Spread Betting ETF’s

ETF’s have been heralded as one of the greatest financial innovations in recent years. ETF stands for exchange traded fund, which is an investment fund which is traded on stock exchanges like stocks. An ETF holds a variety of asset classes such as as stocks, commodities and bonds and in theory should trade near it’s Net Asset Value (NAV) over the course of the day. While a large percentage of ETF’s track indices in one way or another, their are now plenty of ETF’s which will give you exposure to a certain group of shares or a region. 

The main benefit of Spread betting an ETF is that it gives you niche exposure to a certain market. While it is possible to get the same kind of niche exposure, for by making Spread bets on several stocks from the same sector. But Spread betting an ETF is much simpler than taking on several individual positions in order to gain exposure to one sector. The wide array of ETF’s available allow you to take positions on almost anything that you could conceive. A prime example of this is the Global X Fishing Industry ETF. Given that there is already a wide range of indices available to spread bet, spread betting ETF’s is only advantageous when you want exposure to particular market sector say US Oil companies.  

Spread betting a ETF can sometimes be advantageous to owning a physical ETF. As Spread betting allows you to hugely ratchet up the amount of exposure that you have to that particular market sector or region. Though there are some leveraged and inverse (short) ETF’s available online they often offer a disjointed relationship due to the fact they are repriced daily. As these funds are designed specifically for day traders in mind. This is why Spread betting can give you both significant leverage and give you inverse position on an ETF without their being a disjointed relationship between the ETF and the underlying assets.  


The advantages of spread betting an ETF can be undermined if you wish to take a long term position, as any advantage can be undone by the overnight costs of a spread bet which might wipe out the gains you were expecting. But for short term exposure to a specific sector, spread betting an ETF can avoid some of the costs linked to trading physical ETF’s. As well as offering the standard benefits of spread betting such as significant leverage and tax-free gains.

Understanding Moving Averages

Moving Averages are one of the simplest technical indicators around. Moving averages do not make predictions about future price movements but they rather they define the current price direction with a time lag. Even though Moving Averages lag, due to the fact that they are based on past data they are useful as they smooth price action and they also filter out noise. The two most popular types of Moving Average used for trading, are the Simple Moving Average and the Exponential moving average. Click on images to enlarge.

A simple moving average is simply the average price of a security over a specific number of periods. The majority of moving averages are based on closing prices, as the name suggests old data is dropped as new data comes along. Exponential moving averages aim to reduce the time lag experienced, by applying a greater weight to more recent data while giving less weight to older data. Also the longer the moving average used the greater the time lag their will be, a 10 day moving average will hug the price data much more closely than a 50 day moving average. As the longer moving average will be based on a far greater range of data points. 

Even though there are clear differences between how simple moving averages and exponential moving averages are calculated. Exponential moving averages will turn more quickly than simple moving averages but are also prone to give more false indications of new trends in price direction. While simple moving averages offer a truer picture for the entire time period in question and some have suggested this makes simple moving averages better if one wishes to identify support or resistance levels.

Different traders often decide to use different time frames when using Moving Averages as an indicator. Short term moving averages (5-20) tend to suit those who are interested in short term trading and short term trends. Chartists who wish to hold a position for the medium term will typically use 20-60 day moving averages. While long term investors will likely only use moving averages of greater than a 100 days. 

By using two moving averages a trader can generate crossover signals. One popular crossover signal used is called the double crossover. A trader using the double crossover method will typically use one relatively short term moving average with another longer term moving average. When the short term moving average crosses above the long term moving average, this is known as a Golden cross and is taken as a Buy signal. Conversely when the short term moving average crosses below the long term moving average this is taken to be a sell signal and is known as a dead cross. A more complicated three cross system can be used where again the movement of the shortest of the three moving averages crossing the over two is taken to determine buy and sell signals. 

Charts created using the Plus500 Platform.

Understanding ADX (Average Directional Index)

ADX, stands for Average Directional Index. This indicator measures the strength of the trend of any given traded instrument. ADX can be useful in determining the strength of the trend present in the instrument being traded. A High ADX reading signals a strong trend and a low ADX reading signals a weak trend.  

When an ADX reading is low, it is likely that the instrument will be trading in a narrow price range. A higher reading means it’s likely that the the instrument is trending either upwards or downwards. On many charting programs the ADX, is couple with two other indicators the Minus Directional Indicator (-DI) and Plus Directional Indicator (+DI). These complement ADX by defining the direction of the trend. Some people ignore these complementing indicators as they feel having to much faith in them can land you in deep water.  
 
On the chart above taken from the very useful StockCharts.com, the thick black line displays the ADX, while the other two lines display the -DI and +DI. The -DI is in red and the +Di is in blue. As you can see on the chart above the ADX begins to rise as the upward trend in Dow Jones Industrial Average is established. You can also witness the -DI in red fall significantly in comparison to the +DI which suggests an upward trend is being established. 
 
On the right hand side of the ADX graph you can see the ADX scale which gives you the ADX value. It is generally held that when the ADX is below 20, the instrument is not trending in any direction. Once the ADX starts rising above 20 a trend is beginning to be established, if the indicator rises above 30 the trend on the particular instrument is particularly strong. The ADX rarely ever rises above 50 and often once the ADX rises to these kind of levels the trends often tend to break down.  
 
Welles Wilder the creator of the ADX indicator set forth a simple trading method to be used with the indicators in his 1978 book, New Concepts in Technical Trading called the DI crossover method. The first requirement to use the system is that the ADX is over 25, so we know their is a significant trend ongoing in the instrument in question. A buy signal occurs when the +DI signal crosses above -DI.  Wilder recommends that you place the stop on the low of that particular trading day, and run with the signal until this level is reached. Conversely a sell signal arises when ADX is over 25 and the -DI crosses above DI+, the stop loss according to Wilder should be set at the particularly days trading high.  
 
The calculations behind ADX, and the related indicators are complex but using the technical signal seems easier but still require practice and discipline. But ADX can be a useful tool for technical traders especially those who like to trade on momentum. 

 

Understanding Bollinger Bands

Bollinger Bands where created unsurprisingly by John Bollinger in the 1980’s. Bollinger Bands are a piece of technical analysis used to determine the highness or lowness of the current price relative to previous trading. The upper and lower Bollinger Bands lie one standard deviation from the current moving average. Generally the default choice for calculating the Bollinger Bands is a simple moving average, but other types of moving averages can be used. The purpose of Bollinger Bands is to give a relative definition of high and low. Prices at the upper band are by definition high and those at the lower band by definition low. 
How Bollinger Bands are used among traders vary greatly. One typical strategy is to Buy when the price hits the lower Bollinger and sell when the price returns to the moving average. While other traders buy when the price breaks through the the upper Bollinger and conversely sell the instrument when the price breaks through the lower Bollinger band. Bollinger bands uses are not just used to limited to those trading stocks and commodities. Some option traders, sell options when Bollinger Bands are historically far apart and Buy options when they are historically close together, in both instances the options traders are expecting the volatility to revert back to the historical norm for the particular instrument.  
 
The effectiveness of Bollinger Bands is highly contentious with their being seemingly conflicting evidence. A recent study on the effectiveness of Bollinger Bands on the Chinese Markets found that such a strategy could be used to make a profit even after trading costs where considered. Others advocate the use of Bollinger bands with stop losses as an effective strategy to trading the markets. But there is still no clear consensus regarding the effectiveness of Bollinger bands as a trading tool.

Forex trading – Why the odds are stacked against you

The Foreign Exchange Markets are at best a Zero-Sum game. A Zero-Sum game is a game or activity where improving your on situation can only come at the cost of worsening another persons situation. Things get worse for the retail Forex trader as they are participating in a market place with many experienced and well capitalized traders, inexperienced retail traders are expected and are likely to be at a significant informational disadvantage.  

Things get worse for the individual retail trader as almost by definition retail traders are vastly under-capitalized. This makes the retail trader subject to the problem of gamblers ruin. In a fair game (one with no informational disadvantages) between two individuals that continues until one player goes bankrupt, the least capitalized player has a much higher chance of going bankrupt first. But since a retail Forex company is effectively speculating against the whole market they have very little chance of going bankrupt. The retail trader is also at a disadvantage as they have to pay a larger bid/ask spread which makes the odds for winning at Forex trading less than those experienced in a fair game. The retail trader can also experience other additional costs which again make it yet harder to come out on top. 

While there are opportunities that allow for individuals to make unusually large returns, but this does not mean that more people could earn the same returns even with the same tools and knowledge. Information about to how  to earn money trading such opportunities is a nonrival good while the particular trades themselves are a rival good. For example the amount of buried treasure on a tropical island remains the same no matter how many people are selling maps or information to treasure hunters seeking the buried treasure.

Does this mean that you can’t earn money trading Forex? No, it doesn’t it just means the odds against you earning money trading Forex are significantly stacked against you. The Chief executive of FXCM said that he would be surprised if 15% of day traders where profitable. Those interested in Forex should bare this in mind before they jump into trading Forex. 

Made To Trade’s: Top 5 Trading Documentaries

When I first started becoming interested in trading I watched numerous trading documentaries. There are some great trading documentaries out there available to watch for free online. Today I intend to list what I regard to be the 5 best trading documentaries, the list covers a range of different topics 


1. Trader – Paul Tudor Jones 

This American documentary follows infamous hedge fund manager Paul Tudor Jones throughout a trading day providing insight into how a typical day might look, as well looking at the unique personality that is Paul Tudor Jones. Filmed in 1986 the documentary features Paul Tudor Jones prediction of the 1987 collapse of equities. Even though the documentary has a somewhat dated feel, I thoroughly enjoyed the documentary. Though it can be said that the documentary is not particularly educational.  


2. Billion Dollar Day 

Another old documentary from the 1980’s Billion Dollar Day follows a day in the life of three different currencies traders in London, Toyko and New York respectively. While the times have changed since Billion Dollar Day was originally filmed, the film offers a very interesting perspective into the workings of the Forex market. The documentary is both thoroughly engaging  as well as being educational at the same time. A must watch for anyone who has an interest in the Forex markets. 


3. Million Dollar Traders

This documentary is part experiment and part reality show by hedge fund partner Lex Van Dam to determine whether he take a group of pre-selected normal people and train them to become successful traders who will be given a million pounds of capital to manage (Van Dam has an online training program Surprise! Surprise!). The most interesting thing about this particular documentary is the insights it provides into the psychological aspects of trading. It soon becomes apparent that many people simply can’t hack it. An interesting watch for those who are interested in trading and those wondering what it really takes to be a successful trader.  


4. Floored 

A documentary film that I personally love and have featured on this blog before. The documentary floored chronicles the decline of open outcry trading on the CME, with the majority of commodity trading being done electronically this documentary chronicles the slow decline of the dominance of the rowdy boys in the pit and the rise of algorithmic traders. A very interesting watch a lot of the traders are larger than life characters and it gives you a great look into the life of a Pit Trader who soon might be an extinct breed. 


5. Trillion Dollar Bet

Long term capital management is a now a somewhat infamous hedge fund that imploded in the late 90’s. This group of Phds and scientists aimed to take on the markets with new quantitative methods that were meant to reap huge rewards while effectively eliminating luck. This all went wrong when in 1998 their carefully built models feel apart. The documentary is interesting and engaging acting as a stark warning about the dangers of Black Swan events. The documentary may be a little dry for some. 

A look at the efficient market hypothesis

The efficient-market hypothesis asserts that financial markets are informationally efficient. An individual cannot significantly outperform the market on a risk adjusted basis. This implies that over a long run a trader can not expect to outperform the market, leading to some to recommend index tracking funds over other forms on investment (See a Random Walk Down Wall-Street). The efficient-market hypothesis exists in three forms: 

  • Weak form: prices of traded financial instruments already reflect all previous publicly available information. 
  • Semi Strong: prices of traded financial instruments already reflect all publicly available information and respond instantly to reflect new publicly available information. 
  • Stong form: adds to the claim of the semi strong hypothesis by saying prices instantly reflect hidden or insider information. 
The efficient market hypothesis has received both theoretical and empirical criticism. Generally the empirical evidence for the efficient market hypothesis has been mixed, with stronger empirical evidence existing for both the weak and semi strong form of the hypothesis. Though behavioral economists have pointed to various market inefficiencies caused by combination of cognitive biases such as overconfidence, overreaction, information and representative bias. 
 
In recent times the efficient market hypothesis and the belief in rational markets has come under criticism for what some believe it’s role in the financial crisis of the late 2000’s. From the point of view of the efficient market hypothesis, speculative bubbles represent a clear anomaly to the hypothesis which can not be explained away. Sudden market crashes of the kind that happened on Black Monday in 1987 are unexplained but are allowed by those who hold the weak form of the hypothesis as they are seen to be rare statistical event.  
 
The efficient market hypothesis seems to be questionable on other grounds as their seems to be a number of traders and hedge funds who have continually beaten the performance of the underlying market, while over the short term this may statistically likely continued long term performance which significantly outperforms the market place starts to become highly unlikely. Other empirical evidence like the work done by Prof. Andrew Lo and Craig MacKinlay seriously undermines the efficient market hypothesis.

Assumptions behind the Black-Scholes Model

The famous options pricing model known as the Black-Scholes model or Black-Scholes-Merton, can help it’s users deduce the correct price for European Style Options. The model came first came to prominence in the 1970’s and is now widely used within the world of Options trading. The Black-Scholes model has become somewhat infamous after the collapse of gigantic hedge fund Long Term Capital Management who put to play the model they themselves had created. Behind the Black-Scholes model lies several assumptions, today we are going to go through and examine each of the assumptions. 

There is no arbitrage opportunity 
An arbitrage opportunity is an opportunity to make a risk-less profit by Buying and Selling in two different market places. Back when the Black-Scholes Model came onto the scene there were plenty of arbitrage opportunities in the financial markets. For example commodity traders were able to set up arbitrage desks trading price discrepancies present in two different open outcry markets. While the majority of arbitrage opportunities of the kind mentioned above have disappeared, it is not impossible to exploit arbitrage opportunities for risk-less profit.  
 
It is possible to borrow and lend at a constant risk free rate 
A important part of the model relies on the idea that at any moment in time there is a riskless rate which one can both borrow and lend at. Firstly it’s clear that such a risk free rate wouldn’t remain constant and would be subject to change. This issue for the Black-Scholes Model was overcome by more complex versions that can account for changing interest rates. But it can also be seen that the idea there is a riskless rate which can both borrow and lend at is questionable. When taking about a risk free rate of return one is normally talking about short term government bonds or LIBOR. But since the financial crisis of 2008 the idea that these represent a truly risk less proposition has become more dubious with bonds being seen in a somewhat different light.  In times of turmoil it is difficult to see whether this assumption really does hold true. 
 
It is possible to both buy and sell any amount, even fractional of stock,(including short selling). 
This is also a very questionable assumption there will be times when you will not be able to buy or sell stock including short selling. As there may not be the liquidity or people willing to loan the stock in order for you to be able to short sell it. Again this another assumption that seems problematic for those who wish to use the Black-Scholes model. Again during the 2008 financial crisis there were periods where certain stocks were totally unavailable for short sale as there was more demand to short sell the stock than there was stock to be short sold.  
 
The Black-Scholes models also contains other assumptions more expanded versions of the model can avoid or account for these assumptions. While these assumptions and the questions surrounding them are some cause for concern don’t rule out using the Black-Scholes as tool in your trading arsenal. Just remember to becareful not to accept Black-Scholes or any other model as trading law. 

Where to gather historical Data

When creating a strategy or developing a trading system, historical data is required. Historical Data of various sorts can be found online, here we are going to outline some of the sources of historical data. 

Commodities 
Forex Pros, provides CFD price data going back several years while CFD data isn’t the same as the underlying price it tracks the price movements. I personally have used this data to build models to predict future movements in Crude Oil prices with impressive accuracy.

Moore Research Centre Inc, provides historic futures data comprising data from all the major markets. With a history of data that goes back several years.

Stock & Indices Prices  
Yahoo Finance, offers a wide array of historical date on all the major stock markets, as well as analysts targets etc. Historical data can also been downloaded as an excel spreadsheet

Google Finance, similar to Yahoo except Google also offers live prices on a number indices and indexes and continue to add more live feeds. Again Historical data can be download as an excel spreadsheert

Live Charts, offer a wide array of historical stock data for free download. Will be of particular interest to people who are interested in trading European Stocks

Forex & Futures 
Forex Pros, offers historical data on numerous Forex pairs though the historical data is comprised of CFD prices, it is still accurate enough to build models especially if you intend to trade using CFD’s

Trading Blox, offers a limited range of free historical data that can be downloaded for free, the selection is quite good and the data is updated daily. 

Global View, offers historical data for a limited range of Forex pairs going back years and years into the past. The data is easy to access and import into programs like excel.

Pi Trading, offers historic data on a number of Indices, Futures and Forex pairs. All can be downloaded for free as a zip file.

Feel free to leave any other suggestions or sources you use.

Documentary Film : The Black-Scholes Formula

The famous Black-Scholes Merton Formula revolutionized the world of options giving Options Traders a way to accurately price options. This documentary charts the rise of The Black-Scholes Formula and the effect it had on the world. Also taking a look at the fall of Long Term Capital. The documentary has been posted on Youtube and is in 5 parts. 

[youtube=http://www.youtube.com/watch?v=o_UxB6EEqWo]

Hope you enjoy.