Updated: Aug 14, 2020
Following the 2008 financial crisis, the term 'leverage' became a dirty word. Consumers were over-leveraged with jumbo mortgages, banks leveraged their equity as much as 30 to 1, and corporations were drowning in debt. Leverage is a double-edged sword, amplifying not only the upside, but also the downside of asset performance.
Consumers use leverage in all aspects of their life. They use credit cards to borrow money for funding short-term purchases, mortgages to finance their homes, and potentially borrowing against 401K plans or life insurance policies. There is typically a cost to borrow money. The average credit card interest rate is 18.6%, and current 30-year mortgage rates are roughly 3.0%. This type of borrowing is usually what people conceptualize when thinking about leverage. But how should futures traders think about trading on margin and leverage?
Unlike stock trading, futures exchanges and brokers require traders to post margin when trading a futures contract. They are not required to fund the entire value of the contract they are trading. For example, the CME E-mini S&P 500 futures contract value is equal to 50 times the S&P 500 Index value. Currently the S&P 500 Index price is $3,351, so the notional value of the futures contract is $167,550. However, the CME exchange currently only requires $12,000 to trade one contract. Therefore, they are providing leverage similar to any other form of borrowing. There is one key difference - there is there is no direct cost for this leverage, its essentially free leverage! This certainly beats paying 18.6% on your credit card balance.
Leverage, if used conservatively, can be a powerful tool to amplify returns. However, in the world of derivatives, it can be very difficult to estimate how much leverage you are actually using and how much capital you need for your trading strategies. At Algorithmic Futures, we've crafted portfolios of trading algorithms and provide recommended account sizes based on the required margins for those trades and expected total portfolio drawdowns.
Algorithmic Futures optimizes the portfolio construction so that our backtest has approximately -30% maximum monthly drawdown. While this typically equates to 35%-40% on a daily time-frame, we believe this offers a relatively conservative approach. This level of drawdown is much lower than the S&P 500 Index, which experienced roughly -58% drawdown during the 2008 financial crisis. If investors have an expectation for the level of drawdowns, this helps reduce emotion and prevent rash decisions making during drawdowns. While there are inherent risks to trading futures contracts, Algorithmic Futures trading strategies are designed to provide attractive risk-adjusted returns, with what we believe is conservative use of leverage.