QuantNova.jl

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Backtesting ​

Run historical backtests with customizable strategies.

<img class="only-light" src="../assets/viz-dashboard-light.png" alt="Backtest Dashboard"> <img class="only-dark" src="../assets/viz-dashboard-dark.png" alt="Backtest Dashboard">

Quick Start ​

julia
using QuantNova
using Dates

# Define strategy
strategy = BuyAndHoldStrategy(Dict(:AAPL => 0.6, :GOOGL => 0.4))

# Historical data
timestamps = [DateTime(2024, 1, i) for i in 1:252]
prices = Dict(
    :AAPL => rand(150:0.1:160, 252),
    :GOOGL => rand(140:0.1:150, 252)
)

# Run backtest
result = backtest(strategy, timestamps, prices; initial_cash=100_000.0)

# Analyze results
println("Total Return: $(result.metrics[:total_return] * 100)%")
println("Sharpe Ratio: $(result.metrics[:sharpe_ratio])")
println("Max Drawdown: $(result.metrics[:max_drawdown] * 100)%")

Built-in Strategies ​

BuyAndHoldStrategy ​

Invest once in target weights and hold:

julia
strategy = BuyAndHoldStrategy(Dict(:SPY => 0.6, :AGG => 0.4))

RebalancingStrategy ​

Periodically rebalance to target weights:

julia
strategy = RebalancingStrategy(
    target_weights=Dict(:SPY => 0.6, :AGG => 0.4),
    rebalance_frequency=:monthly,
    tolerance=0.05
)

Custom Strategies ​

Implement generate_orders(strategy, state):

julia
struct MomentumStrategy <: AbstractStrategy
    lookback::Int
    # ... fields
end

function QuantNova.generate_orders(s::MomentumStrategy, state::SimulationState)
    # Your logic here
    return orders
end

Visualization ​

QuantNova provides built-in visualization for backtest results using Makie.jl.

Equity Curve ​

<img class="only-light" src="../assets/viz-equity-light.png" alt="Equity Curve"> <img class="only-dark" src="../assets/viz-equity-dark.png" alt="Equity Curve">

julia
using CairoMakie  # or GLMakie for interactive plots

spec = visualize(result, :equity; title="Portfolio Value")
fig = render(spec)

Drawdown ​

<img class="only-light" src="../assets/viz-drawdown-light.png" alt="Drawdown"> <img class="only-dark" src="../assets/viz-drawdown-dark.png" alt="Drawdown">

julia
spec = visualize(result, :drawdown; title="Drawdown Analysis")
fig = render(spec)

Returns Distribution ​

<img class="only-light" src="../assets/viz-returns-light.png" alt="Returns Distribution"> <img class="only-dark" src="../assets/viz-returns-dark.png" alt="Returns Distribution">

julia
spec = visualize(result, :returns; title="Daily Returns")
fig = render(spec)

Rolling Metrics ​

<img class="only-light" src="../assets/viz-rolling-light.png" alt="Rolling Metrics"> <img class="only-dark" src="../assets/viz-rolling-dark.png" alt="Rolling Metrics">

julia
spec = visualize(result, :rolling; title="Rolling Performance", window=63)
fig = render(spec)

For a complete walkthrough with all visualization types, see the Backtesting Demo.