Andrew Gibbs has been involved in the financial markets since 2001 and is the founder and CEO of Halifax New Zealand.

Andrew has extensive experience in all forms of equity and derivative contracts, managing millions of dollars and trading a number of markets around the world.

In this episode we discuss volatility and methods to trading the VIX plus the benefits and methods of including fundamental data in technical quant models.

Topics discussed

• Instruments you can use to trade volatility and the benefits or disadvantages of each
• What makes the VIX attractive to trade and why it often trends over time
• The types of trading styles that suit the VIX
• The dangers of trading volatility products
• Seasonality in the VIX
• How to get started building volatility trading models
• Fundamental data and the types of fundamental datasets that work well in quantitative models
• Why some fundamentals work better than others
• The frequency of fundamental data release and how that dictates trading model style
• How to account for revisions to data
• The impact of including fundamental data can have on trading results
• Technical vs Fundamental data and which tends to be more robust
• Issues with fundamental data and company reporting accuracy
• How to reduce the chances of investing in a company that is likely to go bust
• Combining fundamentals and technical data and how to test
• How to get started building fundamental quant models

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.

Jay Kaeppel has over 25 years experience in the financial markets.

He has worked as the Head Trader for a CTA and published a number of popular trading books on Futures, Options and Stock Market Seasonality.

He also spent a number of years writing a weekly column titled “Kaeppel’s Corner” and publishes on his blog “Jay On The Markets”.

He is now Portfolio Manager for Alpha Investment Management, offering strategies such as the ‘Alpha Multi-Income Strategy’ to investors.

In this episode we discuss a number of seasonal tendencies, how they can be integrated into a trading model, the applications of the Known Trend Index and the reasons why most traders fail.

Topics discussed

• The Santa Claus rally - what it is and how to trade it
• How to use seasonality to complement other models
• Seasonality tendencies around holidays
• Monthly seasonal tendencies and a simple monthly seasonal system that vastly outperforms stock index returns
• Boiling down the trading process into 4 simple words
• Using leveraged ETFs for seasonality trades
• The worst performing month of the year (it’s not October)
• Converting seasonal tendencies into a trading model
• A simple seasonal sector system that takes only 6 trades per year
• Diversification vs Specialisation and the impact it can have on trading and drawdowns
• Are seasonal trading strategies just data mining?
• The Known Trends Index (KTI) and how it can be used in trading
• Why most traders fail

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.

Laurent Bernut was a systematic short seller with Fidelity for 8 years. His mandate was to underperform the longest bear market in modern history: Japanese equities.

Prior to that, he worked in the Hedge Fund world for 5 years.

He now runs an automated Forex strategy and travels the world with his family.

In this episode we talk all about Short selling, creating shorting strategies, the challenges of implementation and how to manage risk. We also discuss the importance of exits, insights into Bear markets, autotrading Forex and why complexity is a form of laziness.

Topics discussed

• The benefits of developing a strategy on the short side first and why long/short symmetry is important
• Challenges with executing short systems and solutions
• The most important aspect to worry about when short selling
• Finding short candidates in a Bull market and why you should ignore absolute performance
• Tips to creating profitable short strategies
• The importance of exits and how to test them
• Insights into Bear markets
• The 3 wrong questions to ask during a Bear market and the 3 best ones to ask
• A simple method to identifying Bull and Bear markets
• Why complexity is a form of laziness
• Using MT4 as a professional trading platform
• Why being disciplined is a myth
• The type of strategies that work in the Forex markets
• The Common sense Ratio and why it’s more robust than the Sharpe ratio

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.

Thomas Stridsman has over 20 years experience in the financial markets.

He was an editor for Futures magazine and published two books on trading system development and money management.

He is now a fund manager at Alfakraft, specialising in short-term trend following strategies with a focus on dynamic size allocation and risk distribution algorithms.

In this episode we discuss strategy testing, why you need to normalise metrics, tips to creating robust strategies and why he doesn't test entries and exits any more (and what to focus on instead).

Topics discussed

• The differences between short term trend following and long term trend following
• Why backtesting metrics should be normalised to give an accurate picture of performance
• Why you should look to restrict the number of consecutive winners and losers
• The difference between a good model and a profitable one
• Tips to creating robust systems
• Trading costs and when to include them in testing
• Using standard deviation to determine system robustness
• How his systems development approach has changed over the years
• The one particular insight that propelled his trading forward
• Applying Optimalf to position sizing
• The future of trading

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.