Tim Sykes and Penny Stocks – Part II

I am working my way towards testing out the “systems” promoted by Tim Sykes and others of his ilk regarding Penny Stocks.

The task is made no simpler by the failure to clearly specify entry and exit rules by those who promote penny stock trading. We hear about chart patters,”super nova”, support and resistance. We hear about buying dips. We hear about the fabulous profits to be made. Unfortunately, these profits seem largely to have been made by discretionary trading, since Mr Sykes and his students never actually manage to quantify their systems in such terms as could be communicated to a computer by code. And back tested.

These people say that their skills represent an art rather than a science, and I have a certain sympathy with that view. Clearly none of these people have the right skills to think about their trading in a quantitative way and that is perfectly understandable and acceptable.

Reading their posts on the many social media websites they inhabit makes it clear that they do not follow strictly quantifiable rules. And indeed, why should they? Nonetheless, their decisions as to when to buy and sell must be made on some basis and it would be interesting to find out whether, if they thought very hard and recorded their motivations for entering and exiting a trade, they could actually come up with concrete reasons for their decisions.

Most often, Sykes and his proteges will be celebrating trades they profited on and ruing trades they missed. The constant refrain on losing trades is “if”….”. If I had held overnight, if I had sold before the close. On winning trades by intuition, they chose the right course of action.

These guys claim (and I have no reason to doubt them) that they have more winning trades than losers, and that the average win exceeds the average loss. An enviable and unusual achievement.

One “system” is to buy into strength, to buy into a stock the day after it has had a substantial gain on substantial volume.

Another system is to short such trades which have been pumped and therefore will eventually be dumped.

That pumps and dumps exist is self evident. The trick is how to benefit from both the pump and the dump. Or at least from one or the other.

I have been working with the Quantconnect online back tester, since after a painful period of familiarization, I believe it to be excellent software. It also has the advantage of offering OHLC bars for seconds as well as tick data. It is about to roll out bid and offer data and volume at the b/o thus, back testing can become even more realistic.

So far, my back testing has been very simple and limited. If the stock rose x% yesterday on high dollar volume, buy at the open the next day and sell at the close. And the reverse: sell at the open the next day and cover at the close. My universe is many thousands of US stocks (including stocks which are no longer trading) whose stock price at the time of the trade (or rather the day before) was below $5 and dollar volume greater than $100,000.

I intend to move on and code profit taking measures intraday but for the time being, I believe my work has provided me with some valuable insight.

By way of example let us assume the price movement triggering an entry is 50%. The stock must have moved up 50% the previous day on high volume.

Bet size used was a maximum of 1% and the test period was from the beginning of 2014 to date.

Here is the breakdown:

Taking long trades only:

Av. Win 0.49%

Av. Loss -0.44%

Number of winning trades (%) 21%

Number of losing (%) 79%

CAGR -23.4%

Max DD 80.4%

Taking short trades only:

Av. Win 0.29%

Av. Loss -0.41%

Number of winning trades (%) 63%

Number of losing (%) 37%

CAGR 2.72%

Max DD 27%

Now clearly, Sykes and his friends do not buy at the open and sell at the close – or not usually. They are discretionary day traders and something prompts them to take trades at various times during the day. What causes such intra day entries and exits is not quantified – and these traders may claim that the reasons for such decisions are un-quantifiable.

Nonetheless, in these days of high frequency trading, it is possible to ape the antics of these people, if they can explain what it is they are doing. Or if you can guess or assume what they are doing.

As you can see from the above, statistically, shorting looks the smarter move. After all penny stocks achieve that sobriquet because they lose value over time and become worthless. But such stocks are hard to borrow. Prima facie, the long side of the trade looks a disaster.

But it is early days. Let’s see how this progresses. There will be errors in my code and my thought process and I am far from reaching and conclusions at this stage.

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