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Why Probability Based Trading Is Not Working...
Part II: Short Puts
In Part I we used Credit Spreads to demonstrate why most of the traders who incorporate Probability Based Trading into their trading are losing money. Those who have not read Part I can click here.
In Part II instead of Credit Spreads we will analyze Short Puts to demonstrate that problems with Probability Based Trading are not related to a certain option strategy. They arise from the common assumption that historical behavior of the underlying can be characterized by the normal distribution and implied volatility.
So let’s cut to the point and show the results of the search through the universe of possible Short Puts on a selected trading date. Our filtering criteria would be similar to the ones that were used in Part I - Theoretical Probability to be high and at the same time greater than Stress Test Probability.
Image A: Report courtesy of EzTrade Builder - Product of EzTrade, Inc.
As can be seen from this table (Image A) the Probability of Profit that is calculated based on the assumption of a Normal Distribution and volatility equated to the implied volatility, is extremely high - over 85%. Most traders would certainly take a trade with such probability… And in 6 out of 10 cases would lose a substantial amount of money…
To understand why this is happening let’s take a look at the historical behavior of BGC (General Cable Corp…)
Image B: Chart courtesy of EzTrade Builder - Product of EzTrade, Inc.
The red line on the top pane of this chart (Image B) represents the normal distribution “Bell Curve.” The green bars represent statistical occurrences of the historical moves of the underlying asset. As it can be clearly seen the real historical distribution of this stock does not even closely resemble normal distribution.
Further analysis of the Theoretical Probability vs. Stress Test Probability, can be done using Probability table (Image C.)
This table demonstrates that the Stress Test (ST) probabilities, calculated based on real 1 Year - 5 Year histories of the stock, equate to almost half of the Theoretical probability.
What is this information telling or should I say “screaming” to the trader?
This information is an indication that Stress Test analysis of real historical behavior of BGC gives you less than a 50% probability of the trade being profitable. You should consider additional review of trades that have such discrepancies in probabilities, unless there are facts (news, change of fundamentals etc.) that override previous historical behavior.
We know that two major assumptions in calculation of commonly used One-Size-Fits-All formula for Theoretical probability are: normal distribution of underlying asset and volatility equated to implied volatility. We have already demonstrated that historical distribution of BGC does not resemble the normal distribution. Now let’s take a look at implied volatility.
Image D: Report courtesy of EzTrade Builder - Product of EzTrade, Inc.
The absolute value of implied volatility doesn’t tell you much, but percentile or a comparison of the current value to its historical values can give you a clue… Such a low implied volatility percentile can indicate that the market does not anticipate a big move in the near future. On the other hand our historical analysis indicates that this stock is capable of big moves.
Can you always rely on market “wisdom” and make your trading based on it? Absolutely not… If the market view is always right then there would be no reason to trade options at all, as you would constantly be on the losing side. Only the ability to beat the market makes trading profitable.
Now let’s take a look at the day-by-day behavior of this trade from its inception to expiration and find out whose prediction on volatility and potential moves were right.
Image E: Chart courtesy of EzTrade Builder - Product of EzTrade, Inc.
On this chart (Image E), the top pane shows closing price (blue line) and selling strike (horizontal red line.)
The bottom pane shows daily option prices (red line) and profit/loss values (green line.) As can be seen during the trade, the stock dropped in price from over $41 to less than $26.
This significant drop of around 40% was not anticipated by the market, but was predicted by our Stress Test Analysis. The main outcome - use of the One-Size-Fits-All formula to calculate probability of success could result in a big and costly failure.
The result of the BGC trade is not an example of an insulated occurrence. Take a look at the Track Record Report for Short Put strategy. This report allows for the viewing of trade signals generated by filtering criteria during a one year period. As part of the filtering criteria Theoretical Probability was set greater than Stress Test Probability.
The result is a loss of $55,798. The reason why the loss exceeds the initial account of $50,000 is that buying power for each trade is calculated based on “Best Exit” and not for “Exit on Expiration.” In this report, we tried to show all trades that potentially could have been taken if selection was based on tested filtering criteria. BGC was one of the trades that the Track Record Report generates (line 113), but not the only one that cause substantial loses.
To get more confirmations on the fact that historical behavior of the underlying in many cases can’t be described by normal distribution and implied volatility, one can use Track Record Report to perform the similar analysis and view the Detail Report for particular stock.
By working through this Track Record Report one can argue that 70% of the trades that have similar conditions as BGC end up profitable. That is true… But you always have to remember that even 100% probability does not guarantee an event happening. Probability describes only likelihood of the event.
Ability to quantify your risk and make calculated decisions forces traders to use probability based trading. It does not preclude them from losses, but allows selecting probability based on the traders risk tolerance. Stress test analysis provides effective management of expectations and substantially improves final results.
To prove this take a look at the Track Record Report, where filtering parameters are set to take advantage of Stress Test Probability. This report gives an overview of all trades from 2008 till September 2013. If you scroll through the report to find the summary line for year 2011 (green row between line 346 and 347), you will see that profit with “Exit on Expiration” is $77,424. Compare this to losses of $55,798 and the advantages of using Stress Test Probability will speak clear and loud!