The Experience attribute is a filter for statistical significance - it's impossible to rule out luck from a track-record with a single trade! The more data you feed the system, the more reliable the assessment!

Lack of experience seriously handicaps a DARWIN´s D-score. D-scores for DARWINs below an Experience grade of 10 are penalized - the further from 10, the heavier. The good news is that Experience is the only Attribute that only grows - it CAN´T fall.

A 10 is granted for Experience equivalent to 1 full year of non-stop, daily trading of uncorrelated assets with homogeneous leverage and duration. Or, a 10 grade in Experience = 12 D-Periods, if you will.

D-Period

Experience is tracked in D-Periods.

1 D-Period is approximately equivalent to one month (22 market days) of daily trading.

BUT: D-Period doesn´t just credit time. It accounts for market exposure, as follows:

  • Independent trading decisions - e.g. multiple simultaneous trades in a single asset (or highly positively correlated assets) accrue the same experience as a single trade in that asset
  • Scattering of length of individual positions
  • Scattering of D-Leverage across individual positions 

Global D-Score is penalized for all strategies with Experience below 12 D-Periods - the heavier, the further away from 12 D-Periods. Similarly, trades further away in history than 12 D-Periods are ignored for the scoring, to ensure that analysis is focused on the most recent (and therefore, relevant) data.

In order to collect 1 D-period of experience, any trader needs to meet 2 criteria:

  • 15 trading days => Days in which the trader has operated (buy, sell, partial sell, etc.)
  • 18 representative trading decisions. We measure how representative a decision is based on 2 factors: D-leverage and Duration. In fact, we calculate every single position's representativeness with the following formula: Market Exposure = D-leverage * Sqrt Time

We grant 1 full representative decision to the position with the highest exposure within the last 15 trading days. With this one acting as a benchmark, we calculate how representative the other positions, opened in the last 15 trading days, are.

EXAMPLE

Let me illustrate this with an example with just 2 positions:

  • POSITION 1:  D-leverage of 30 and 60 minutes with a total market exposure of 232.37 (30*sqr 60). 
  • POSITION 2:  D-leverage of 50 and 45 minutes with a total market exposure of 335.41 (50*sqr 45).

Darwinex calculates the market exposure of all the positions closed over the last 15 trading days -duration in minutes- and use the one with the highest market exposure as a benchmark -in our example position 2-. This position -the most exposed- will be granted 1 representative trading decision and Darwinex will calculate the "representativeness" for the rest using this as a benchmark. 

In our example, the position with the highest exposure has yielded a value of 335.41. Darwinex grants this position 1 representative decision. In order to calculate the "representativeness" of position 1 in the above-mentioned example, we need to divide the market exposure of this position by the most exposed one: 232.37/335.41 = 0.6927. Therefore, these 2 positions make 1.6927 representative decisions.  In order to get a D-period, you´ll need 18 in more than 15 trading days as explained in this article.

D-Period Duration Chart

This chart displays a DARWIN’s cumulative experience in D-Periods, plotting natural days required to clock 1 D-Period on the vertical axis.

The graph is very useful to assess how active a DARWIN is, and how long it requires to clock a full month in the market. It´s impossible to clock it in less than 15 days, and there´s no higher bound.

There are two core purposes to it.

  1. The first is comparing experience apples-to-apples across strategies. A scalping strategy with 5 D-Periods proves the same experience as a swing strategy with 5 D-Periods - despite radically different trading styles.
  2. The second is to assess trading intensity: Darwins with stable trading intensity -horizontal graph without spikes- are likely more disciplined and predictable - and thus investable - than others where spikes likely hint at changes to the strategy.

To keep things up-to-date, data older than 12 D-Periods does not count.

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