  Backtest is a way of financial risk evaluation which helps to analyze how our
trading algorithm would work in markets with past time frame. The high
volatility situation has always been a critical situation which creates
challenges for algorithmic traders. The paper investigates different models of
sizing in financial trading and backtest to high volatility situations to
understand 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 be
controlled using short and long positional size. The paper also investigates
stocks with AR, ARIMA, LSTM, GARCH with ETF data.
