Strategy lab
Every strategy from 151 Trading Strategies and all 101 Formulaic Alphas as formulas you can edit and backtest on ten years of daily stocks, ETFs, futures, forex and crypto data. Free, in your browser.
18.2CryptocurrenciesBacktestProxy
Artificial neural network
Forecast short-term bitcoin moves with a neural network fed technical indicators such as moving-average gaps and momentum. The lab’s version trades a simple vote of those inputs instead of training a network.
Proxy. No network is trained: the inputs are combined with equal weights. Crypto trades every day, so annualisation uses 365 days.
Edit anything; the result updates as you type. Lines like window = 20 become sliders.
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Hypothetical backtests on daily closes with no slippage unless you add costs. Survivorship bias applies: the stock list is today’s large caps. For learning, not investment advice. Data: Yahoo Finance via yfinance.
- Source
- 151 Trading Strategies
- Section
- 18.2 · Cryptocurrencies
- Asset class
- Crypto
- In the lab
- Full backtest
Artificial neural network (18.2)
Forecast short-term bitcoin moves with a neural network fed technical indicators such as moving-average gaps and momentum. The lab’s version trades a simple vote of those inputs instead of training a network.
Key equation
Lab formula
// Vote of three technical inputs the paper feeds to its network
ema_gap = sign(ema(close, 10) - ema(close, 30))
momentum = sign(close / delay(close, 14) - 1)
ma_gap = sign(close - sma(close, 50))
(ema_gap + momentum + ma_gap) / 3No network is trained: the inputs are combined with equal weights. Crypto trades every day, so annualisation uses 365 days.
How the backtest works
The formula is evaluated for every asset on every day. Its values become positions at that day’s close, using the portfolio rule you pick, and earn the next day’s close-to-close return. Costs are charged in basis points on the amount traded. Everything runs in your browser on daily data from Yahoo Finance, adjusted for splits and dividends.
More in Cryptocurrencies
Source: Kakushadze, Z. and Serur, J. A. (2018). 151 Trading Strategies. Palgrave Macmillan. SSRN 3247865. Summaries are our own.