How can a Day Trading TA price action pattern trader apply this wisdom?
Why does this happen ? Please help
- Thread starter cashclay
- Start date
ABSOLUTELY NOT!
The backtest is THE most important thing.
If your trading system cannot make money after 500 or 1000 historical trades just go back to bed.
No mathematical edge no money, period.
Traders should NEVER risk one penny on untested, unproven trading "systems", end of story.
PS: by the way, mathematical edge means beating buy and hold by some comfortable margin, usually 5% or more.
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"For some reason"? LOL! This is exactly why one of the cornerstones of technical trading is to "sell resistance*".
*This info should be ignored by traders who believe "TA doesn't work".
Yeah but WHY is that particular level a resistance though?? Why not other levels?? This is what @cashclay is trying to find out. And when you can't find any explanations to justify that particular level being a resistance, that's when all the TA non-believers proclaim "TA does not work". LOL
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This is a rather poor answer coming from a pro in my opinion. For every transaction, there is a buyer and a seller. Their motivations might be different, and that is what creates the sudden moves, but it doesn't change the fact that for someone to want to sell, someone has to buy, and vice versa.
Disagree. Even trading sim is a waste of time if you don't already believe you "know the chart plays".
Scatty's formula for becoming a winning trader...
1. Learn some of the chart plays
2. Trade your plays in sim and find out you don't "have it down" like you hoped you do.
3. Back to chart study
4. Back to #2.
5. Rinse and repeat until it appears you've got a winning plan.
6. Go live with small $$
7. Learn things about your reaction to money stress and have your discipline (or lack thereof) be accounted for.
8. When your small money results are consistently good and you have a handle on capital preservation, then you can consider "trading for real".
Good luck to all.
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I played the $5 calls and took a quick gain because sellers were brutal. You could see the sellers keep refreshing unlike ISEE or NEGG killing the shorts.
What exactly is the thought process that led you to that conclusion?
Evenly-spaced sharp spikes and plunges, responding to increases/decreases in price, arguably volume. My comment is based on an understanding of Transaction Cost Analysis and Implementation Shortfall. Basically, the goal is to generate and take profits while minimizing both transaction costs and share price. This is typically accomplished with an algorithmic approach: structured buys and sells at regular intervals, often linked to volume, but not always.
The OPs question was why these sharp spikes and plunges occur; this seems a plausible explanation. It always puzzled me why technical traders don't spend more time studying algo design and construction. Today's market is absolutely DOMINATED by algos, AI, and the like. That's the tell--that's what's painting the tape in specific patterns! If you can spot an algo's signature on an instrument, you'll be in the money quickly.
I've even seen algos to paint the tape and create a specific pattern to generate a desired response from pattern day traders. E.g., if you've got some capital, it's not too hard to paint a head-and-shoulders in an instrument with relatively low volume, right? Just Buy, Sell, Buy, Buy, Sell, Sell, Buy, Sell.
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I'm going to give you a very important lesson in price action:
1. There are market orders (includes some algos)
2. There are limit orders (includes some algos)
Market orders are the flows between buyers and sellers and vice versa at the best available price. Limit orders are some distance above and below the best price, or they would be marketable and execute. Prices fluctuate "randomly" when flow is sufficient to keep prices from hitting the limit order book (which you cannot observe).
Under market efficiency rules, the price of a stock should reflect all known prices. So when new information comes out, it should look like this:
Instead, in real life, the market "overreacts" to information, and the actual profile of price is more similar to this:
Note: the actual shape of over/underreaction can vary, but the concept is the same
Why does this happen? Well, the last price before new information was the equilibrium where supply met demand at existing information.
With new information, there is a shock to volume (on either the bid or offer), which pushes the stock above and beyond the new equilibrium price. The return from selling an overreaction is the compensation for providing liquidity in a tight market, which means you are a net seller of a stock that is seeing a spike higher. If you buy, instead, you are assuming that there will be additional momentum in volume.
Going back to this stock:
Here is an analysis of average volume at time, which is useful in seeing what's happening to a stock.
You can see when 1) volume spiked higher, 2) when it peaked, and 3) the gradual decrease in new avat. This tells us that most of the exogenous shock occurred at the start of the day.
Without looking at the stock, I can infer that there would have been a big spike in price (overreaction) followed by a period of decreasing volatility and more stable prices.
Another thing to note-- most trades are crossing in darkpools:
Finally, we review price and volume data:
As expected, it looks like the stock followed the general overreaction function. Stock ends the day just under 20% higher:
Why did volume increase so much?
Well, large investors make decisions based upon an analysis of future cash flows, the value of a security, and how likely a company is to hit its targets.
These are the biggest investors in the company:
- CGP and Grand Decade (China Pharma) own 40%+
- Avidity (ex-Citadel healthcare focused fund)
- Sirtex (medical device company owned by CGP)
If you go back to the value of a security -- it is the sum of future cash flows discounted by present value. The discount rate (and multiple if you're using that) will incorporate the probability of a stock reaching a cash flow number.
In this example, from equity research, we see that an analyst has these probabilities for product success:
And does not expect revenue until 2022:
Well, today's news added information that potentially increased the probability of product success and may speed up their revenue timeline:
Compare that to this list of upcoming catalysts:
Sometimes the market needs time to digest complex news ("the slow diffusion of information"). This might be the situation here, which means we may continue to see elevated volatility until more details about the Merck trial is released.
1. There are market orders (includes some algos)
2. There are limit orders (includes some algos)
Market orders are the flows between buyers and sellers and vice versa at the best available price. Limit orders are some distance above and below the best price, or they would be marketable and execute. Prices fluctuate "randomly" when flow is sufficient to keep prices from hitting the limit order book (which you cannot observe).
Under market efficiency rules, the price of a stock should reflect all known prices. So when new information comes out, it should look like this:
Instead, in real life, the market "overreacts" to information, and the actual profile of price is more similar to this:
Note: the actual shape of over/underreaction can vary, but the concept is the same
Why does this happen? Well, the last price before new information was the equilibrium where supply met demand at existing information.
With new information, there is a shock to volume (on either the bid or offer), which pushes the stock above and beyond the new equilibrium price. The return from selling an overreaction is the compensation for providing liquidity in a tight market, which means you are a net seller of a stock that is seeing a spike higher. If you buy, instead, you are assuming that there will be additional momentum in volume.
Going back to this stock:
Here is an analysis of average volume at time, which is useful in seeing what's happening to a stock.
You can see when 1) volume spiked higher, 2) when it peaked, and 3) the gradual decrease in new avat. This tells us that most of the exogenous shock occurred at the start of the day.
Without looking at the stock, I can infer that there would have been a big spike in price (overreaction) followed by a period of decreasing volatility and more stable prices.
Another thing to note-- most trades are crossing in darkpools:
Finally, we review price and volume data:
As expected, it looks like the stock followed the general overreaction function. Stock ends the day just under 20% higher:
Why did volume increase so much?
Well, large investors make decisions based upon an analysis of future cash flows, the value of a security, and how likely a company is to hit its targets.
These are the biggest investors in the company:
- CGP and Grand Decade (China Pharma) own 40%+
- Avidity (ex-Citadel healthcare focused fund)
- Sirtex (medical device company owned by CGP)
If you go back to the value of a security -- it is the sum of future cash flows discounted by present value. The discount rate (and multiple if you're using that) will incorporate the probability of a stock reaching a cash flow number.
In this example, from equity research, we see that an analyst has these probabilities for product success:
And does not expect revenue until 2022:
Well, today's news added information that potentially increased the probability of product success and may speed up their revenue timeline:
Compare that to this list of upcoming catalysts:
Sometimes the market needs time to digest complex news ("the slow diffusion of information"). This might be the situation here, which means we may continue to see elevated volatility until more details about the Merck trial is released.
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I'm not sure where you get your understanding of TCA and implementation shortfall from. I was a desk trader and no one was using algos to paint head and shoulders to improve TCA or IS lol. For most large trades, a trader will seek non-exchange liquidity before lighting up.