- Introduction to Quantitative Trading
- Quantitative Trading - Advantages and Disadvantages
- Types of Quantitative Trading Strategies
- Momentum Strategies
- Mean Reversion Strategies
- Market Making Strategies and Day Trading Strategies
- How to Generate Trading Ideas
- Designing A Trading Strategy For Profit
- Backtesting a Trading Strategy - Considerations
- Risk Management of a Trading Strategy
- Risk Indicators - VIX Index and TED Spread
- Plotting the VIX Index and TED Spread in R
- Introduction to Quantmod in R
- Downloading Data Using Quantmod Package in R
- Creating Charts with Quantmod
- Data Analysis with Quantmod in R
- Measuring Overall ETFs Performance
- Quantstrat Example in R - EMA Crossover Strategy
- Quantstrat - EMA Crossover Strategy - Performance and Risk Metrics
- Quantstrat Example in R - RSI Strategy
- Quantstrat Case Study - Multiple Symbol Portfolio
Risk Management of a Trading Strategy
Lastly we should have rules to manage the risk of the strategy. Risk and money management are the most important aspect in a trading strategy. This field focuses on drawdowns, leverage and volatility. It is important that any trading plan contains a risk management approach to minimize drawdowns, by the use of stop loss or stop limit orders, as well as avoid days of higher volatility.
Traders and investors should have in their mind an integral plan to execute trades or enter into a new position. Within this plan, the risk management of transactions and positions is the most important feature in the long term. On many occasions, investors or traders earn great profits in bull markets but they lose all or almost all their portfolio value when a bear market starts.
One of the main concepts in analyzing the risk of a strategy is the Maximum Drawdown that the strategy has. The Maximum Drawdown is defined as the accumulated loss of buying an asset in their highest point and selling at their lowest point during a period of time. Drawdown in contrast, refers to the decline in value in the next period from a previous local maximum.
The Maximum Drawdown is a good measure for funds and portfolio managers to become aware of the maximum possible loss of a strategy in a certain period. The important property of the Maximum Drawdown is that its value was obtained from a real world financial series and is not originated from a model with some theoretical assumptions as many times happens.
Some risk metrics such as the Value at Risk (VaR) of a portfolio assume that the returns of the strategy are independently and normally distributed. In the real word, returns have fat tails and serial correlation, and their distribution differs from a normal distribution. The VaR doesn’t reflect the large losses during the history of the financial market.
The Calmar Ratio is a risk metric that accounts for the Maximum Drawdown of a strategy. The Calmar Ratio is defined as the compounded annualized growth rate divided by the Maximum Drawdown over the same period. Unlike the Sharpe Ratio, the Calmar Ratio cannot be scaled to different time horizons, so portfolios that use the Calmar Ratio should have the same backtesting period.
In order to develop a more realistic approach of risk management, in the past few years, new measures of risk have been proposed that focus more on the drawdowns and Maximum Drawdowns rather than the volatility or VaR. This approach takes into account the drawdown distribution which uses the drawdown (magnitude and duration) to define the loss function.
There are other methods to achieve and appropriate risk management and control risk in trading strategies that are more related with strategies based on single or a few assets. One of these methods is the Constant Proportion Portfolio Insurance (CCPI), which has the rule of adjust the order size when the strategy has a drawdown.
In case of a drawdown, the CPPI will decrease order size faster making almost impossible that the account approach to the maximum drawdown. The method controls leverage with regards to the current drawdown. If the current drawdown increases, the leverage would decrease. A drawback of this method is that it doesn’t prevent for a big drawdown during an overnight gap.
A common method to avoid losses is the usage of a Stop Loss. The common application of the Stop Loss is to exit an existing position whenever its unrealized P&L drops below a threshold. The Stop Loss only works when the market is open. If the prices “gap” down or up when the market opens the Stop Loss order may be executed at a much lower/higher price.
Also, a Stop Loss is a safety tool either in a mean reversion or a momentum strategy. In case of a mean reversion strategy, a regime change from mean reversion to a trending behavior could cause great losses if the account doesn’t have a Stop Loss. Momentum strategies benefit from Stop Loss orders in cases of a reversion in price that could cause drawdowns in the strategy.
As we stated, the risk of a mean reversion strategy is different from the risk in a momentum strategy. This means that the stop loss order is used differently in the two approaches. In a momentum strategy the use of a Stop Loss is more straightforward as it prevents losses when prices reverse. In a mean reversion strategy the price is ranging and the Stop Loss should be greater than the maximum intraday drawdown.