These are very strange market characteristics of every day up the stairs to falling off a cliff – it shows you how silly and irrational markets really are (there goes the efficient market hypothesis).

Even though algorithmic trading systems, like Intraday Futures Trading Bot, thrive on this type of volatility, they will still have increased risk during such a period. When working with long-term statistical-based systems, sometimes bad luck can play out over a handful of trades. Therefore, traders must modify risk management and trade position size to ride through this potentially extended period of uncertainty. With any algorithmic trading systems, nobody knows when the strong trades will come; there is always a chance algorithmic trading systems suffer a couple of bad trades during volatility before the odds begin to play out (see metrics). Traders who trade a position size in excess of their comfort levels will always be forced sellers, and many cannot handle the undue stress of violent swings in the market.

Markets are moving in a massive daily range and still trading close to all-time high prices. To consider how futures algorithmic trading systems may fare during a volatility spike, we need to do some calculations regarding drawdown values. Taking the Emini S&P Futures market (ES) as an example:

• ES is trading in a 3-4% range during a volatility spike, and we must consider that quant systems will have to increase the level of risk they take on each trade; otherwise, they will get chopped to death. Trying to make stops smaller during periods of violent swings is a recipe for disaster and one the markets love to expose.
• Assuming an algorithmic trading system takes a 3% daily range stop on a hypothetical trade, then this equates to 80 ES points per contract (each point is $50), which equals a whopping potential $4k drawdown per contract. Ordinarily, from a pure dollar value, this would be considered large, but at current prices, it would be unrealistic to consider a 3% move extensive. If the ES is moving 3 to 4% daily range, then the dollar value per trade is going to be far greater than the historic dollar value.

Many investors look at past historical values as something set in stone but never heed advice to normalize drawdown values to current levels – please see the following blog post, which outlines: Why drawdown can be a very misleading metric.

The reason we advocate day trade-only algorithmic trading systems is because swing trading systems often give up a whole year’s gains during a powerful move down, especially in futures markets where the talking heads fail to mention the moves overnight, which can be just as brutal. For example, the Dow Jones futures were limit down Tuesday night before rallying up – this is another 4 to 5% decline which is ignored by the average investor not accustomed to 24-hour trading. The ES market has declined 12% from the peak, so pretty much most swing traders will be heavily underwater. In contrast, day trading systems only need a couple of decent trades to make some good gains should the volatility continue.

Investors should always consider their own position size relative to the current market range and dollar value per contract. Markets move only in percentages; always consider that any trading systems have to assume some level of risk when trading a volatility spike. If the range is large, then often stops have to be large. Risk and position size should always be adjusted to take this into account, especially margin requirements which are often doubled by brokers during a volatile period. Consider a swing trading system holding through this decline, a 12% decline, including the overnight sessions, will easily lead to a margin call for most investors who are then forced to sell at the low, whereas if they had taken a cautious approach to risk, they would have recovered most of this loss simply two days later. If traders cannot handle a potential loss of 3% market range per contract, they should consider changing their position size or simply halt trading during these periods. Day trading algorithmic trading systems thrive on volatility, so it defeats the purpose of using them if you cannot handle the risk; it would be more suitable to simply invest in a different type of longer-term low-risk investment.

Futures trading can entail a tremendous level of risk. Unfortunately, for investors with low levels of capital, they must still trade a minimum of 1 contract; you cannot trade 1/2 contract or 1/4 contract, so you must assume the current market risk – there is no way to avoid that risk if you want to trade during a volatile period. Our advice during a volatility spike is to trade a position size that does not make you a forced seller and allows you to comfortably take day trading stops of 2-3% should the market be operating in a similar range. It must always be reiterated that the markets care very little about points or dollar value but work primarily in percentages. The talking heads and headlines show the Dow falling 1000 points as a historical event. However, in reality, this one-day drop does not even feature on the list of biggest percentage drops historically.

Investing your own money is a very difficult thing to do. To properly invest, you need to emotionally detach yourself from your money. Many investors are incapable of removing their “gut feelings” from the equation even when using algorithmic trading systems. Those who hire advisors and buy-and-hold style money managers are also at the mercy of volatile markets. The investors often find themselves second-guessing their advisor and perhaps searching for another, usually with very little patience. As the market heads back up, the investor feels satisfied with their new advisor—until the next downturn. The whole process will begin again and later repeat itself. This behavior makes it difficult to achieve personal investment goals, and we find the average investor constantly succumbs to irrational exuberance and excess risk during an up period and then has no stomach to handle a drawdown. Many studies in behavioral finance have shown the average investor to consistently lose money even with very strong long-term funds.

Please see the following blog post, which outlines: Why You Need to Use Alternative Data