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Better System Trader

If you’re looking for inspiration, motivation and practical advice on improving your trading results, Better System Trader delivers every week. Each episode brings you an expert trader who shares their own story, along with the steps, both good and bad, that they’ve taken on their path to success. With a focus on actionable insights, the tips and tricks used by the experts contain loads of value, providing you with insanely practical tips and tools you can start using TODAY. Improve your trading with Better System Trader.
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Now displaying: 2016
Dec 24, 2016

So here it is: The Top 10 Trading Lessons for 2016!

I have to admit, creating this list was really fun. Not only because I got to look back and remember all of the great episodes we released and the knowledge that these fantastic guests shared with us, but also because I had the chance to think about the impact these episodes hopefully had on your trading too.

This Top 10 List was chosen based on a few factors, including download stats, feedback from listeners and some of my own personal favorites. So although this list is not solely based on analytics, each episode was chosen with the intention to offer powerful trading insights as you move into the new year.

So if you missed any of these episodes, make sure you listen to them before we ring in the new year!

Also make sure to download the FREE BONUS audio package — This audio contains the biggest trading lessons from each of the guests in this Top 10 list and I compiled them to make sure we all learn from their insights. It’s only short but it’s packed with valuable info!

One last note: NONE of this would be possible without you and your support. So I want to THANK YOU for a fantastic 2016!

So (drumroll please…..) here they are: My Top 10 Trading Lessons for 2016

Dec 11, 2016

As markets become more mature and more efficient, it can be become increasingly difficult to find sustainable edges.

Many traders are looking at the same data and using the same techniques, so what are our options here?

2 of the obvious options we have are:

  • Try to find a unique approach to the markets or at least something that isn't so popular,
  • Explore alternative markets where inefficiencies are more prevalent.

In this episode, our guest Bert Mouler is going to discuss both options and share his solutions.

Bert has been an independent trader for close to a decade and is the President and CIO of Profluent Capital, which uses advanced AI and machine learning technology to produce uncorrelated alpha for their clients.

In our chat today, you will learn:

  • Cryptocurrency markets – what to trade, the huge inefficiencies that exist and finding edges in the bitcoin markets
  • The advantages and disadvantages of Machine Learning and tips to use it effectively in trading
  • Feature engineering and the importance of looking at data in unique ways
Nov 27, 2016

Most trading strategies have an optimal type of market condition where they work at their absolute best, so having an understanding of market conditions and being able to detect and adapt to them can really have a huge impact on trading performance.

But how can we measure market regimes properly?

What techniques can we use to find that delicate balance between stability and reactivity so that it improves performance rather than reduces it?

Our guest for this episode, Alan Clement, has completed considerable research into market regimes and is going to share his knowledge with us today!

Alan is a Certified Financial Technician, full time independent trader, quantitative trading systems designer and private investment consultant.

In our chat today, you will learn:

  • Market regimes – what they are and how they can impact the performance of your trading strategies
  • The different types of Market Regimes and key aspects to consider when defining them
  • Indicators, market breadth and intermarket measures – which ones are the best for detecting market regimes?
Nov 13, 2016

The performance profile of Mean Reversion is extremely desirable to a lot of traders.

Mean reversion trading strategies can produce high win rates and a smooth equity curve, however there are risks, which can result in giving back a large portion of profits, or of your trading account, some times in a very short period of time.

So what can you do to build mean reversion strategies that produce consistent profits while managing risk effectively?

Todays guest, PJ Sutherland, is here to share the knowledge he has gained from years of research and trading mean reversion strategies, and as you’re going to hear, he has some really interesting insights to share with us.

PJ has extensive experience in the development and deployment of quantified trading systems and has been active in the market for the past decade.

He is the founder and director of Alpha Investment Advisors, providing research to hedge funds and prop trading firms, and the founder of the website Quantlab for private traders.

In our chat today, you will learn:

  • The key drivers of short-term returns in mean reversion trading
  • The impact of market environments on mean reversion strategies and how to detect and adjust strategies to varying market conditions
  • Should you 'Catch a falling knife' or wait for confirmation? How to determine which entry technique is best for you
  • Building a portfolio of strategies using parameter ranges across the mean reversion curve
  • Simple but powerful techniques to managing risk in mean reversion strategies
Oct 30, 2016

There are a number of different aspects to trading that we really need to get a handle on to increase our odds of success. Some aspects we often put a lot of thought and analysis into, and others we may not consider so carefully or at all, which could be impacting our trading results without us even realizing.

Todays guest, Dr Howard Bandy, is here to discuss the foundations of trading, and some of these aspects we really need to consider, whether we’re just starting out or a more experienced trader.

Howard has over 50 years experience in the research and application of modelling and simulation of financial systems.

He has previously worked as a senior research analyst for a CTA firm, is a consultant to trading companies and individuals, as well as being an international speaker and publishing a number of books on quantitative trading systems.

In our chat today, you will learn:

  • How to systematically choose the right markets to fit you risk profile, trading style and objectives
  • The 3 characteristics a market must have to be tradable
  • The difference between Impulse signals vs State signals and how they can be used to manage trades and monitor trade health
  • The four parameters you need to understand to define your own risk tolerance
  • Choosing the best objective function to evaluate trading strategy performance
Oct 16, 2016

Why is it that some traders can create trading strategies that perform well in real-time trading while other strategies fall apart?

How do some traders keep their trading strategies fresh and adaptive to market conditions while other strategies just stop working altogether?

Robert Pardo, president of Pardo Capital, author of the book ‘The Evaluation and Optimization of Trading Strategies’ and creator of the ‘Walk Forward Analysis’ approach, is here to chat about creating and optimizing strategies that are robust and continue to work in the future.

In our chat today, you will learn:

  • Common mistakes traders make that can cause strategies to fail in real-time trading
  • The dangers of traditional optimization techniques and how they can be reduced and even overcome
  • How to determine if a strategy really is robust, while keeping it fresh and adapting to market conditions
Oct 2, 2016

Who wants a steadily rising equity curve with little or no drawdown? I'm sure most traders do, but unfortunately it doesn’t usually end up that way.

Drawdown is a big part of trading and can be one of the the biggest challenges traders face, so what techniques can we use to potentially help reduce drawdowns?

Our guest for this episode, Scott Phillips, is going to share techniques he uses to manage drawdowns in his own trading.

In our chat you will learn:

  • How to quickly test a trading idea to determine if it’s worth more investigation
  • Why it’s so important to understand market types, the impacts it could be having on your trading results and how you can leverage this knowledge to create strategies with enhanced performance
  • How to improve your trading results through better trade management and multiple exits.
Sep 18, 2016

Building robust trading strategies that can detect and adapt to market conditions can be a real challenge, and failure to do so can often result in poor trading performance and drawdowns.

How can we build more robust trading strategies that adapt to market conditions as they change?

Our guest for this episode, John Ehlers, who has a guest on episode 48, joins us to share some common problems traders face when building trading strategies along with tips on how to overcome them.

In our chat you will learn:

  • Tips and techniques to detecting and adapting to market conditions
  • Common problems traders face with indicators and how to fix them
  • The 4 requirements to building a robust trading strategy
  • How the conventional wisdom of using indicators causes late signals and how to use them to anticipate instead
  • A simple technique to determine if your indicators are working properly for the market conditions
Sep 4, 2016

Trading algorithmically based on sentiment data is a relatively new field compared to more established approaches. With the explosion of social media and computing power, the analysis of sentiment data has also increased, with some hedge funds committing considerable resources to researching the applications of sentiment data in trading.

However, there is also some skepticism of the value of analyzing social media for trading, so what is sentiment trading all about? Can sentiment actually be used in trading models and how?

Our guest for this episode, Richard Peterson, has been analyzing sentiment for over 20 years. He started what was probably the world’s first fund specializing in sentiment trading, and now runs a company called MarketPsych, specializing in the collection and analysis of sentiment data.

In our chat you will learn:

  • Why sentiment is so important and how it can give traders an edge
  • The challenges of using sentiment data in trading models
  • The best and worst markets for sentiment analysis as a predictor
  • Applications of sentiment analysis in quant models and the future of sentiment analysis
Aug 21, 2016

Whether you’re a retail trader with a small account or a fund manager with millions or billions under management, something that we all need to consider carefully as traders is how or where we’re going to use the money in our trading accounts.

'Capital allocation' sounds boring but it can have such a huge impact on our trading results. Unfortunately, it can sometimes be overlooked for other aspects of trading like entries and exits, leaving traders with an inefficient use of their capital and can result in lower returns and poor performance.

Can we use our trading capital more efficiently to achieve higher returns? And if we can, then how?

Todays guest, Michael Melissinos, started out as a junior analyst at Bear Stearns and is now running his own systematic trend-following fund Melissinos Trading.

Mike is a competitive guy, always looking for ways to improve his trading performance and in today’s episode he's going to share with us some practical ideas and research, including:

  • The 3 most important things that influence trading performance
  • Why what you trade is more important than entries and exits
  • Ideas to improve trading results through dynamic capital allocation
  • How to use indicator scores to measure trend strength
  • And much more.
Aug 8, 2016

Today’s guest is a trader that has been requested quite a few times actually, I’ve had a lot of requests to have this person as a guest on the show, and the guest is Adam Grimes.

Adam has two decades of experience in the industry as a trader, analyst and system developer and is currently Chief Investment Officer of Waverly Advisors.
He’s previously held positions at Level Partners, MBF Asset Management and SMB Capital and is the author of ‘The Art & Science of Technical Analysis: Market Structure, Price Action & Trading Strategies’.

For those of you that know Adam and his work, his approach to trading is a mix of quant and discretion, and I think even if you’re a purely systematic or quant based trader it’s interesting to hear other people’s approaches and points of view.

So we start off the chat by discussing his approach of mixing quant and discretionary models, and then we move onto behavioral factors in the market and why approaches that look at the market as purely rational fail.

We then end the chat discussing Keltner channels and their applications to trading, so there’s quite a variation in topics here but I’m sure you’ll find it interesting.

Topics discussed

  • Mixing discretionary decisions with a quantitative framework
  • Why behavioral factors in the markets are so important and why approaches that look at the market as purely rational fail
  • The application of Keltner Channels in trading
Jul 24, 2016

When I was preparing for the previous podcast episode on system trading through the Brexit, I had to review some of the past podcast episodes so that I could include some background content for the guests, and as I was going through some of those past episodes I realized that there was so much great information in them that I had already forgotten about.

I even found some concepts or ideas that didn’t really catch my interest because it wasn't appropriate to my trading at the time but it’s now more relevant to me personally, so I thought it might be time to do another review of some of the past episodes as a reminder and to perhaps gain or reinforce past insights.

Last year, we did a podcast episode where we reviewed episodes 1- 20. That was episode 30 if you’d like to go back and hear that.

In this episode we'll review lessons and highlights from episodes 21-40. Some of the topics we’ll be discussing are:

  • How to never run out of trading ideas,
  • The importance of creativity and a simple technique to increasing our creativity,
  • How to manage data mining and avoid overfitting,
  • A number of approaches to building robust trading strategies,
  • How to bet bigger with a smaller overall risk,
  • Plus much more!

 

Jul 10, 2016

The results of the Brexit decision took a lot of people by surprise and the markets reacted accordingly. What was interesting about this market event is that we all knew the date and time period when the Brexit votes would start rolling in, so we had a rough idea when we might see some type of market reaction, if the market reacted at all.

As systematic traders, what should we do in this type of situation:

  • Should we continue trading as usual, following our systems?
  • Should we override our systems to reduce exposure, or perhaps temporarily stop trading altogether?
  • Are there any other approaches that we should consider?
  • How do we go about deciding what to do?

In this episode we’re asking 13 system traders and past guests of the podcast (actually it's 12 past guests and one future guest) about their approach to trading around the Brexit vote.

I’ll be asking them what their trading plan was going into the Brexit decision and you might be surprised with some of their answers.

I’ll also be asking them what factors they considered to reach that decision, whether they were happy with the approach after the event and any key learnings we can get out of this experience.

I personally found it really interesting to hear what they had to say so I’m sure you will too.

Topics discussed

  • How 13 pro system traders approached the Brexit decision - did they trade through it, reduce exposure, stop trading or something else? Their answers may surprise you!
  • The factors they considered when deciding on that approach
  • Lessons learned and insights from their results and the market reaction to the Brexit decision
Jun 26, 2016

Traders are always looking for an edge and today's guest shares a simple approach he calls an 'unfair trading advantage', that can have a dramatic impact on trading strategy performance.

The guest on this episode has been on the show before, to discuss breakout trading strategies back in Episode 43. In that episde we discussed the steps to building breakout strategies and we even released a breakout strategy toolkit, included an ebook, cheatsheet and EasyLanguage code for 2 breakout trading strategies.

In this episode, our guest Tomas Nesnidal will be sharing a different trading approach, and it’s something he likes to call ‘an unfair trading advantage’.

He’s going to explain to us what it is and why he calls it an 'unfair advantage.' It's something that a lot of traders have probably heard about but perhaps are not aware of how to use it properly or even the positive impact it can have on trading results.

Tomas will explain it in this chat so take a listen!

Topics discussed

  • An 'unfair trading advantage' all traders should consider for their own trading strategies
  • The technique that most traders have probably heard about but don't know how to use properly
  • The incredible impacts this technique can have on trading performance
Jun 12, 2016

Today we’re covering a topic which can really be a concern for traders of all levels, from beginner to pro, and that is the topic of strategy evaluation.

  • Have you ever found that real-life performance does not match expected results?
  • Or perhaps you have a strategy that is stuck in a drawdown and wondering if it’s actually broken?

I’m sure we’ve all heard of data mining bias, over-optimization and curve fitting and the impacts this can have on our trading accounts.

We may be even using techniques such as Out Of Sample testing, Walk Forward Analysis, Monte Carlo analysis and a number of other measures to identify or reduce the impact of these issues, but do these approaches actually work? Are there limitations or dangers with these techniques? Are there better ways?

In this episode we talk to someone who evaluates trading systems for a living, plus his research into system evaluation techniques has won awards. The guest is Dave Walton.

Dave was the winner of the Wagner award in 2014 for a paper titled ‘Know your system – turning data mining bias to benefit through System Parameter Permutation’.

In our chat today we talk about the technique in his paper and how it can be applied to trading strategy evaluation. We also discuss some of the assumptions and limitations of the approach, and he shares with us some valuable insights he’s made since publishing the paper which have resulted in an updated approach he now considers a better alternative, so make sure you listen out for that.

Topics discussed

  • How the typical approaches to system development can introduce datamining bias without you knowing
  • The types of systems that can increase the chance of data mining bias and what to look for
  • How the method of splitting your out of sample data could be causing you to throw away good strategies
  • Out of sample, walk forward analysis and Monte Carlo - do they actually reduce data mining bias?
  • The problems with using Monte Carlo analysis to assess strategy performance and why it doesn’t protect from overfitting
  • System Parameter Permutation - how to use it, why use the median, parameter range selection and new insights since the SPP paper was published
  • How System Parameter Randomization solves some of the issues of System Parameter Permutation
  • Stochastic modelling and how it can be used to determine if a rule is adding value to your strategy
May 29, 2016

Nelson Freeburg was the editor of Formula Research, a newsletter that developed systematic timing models for the stock, bond, and commodity markets.

He was also a research consultant working with institutional money managers to design proprietary timing models.

Nelson had been an active trader since 1980 and occasionally spoke about his work to audiences around the world.

In this episode, Linda Raschke shares memories of Nelson, his approach to model development and what we can learn by studying his work.

Topics discussed

  • Timing models and the components Nelson used in his models
  • Russell growth vs Russell value model
  • Out of sample testing and sample size
  • Why Nelson focused so much on reducing drawdown
  • Nelsons biggest strengths in modelling and what we can learn from his approach
  • Voting systems
  • The benefits of overlaying models
May 15, 2016

Markets are constantly changing. Trading edges come and go.

In an industry with such a low survival rate, where some areas are changing at an ever increasing rate, what does it actually take to not only survive, but thrive, over an extended period of time?

The guest on this episode, Linda Raschke, has been trading for over 35 years. She traded for several hedge funds before starting her own, ranking 17th out of 4500 hedge funds by Barclays Hedge for 'Best 5 year performance'.

She's experienced a large number of changes in the industry, some of them have been huge, but she’s managed to adapt and continues trading even today.

Linda stand out from the crowd for three factors: Performance, Longevity and Consistency, so what does it actually take?

What has she learnt over the years and what can we do to improve our own chances of performance, longevity and consistency?

In our chat with Linda we discuss some of the changes she’s experienced over the years and the impacts this has had on trading. We also hear about her approach to modelling the markets, understanding market behavior, trade management, day trading techniques and some fantastic questions submitted by fellow listeners. Make sure you don’t miss those!

Topics discussed

  • Changes in the markets over time and the impacts that has had on strategies and their performance
  • How to use modelling to identify market behavior and edges
  • AI, machine learning and neural network techniques
  • Tips and factors to consider when daytrading
  • Reading market behavior throughout the day

PLUS loads of great questions submitted by Better System Trader listeners!

May 1, 2016

Trading can be tough, markets are noisy and finding signals in the market noise can be challenging. Also, applying indicators to trading strategies can introduce lag, however a lot of traders don’t even realize the lag their indicators are introducing or the impact it can have on trading. In fact, the guest in our chat today, John Ehlers said “One of the biggest enemies of traders is lag”.

So, what's the solution?

John Ehlers is well known in the commodity futures arena as the Creator of MESA, having pioneered the MESA method of cycle analysis in the late 1970's and becoming the founder of MESA Software.

He is author of four books including Rocket Science for Traders, Cycle Analytics for Traders, Cybernetic Analysis for Stocks and Futures and MESA and Trading Market Cycles.

He has also been a contributing editor of Stocks & Commodities, winning a number of awards for his work.

In our chat with John we discuss the issue of indicator lag, the impact it can have on trading and some solutions. We also talk about applications of Digital Signal Processing in trading, the MESA approach, regime switching, Cycles and the mistakes people make trading cycles.

Topics discussed

  • MESA and it’s application to trading
  • Alternatives to the MESA approach and which is best for the markets
  • How cycle length can determine indicator length
  • Common mistakes people make with cycles
  • Cycles and DSP techniques as regime filters
  • The problems caused by indicator lag and solutions to reducing lag
  • The best low-lag filter and oscillator available
  • Getting started with Cycles and DSP

 

Apr 17, 2016

Backtesting and execution are such key parts of algorithmic trading so choosing the wrong platform can have a huge impact on our trading.

There are loads of trading platforms available and a lot of considerations which need to be made when choosing one that suits our needs, so in this episode we’ll be discussing backtesting and execution platforms with Nitesh Khandelwal, department head at QuantInsti who also co-founded iRageCapital and iRage Global Advisory Services.

After our chat on algorithmic trading platforms we’ll also cover statistical arbitrage, high frequency trading and some interesting audience questions, so listen out for those.

Topics discussed

  • The 3 key components to an algorithmic trading platform and the basic questions you need to answer before choosing a trading platform
  • Why backtesting and execution platforms should be separate
  • Choosing a programming language and why python has become a popular choice in trading
  • The benefits and drawbacks of using python in trading
  • Statistical Arbitrage, how it came about and the benefits of the approach
  • The primary risks of statistical arbitrage, especially during times of market stress and how they can be reduced
  • The most important factor in stat arb trading
  • Common mistakes traders make when building statistical arbitrage models
Apr 3, 2016

I’m sure we all want to create trading strategies that perform better and last for longer but there are a number of issues we need to look out for when developing robust trading strategies, some are well-known and some perhaps aren't.

In this episode we’ll be talking with Perry Kaufman about strategy development and more specifically some of the issues that can catch us out when creating trading strategies. Perry raises some interesting points about optimization that may not be well known plus he shares loads of tips to creating more robust strategies.

Perry writes extensively on markets and strategies, having published fourteen books and has just released a new book on building algorithmic trading strategies, which we'll be discussing in this episode.

He has worked and consulted to a number of successful CTA, investment and prop trading groups, creating systematic trading and hedging programs.

This is also his 2nd appearance on the podcast, appearing as a guest way back in Episode 10.

Topics discussed

  • The most robust type of systems
  • How your choice of optimization values could be misrepresenting your results and how to choose parameters that give a more accurate picture
  • The mistakes traders make when analyzing optimization runs and tips to doing it properly
  • How to really determine if a new trading rule is robust
  • Reducing risk by using multiple parameters
  • What the number of profitable runs in an optimization can tell you about the robustness of a strategy
  • Why diversifying across strategies instead of across markets could be a better approach
  • The challenges of building robust strategies using Genetic Algorithms and Neural Networks
Mar 20, 2016

Andrea Unger is the only trader to ever win the World Cup Championship of Futures Trading ®* titles 3 years in a row, with returns of 672% in 2008 (futures division), 115% in 2009 (futures division) and 240% in 2010 (futures & forex division).

This is his 2nd appearance on the podcast, he was also a guest on Episode 16.

In this episode Andrea discusses his approach to trade entries, how the traditional approach to entries can limit our ability to read the market and how he's modified the standard approach to identify entry opportunities.

Topics discussed

  • The typical approach to entries and how Andrea uses a modified approach to identify and test his entries
  • Why starting an entry with a setup can limit your ability to read the markets
  • The grouping of setups and how the style of trigger you use can determine the most appropriate setup
  • The best timeframes for indicators and the impact lower timeframes can have on indicators
  • Combining intraday and daily timeframes for better entries
  • How Daily Factor can be used to determine the type of move to expect next
  • Symmetrical patterns - when it makes sense to use symmetry and when it doesn’t

 

Mar 6, 2016

Back in Episode 32 we had a chat with Laurent Bernut, a systematic short seller who spent years working in the Hedge Fund world specializing in short selling strategies.

He shared loads of knowledge with us in that episode but we actually had a lot more to talk about. We ran out of time back then so in this episode we’re going to continue with the chat, covering a bit more on short selling, including common problems and mistakes traders make when short selling, the 5 psychological stages of a bear market, how these stages manifest in market behavior and where we are now.

We also chat about his Convex position sizing model, visualizing your trading edge and how to tilt it more in your favor PLUS he shares with us a special trick to switch our minds from a flight or fight mode back into a state of flow.

We also have some great questions submitted by podcast listeners so listen out for those.

Topics discussed

  • Common problems traders face when short selling
  • When to never short a stock
  • The 5 psychological stages of a bear market, how they manifest in the markets and where are we now?
  • How Laurents Convex position sizing model adapts position size differently in periods of performance and drawdown
  • Visualizing your trading edge and tilting it in your favor based on trading style
  • The main components of a short trading strategy
  • Why a break of support is often not the best place to enter a short trade and what to do instead
  • A simple 'jedi mind trick' that switches your mind from fight or flight into a flow state
Feb 21, 2016

Tomas Nesnidal has been a full-time trader for over 11 years, specializing in automated algorithmic trading strategies.

He has experience with a number of trading styles, including option trading, spread trading, statistical arbitrage and market internals but in this episode we’re going to discuss one of his other specialties, breakout trading.

In our chat we discuss the key components of a breakout strategy and how to combine them to create profitable trading strategies. We also discuss the degradation of strategies over time, how to add new life into old strategies and why creative thinking is such an important aspect of successful trading.

In this episode we discuss

  • The benefits of trading breakout strategies and what makes a good breakout strategy
  • How to build profitable breakout strategies using 4 key components
  • The degradation of strategies over time and how to add new life into old strategies
  • Using filters to improve trading results
  • Adapting strategies to market conditions
  • The best timeframes and markets for breakout strategies
Feb 7, 2016

Murray Ruggiero is the chief systems designer and market analyst at Tuttle Wealth Management, with around 200 million dollars under management.

He is one of the world’s foremost experts on the use of intermarket and trend analysis in locating and confirming developing price moves in the markets.

He is also a speaker, author and has been a contributing editor to Futures magazine since 1994, producing over 180 articles.

In this episode we discuss various aspects of system development, including optimization, curve-fitting and creating robust strategies. We also discuss why strategies must have a premise, the importance and applications of intermarket analysis, cycles and a bunch of great questions from the audience.

In this episode we discuss

  • Factors to success in system development
  • Why it’s important to understand the underlying premise of a system
  • Techniques to reduce or avoid curve-fitting and develop robust strategies
  • Why Intermarket Analysis is so important and how it can be used to create profitable trading strategies
  • How to get started with intermarket analysis and common issues traders face
  • Using cycles to detect market breakouts and other applications

PLUS questions from the audience on...

  • How to determine if a strategy has broken down or is just in a normal state of drawdown
  • The relationship between drawdown and time
  • Creating robust strategies and which ones have stood the test of time
  • Performance of Tuttle Wealth Management and the differences between managing money for others and trading your own money
  • Exits and how to choose the correct exit for your entry method
  • Effective uses of AI in trading
  • Regime switching between strategies
  • The future of trading
Jan 24, 2016

For those traders looking for an edge in every aspect of trading, today's topic is something that isn't discussed too much but has had a great impact on the 2 guests of this episode.

The topic is collaboration in trading and the guests are Michael Cook and Kevin Davey.

Both of these guests have appeared on the podcast before, with Michael being a guest on Episode 39 and Kevin being a guest on Episode 5 and Episode 38.

Both have extensive trading experience too, successfully trading their own money and others.

In this episode they share the impact collaboration has had on their own trading as well as why collaboration is so important, the actual benefits to traders, how to find the right people and tips to maximising effectiveness.

In this episode we discuss

  • Why it pays to put the work into strategies other people would find awkward or too difficult
  • Why collaboration is so important in trading
  • The benefits of collaboration and what you could be missing out on
  • The different levels of collaboration and tips to maximising it's effectiveness
  • How to determine if someone may be a good fit for collaboration
  • How to find traders to collaborate with
  • The most important aspects of trading
  • The most common mistake traders make
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