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Backtest is a way of financial risk evaluation which helps to analyze how ourtrading algorithm would work in markets with past time frame. The highvolatility situation has always been a critical situation which createschallenges for algorithmic traders. The paper investigates different models ofsizing in financial trading and backtest to high volatility situations tounderstand how sizing models can lower the models of VaR during crisis events.Hence it tries to show that how crisis events with high volatility can becontrolled using short and long positional size. The paper also investigatesstocks with AR, ARIMA, LSTM, GARCH with ETF data.

Sizing Strategies for Algorithmic Trading in Volatile Markets: A Study of Backtesting and Risk Mitigation Analysis