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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: October, 2015
Oct 31, 2015

Greg Morris was Sr. Vice President, Chief Technical Analyst, and Chairman of the Investment Committee for Stadion Money Management, overseeing the management of over $5.5 billion in assets. 

He has been featured in the media a number of times, being invited to lecture about technical market analysis around the world.

He is currently semi-retired, serving as a consultant and working on a few projects, including golf.

In this episode we talk about the real definition of risk and how to manage it, the applications of market breadth and how the 'Weight of the evidence' concept can be used in trading.

Topics discussed

  • Why defining risk as volatility isn't accurate and what risk really is
  • Can diversification actually be used to minimise risk?
  • Why Rebalancing doesn't make sense
  • The ‘Weight of the evidence’ concept and how it can be used in trading
  • Why it’s important to test indicators over non-standard ranges
  • What market breadth measures can reveal in market tops
  • Different types of breadth and their applications in Trend Following
  • Selecting indicators and why diversification of indicators is vital
  • How often should you tweak your model if something isn't working so well
  • The current state of the market

 

Disclaimer:
Trading in the financial markets involves a substantial risk of loss and is not suitable for everyone. All content produced by Better System Trader is for informational or educational purposes only and does not constitute trading or investment advice. Past performance is not necessarily indicative of future results.

 

Oct 25, 2015

A couple of weeks ago I went back through all the guests we've had on the show so far and realised how very fortunate we've been to have so many fantastic guests on the show, sharing their knowledge and experience, some of them with more than 50 years of trading experience!

To be honest, I’d actually forgotten some of the topics we’d covered so far and going back through them was an excellent reminder of all the valuable information the guests had shared, so for Episode 30 I thought it might be a good idea to revisit some of the highlights from the earlier episodes so that those that haven’t heard them will go and listen to them, and those who have already listened may get some value out of hearing the highlights again.

I know when I went back through them it reminded me of some things that I wanted to test or investigate further, and I really found it a valuable exercise so I hope you do too.

This episode will cover some of the highlights from episodes 1 to 20; some of my favourites and some of yours.

Topics discussed

  • How to find new trading ideas every day
  • Using optimisation to understand market behaviour, not to find the optimal parameters
  • How the level of market noise can indicate the type of strategy to trade
  • Tips to creating robust models
  • Avoiding over-optimised trading strategies
  • Combining multiple conditions or strategies into an ensemble system
  • Why simple systems are better than complex ones
  • How market timing can improve strategy performance
  • The concept of conditional trading and why you need to consider market context
  • Testing the effectiveness of entry and exit rules
  • The type of strategies that should have stops and when stops don't make sense
  • Factors to consider when choosing a position sizing strategy
  • How dual momentum can produce profits and protect in a downturn
  • Trading the equity curve to protect capital
  • Why traders should focus on process and not outcome

 

Disclaimer:
Trading in the financial markets involves a substantial risk of loss and is not suitable for everyone. All content produced by Better System Trader is for informational or educational purposes only and does not constitute trading or investment advice. Past performance is not necessarily indicative of future results.

Oct 18, 2015

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

He is also a councillor with the Australian Technical Analysts Association and contributes to the technical analysis articles for Fairfax press.

In this episode we talk about Rotational trading systems, the impact of stops on results and alternatives to managing risk. Alan also shares some interesting tips into measuring system health, dynamic position sizing and anticipating trading signals.

Topics discussed

  • Rotational trading - entries, exits and managing risk
  • Methods to measure momentum in trend following strategies
  • The impact of stop losses in trading systems and alternatives to managing risk
  • Tips to position sizing without a stop loss
  • Using dynamic profit targets to reduce risk and increase return
  • Why drawdown is not a single number
  • Using Monte Carlo analysis as a dynamic position sizing tool
  • Methods to determining current system health
  • Factors to consider when creating a system health metric
  • Choosing the right Backtesting metrics and using them in live trading
  • Five factors to consider when choosing a strategy to suit your personality
  • Anticipating trading signals, the benefits, challenges and solutions
  • How to anticipate trading signals without reverse-engineering indicators

 

Disclaimer:
Trading in the financial markets involves a substantial risk of loss and is not suitable for everyone. All content produced by Better System Trader is for informational or educational purposes only and does not constitute trading or investment advice. Past performance is not necessarily indicative of future results.

Oct 11, 2015

David Aronson is a pioneer in machine learning and nonlinear trading system development and signal boosting/filtering.

He is author of “Evidence Based Technical Analysis” and his most recent book "Statistically Sound Machine Learning for Algorithmic Trading of Financial Instruments" is an in-depth look at developing predictive-model-based trading systems.

He was also an adjunct professor of finance, regularly teaching MBA and financial engineering students a graduate-level course in technical analysis, data mining and predictive analytics.

In this episode David shares research into the effectiveness of indicators to identify Bull and Bear markets; he’s tested a large number of indicators and combinations with some interesting results! We also discuss issues with data mining, conditions where traditional methods of measuring data mining levels can be problematic and then finish up with the future state of Technical Analysis.

Topics discussed

  • What the popular Golden and Death Cross can tell us about the probability of a Bull or Bear market
  • Using the RSI indicator to determine market state
  • Methods to reduce the lag the 50/200 Moving Average crossover experiences
  • Using ADX and Price Variance to identify Bull and Bear markets
  • Creating indicators based on the value of other indicators
  • Modifying the McClelland Summation Index indicator to identify market states
  • How datamining increases the chance of good luck in the results
  • Why the White's Reality Check and Monte Carlo Permutation methods breakdown using certain data-mining approaches
  • How the role of Technical Analysis could change over the next 10 years
  • New developments in Machine Learning which may see the end of the role of technicians

 

Disclaimer:
Trading in the financial markets involves a substantial risk of loss and is not suitable for everyone. All content produced by Better System Trader is for informational or educational purposes only and does not constitute trading or investment advice. Past performance is not necessarily indicative of future results.

Oct 3, 2015

Dr. Gary Dayton has been an active trader since 1999 and is President of a consulting firm that specializes in developing “peak” performance in traders.

His approach to trading psychology is very different to the traditional approaches used by other trading coaches, introducing traders to the practise of mindfulness to not only overcome fear and other unwanted trading emotions but to develop the concentration and focus needed to trade successfully.

In this episode we discuss why traditional approaches to controlling emotions don't work, the role of emotions in trading and how mindfulness can improve trading performance. He also shares some tips on how to get started practising mindfulness, the benefits it can have outside of trading and how the approach of Mental Parking can increase focus.

Topics discussed

  • Comparisons of sports and trading performance
  • Traditional approaches to handling emotions in trading and why they don't work
  • Why it’s impossible to suppress your emotions
  • Landing a plane in the Hudson River and what the Captains response teaches us about trading
  • The role of emotions and how experienced traders actually leverage emotions in trading
  • The concept of Mindfulness and the benefits to traders
  • How to use Mindfulness when trading
  • The evidence that Mindfulness can improve trading performance and how it impacts the brain
  • How to get started practising Mindfulness
  • How to use Mental Parking to increase focus and productivity
  • How exercise can improve mental and trading performance

 

Disclaimer:
Trading in the financial markets involves a substantial risk of loss and is not suitable for everyone. All content produced by Better System Trader is for informational or educational purposes only and does not constitute trading or investment advice. Past performance is not necessarily indicative of future results.

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