Not to mention swing or position strategies where trades can last weeks. It should be avoided to analyse past static charts. I have seen this many times, people just deploy past charts and validate strategy against the charts. The human brain is extremely good — and creative — at finding patterns, so just finding the patterns on past charts is not enough. An empty right side of the chart is needed to feel the strategy and understand how do you perform under those conditions.

Additionally, a common mistake is to avoid analysing simulated trades — to avoid analysing trades in general —. You can learn from profit or loss trades and identify conditions that might lead to generating filters that improve profitability.

Strategy #1: RSI2

It is better to try and post-analyse two hundred trades than just test trading one thousand ones. It is also important to correlate and annotate market conditions to each trade, i. This will allow to further enrich the statistical analysis and further refine the strategy. While discretionary trading has a reputation of being closer to sorcery than to science, there is nothing far from it to be true. Although a certain degree of art is required, it can be considered a more heuristic experience than esotericism. The scientific part of discretionary trading comes from the rules of engagement i.

Statistics must be collected for backtesting, demo and live trading stages. Contrary to what you might think it is not needed to do complex analysis, as you can get quite interesting information based on very basic statistics figures.

234# KiwiK Trading System

The above figure shows the statistics provided by the tool. The whole trade details can be exported to Excel to further analyse the results, but even this basic set will provide enough information to validate or discard the strategy. In this example, the strategy has been selected to cover all but the trades have been performed just during the first month at the time of writing this article as stated, not enough sampling data for a meaningful analysis of the strategy.

The information is anyway enough to cover the key statistical figures and how they shall be interpreted. This is the obvious count for the number of trades executed detailing the win and loss ones. This is the formula for average profitability per trade, which basically states how much money is made out of each trade on average. A positive number will reflect a profitable strategy, a negative number will reflect a non-profitable strategy:. Depending on the strategy followed you will face longer or shorter sequences of winning or losing streaks.

180# RSI System

Some strategies fail often than others incurring on small losses that are largely recovered with a few winning trades. Others are more compensated and will present a similar number of lengths for winning and losing streaks. The relevance of knowing in advance how many losing trades you can expect from a strategy is relevant to determine what to expect. Your account shall be properly sized to withstand not only this number of loosing streak but a larger one.

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While this is just an indicative factor simulation does not ensure future reliability it is a good indicator on what to expect on reality. In this specific test, we had a maximum of 3 losing trades and a maximum of 6 winning trades. This can be taken as a reference so you shall be prepared to at least twice these figures. Withstanding a long losing streak might be a hard experience, especially if you are stressing the amount of capital you are risking per trade.

Knowing in advance what you might expect shall help you to cope with the turbulence and it would also help to detect when something truly deviates from the original plan so you can pause operations before it is too late. Maximum profit per trade and minimum profit per trade can be misleading. Actually while preparing a strategy, it is good advice to prepare it for a given trade size.

In this particular example, symbol stats leverage and lot size has been arranged so the profit and loss figures are given in FDAX points. This allows later sizing operations to fit our risk. This means that you can later upgrade or downgrade the size based on your trading account and risk profile.

Based on the stats we notice that the maximum losing trade lost For Forex pairs you would also need to incorporate the current exchange rate of the pairs against the base currency of your trading account. My personal view is that you do not need to be too strict with the figures; staying around an acceptable losing figure is easier to operate and allows you to operate fixed lots. Keeping your loses narrowed down is the important part of risk management. You can review sizing on a quarterly basis or simply based on equity curve mid or long term evolution.

It is easier. Note that while trading leveraged derivative instruments such as futures or CFDs, you need to think more in notional value than in actual trading account.

Pin on Forex Trading

You will be required to allocate much less money than the notional value of your investment, but you shall still understand that the leverage counts both for losses and profits. My personal preference is to think always in terms of notional values. It shall be also noted that the maximum percentage or risk per trade really depends on each individual.

There are many ways of determining this value and it is not just related to your trading account but to your available capital and wealth. There are people with less capital but a strong wealth so their capital has relatively small relevance and people with more capital but a weak wealth so preserving their capital is paramount. Your risk profile also plays a significative role. The important point with risk management is to have something in place and to clearly understand what it means for your risk profile, wealth and personal situation.

Which specific risk management shall be applied depends on every individual. Max drawdown simulates the maximum erosion experienced by your trading account during the backtested period. In the course of a downward trend, if the GG-RSI-CCI custom indicator creates golden candlesticks inside its indicator window, it signifies a decreased volatility thus leading to uncertainty in the market sessions. Utilize this strategy at your own risk.

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Like this: Like Loading Leave a Reply Cancel reply. The entry and exit signals are quite straightforward. Go long when the 2-period EMA crosses the 4-period EMA from below and continues higher, with the stochastic being below Conversely, short signals are provided when the 2-period EMA crosses the 4 EMA from above and continues lower, while the stochastic is above You should exit the position when the EMAs cross each other back, or when the stochastic enters the overbought or oversold areas and respectively.

As for the stop loss, you can use a trailing stop with an absolute or percentage value according to your own preference, or you can set an exact stop-loss level. This should be the low of the entry day for a long position, or the respective high for a short position. In any way, a risk-to-reward ratio of at least is advisable to be aimed at. The general trend is bullish and so we will refrain our entries only to long, with-trend, positions. Our first signal is generated at bar 1 when the 2-period EMA black line crossed above the 4-period EMA purple line and the stochastic was below 50, but was edging higher.

We enter on the next bar, at the high of bar 1 , thus at 1. Because it is at 1.