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Algorithm Statistics
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Overview

## Introduction

The Algorithm Statistics section of the documentation will cover key statistics as well as advanced concepts about the ScaleTrade algorithm.
Key statistics includes Trading Frequency, Net Profit, Win Rate, Profit Factor, and Drawdown.
Advanced concepts includes Market Neutrality, Slippage and Latency, and Alpha Decay.
All of these statistics are generated based on the current selection of securities that the ScaleTrade algorithm is trading. The official list of these securities, including the parameters used, can be found within the ScaleTrade Discord, for all ScaleTrade members.

# Key Definitions

Trading Frequency refers to the rate at which the algorithm enters and exits positions. These rates fluctuate from security to security. However, by being able to calculate the average rate across all securities in the trading pool we can generate a rough estimate for out-of-sample securities. A variety of factors influence this value, including the security's liquidity, market conditions, algorithm settings, and algorithm resolution.

## Net Profit

Net Profit refers to the percentage of profit generated over a given period of time. In our statistics section, we will observe the net profit for securities generated over varying time periods and how these numbers allow us to make inferences about the algorithm's performance. The general formula for net profit is as follows:
$NetProfitPercent=(\frac{EndingBalance}{StartingBalance}-1)*100$

## Win Rate

Win Rate is the percentage of trades won out of the total amount of trades taken. These refer to round trip trades, where an entry and exit are both submitted fully closing the position. We will explain how win rate factors into the algorithm, how it relates to trading frequency, and what the ScaleTrade algorithm's win rate means. The general formula for win rate is as follows:
$WinRatePercent=(\frac{WinningTrades}{TotalTrades})*100$

## Profit Factor​

Profit Factor is a value that represents the ratio of gross profits to gross losses. A profit factor of 1 or greater denotes a profitable system, whereas any profit factor below 1 determines a losing system. In this section, we will observe the profit factors generated across the varying backtests and what they mean. The formula for profit factor is as follows:
$ProfitFactor=\frac{GrossProfits}{GrossLosses}$

## Drawdown

Drawdown refers to the maximum difference between the portfolio's maximum value and any point thereafter. We will be observing the relationship between the net profit and the drawdown of the algorithm, and how these two can be used to determine performance against the underlying. Drawdown can be calculated as follows:
$DrawdownPercentage=\frac{PortfolioMaximumValue}{LowestSubsequentPortfolioValue}$

## Market Neutrality

A Market Neutral algorithm is an algorithm that does not have a bias toward a long or short market regime. This means that it enters and exits both long and short positions with the same conditions, with the goal of profiting in both a bullish and bearish market.

## Latency

Latency refers to the time it takes for an order to be sent from the trader's machine to the exchange to be filled (can be thought of as general internet latency). Because the ScaleTrade algorithm isn't a high-frequency trading (HFT) algorithm, we won't be going in-depth into the logistics behind latency. It is just a factor to be considered when trading regardless of using ScaleTrade or not and should be actively monitored should you be prone to unstable internet connections.

## Slippage

Slippage refers to the gap between the bid and ask price for a security. This range causes orders to be filled at a rate worse than optimal and often leads to a minor loss when the position is filled. Market orders are susceptible to slippage, as they focus on getting filled rather than filling at a good price. We will be discussing ways to limit slippage, the different approaches we will be offering, and how slippage affects our returns.

## Alpha Decay

Alpha Decay is a term used to describe the loss in predictive power of an alpha model over time. Alpha is a metric used to determine an algorithm's ability to beat the market, hence making ScaleTrade's algorithm an alpha model. The phenomenon occurs for a variety of reasons and we will be covering them in the Alpha Decay section.