PRESENT SHOCK - Psychology and Money Management | futures io social day trading
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  #1 (permalink)
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Algorithmic trading techniques and (HFT) high frequency trading have dramatically altered the behavior of U.S. equity markets. If you are an active, short term trader, you have probably noticed that the markets have radically changed, and have become increasingly more difficult to trade. The development of AT was initially intended to be a solution for the reduced liquidity in the markets (as a result of decimalization), and then as a tool to more effectively arbitrage disparities in the markets. However, people often find alternative ways to profit from technological solutions, by bending the rules and exploiting the system, and algorithmic trading is no exception to the rule.

Before traders can begin to adapt to the new trading environment, traders need to understand how algorithmic trading techniques work, and the effects they have on the markets. While algorithmic trading was not developed originally for the purpose of implementing the toxic or predatory strategies described below, these techniques dramatically affect the way the market trades in the short term, and if not recognized will place the individual trader at a substantial disadvantage.

Liquidity-rebate traders take advantage of volume rebates of about 0.25 cents per share offered by exchanges to brokers who post orders, providing liquidity to the market. When they spot a large order, they fill parts of it, then re-offer the shares at the same price, collecting the exchange fee for providing liquidity to the market. This strategy doesn't require the trader to make a profit on the trade. If the trader breaks even, or even loses a small amount on the trade, the rebates he receives for providing liquidity, will generate a profit.

Predatory algorithmic traders take advantage of the institutional computers that chop up large orders into many small ones. By placing small buy orders that are quickly canceled, the predatory algo trader, fools the institutional computer into bidding up the price of the stock. After the price of the stock, is forced up to an artificially inflated level, the "predatory algo" shorts the stock.

Automated market makers "ping" stocks to identify large reserve book orders by issuing an order very quickly, then withdrawing it. By doing this, they obtain information on a large buyer's limits. They use this information to "front -run" orders by buying shares elsewhere and selling them to the institution they traded in front of.

Program traders buy large numbers of stocks at the same time to fool institutional computers into triggering large orders, creating volatile market moves. The program traders race the large orders, taking profits against, the very orders they triggered to move higher.

Finally, flash traders expose an order to only one exchange. They execute the order only if it can be carried out on that exchange without going through the "best price" procedure intended to give sellers on all exchanges a chance at best price execution. The SEC has now promised to ban this technique.

My personal trading strategy includes, looking for technical setups, interpreting price action, analyzing capital flows, and utilizing a disciplined money management methodology. The previously mentioned practices have led to the following changes in the market's behavior, and forced me to adapt accordingly.

Buying new highs, and selling new lows, rarely works now. Chasing momentum can be like chasing your own tail, as the market rarely follows through. Passive algorithms designed to sell-the-new-high, or buy-the-new low, dictate that traders need to take into account this phenomena, and make adjustments.

As a result of HFT, stocks touch more price points and may cause you to be stopped out of more positions. Algorithms are configured to "hunt stops", forcing the market to reach prices, that would not be reached under normal conditions, and elect stops. In addition, false buy and sell signals are more prevalent now, as competing algos battle one another.

Large institutional buy or sell orders, that used to move the market dramatically, are now executed more efficiently, and have less impact on the market. This makes momentum trading less profitable, and more difficult.

Limit orders may be difficult or impossible to get filled as HFT programs "step in front" of your orders, and slippage is greater, as programs drop the bids for lower prices, when they sense a sell order, or raise their offers, when they sense a buy order.

Traders' percentage of winning trades is likely to drop, and their risk-reward ratio may be less favorable now, so it is important, that money management remains the most important part of their trading strategy. In the "new" market dominated by HFT , setups that might have previously worked extremely well, either no longer work, or work marginally. However, variations on these setups might work extremely well, if adapted properly to the HFT environment. In other words, if you know what the HFTs are doing, and the effect they are having on the market, you can wait for the algos to do their thing, and react accordingly.

If traders want to remain successful, they must periodically remake themselves and their trading, by learning to adapt to changing market conditions. They first need to recognize why and how the markets have changed, and then they need to adjust their trading style so they can successfully adapt to how the markets currently trade. Loopholes in market rules give high-speed traders an unfair advantage, by allowing them to see what others are doing, or intending to do. Their computers can essentially trick or fool slower traders' computers, into giving up profits, and can do so in milliseconds. The repercussions of these actions have irrevocably changed the way the market trades, and has forced successful traders to adapt to a new market dynamic.

Last edited by tigertrader; October 9th, 2010 at 03:56 PM.
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  #3 (permalink)
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I absolutely agree with the above.

Trading is an Evolutionary Game

Trading is an evolutionary game. Strategies that have worked yesterday will not work today, and today's strategies will not work tomorrow. Similar to the evolution of species, trading strategies evolve and attract new predators. For further information on this, I recall the Axelrod Tournaments, which show how simple strategies, such as Tit-For-Tat dominated the early tournaments, while complex strategies took over at a later stage.

It is absolutely crucial to understand, who the other market participants are and what strategies they use. Technology is nothing else than a catalysator for change, so we are in a pond with large fish and smaller fish, and we compete for the same rare resources.

Most of trading strategies are either predatory - see the Turtle Soup Setup as an evolutionary response to the simple breakout strategies traded by the Turtle Traders - or sort of freeriding, such as neural nets and HFT exploiting the way large fish moves.

How does this affect your edge?

The understanding that I trade against others has already fundamentally changed my trading. The first generation algorithms that were used to execute large orders, were probably based on the TVAP, VWAP of the current day as a benchmark. Execution by following the typical volume profile of a trading day - see also relative volume indicator - with more or less aggressive corrections, if the actual volume deviates. Meanwhile the larger actors have more refined strategies, but the VWAP still works. So I do not have any more EMAs on my chart, but just the VWAP. It is an important trend filter, and I bet that the correction mechanism of larger buy programs use it to buy or sell near or at the benchmark. It becomes suppüort or resistance on trending days and an attractor/magnet on balancing days.

The electronic algorithms dominate the shortest time frames. As a human machine I am not competitive in that area. Making decisions in a few seconds can only be rule-based, and machines are better at executing rules. So I am not adventuring into that area. It is a dangerous area for the small fish I am. Also I am not aware of intermarket arbitrage, which might afffet this area.

But automated trading algorithms can be exploited as well. Any trendfollowing system suffers whipsaws if the price swings around unreasonably, so each generation of trading algorithms attracts its set of predators.

When watching the different instruments there are considerable differences. ES produces larger swings than the better trending YM. Possible reason: With its high liquidity ES is better suited for automatic trading systems, as the risk of not getting filled is low. These systems and the automatic execution algorithms certainly attract more and different predators than the price action of YM. I believe that ES has become one of the most competitive playing fields, and that few will earn profits by playing that game.

Easier to find a niche, which suits our capabilities and where competitivity is lower than in ES. Stocks are certainly easier to trade than futures, longer timeframes are easier to trade than shorter time frames, as risk aversion drives the undercapitalized traders into short time frames, where algorithmic predators are sitting and waiting for them.

Welcome in the Jungle

Yes, it is a jungle, and some of the species now have iron lungs.

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Meanwhile the larger actors have more refined strategies, but the VWAP still works.

Talking to my instititional investor/broker friends, shows that VWAP is still one of the key benchmarks that they are judged by.

Two great posts - thanks.


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