What does the Market Correlation (Mc) attribute tell us about a trading strategy / DARWIN?

This Investable Attribute tries to quantify the value added through the trader's decision making, evaluating his returns versus those of the underlying assets he trades.

What is it?

 

Correlación con Mercado (Mc)

Correlation is a statistical value measuring the relationship between two variables. It is used by Darwinex in the calculation of the Market Correlation (Mc), the Investable Attribute covered in this article.

Market Correlation attempts to quantify the added value generated through the trader's decision making, evaluating their returns versus those of the underlying assets traded.

Why? Well, imagine that a DARWIN investor could obtain the same return as with the DARWIN, simply by investing in the underlying asset in which the DARWIN trades. What incentive would there be to invest in the DARWIN instead of the underlying?

But if a DARWIN improves the returns offered by the underlying assets, value creation by the trader is beyond doubt.

As with the other Investable Attributes, Market Correlation (Mc) is scored from 0-10. It takes into account the last 12 D-Periods of Experience, and can fluctuate up and down.

How is it calculated?

To calculate the score, we compare the DARWIN return graph (excluding commissions, spread and swap) with the return curves of the underlyings traded by the DARWIN.

The more similar the graph, the higher the correlation and thus lower the score the DARWIN will have for the Mc attribute.

Two additional factors are also taken into account:

1. Leverage

The decision to employ more or less leverage in a trade is considered a separate trading decision from the decision to go long or short a given asset, and is included in the formula for calculating the Mc score.

To illustrate this, imagine a trader whose returns are very correlated with the assets which he trades, but who typically increases leverage when the underlying assets' returns are positive, and decreases leverage when the underlyings returns are negative. In this example it is clear that the trader's decision making is creating added value and as such his Mc score will not be severely penalized by our algorithms despite exhibiting a high correlation with the market.

2. Calculated per Position in a given underlying

The Market Correlation (Mc) score is calculated per position in a given underlying

Where can I see the Market Correlation (Mc) score? 

DARWIN Profile

As with the other Investable Attributes, you can find this information in the upper right corner of the DARWIN page.

Barra atributos

NOTE: By placing your mouse over any Investable Attribute you can see the score and a brief description of the attribute.

Investable Attributes tab

Within any DARWIN page, click on the Investable Attributes tab and then on Mc in the horizontal menu.

Market correlation-1

 

Both paths will take you to a correlation analysis of the positions opened by a DARWIN provider in a asset:

Market correlation pie chart

For each currency pair traded, there are three pie charts showing the weight of long and short positions, duration and exposure to the market for the selected period.

On the right hand side you also have access to important information like the total correlation factor and the asset with highest correlation.

Correlation values between -0.30 and +0.30 are considered low

Tips

Below we provide some tips in relation to the Market Correlation (Mc) Investable attribute

1. DARWIN Provider value add

The lower the correlation between the returns of the assets traded and the return of the DARWIN, the higher the value added by the DARWIN provider and the higher the Mc score.

2. Selected timeframe

Calculated correlation can vary significantly depending on the selected timeframe.

3. D-Score impact

Mc has a relatively high weight in the calculation of the D-Score and as such a poor Mc score will have significant impact on the overall D-Score.

Want to learn more?

If you want to know more about the Mc attribute, we recommend this webinar recording from minute 11.45 onwards.