Oymyakon is a small village in Russia, where the average Winter temperatures drops to a bone-chilling -50 degrees Celsius (-58 Fahrenheit).

The village is widely accepted as the coldest inhabited place on Earth, and it’s so cold there that the electronic thermometer they installed as a tourist attraction actually broke after the temperature got too cold!

Now THAT is cold.

If you were preparing to go on a holiday there, what would you pack?

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At those temperatures, being in the wrong clothing for even just a few minutes could be disastrous, so you want to make sure you plan and pack the right clothes so you don’t suffer in the cold too much.

Contrast that to Death Valley in California, where the average summer temperature reaches 47 degrees celcius (117 Fahrenheit). If you went outside in that heat dressed for a holiday in Oymyakon you’d probably suffer quite a lot too – and fry like an egg in no time.

From these examples, it’s pretty clear that whenever we’re visiting a new environment, it’s always wise to do some research first.

If you’re not fully prepared, the experience could be very uncomfortable.

You would suffer.

Or in extreme cases it could easily lead to serious injury. Even death.

And the same applies to creating trading strategies. If you’re not full prepared and try trading the wrong type of strategy for a market or timeframe, it can cause serious injury to your trading account.

'If you’re not full prepared and try trading the wrong type of strategy for a market or timeframe, it can cause serious injury to your trading account.' Click To Tweet

So what can strategy developers do to be better prepared for the markets, so they’re not left suffering out in the cold or fried to a crisp?

Here’s a guest post from Martin Lembak explaining a simple way to determine the best type of trading strategy for a market and timeframe.

Cheers,

Andrew

 

A SIMPLE WAY TO DETERMINE THE BEST TYPE OF TRADING STRATEGY FOR A MARKET

One of the most important steps a trading strategy developer can take before starting to create a trading system is to determine the characteristics of a particular market and timeframe.

'One of the most important steps a trading strategy developer can take before starting to create a trading system is to determine the characteristics of a particular market and timeframe.' Click To Tweet

That is, to use the principle of least resistance and trade trending markets with trend (divergent) strategies and choppy markets in a countertrend (convergent) fashion.

Of course, it’s highly dependent on the chart timeframe too, and so for example where weekly bars can have trending properties, a 15-minute bar chart for the same market can show mean reversion properties.

The classic way to determine trendiness or non-trendiness with a higher level of statistical significance would be to utilize econometric/statistical tests of data time series such as Autoregressive functions, Autocorrelation, ADF, Hurst exponent, Variance ratio, Half life for regular time series and/or Johansen cointegration test for spreads, and so on.

Still, some successful developers also have their own approaches based on simple logic.

Let’s have a look at one of these approaches based on daily bars.[1]

Here we test a very basic trend strategy using the daily closing price and simple moving average (MA) crossover for different lengths of MAs. The strategy buys when the closing price is above the MA and reverses short when below the MA and vice versa.

The average profit/loss per trade is measured and accumulation of this statistic in time is plotted as an equity curve. The strategy is applied to daily data for 56 commodity futures markets, using 30 years of historical data.

Here is the accumulated average profit per trade for the portfolio using 4 different MA lengths:

Past performance is not indicative of future results. Hypothetical example for educational /informational purposes only. Always trade only with risk capital.

We can see that commodities futures as a portfolio data series is trending in nature for parameter look-backs from 20 days up and targeted holding periods of about 90-100 days on average.

Considering this property, it appears trend-following could be more appropriate, so we can build a more sophisticated and robust trend trading strategy, with quality risk management, based on this observation.

The same simple principle can be tested for mean reversion, such as buying at the lower Bollinger Band and selling short at the upper band. Again, this can be completed for different timeframes and markets to determine if possible countertrend trading strategies might be more viable.

Now, talking about trend and countertrend strategies – would you like to know which works better based on my experience with almost 1,000 strategies in actual trading from traders/ system developers from all around the world? 

Then check out: www.systemtradingunleashed.com 

Martin and the STU team

 

 

[1] Keith Fitschen: Building Reliable Trading Systems

Finally end the frustration and confusion of getting started in systematic trading

✓  The 6 key steps to fast-track your system trading success today ✓  The secrets of what to do and what NOT to do – saving you time, money and endless frustration ✓  From a veteran broker who has executed and analyzed almost 1000 different trading strategies over his 15 year career – so he knows what works in real trading and what doesn’t!

DISCLAIMER: Trading involves significant risk of loss and is not suitable for everyone. People can and do lose money. Hypothetical results have many inherent limitations. Past performance is not necessarily indicative of future results.

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