Who is behind Matrix?

MatrixTrade.com is the brainchild of seasoned trader and economist Ed Matts. Ed was one of the earliest technical traders in London in the 1980s, and went on to provide analysis for banks and other City institutions, pioneering the use of Elliott Wave and other technical formations.


What do the letters V C and F I T S mean on your analysis chart?

These are the conditions of the instrument or market. Each letter stands for a particular factor that helps determine the best analysis (FITS) and trade set ups (VC). They are all marked out of five.

V is future volatility as opposed current or implied (option) volatility. An instrument which moves by 1% most days is said to be more volatile than one which moves by 0.25% on average. Current or past volatility is measured precisely by Average True Range (ATR), a study on most charting packages. At Matrix, our measure is a forecast volatility and therefore less precise (1 for no volatility, 5 for extreme) but seeks to project future volatility through analysis of market conditions. For example a quiet day before a major event would typically have a low V score such as 1 but the next (event) day would be potentially high such as 5.

C is Clarity. This helps determine probability. The greater the clarity the more we expect a market to follow a certain path and therefore raises the probability of an associated trade. Again, we set a figure between 1 for an very unclear picture, and 5 for the clearest.

What we seek is high volatility (5) and high clarity (5) or what could be described as 'volaclarity'. Clearly we want to stay away from highly volatile (5) unclear (1) markets.

The next part is the Matrix proprietary FITS score. This measures factors that are most likely to affect the future performance of the instrument. For example, the F score would be high for USD instruments immediately after a FOMC rate-setting meeting or in a fundamentally driven trend, but lower at other times in ranging markets. The I score would be high if another market was moving the instrument. The T score would be high if the price action was consistent with establish technical patterns. The S score would be high when the sentiment of human or the processes of algorithmic traders were driving the market.

Besides a better understanding of what is really moving a market, the FITS scores are important in deciding which indicators will work best (both theoretically and historically) and be weighted accordingly.  Be careful using RSIs and even sentiment reports within fundamentally driven trends; understand that economic indicators may produce surprising results when sentiment is extreme, and be circumspect with many isolated indicators when another market is driving the instrument.

Here are the definitions:

F is for Fundamental analysis - the real world study of countries, governments, companies or commodities, determined by economic data such as interest rates, GDP, unemployment levels, and PMIs. We look to identify fundamental trends that can be monitored through such data AND price action.

I is Intermarket Analysis - the dynamic study of the extent to which one market influences another. Matrix seeks to identify correlations (causal or non-causal) in the same or adjacent time periods.

T is Technical Analysis - the study of price action (and other price related data) to identify particular patterns or relationships which markets form, such as triangles, trendlines, Elliott Waves, Fibonacci levels and other well-documented and frequent patterns. Matrix seeks to identify the conditions and markets where particular formations work best or fail.

S - Sentiment Analysis – This is traditionally the study of the views/trades of the market, expressed in such statistics as commitment of traders, and general worry about uncertainty. Matrix seeks to translate the variety of reports and media (social and public) into probable market positions and the likely ensuing effect on price.

However since the growth of algorithmic trading and in particular the explosion of High Frequency Trading since 2008,  the impact of quantitative trading cannot be ignored. Matrix seeks to identify shorter term price action that is repeating itself ‘robotically. in the form of fractals.

In the broader sense, that is, the longer timeframes, sentiment is also taken to include seasonal and cyclical patterns. Matrix seeks to determine and exploit any such repetition. 

These four factors cannot be absolutely precise, so they are scored on the relatively coarse scale of 1-5. Together with the volatility and clarity, we can generate a probability of a particular trade’s success and therefore coupled with the absolute risk/return ration (the target distance divided by the stop loss distance) we generate our ‘Matrix’ score for the trade.

For example, if we consider the Canadian dollar

Future Volatility would be high preceding either an RBC announcement, or through Intermarket, news about oil rig counts or EIA stock levels.
Clarity would depend on whether the instrument’s recent price/action was as expected.
Fundamentals would examine existing (not future) Canadian GDP and other economic reports.
Intermarket would examine the price of oil, for which the CAD is a well-known proxy.
Technical would look at the USDCAD chart, to determine known bullish or bearish patterns
Sentiment would check the current traders position on USDCAD, and also whether there was any uncertainty about future Canadian events.
Quantitative analysis would determine whether a previous price/action fractal, especially in similar market conditions, could be overlaid on to current price/action to generate a map for the future.

What is a Matrix Trade?

Matrix seeks the best trades by combining the highest probability of success with the best risk/reward (RR) ratio. The risk is the distance from the entry to the stop loss (SL). The reward is the distance from the entry to the target price, sometimes called the ‘take profit’, in both cases abbreviated to TP.

We attempt to measure the likelihood of a market following a particular direction through the clarity of that market and the clarity measure (C). The clearer a market is, the higher the probability of it following the projected path to a specific level. However, that is not the same as the probability of a buy or sell trade reaching a specific profit target without hitting a stop loss. That probability is necessarily lower.

We therefore seek a trade that will have the highest probability of reaching a TP determined by our market analysis without it reaching the SL.

Some traders always set a particular RR, eg 2:1, usually just expressed as 2. This is a perfectly acceptable approach to risk management but does not necessarily take into account the market or the probability of success. Some set a TP first and then set a ‘financial’ stop that reflects a particular risk return (Traders Equation). This is also acceptable as it factors in the market and probability of it reaching the target but does not necessarily factor in the probability of the stop being triggered. However neither are optimal, but may do well if the ‘edge’ that suggests the trade already factors in this probability, eg buying / selling a trendline.

We seek to optimise this process by identifying the trades that reflect market conditions the most; that is, trades that are most likely to succeed (highest probability) with a particular entry, SL and TP. Although we put market conditions first and therefore generally place greater emphasis on probability than the RR (even greater than 2) this does not matter. We seek to optimise which trades we take and the amounts by a combination of the probability and the risk/return: the payout. Or as we call it, the Matrix. Our formula is

Matrix Score = Probability% * RR * 10

We multiply by 10 for clarity. Note that the Matrix score is a combination of risk/reward and probability. So it is not simply a percentage risk, ie it is possible for a Matrix Score to exceed 100. This would normally only happen in the longer timeframes. Where the Matrix score is greater than 15 we will take the trade and the extent by which it exceeds 15 also influences the amount we risk. This approach also allows great flexibility for the Matrix trader, as they can enter a trade earlier or later provided their risk return still produces a payout of 1.5 or higher as the probability of the trade is unchanged.. However they may want to adjust the amount they risk accordingly to reflect a lower payout.

When a trade is set but it says NO TRADE this is because it has not met the Matrix threshold of 15. Matrix seeks to identify the best trades across many markets and timeframes and therefore does not need to take every trade or trade a particular market all the time. However, that does not mean the NO TRADE trade is a bad trade, it means it may not over time be as good as a Matrix Trade.

Does each timeframe stand alone?

The complete analysis of the instrument covers all four timeframes, but there is a different commentary and a different trade signal for each timeframe. Also, some of the evidence charts may be slightly applicable to adjacent timeframes. The main charts on the left hand side of the page are always as follows

8 Hour Time Frame = Five Minute candle chart
48 Hour Time Frame = Hourly candle chart
10 Day Time Frame = Daily candle chart
3 Month Time Frame = Weekly candle chart

On some instruments we do not analyse or issue signals for the 8-hour timeframe, as a matter of policy.

The trade signals for each timeframe stand alone. In many cases the signals in some timeframes will act as a hedge for those in the longer timeframes, although by convention, we put the hedge in the same timeframe as the original trade.

When do trades expire?

Day traders should note our specific policy for our 8-hour timeframe signals. If these are not filled, they are closed at the end of the day. The 'end of the day' is defined as follows

European Indices (eg GER30, UK100)                - 2100 UK time (for orders issued before 1800)
US Indices (eg SPX500) and commodities        - 2200 UK time (for orders issued before 1900)
Currencies                                                                - 0000 UK time (for orders issued before 2100)

Orders issued within three hours of the expiry time expire the following day, for example an SPX signal issued at 2000 Monday, expires 2200 Tuesday.

This means that any 8-hour order you see is only valid for the day it is posted, unless it fills before the deadline. If your broker software has a 'good till' feature on the order entry system, you should use that and enter the current date, and the time shown above, to automatically expire the order.

For filled 8-hour trades, and all 48-hour and longer timeframe trades, if the trade is filled it always runs to conclusion, either hitting the target or stop, or in the case of options reaching expiry date, or being explicitly closed. (Sometimes trades are partially closed or 'cut', in which case the remaining part of the trade still runs to these rules). Unfilled orders in these timeframes are implicitly cancelled when we issue a new trade for that instrument in that timeframe.

Double verification : Why am I sometimes stopped out when your trade is still running

Matrix Trade uses a double verification system for its trade signals: both exchange and spreadbetting prices. As our trades are actual trades we rely on actual exchange prices as do many professional/institutional traders for entries and exits. These are available through professional information services such as Bloomberg and Thomson Reuters, but can also be found on the exchange’s own information pages and consumer free services such as Google Finance and Yahoo Finance.

However as we have a significant retail following that uses spread betting companies (where the actual prices are spread) we ensure our trades are also consistent with these ‘spread prices’. In some cases however these prices may be spurious as their algos (that adjust futures prices for cash and vice versa) are sometimes wrong.

In practice, this means we only record a signalled trade if both exchange and spreadbetting prices have traded at our level. If only one price provider reports the entry price being hit we will not record it as a Matrix Trade even though this may mean we have the actual position. Similarly a trade will not be stopped if only one price providers reports it being hit; invariably it is the spread price that hits not the actual price.

Where the position is stopped by one provider, this does mean some of our followers will no longer have the trade but we will. In this instance we will seek the soonest appropriate place to stop the trade so that those stopped can rejoin the trade.

What is the purpose of Multi Time Frames?

Analysing a market across different times frames is very helpful. By generally taking a longer term view and increasingly narrowing it down into the shorter term, this improves analysis by providing context and helps fine tune trading strategies. It also arguably increases the probability of a view and trade being successful.

This is essentially why Matrix distinguishes between different time frames. We use

Next 8 hours       Next 48 hours
Next 10 days      Next 3 Months

We have found these to be the most common periods for perspectives and therefore volatility and cycles.

Markets are believed to be more random and less predictable in the shorter term. Much freely available analysis is driven by price (as opposed to price action) and therefore more likely to analyse a market inside out: transcribing views from the shorter term out to the long term. This is dangerous as it risks giving a disproportionate weight to current as opposed to continued influences and therefore generally downplays fundamental trends that could well be driving a market.

Similarly, swing or position trading strategies that transcend daily ‘noise’ are believed to be more successful than day trading that seeks to take advantage of that noise. Market returns generally support this. If markets are increasingly random in increasingly shorter term time periods, then this would make sense. However, since the explosion of Higher Frequency Trading algorithms since 2008, we have found this robotic noise can be very predictable. After all trading robots are programmed to do the same thing confronted with similar conditions. Trading the noise in the context of a more melodious tune has advantages.

Trading Multi Frames both optimises our trading strategies but also suits different circumstances and profiles.

People trade differently or want to trade differently at times due to their own or market circumstances. At Matrix we therefore aim to cater for this by providing a continued stream of optimised trades in one time frame. If you only ever look at a market in the evening our different time strategies can help you trade medium term. And iif you have a day off then our day trading strategies will hopefully prove a lucrative diversion. Similarly if you are a professional day trader but have conviction with a market, Matrix can help time and maintain a medium term trading strategy.

However, there is a real advantage of trading over multi time frames: It enables the trader to increase or decrease their risk and opportunity in line with market conditions and probability. By trading across periods, we are able not only to fine tune entry and exits (risk returns) for swing or position taking but also leverage at times of more or less favourable volatility. In other words buy/sell more when the probability of strength/weakness is greater or buy/sell less when the risk of possible adverse movements increases.  This enables a number of hedging strategies that can smooth the more volatile and debilitating income streams but also provide greater insight into a markets next move. Sometimes you have to step outside to find which way the wind is blowing.

If there are successful basic trading approaches why bother with a more advanced system?

By introducing more variables into the trade framework, strategies can be tailored more to a particular market and time and, not least, the trader.

5 Reasons:

Money: Proven to increase performance and therefore overall profitability over time.
Adaptability: Encourages the right trade for the prevailing market condition. Many simple approaches can win big in certain markets but lose badly in others. Matrix seeks the best trade for that particular market.
Tradability: Enables comparison with previous trade setups to identify the historically proven best trade for the current market but also comparison between trading opportunities across all markets to identify the best current trade.
Regulation: Instils greater necessary discipline. A larger number of rules and guidelines ensures a more disciplined approach and mindset.
Individuality: Empowers the selective trader by identifying the better trades in different markets and time frames to suit individual needs.
Xcellence: Inspires self-improvement. By comparison of more market and trading factors with performance this encourages more consideration, self-assessment and improvement.

What is a hedge?

Please click here for our separate page on hedging