On the predictability of stock prices: a case for high and low prices

This paper contributes to technical analysis (TA) literature by showing that the high and low prices of equity shares are largely predictable only on the basis of their past realizations. Moreover, using their forecasts as entry/exit signals can improve common TA trading strategies applied on US equity prices. We propose modeling high and low prices using a simple implementation of a fractional vector autoregressive model with error correction (FVECM). This model captures two fundamental patterns of high and low prices: their cointegrating relationship and the long-memory of their difference (i.e., the range), which is a measure of volatility.