Intro

SpreadFighter is quite different from the usual retail-client trading and analytical solutions.

The platform's models do not provide completely ready-made "signals", "entry points", etc. SpreadFighter gives people a good tool to find inefficiencies/gain market advantage in an efficient market.

<aside> 💡 The market is a closed environment and a zero-sum game. If someone is making money, then someone is losing. There is no other way around it. The model of giving away naked signals, publicly available copy-trading, etc. is a priori a failure. If you do not understand this, make sure you understand why.

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In order to maximize the full potential of SpreadFighter trading and analytical tools, you need the skill of research, namely:

  1. A basic understanding of the math and knowledge of market mechanisms
  2. A basic understanding of how various market phenomena will be reflected in market data (volatility, volume, tape speed, liquidity, open interest, correlation, classic and synthetic spreads, etc.).

<aside> 💡 Example: "inflation rises → Fed raises key rate → credit becomes more expensive → production shrinks → people get laid off → purchasing power falls → demand falls → prices fall → inflation falls → Fed lowers rate", etc.

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  1. The skill of asking the right questions and specific tasks.

<aside> 💡 "What altcoin should I buy with $100 so I can have a Lambordgini tomorrow!" - is a bad question. "How will the volatility of a particular asset change relative to the broad market during a pump-and-run? Through what function of math can I give an unambiguous answer that the volatility has changed?" - good questions.

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  1. Basic understanding of risk management and the allocation of winrate, gains and losses in different types of strategies.

If you have competencies in the above points, the use of professional analytical tools will be much more productive, because: there will be an understanding:

  1. what task the user is facing,
  2. what models and tools can help to solve this task.

Below are several presets of workspaces, as well as examples of using the platform for different types of strategies, approaches and time frames: from short-term inefficiencies, to long-term portfolio trades and synthetic positions.

Example trades

Layering in the RUNEUSDT Perpetual limit order book

<aside> 💡 The user is looking for layering algorithms by means of which unscrupulous market participants influence prices. The activity of such participants is reflected in liquidity, volatility and market depth. The user trades mean reversion to average fair prices after the algorithm is turned off.

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RUNE 24.02.2024 at 12:15 UTC+3 The Layering highlighter pattern indicates the appearance of the layering algorithm in the limit order book.