Magik Analysis

Overview

Magik Analysis is a stock and crypto market analysis tool which enables running complex trading strategies over historical datasets.

Technologies Used

  • AlphaVantage: API used for fetching and caching historical data
  • Python: core language for analysis engine

Description

Magik Analysis aims to simplify stock and crypto analysis by abstracting the strategy design component of backtesting. Users are able to create unique trading strategies using either provided indicators or by implementing custom indicators, which can be used as part of a trading strategy. Strategies are defined using JSON, parsed, and fed through a logic engine that asserts whether the provided criteria were triggered and keeps track of the performance of the strategy over historical datasets. Such datasets can be provided locally or fetched from the AlphaVantage API.

Trading strategies in MAGE are defined using JSON configuration files. This declarative approach allows you to build complex conditional trading logic without writing code.

Structure

Basic Template

{
    "name": "Strategy Name",
    "description": "Strategy description",
    "dataSpecifications": [...],
    "signals": [...],
    "actions": [...]
}

Top-Level Fields

Field Type Required Description
name string ✓ Strategy identifier used in reports and output files
description string ✓ Human-readable explanation of the strategy logic
dataSpecifications array ✓ Define symbols, data sources, and indicators
signals array   Reusable boolean conditions that can be referenced in actions
actions array ✓ Trading instructions (buy/sell) with trigger criteria

Data Specifications

Defines the market data and technical indicators required for your strategy.

{
    "symbol": "6B.FUT",
    "source": "LocalFiles",
    "marketType": "FUTURE",
    "timeSeries": "1h",
    "indicators": [...]
}

Fields

Field Options Description
symbol string Ticker symbol or $1 as placeholder
source LocalFiles, AlphaVantage Data provider
marketType FUTURE, SPOT, CRYPTO, EQUITY Asset classification
timeSeries 1h, DAILY, etc. Candle time resolution
indicators array Technical indicators to compute

Indicators

Each indicator calculates a technical value that can be referenced in your strategy logic.

{
    "name": "rsi",
    "identifier": "RSI_14",
    "config": {
        "real": "close",
        "timeperiod": 14
    }
}
Field Description
name Indicator function: rsi, sma, delta, sbh, var_change_pct
identifier Variable name used to reference this indicator in criteria
config Indicator-specific parameters

Common Indicators

RSI - Relative Strength Index

{
    "name": "rsi",
    "identifier": "RSI",
    "config": {
        "real": "close",
        "timeperiod": 14
    }
}

SMA - Simple Moving Average

{
    "name": "sma",
    "identifier": "SMA_50",
    "config": {
        "real": "close",
        "timeperiod": 50
    }
}

Delta - Change between two points

{
    "name": "delta",
    "identifier": "DELTA_RSI",
    "config": {
        "indicator": "RSI",
        "d1": 0,
        "d2": -6
    }
}

SBH - Session-Based High/Low

{
    "name": "sbh",
    "identifier": "SBH",
    "config": {
        "pre_session": [0, 5],
        "session_a": [6, 12],
        "session_b": [13, 20]
    }
}

Signals

Optional reusable conditions that act as boolean flags. Once triggered, they remain active until reset.

{
    "identifier": "BULLISH_SIGNAL",
    "criteria": {
        "var1": {
            "symbol": "6B.FUT",
            "var": "RSI",
            "offset": 0
        },
        "op": "lt",
        "var2": {
            "symbol": null,
            "var": 30,
            "offset": 0
        }
    }
}
Field Description
identifier Signal name to reference in actions
criteria Logical condition that activates the signal

Actions

Define when and how to execute trades.

{
    "action": {
        "do": "MARKET_BUY"
    },
    "symbol": "6B.FUT",
    "size": {
        "size": 10,
        "type": "STANDARD"
    },
    "criteria": {...},
    "followUpActions": [...]
}

Action Types

Type Description
MARKET_BUY Open or add to a long position
MARKET_SELL Close long position or open short
SIGNAL_RESET Reset a signal flag to inactive

Size Configuration

Field Values Description
size number Quantity or percentage
type STANDARD, PERCENT Fixed units or % of position (1.0 = 100%)
transform object Optional dynamic sizing function

Transform Example

"size": {
    "size": 10,
    "type": "STANDARD",
    "transform": {
        "method": "rsi_inverse_range",
        "configuration": {
            "symbol": "6B.FUT",
            "variables": ["RSI"],
            "rsiRange": [30, 70]
        }
    }
}

Criteria Logic

Criteria define conditional logic using comparison operators and AND/OR chains.

Structure

{
    "var1": {
        "symbol": "6B.FUT",
        "var": "close",
        "offset": 0
    },
    "op": "gt",
    "var2": {
        "symbol": "6B.FUT",
        "var": "SMA_50",
        "offset": 0
    },
    "and": [...],
    "or": [...]
}

Variable Object

Field Description
symbol Symbol to reference, or null for global variables
var Variable name (see Variable Reference below)
offset Lookback period: 0 = current, -1 = previous bar, -6 = 6 bars ago

Comparison Operators

Operator Meaning
eq Equal to
gt Greater than
lt Less than
gteq Greater than or equal to
lteq Less than or equal to

Logical Operators

  • and: Array of criteria - ALL must be true
  • or: Array of criteria - ANY can be true

Example: Complex Criteria

{
    "var1": {"symbol": "6B.FUT", "var": "RSI", "offset": 0},
    "op": "lt",
    "var2": {"symbol": null, "var": 30, "offset": 0},
    "and": [
        {
            "var1": {"symbol": "6B.FUT", "var": "close", "offset": 0},
            "op": "gt",
            "var2": {"symbol": "6B.FUT", "var": "SMA_50", "offset": 0}
        },
        {
            "var1": {"symbol": "6B.FUT", "var": "position", "offset": 0},
            "op": "eq",
            "var2": {"symbol": null, "var": false, "offset": 0}
        }
    ]
}

This reads as: “RSI is below 30 AND close is above SMA_50 AND no position is open”

Variable Reference

Market Data

  • open, close, high, low, volume

Timestamps

  • timestamp.hour - Hour of day (0-23)
  • timestamp.day - Day of week
  • timestamp.minute - Minute

Indicators

Use the identifier defined in your data specifications:

  • RSI, SMA_50, DELTA_RSI, etc.

Position Data

  • position - Boolean, true if position is open
  • position.quantity - Current position size
  • position.pnl - Unrealized P&L

Signals

Reference signal identifier names directly:

  • BULLISH_SIGNAL, TREND_ACTIVE, etc.

Portfolio

  • portfolio - Portfolio object with all positions

Complete Example

{
    "name": "RSI Oversold Long",
    "description": "Buy when RSI drops below 30 and price is above 50-day SMA",
    "dataSpecifications": [
        {
            "symbol": "6B.FUT",
            "source": "LocalFiles",
            "marketType": "FUTURE",
            "timeSeries": "1h",
            "indicators": [
                {
                    "name": "rsi",
                    "identifier": "RSI",
                    "config": {"real": "close", "timeperiod": 14}
                },
                {
                    "name": "sma",
                    "identifier": "SMA_50",
                    "config": {"real": "close", "timeperiod": 50}
                }
            ]
        }
    ],
    "signals": [
        {
            "identifier": "OVERSOLD",
            "criteria": {
                "var1": {"symbol": "6B.FUT", "var": "RSI", "offset": 0},
                "op": "lt",
                "var2": {"symbol": null, "var": 30, "offset": 0}
            }
        }
    ],
    "actions": [
        {
            "action": {"do": "MARKET_BUY"},
            "symbol": "6B.FUT",
            "size": {"size": 10, "type": "STANDARD"},
            "criteria": {
                "var1": {"symbol": null, "var": "OVERSOLD", "offset": 0},
                "op": "eq",
                "var2": {"symbol": null, "var": true, "offset": 0},
                "and": [
                    {
                        "var1": {"symbol": "6B.FUT", "var": "close", "offset": 0},
                        "op": "gt",
                        "var2": {"symbol": "6B.FUT", "var": "SMA_50", "offset": 0}
                    },
                    {
                        "var1": {"symbol": "6B.FUT", "var": "position", "offset": 0},
                        "op": "eq",
                        "var2": {"symbol": null, "var": false, "offset": 0}
                    }
                ]
            },
            "followUpActions": [
                {
                    "action": {"do": "SIGNAL_RESET", "signal": "OVERSOLD"}
                }
            ]
        },
        {
            "action": {"do": "MARKET_SELL"},
            "symbol": "6B.FUT",
            "size": {"size": 1.0, "type": "PERCENT"},
            "criteria": {
                "var1": {"symbol": "6B.FUT", "var": "RSI", "offset": 0},
                "op": "gt",
                "var2": {"symbol": null, "var": 70, "offset": 0}
            }
        }
    ]
}

Key Features

  • Backtesting of complex trading strategies
  • Caching of historical candle datasets
  • Generation of reports, including strategy trades and performance
  • Complex logic engine for handling strategies

What I Learned

I have worked with market data before, so this project was really about taking the knowledge I had already built on other projects and rolling it into this idea. That being said, I did explore some public Python libraries for trading indicators and used the AlphaVantage API for the first time. This was also the first time I had worked with futures data, so I learned about some of the complexities involved in contract rolling and had to implement a data aggregator to roll all the data into a single set.

← Back to Projects