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When I first started trading, I used to beat myself up when my equity curve was either losing money or not growing consistently like I wanted it to. Consequently, I would constantly search for better entries, better systems etc. It finally dawned on me that there was a strong correlation to my equity curve and ES (S&P mini futures) volatility. My pnl would increase rapidly during periods of high volatility and would remain stagnant in periods of sideways or up-grinding markets. Contrary to pundits and pushy trading educators, traditional (albeit boring) academic finance can be a value-added tool in the retail trader’s arsenal. Stephen J Taylor introduced the notion of Stylized Facts, which provide great insight into our basis for understanding volatility and the best scenarios for intraday trading. In Asset Price Dynamics, Volatility, and Prediction Taylor lists some Stylized Facts for intraday returns: Intraday returns have a fat-tailed distribution, whose kurtosis increases at the frequency of price observations increases. Intraday returns from traded assets are almost uncorrelated, with any important dependence usually restricted to a negative correlation between consecutive returns. There is a substantial positive dependence among intraday absolute returns, which occurs at many low lags and also among returns separated by an integer number of days. The average level of volatility depends on the time of day, with a significant intraday variation. There are short bursts of high volatility in intraday prices that follow major macroeconomic announcements. What can we learn professor Taylor’s study? One, its really important to break intraday trading in futures or equities into timeframes. Traders make money by being on the correct side of substantial price fluctuations; however, if one is trading during a period of low volatility the likelihood of profitable scalp trading is very low. Two, bursts of volatility following major macroeconomic events can offer savvy traders great opportunities to take advantage of technical chart patterns. Thirdly, we also know that volatility comes in bunches. Meaning that there is a strong likelihood that periods of larger price movement tend to cluster together. Lastly, traders can use this to extrapolate the best times of day for a particular style of trading. For example, during the first hour (initial balance) traders might use a scalping strategy as a opposed to a trend following strategy, while in the afternoon a trader might be better served to hop on the established trend for the day. In conclusion, if retail traders can align strategies with probable periods of high and low volatility they will see their overall equity curve increase exponentially. Green Trading, Voltrader
