Systematic Trend Trading

The Riddle of Diversified Systematic Trend Following



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Is Trend Following Dead?

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https://atstradingsolutions.com/is-t...ollowing-dead/

The Importance of Dynamically Adjusting your Trend Following Models

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An Enquiring Walkthrough of GBPJPY with Satin Jackets

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ATS Algorithm Update

Traders Outpost Podcast 09 - Trend Trading Truths

In this episode we dig deep into the essential factors for long term robustness, look at performance of simple breakout, trailing stop and fixed target solutions and future plans.

A bit of fun for a Wednesday night :-)

Why trend following?….Well perhaps the current market shenanigans provides a timely reminder of this powerful technique.

The following video provides a brief overview of the introductory processes we engage to derive robust trend following sub portfolios at the individual market level which are then later consolidated into robust and powerful fully systematic diversified trend following portfolios.

TRADERS OUTPOST PODCAST 10 – COMPOUNDING, PORTFOLIO BUILDING AND MARKET MADNESS

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CTA Fund Performance Report - February 2020

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Mapping to Market Process

So you are a trend follower who has a variety of different trend following systems you would like to assess. How do I assess the best systems and their parameter values to use?

Traditional wisdom without digging deeper into the rationale says that you adopt best practice approaches to data mining and optimisation where you eliminate anomalies, use Monte Carlo across your Parameter sets, conduct walk forward and bootstrapping tests etc etc etc......

However the floor in this assumption is that you are data mining for a specific market condition as opposed to a fundamental feature of price in a 'fat tailed' environment. If you approach diversified systematic trend following with 'best practice' data mining approaches as that suggested by Darwinex etc.....you will be left floundering.

A really handy technique that is valid for trend following is the Map to Market Process.

The single most important feature of trend following is to remember it is the market that develops trends....and not your system. If markets are trending then your trend following system should be performing. If markets are not trending then your system should be stagnating or possibly in drawdown. Understanding this critical relationship is the means to determine whether your system is curve fit to noise or if it has a chance at being a robust trend following system to add to your diversified arsenal.

Here is how we map to market. We first plot the market data against our equity curve. We then look at the market data and highlight trend following environments in green where clear trends exist with limited volatility. We then refer to the equity curve and the drawdown profile. We should have significant step ups in equity curve and rapidly diminishing drawdowns (helped by positive skewed systems).

If your trend following system is not experiencing this relationship in the Map to Market function during favourable 'trending' market conditions....then it is likely a dog or a curve fit result.

We then highlight messy market movements with volatile swings which do not exhibit nice clean trending conditions in red. During these periods your system should be stagnating or worse still entering increased drawdowns. If it isn't, then once again you have a curve fit result that does not meet the logic of the market condition.

It is very important to focus on the red 'underperforming' sections of your backtest. They represents the areas of system weakness you need to pay attention to. Doing this process with different systems and across markets and asset classes allows you to work out the strengths and weaknesses of each system which assist you in compiling a diverse portfolio that can weather future uncertainty.

So this is how the Map to Market Process looks visually.



Doing this process with different trend following systems allows you to compile collections that address the strengths and weakness of the market condition to produce powerful trend following portfolios that stand the test of time. While we never know what the future brings, if your logic is tied to the market condition, then if the future presents good trending environments, then your system should continue to perform but during unfavorable regimes stagnate but protect capital.

Hi Copernicus

Like your 'Mapping to Market Process' systematic approach

Re.

do you do this bit - distinguishing the trending phases 'where clear trends exist with limited volatility' - just by eye/discretion (subjective) or operate a systematic specific rule-based way of defining this? I assume the latter, in order to be consistent. Do you use a particular trend (& volatility) indicator?

Cheers

At the moment it is just used as a final validation method once we have compiled a subportolio for a discreet market. A final visual discretionary check against an otherwise systematic process. :-)

WOW，Thank you for your sharing.

Excellent Paper from Ole Peters - The ergodicity problem in economics


Abstract
The ergodic hypothesis is a key analytical device of equilibrium statistical mechanics. It underlies the assumption that the time average and the expectation value of an observable are the same. Where it is valid, dynamical descriptions can often be replaced with much simpler probabilistic ones — time is essentially eliminated from the models. The conditions for validity are restrictive, even more so for non-equilibrium systems. Economics typically deals with systems far from equilibrium — specifically with models of growth. It may therefore come as a surprise to learn that the prevailing formulations of economic theory — expected utility theory and its descendants — make an indiscriminate assumption of ergodicity. This is largely because foundational concepts to do with risk and randomness originated in seventeenth-century economics, predating by some 200 years the concept of ergodicity, which arose in nineteenth-century physics. In this Perspective, I argue that by carefully addressing the question of ergodicity, many puzzles besetting the current economic formalism are resolved in a natural and empirically testable way.

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Reality versus Illusion - The Search for the Underlying Bias in Market Data for Price Followers

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Backtesting Basics: Four biases to know by heart

https://medium.com/auquan/backtestin...t-cec3f62a11b4

very good Copernicus

Cheers G :-)

Traders Outpost Podcast - Episode 14: A Discussion on the Donchian Breakout Look-back Period

In this episode, Fred and Rich respond to a forum members query regarding the recommended length of look-back to use for our Donchian Breakout models.