CFDsContracts for Difference

Comparison of online CFD (Contracts for Difference) brokers

The below is a comparison of CFD brokers that are provided to the Australian market. While the fees may differ for CFD brokers in different countries, the structure is usually quite similar. And stay tuned for a global index for comparing Contract for Difference brokers and providers.

  • all dollar values in AUD
  • OCR = official cash rate

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www.icmarkets.com.au BrokerOne One Financial CFD Trading City Index CMC Markets Commodoity Broking Services CommSec Cube Financial Group E*Trade First Prudent Markets Get Financial Halifax Online i-deal IG Markets Macquarie Bank Man Financial Marketech Pacific Trader Sonray Capital Markets Tricom
CFDs offered Yes Yes
Commission 0.00% 0.00% 0.10% 0.06-0.10% 0.06-0.10% 0.08-0.10% 0.125% 0.22′ 0.125-0.175% 0.10% 0.10% 0.18% 0.10% 0.8-0.10% 0.07-0.12% 0.125% $0 0.075-0.10% 0.125-0.20% 0.10%
Phone Yes 0.10% 0.08-0.10% 0.25% (Min $54.60) 0.22% 0.125-0.175% 0.10% 0.10% 0.18% 0.15% 0.08-0.10% Internet only 0.175% $25/0.10% 0.075-0.10% 0.125-0.20% 0.10-0.50%
Minimum Commission $0 $10 17.50, lower if turnover > 500 K per month 10% $8 $10 for trade size < $5000 $25 for ASX $0 AUS $30
Interest (Long) 0 OCR + 2% OCR + 2% OCR + 3% OCR + 2% OCR + 3% OCR + 3% OCR + 2% OCR + 2.5% OCR + 2% OCR + 2.5% OCR + 2.5% OCR + 3% OCR + 2% OCR + 2.5% OCR + 2.5% OCR + 2-3%
Interest (Short) 0 OCR – 2% OCR – 2% OCR – 3% OCR – 2% OCR – 3% OCR – 3% OCR – 2% OCR – 2.5% OCR – 2% OCR – 2.5% OCR – 2.5% OCR – 3% OCR – 2% OCR – 2.5% OCR – 2.5% OCR – 2-3%
Monthly Platform Fees FREE Free Free Free $40.70 Free $79.90 $55 Free Free Free Free Free $40.70 Free Free Free Free
Live Data Fees FREE $38.59 free after 10 trades $41.25 free after $50 of commission $35 $41.25 Free Free Free $38.50 $45.00 $38.50 Free $40.70 $41.25 Free $37.50 $38.50 $38.50
Min Opening Balance $250 $100 $1000 $5000 $5000 $10,000 $5000 $5000 $5000 $2000 $5000 Nil $5000 $5000 $5000 Nil $3000 $5000
‘Guaranteed Stop Losses Yes Yes Yes No No Yes No No No No No Yes Yes No No No No No
# of long ASX CFDs N/A 318 S&P ASX 500 588 492 S&P ASX 500 509 2,600+ 286
# of short ASX CFDs N/A 202 300+ ~340 196 370+
Overseas CFDs Yes N/A Shares in the FTSE 350 and other UK, S&P 500, NASDAQ 100 and other US. N/A Shares in the FTSE 350, DOW 30, S&P 500, NASDAQ LSE, NASDAQ, NYSE
Spread
www.icmarkets.com.au BrokerOne One Financial CFD Trading City Index CMC Markets Commodoity Broking Services CommSec Cube Financial Group E*Trade First Prudent Markets Get Financial Halifax Online i-deal IG Markets Macquarie Bank ‘Man Financial Marketech Pacific Trader Sonray Capital Markets Tricom
Margin for ASX CFDs N/A 3-10% 5-80% 3-90% 5-75% 5-45% 5-80% 5-100% 10%
Margin for US CFDs 0.5%-1% 5% from 10%
Margin for LSE CFDs N/A 5% from 5%
Margin for other Equities CFDs 5% for European, 3% for commodity. 1% for index, sector, treasury From 10% 5% for indices
Margin for FOREX Trading 0.5%-3% 1%
Margin for index and sector 1% 1%, 2% 5% for indices
Stop Entry Orders Yes Yes Yes Yes
Stop Loss Orders Yes Yes Yes Yes Yes
Guaranteed Stop offered Yes Yes
Guaranteed Stop: Minimum Distance 5% away from CMC market for share CFDs, 1% away for indices 5%
Guaranteed Stop: Premium 1-10 points for share CFDs, 2 points for AUSSIE200, NDAQ100, UK100 indices 0.3% of trade size
Guaranteed Stop: Cost of moving
CFDsContracts for Difference

Trading Volatile Markets

Everybody has felt the US Subprime crash, or the “credit crunch”. It has affected all of the major stock markets in the world, hit some of the largest investment banks and crippled other financial organizations who focus in the lending space both large and small.

There are a couple of things one can do in this time of news driven, manic volatility to help reduce risk and losses.

“Reduce your position sizes, move your stops further away on long-term trades while keeping them tight for day trades, take profits on short-term trades for frequently, and be more patient with longer term positions”

Day Trade

In times like this, the gaps stocks can experience can be literally ridiculous. On the ASX for instance, Macquarie Bank (MBL.AX) experienced movements of 5-8% over night! For Australia’s largest and most prosperous investment bank, that has close to no exposure to the US subprime markets, movements like this can seriously damage a CFD traders portfolio (trust me I know). But I suppose that is to be expected when trading thought the most volatile period our markets have experienced in 15 years.

An easy way to combat these leaps in price is to close out at the end of the day. Yes, you may be cheating your self out of potential profit, but in this type of market, even the savviest trader cannot pick the intra-day movements of the US markets… Collecting profits, dodging the overnight movements and reopening positions after analyzing overnight movements in the overseas markets can be one of the most effective ways to navigate through these treacherous times.

The Overseas markets

As an Australian trader it is common knowledge that what the US market does will drastically affect what our market does. This can be easily obtained by looking at a comparison of the Australian stock exchange against the US. This great influence, even more so in this time of market volatility, adjusting your stops according to overnight movements in the US market is utterly necessary.

This means waking up every morning and checking your stop against the movements in the overnight market, and ADJUSTING them based on what happened over night. This means taking wider stops to ensure you don’t close out of your position at a ridiculously low price because of wise spread panic, sometimes it might mean removing your stop all together, if you have a long term trade in place.

Large intraday spikes that cause prices to hit your stop can be a CFD trader’s worst nightmare, don’t let it be yours.

CFDsContracts for Difference

Win/Loss Ratio

The Win/loss Ratio in Cfd Trading

Among the questions often asked by clients when selecting an adviser or a system for CFD trading is what percentage of recommendations they can expect to be winners, and how much should they expect to make each month, year or whatever. These form part of a natural psychological comfort zone, but may be part of the reason why so many people fail as traders.

In any area of speculation, whether it is stockmarket investment, spreadbetting, forex trading or CFDs, if the underlying system has a small edge, it is only the first part of potential success. The key to achieving constant returns lies with a correct approach to the win/loss ratio and not in expecting any particular level of gains, which can distort the underlying methodology. CFD traders have the ability to go long and short at will, and online trading makes it easy to adjust stops and targets at any time.

An example of a good win/loss ratio that fails

Consider this example: a CFD trader selects a system where there is a supposedly proven record of seven out of each ten trades proving to be winners. The idea might be that each trade has a target return of 3%, and if it is achieved the position is closed. If the trade however shows a loss of 3%, the expectation is that it should recover and the position is doubled up, with the hope of returning to parity or even making a 6% gain. Now if market or share movements were a random sequence, it would not make any difference where one entered or exited. The overall returns would over time be neither a gain nor a loss, but costs and the spread on trading would result in a virtual guaranteed loss in due course (the casino approach).

Having a slight edge is not enough

If this system had an edge though, the expectation might be that the 3% target would possibly be hit six out of ten times, thus making it a virtual winning approach. But the problem lies in the fact that although markets and shares do have short term periods when there appears to be random action, they can both trade a range and trend strongly at other times â?? this is what is known as regular irregularity, which might seem a paradox, but happens all the time in financial markets. Shares often move very quickly in one direction, and this trend can continue for far longer than expected, which creates two problems.

First, taking a 3% profit on a trade may appear to be very satisfactory, but it can often be seen in hindsight that the profit was taken too early, so despite achieving a winning trade there is an element of regret that more was not taken. Second, if the position is showing a loss, then the trade should in the real world be deemed to be incorrect and closed out. But in using such a system as this, by doubling up or averaging the position on losses, all that is achieved is an increase in risk â?? the trader might be lucky in some situations, but one or two trades out of the ten may cause severe problems. There is also the emotional capital that is tied up in losing trades.

This type of system typically might produce say six 3% winners, two evens (where one position was doubled up and returned to parity) and two 10% losers. Here the overall loss would be 2%, despite the good win/loss ratio, and this is clearly a dangerous way to play the markets, but many traders operate exactly in that way.

Improving the risk/reward

The first point is to set a stop loss on each trade and stick to it. Doubling up simply doubles the risk â?? that is fine if there is another system signal that reinforces the first trade, but generally that is not the case. The problem that then occurs is that if the stop and targets are quite close in percentage terms, the bouts of short term randomness mean that it can almost be like coin tossing, which with costs is a futile approach.

The key is therefore to ensure the gains are much greater than the losses, so that even if one only achieves four wins out of ten, there may be two big winners in there. If a trader decides that a 3% average loss is acceptable, then what average gain should be sought? This is the $64 question, and the key is to let profits runs as much as possible within a clearly defined trend. The following rules are part of the methodology used at Blue Index for the longs and shorts CFD portfolio, and the long term results have so far proved more than satisfactory.

Some simple rules for a consistent winning approach

1. If searching for stock trades, try to choose high volatility or beta shares â?? these have a higher chance of being in a trend rather than trading a range or exhibiting random action.

2. The expected initial target should always be at least twice the stop loss. If the average stop loss set is 3%, the CFD trader should look for 6%-plus gains on each trade as a starting point.

3. Try to set individual stops and limits with reference to the underlying action. If a share has moved 10% one day, it is likely to exhibit an intra-day range of much more than 3%, so the stop and target should be widened accordingly. Also support and resistance levels are very useful reference points for setting price targets FAYETTEVILLEHOME-TOWNINFO.INFO .

4. If the trade hits the initial target, either close the position if support or resistance around that area is seen to be valid, or move the stop up to protect profits and let the position run.

5. If there is a sudden reversal in share price trend, close the position, whether it is winning or losing. The swings and roundabouts of trading usually mean that these unexpected trend changes even themselves out.

6. Make sure you are never exposed too much in one direction. If for instance the market falls heavily from the open, then it doesnâ??t matter, as even if there are more longs and shorts in your list of open positions, the huge gains on the shorts should outweigh the stops hit on the longs.

Target returns

As for target returns, many traders have unrealistic expectations. A system that can offer huge returns inherently has to have a higher risk, but bear in mind this simple fact business . Warren Buffett has achieved just over 20% per annum returns on his investment fund, and he did not need to use leverage to become the worldâ??s second wealthiest man..

CFDsContracts for Difference

Commodity Channel Index

The Commodity Channel Index (CCI) is an oscillator originally introduced by Donald Lambert in an article published in the October 1980 issue of Commodities magazine (now known as Futures magazine).

Since its introduction, the indicator has grown in popularity and is now a very common tool for traders in identifying cyclical trends not only in commodities, but also equities and currencies. The CCI can be adjusted to the timeframe of the market traded on by changing the averaging period.

Calculation

The CCI is calculated as the difference between the typical price of a commodity and its simple moving average, divided by the mean deviation of the typical price. The index is usually scaled by a factor of 1/0.015 to provide more readable numbers:

CCI = \frac{1}{0.015}\frac{p_t - SMA(p_t)}{\sigma(p_t)},

where the pt is the typical price (average of the high, low, and closing prices), SMA is the simple moving average, and σ is the mean deviation.

Interpretation

The Commodity Channel Index is often used for detecting divergences from price trends as an overbought/oversold indicator, and to draw patterns on it and trade according to those patterns. In this respect, it is similar to bollinger bands, but is presented as an indicator rather than as overbought/oversold levels.

The CCI typically oscillates above and below a zero line. Normal oscillations will occur within the range of +100 and -100. Readings above +100 imply an overbought condition, while readings below -100 imply an oversold condition. As with other overbought/oversold indicators, this means that there is a large probability that the price will correct to more representative levels.

CFDsContracts for Difference

Trix

Trix (or TRIX) is a technical analysis oscillator developed in the 1980s by Jack Hutson, editor of Technical Analysis of Stocks and Commodities magazine. It shows the slope (ie. derivative) of a triple-smoothed exponential moving average. The name Trix is from “triple exponential.”

Trix is calculated with a given N-day period as follows:

  • Smooth prices (often closing prices) using an N-day exponential moving average (EMA).
  • Smooth that series using another N-day EMA.
  • Smooth a third time, using a further N-day EMA.
  • Calculate the percentage difference between today’s and yesterday’s value in that final smoothed series.

Like any moving average, the triple EMA is just a smoothing of price data and therefore is trend-following. A rising or falling line is an uptrend or downtrend and Trix shows the slope of that line, so it’s positive for a steady uptrend, negative for a downtrend, and a crossing through zero is a trend-change, ie. a peak or trough in the underlying average.

The triple-smoothed EMA is very different from a plain EMA. In a plain EMA the latest few days dominate and the EMA follows recent prices quite closely; however, applying it three times results in weightings spread much more broadly, and the weights for the latest few days are in fact smaller than those of days further past. The following graph shows the weightings for an N=10 triple EMA (most recent days at the left):

Triple exponential moving average weightings, N=10 (percentage versus days ago)

Triple exponential moving average weightings, N=10 (percentage versus days ago)

The easiest way to calculate the triple EMA based on successive values is just to apply the EMA three times, creating single-, then double-, then triple-smoothed series. The triple EMA can also be expressed directly in terms of the prices as below, with p0 today’s close, p1 yesterday’s, etc, and with f = 1 - {2\over N+1} (as for a plain EMA):

  : TripleEMA_0 = (1-f)^3 (p_0 + 3fp_1 + 6f^2p_2 + 10f^3p_3 + \dots)

The coefficients are the triangle numbers, n(n+1)/2. In theory, the sum is infinite, using all past data, but as f is less than 1 the powers fn become smaller as the series progresses, and they decrease faster than the coefficients increase, so beyond a certain point the terms are negligible.

CFDsContracts for Difference

Trend line

A trend line is formed when you can draw a diagonal line between two or more price pivot points. They are commonly used to judge entry and exit investment timing when trading securities.

A trend line is a bounding line for the price movement of a security. A support trend line is formed when a securities price decreases and then rebounds at a pivot point that aligns with at least two previous support pivot points. Similarly a resistance trend line is formed when a securities price increases and then rebounds at a pivot point that aligns with at least two previous resistance pivot points. The following chart provides an example of support and resistance trend lines:

Trend lines are a simple and widely used technical analysis approach to judging entry and exit investment timing. To establish a trend line historical data, typically presented in the format of a chart such as the above price chart, is required. Historically, trend lines have been drawn by hand on paper charts, but it is now more common to use charting software that enables trend lines to be drawn on computer based charts. There are some charting software that will automatically generate trend lines, however most traders prefer to draw their own trendlines.

When establishing trend lines it is important to choose a chart based on a price interval period that aligns with your trading strategy. Short term traders tend to use charts based on interval periods, such as 1 minute (i.e. the price of the security is plotted on the chart every 1 minute), with longer term traders using price charts based on hourly, daily, weekly and monthly interval periods.

Trend lines are typically used with price charts, however they can also be used with a range of technical analysis charts such as MACD and RSI. Trend lines can be used to identify positive and negative trending charts, whereby a positive trending chart forms an upsloping line when the support and the resistance pivots points are aligned, and a negative trending chart forms a downsloping line when the support and resistance pivot points are aligned.

Trend lines are used in many ways by traders. If a stock price is moving between support and resistance trendlines, then a basic investment strategy commonly used by traders, is to buy a stock at support and sell at resistance, then short at resistance and cover the short at support. The logic behind this, is that when the price returns to an existing principal trendline it may be an opportunity to open new positions in the direction of the trend, in the belief that the trendline will hold and the trend will continue further. A second way is that when price action breaks through the principal trendline of an existing trend, it is evidence that the trend may be going to fail, and a trader may consider trading in the opposite direction to the existing trend, or exiting positions in the direction of the trend.

CFDsContracts for Difference

Support

A support level is a price level where the price tends to find support as it is going down. This means the price is more likely to “bounce” off this level rather than break through it. However, once the price has passed this level, even by a small amount, it is likely to continue dropping until it finds another support level.

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Stochastic oscillator

The stochastic oscillator is a momentum indicator used in technical analysis, introduced by George Lane in the 1950s, to compare the closing price of a commodity to its price range over a given time span.

This indicator is usually calculated as:

STS = 100 \frac{closing price - price low}{price high - price low}

and can be manipulated by changing the period considered for highs and lows.

Interpretation

Stochastics Fast & Slow

Stochastics Fast & Slow

The idea behind this indicator is the prices tend to close near their past highs in bull markets, and near their lows in bear markets. Transaction signals can be spotted when the stochastic oscillator crosses its moving average.

Two stochastic oscillator indicators are typically calculated to assess future variations in prices, a fast (%K) and slow (%D). Comparisons of these statistics are a good indicator of speed at which prices are changing or the Impulse of Price. %K is the same as Williams %R, though on a scale 0 to 100 instead of -100 to 0, but the terminology for the two are kept separate.

The fast stochastic oscillator or Stoch %K calculates the ratio of two closing price statistics: the difference between the latest closing price and the lowest closing price in the last N days over the difference between the highest and lowest closing prices in the last N days:

\%K = { CP_{today's} - LOW_{lowestNDays} \over HIGH_{highestNdays} - LOW_{lowestNDays} } \times 100
Where:
CP is closing price
LOW is low price
HIGH is high price

The usual “N” is 14 days but this can be varied. When the current closing price is the low for the last N-days, the %K value is 0, when the current closing price is a high for the last N-days, %K=100.

The slow stochastic oscillator or Stoch %D calculates the simple moving average of the Stoch %K statistic across s periods . Usually s=3:

\%D = SMA_3 \; of \; \%K

or more generally:

\%D_n = {\sum_{k=0}^s \frac{%K_{n-k}}{s}}.

The %K and %D oscillators range from 0 to 100 and are often visualized using a line plot. Levels near the extremes 100 and 0, for either %K or %D, indicate strength or weakness (respectively) because prices have made or are near new N-day highs or lows.

There are two well known methods for using the %K and %D indicators to make decisions about when to buy or sell stocks. The first involves crossing of %K and %D signals, the second involves basing buy and sell decisions on the assumption that %K and %D oscillate.

In the first case, %D acts as a trigger or signal line for %K. A buy signal is given when %K crosses up through %D, or a sell signal when it crosses down through %D. Such crossovers can occur too often, and to avoid repeated whipsaws one can wait for crossovers occurring together with an overbought/oversold pullback, or only after a peak or trough in the %D line.[1] If price volatility is high, a simple moving average of the Stoch %D indicator may be taken. This statistic smooths out rapid fluctuations in price.

In the second case, some analysts argue that %K or %D levels above 80 and below 20 can be interpreted as overbought or oversold. On the theory that the prices oscillate, many analysts including George Lane, recommend that buying and selling be timed to the return from these thresholds. In other words, one should buy or sell after a bit of a reversal. Practically, this means that once the price exceeds one of these thresholds, the investor should wait for prices to return through those thresholds (e.g. if the oscillator were to go above 80, the investor waits until it falls below 80 to sell).

George Lane, a financial analyst from the 1950s is one of the first to publish on the use of stochastic oscillators to forecast prices. According to Lane you use the stochastics indicator with a good knowledge of “Elliot Wave Theory”. A Center piece of his teaching is the divergence and convergence of trend lines drawn on stochastics as diverging/ converging to trend lines drawn on price cycles. Stochastics has the power to predict tops and bottoms.

It should be noted that the existence of price oscillations is hypothetical and statistical at best–stock price movements are a consequence of the actions of human decision-makers and past behavior of market variables does not necessarily predict future behavior.

CFDsContracts for Difference

Rahul Mohindar Oscillator

Rahul Mohindar Oscillator (RMO) is a type of technical analysis developed by Rahul Mohindar of Viratech India. It detects trends in financial markets, and is designed to work on Open-High-Low-Close charts for a wide variety of securities including stocks, commodities and FX.

This analysis is most notably included in version 10 of the Metastock technical analysis program.

CFDsContracts for Difference

Resistance

A resistance level is the opposite of a support level. It is where the price tends to find resistance as it is going up. This means the price is more likely to “bounce” off this level rather than break through it. However, once the price has passed this level, even by a small amount, it is likely that it will continue rising until it finds another resistance level.