## What are the main factors for the Algorithmic Trading Strategy?

## Algorithmic trading factors could provide you more accurate ideas

Do you still remember what Algorithmic Trading is? If you are not sure, please check the previous article from Yaonology. It provides a detailed article for algorithmic trading strategies for the beginner.

In this article, we will mainly focus on factors for algorithmic trading strategies.

**What are those factors???**

Yaonology is going to tell you!!!

First, Yaonology is going to introduce some essential numbers for the SP500 algorithmic trading analysis. The below picture shows the important data analysis for SP500 and the explanation of each one.

**Net Profit**: It means profit minus loss. The algorithmic trading strategy will bring you high profits with lower risk. In this picture, it means in the past 24 years, the invest cost $10,000 has increased 60 times

**Total Closed Trade**: In the past 24 years, it has been up to 109 transactions.

**Percent Profitable**: This strategy can get 78.9% winning percentage.

**Profit Factor**: Divide all the money you make by the money you make, so each money you make will be seven times the amount you paid. The above 4 is a good number.

**Max Drawdown**: The max return value is 4.74%.

**Avg Trade**: In average, each transaction earn value is 55.37%.

**Avg # Bars in Trades**: The average number of transactions is 37 days.

After understanding those names and numbers, you must curious about how to define the number is good.

The above are essential nouns to understand the primary analysis data from algorithmic trading for SP500.

Now, you may be wondering why those numbers are trustable.

There are three vital factors to define what is the great number for this strategy:

**Net Profit – Higher Profit, Lower Risk****Percentage > 70%****Profit Factor > 4**

Moreover, the below photo shows why the data from Yaonology is credible.

## Statistic report for different SP500 strategies!

This is the graphic to show **Benchmark(SP500)** and **Yaonology Algorithm(SP500)**.

The data calculated the return from 1994 to 2018 for both two and get the results.

**Statistic result:**

The highest point in this distribution is mean, and it points out the Yaonology Algorithm(SP500) has a higher mean than Benchmark(SP500).

Besides, the width means risk in this distribution. The wider indicates that a more significant change of the return, the risk is higher.

This graphic demonstrates that the mean is higher from the Yaonology side, and Yaonology has lower fluctuating since the width is smaller.

Therefore, those results point out **Yaonology has lower risks**.

According to this statistic, we can see **Yaonology** has an excellent algorithm trading strategy to analyze SP500.

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