables (c) Inefficient or convoluted logic. Eliminating redundancies can speed up your backtesting and improve the clarity of the strategy.

# Organize Your Code into Logical Sections
Most beginners tend to code in one lengthy block. Organizing your code into logical sections, each with a meaningful name to make it much easier to read, modify and optimize parts of the strategy in isolation. Well-organized sections also make it easier to reuse parts of your code in new strategies.

# Improve Your Variable Names
Meaningful variable names are important for readability and maintenance. Rename variables to properly reflect their purpose, using names that are, concise, consistent, and descriptive.

# Add Comments Where Helpful
Comments above important sections of code can help explain the purpose and logic. However, avoid trivial one-line comments. Use comments judiciously to add the most value.

# Combine Multiple Signals into a Composite
Instead of having separate buy signals from different indicators, combine them into a single composite buy signal. This reduces the number of false signals and strengthens your overall entry conditions.

# Introduce Filters to Reduce Noise
Adding price, volume, and volatility filters as parameters can help filter out false signals and reduce noise, particularly for trend trading strategies. Using the "Param Feature" in Amibroker allows testing various filter combinations to find an optimal balance of signals and noise without code alteration. Making an "apx file" for each improvement maintains a reference rather than keeping all this information on paper or in your head. If you don't everything tends to muddle over time.

# Backtest Individual Sections in Isolation
By backtesting each section of your strategy separately, you can identify areas for improvement and optimize individual parts before combining them again.

# Look for Edge Case Issues
Test your strategy with extreme data points and unusual market conditions to identify any edge case errors. Handling these edge cases helps to improve reliability.

# Reward Yourself for Improvements
To stay motivated, set goals for yourself and reward your progress. Even marginal improvements, when compounded over time, can make a big difference to your results.

Ultimately, by thinking critically about your existing trading strategy and applying some of these suggestions, you can fine-tune your code into a more robust and effective system, one that generates better risk-adjusted returns over time.

Skate.

 

[Gringotts Bank]

There's a fine line there between curve fitting and tweaking/refining a system. Or perhaps a blurry line.

Early on in my thread, I didn't just tweak, but made wholesale changes. The discretionary rules have been pretty much set for the last 3 months, though I did add a cumulative volume delta indicator, which is helpful. If my rules started to fail from this point forward, I'm not sure I'd tweak anything. I'd be more inclined to give the whole thing away.

 

[DaveTrade]

There's a fine line there between curve fitting and tweaking/refining a system. Or perhaps a blurry line.

My take on 'curve fitting' is adjusting a system to produce the best results from a specific data set. My take on 'refining a system' is continuing to plug holes in the bucket so it can reduce risk in more varying situations and thereby allow more profits to come.

 

[Skate]

My take on 'refining a system' is continuing to plug holes in the bucket so it can reduce risk in more varying situations and thereby allow more profits to come.

@DaveTrade, I understand your point that continually refining a system allows it to capture more profits. Focusing on refining a trading strategy becomes increasingly important when holes are found. However, I think there are a couple of important aspects to consider when building and optimizing a trading strategy.

While adding complexity through more indicators and filters can help a system adapt to changing markets, there is also a risk of overfitting with unintended consequences as I mentioned earlier today. Therefore, keeping a strategy as simple and transparent as possible is often a good starting point. Complexity should then be added judiciously and with a critical eye.

In the end, striking a balance between simplicity and complexity, as @Gringotts Bank explains requires a deep understanding of the underlying market principles or it just blurs the line between curve fitting and system refinement. Careful consideration of risks and benefits is the key to developing a robust trading strategy that can perform well over the long term. Adding complexity for its own sake, tends to lead to suboptimal results.

Skate.

 

[Gringotts Bank]

My take on 'curve fitting' is adjusting a system to produce the best results from a specific data set. My take on 'refining a system' is continuing to plug holes in the bucket so it can reduce risk in more varying situations and thereby allow more profits to come.

What would be some examples of 'hole plugging'?

My view is that any changes made after the system's start date will constitute curve fitting (unless the change is something that has no effect on the equity curve). Walk-forward testing shows how impactful it is to tweak even one parameter a tiny amount. It's very difficult to create a system that survives a WF test. Difficult for me - I assume also difficult for others but that might not be the case.

 

[Skate]

What would be some examples of 'hole plugging'?

@Gringotts Bank I realise that question was directed towards @DaveTrade but in terms of 'hole plugging' for a trading system, I would like to make a few comments.

In making ongoing refinements to a trading strategy, there is a multitude of possible improvements aimed at reducing risk in varied market conditions, capturing more profits, and improving the strategy's robustness and longevity. While one member reads "fine-tuning" others believe it is nothing more than curve-fitting.

Collectively the few items below represent a 'hole plugging' approach to system development.

# Improving risk management
Adding new stop-loss rules or modifying a take-profit stop, and optimising position sizing, can all help manage drawdowns better. This allows the strategy to survive larger market corrections and volatile periods.

# Adding an additional buy conditional filters
Doing so can avoid trading during unfavourable times or simply implement special rules to improve robustness.

# Fixing specific weaknesses
If the strategy consistently loses money in certain market conditions, instrument types, or time periods, tweaking the indicators, filters, or entry/exit logic for just those scenarios can help shore up those weaknesses.

# Adding confirmations
Adding secondary indicators or checks as "extra requirements" before entering a trade can reduce false signals and filter out risky setups.

All of these "hole plugging" examples still run the risk of overfitting, as you noted. Walk-forward testing is crucial to assessing if any changes genuinely improve the strategy's robustness, or are just fitting historical results. In general, I think simple approaches that emphasise sound market principles tend to survive walk-forward tests better than overly complex systems optimised for backtest performance.

Skate.

 

[DaveTrade]

What would be some examples of 'hole plugging'?

My view is that any changes made after the system's start date will constitute curve fitting (unless the change is something that has no effect on the equity curve). Walk-forward testing shows how impactful it is to tweak even one parameter a tiny amount. It's very difficult to create a system that survives a WF test. Difficult for me - I assume also difficult for others but that might not be the case.

I was thinking about the development stage when I wrote my post but as @Skate has described in the above post, there may be times when an oversight during development would need correction after the system was live.

 

[Skate]

There's a fine line there between curve fitting and tweaking/refining a system

I would sure as hell not trust such an over optimised system... (System design 101: The more you optimise the less robust)

Here are some key things to know about complex trading strategies
Complex trading systems are difficult to backtest properly over historical data. Because strategy complexities involve many inputs, signals, and conditions means you can't reliably prove their effectiveness before applying real capital.

Complex trading systems are hard to optimize. Since there are so many variables and inputs, it's challenging to optimize the parameters of a complex strategy to find the best combination. This leaves potential performance on the table.

Complex trading strategies have lower signal-to-noise ratios. The more variables and conditions a strategy has, the more "noise" it tends to generate in the form of false signals. This reduces the signal-to-noise ratio and degrades performance. They are fragile to some degree and tend to be more susceptible to breaking down during periods of market stress. They often have less "buffer" to absorb shocks.

@Trendnomics reminded me that complex trading strategies with numerous indicators and filters are susceptible to overfitting, which can result in poor out-of-sample performance. Overfitting occurs when a strategy is tailored too closely to past data, making it less likely to perform well under new market conditions.

The more variables a strategy has, the greater the risk of overfitting and the higher the chances of unintentionally identifying patterns in historical data that do not actually provide a true competitive advantage. This susceptibility to data mining underscores the importance of using sound statistical methods and testing strategies on out-of-sample data to ensure their effectiveness.

@Gringotts Bank pointed out that complex strategies are susceptible to fatal flaws, especially if the coding is not executed perfectly. When refining and curve-fitting a system with multiple moving parts, there is a greater risk of overlooking a fatal flaw during testing. These "unknown unknowns" can cause the entire strategy to fail.

In addition, the complexity of a strategy can lead to inconsistency in results. Due to the greater risk of fatal flaws and other reasons outlined above, complex strategies tend to produce more inconsistent results and higher drawdowns compared to simpler strategies.

So in summary, while complex strategies may seem attractive due to all the "levers" they offer, they tend to produce lower and less consistent performance due to the issues around testing, optimization, overfitting, data mining biases, automation challenges, higher noise, fragility and the higher probability of fatal flaws. Simplicity, where possible, often leads to more robust and effective trading strategies. After giving you a taste of the negative side of complex trading strategies, rigorous backtesting justifies some complexity.

Skate.

 

[Skate]

Traders who are able to think creatively
Outside the box, as they say, may be able to identify new approaches & techniques that can give them an edge in the markets. There are always new possibilities for traders to analyse market data & develop their own trading strategies.

The benefits of using complex trading strategies
Complex trading strategies, with multiple indicators, filters, and parameters provide a more refined view of the market by taking into account numerous aspects "simple strategies" just don't see. Complexity can be a valuable tool for consistently generating profits in unpredictable markets.

Complex trading techniques also have the advantage of being more adaptable to shifting market conditions. Traders can respond to changing market conditions and stay ahead of the curve by employing different indicators and filters in real time. Furthermore, additional indicators and filters may be more effective at minimising market noise and spotting trends and patterns that simpler strategies may miss.

While sophisticated trading systems might be difficult to backtest and optimise, extensive testing and study can assist traders in identifying the most efficient indicator and filter combinations. Applying a sophisticated statistical approach can assist in staying up to date with the latest market trends.

To negotiate complicated and ever-changing markets, financial institutions usually employ advanced complex trading strategies rather than trading with simple trading methods. Complex trading strategies are excellent at minimising market noise and filtering out false signals and may be significantly adjusted to fit specific trading styles. By adopting complex trading methods, these traders can capture a greater range of market conditions, identify more profit opportunities, and better manage risk.

While complicated trading systems have drawbacks, such as being more difficult to test and optimise and being more prone to overfitting, the benefits can exceed the risks for experienced traders.

Whether or not to employ a complex trading strategy will be determined by the trader's objectives, risk tolerance, and coding ability. Complex strategies can be an effective tool for experienced traders that have a thorough understanding of market dynamics, statistical methodologies, and mathematical modelling in order to make consistent returns when markets are behaving badly.

In conclusion, while simple trading methods may be effective for some traders, complicated trading strategies can be a great tool for making consistent gains in turbulent markets by allowing traders flexibility, customisation, and adaptation. Experienced traders and organisations can use advanced analytics and customised trading methods that are tailored to current market conditions to remain ahead of the competition.

Skate.

 

[Skate]

Skate.

 

[Gringotts Bank]

Strats should be adaptive, both for the broader market and stock-specific.

Simple example for mean reversion:

Buy signal based upon price falling 1*ATR. This can become 0.5*ATR if the market is trending strongly. Or 2*ATR in a bear market.

Howard also wrote some interesting stuff about adaptive position sizing.

Some individual stocks should probably be excluded if their individual optimization simply never, ever yields profit. Use AB's 'individual optimize' to get an idea for which stocks these are. There's nothig wrong with running a system on 10 chosen stocks because they optimize well over very long TFs. Just make sure they are consistently high turnover stocks with plenty of signals.

 

[Skate]

Trading can be a promising path to financial freedom and independence
But it's not without risks and requires discipline and education. If you're considering embarking on a trading journey, here are some compelling reasons to do so:

# Achieving financial freedom
One of the ultimate goals of trading is to achieve financial freedom. As you age, you'll eventually need to stop working full-time, and your trading can serve as a reliable income stream. Starting early gives you the best chance of building a robust portfolio that can support you for decades.

# Practice makes perfect
When you're new to trading, it's best to start small and trade infrequently. This approach allows you to practice and learn from your mistakes without putting too much capital at risk. As you gain experience and develop your trading strategy, you can gradually take on larger positions.

# It’s easy to get started
You don't need a lot of money to start trading, and you can treat it as a new hobby. Focusing on buying quality companies and holding them for the long run can yield good returns.

# Learning along the way
Admittedly, there's a steep learning curve when you start trading, but it's also part of the journey. You'll learn about market psychology, risk management, technical analysis, and a lot more. The knowledge and skills you gain along the way can give you an edge and make your trading more strategic over time.

In summary, trading can be a pathway to financial flexibility and freedom in retirement, particularly if you start early and practice proper risk management. It's vital to be aware of your emotions, have a long-term perspective, and focus on the learning process, not just the money. Taking the first step towards a more secure financial future, no matter how small, is not only crucial but vital.

Skate.