Max trading system indicators serial#
If this serial correlation isn’t considered correctly, we get bad estimates for future drawdowns. If there are crashes, all open positions tend to move in the same direction, for several days.
values not normally distributed, frequent outliers. But even with several years of backtest/simulation data this is still a small set for a reliable prediction of future behavior. Usually we work with daily return values. To summarize, the equity curve shows quite some problematic properties: Even the “arithmetic average” isn’t well defined in such a case. This makes it very hard to describe the properties of such an equity curve analytically. But the volatility varies fast, values are not normally distributed, there are many outliers (fat tails). Mathematically one considers the daily returns of this equity curve. The segments of an equity curve of a trading strategy is the combination of several random walks (while one or more positions are open) or a constant (if there is no open position). The least common starting point in evaluating the performance of indices, benchmarks, portfolios or trading strategies is the resulting equity curve. In a review of existing performance measures it became obvious, that most measures don’t cope very well with return distributions other than the normal distribution, with serial correlation of returns and other non-linearities. Should be a stable measure: small changes in Portfolio, Basket or system parameters should result in small changes of SysQ. Should work for all types of trading systems (Daily, intraday) all asset classes (stocks, Commodities, Currencies, etc) and even price series. Should be independent of time frame or length of equity curve. Should return the same number after position sizes / leverage are changed. Instead of describing the exact properties of the historical (past) equitiy curve it should say something about the future prospects of the trading system. Should be a practical, useful number which relates to an experienced property of the trading system. The data showed that over the past 5-years, the indicator that performed the best on its own was the Ichimoku Kinko Hyo indicator.We had the following design goals in mind when we developed SysQ: This is just for illustrative purposes only! Moving on, here are the results of our backtest: Strategy This means if we initially had a long position when the indicator told us to sell, we would cover and establish a new short position.Īlso, we were assuming we were well capitalized (as suggested in our Leverage lesson) and started with a hypothetical balance of $100,000.Īside from the actual profit and loss of each strategy, we included total pips gained/lost and the max drawdown.Īgain, let us just remind you that we DO NOT SUGGEST trading forex without any stop losses. We simply cover and switch position once a new signal appears. We are trading 1 lot (that’s 100,000 units) at a time with no set stop losses or take profit points. 
Using these parameters, we tested each of the technical indicators on its own on the daily time frame of EUR/USD over the past 5 years. Cover and go short when conversion line crosses below base line Cover and go short when RSI crosses below 70Ĭover and go long when the conversion line crosses above baseline. Cover and go short when Stoch % crosses below 80.Ĭover and go long when RSI crosses above 30. Cover and go short when the daily closing price crosses below ParSAR.Ĭover and go long when Stoch % crosses above 20.
Cover and go short when MACD1 crosses below MACD2.Ĭover and go long when the daily closing price crosses above ParSAR. Cover and go short when the daily closing price crosses above the upper band.Ĭover and go long when MACD1 (fast) crosses above MACD2 (slow). IndicatorĬover and go long when the daily closing price crosses below the lower band. For now, just take a look at the parameters we used for our backtest.
You’ll learn more about this in your future studies.
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