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BUMBERSHOOT PATTERN (INVERTED UMBRELLA) - Was created by Tokmurzin Askar as he discovered this pattern by him self after many years of trading.  This pattern signalling  for a good and strong impulse 

move and at the end it will look completely  like inverted umbrella.  

BUMBERHOOT EXAMPLE: MU US the picture above showing a perfect setup where the last move must be impule one  and confirming the pattern structure. 

Most sophisticated Institutional trading algorithms for market-making, order execution and trading.

Most sophisticated Institutional trading algorithms for market-making, order execution and trading.

Today we want to show the most sophisticated Institutional algorithms that is used by large institutional clients for market-making, order execution and trading.  



Iceberg (Iceberg)

An algorithm that dispenses orders . Of the true order quantity, only a part is shown on the board, and when the order placed on the board is executed, the next order is placed.


Don't put your order on the board, but take it when you get an order for the price you want to buy on the board.


An algorithm that places a limit order that is a certain value or a certain percentage away from the best quote, and follows it when the best quote fluctuates . Sometimes used for market making.


Place limit orders distributed across multiple prices in order to take a high priority position within each price .

Liquidity Driven Order

Monitor the liquidity of the board and place an order when the liquidity exceeds a certain level.

SOR (Smart Order Rouiting)

Place orders from multiple markets to the best market.



TWAP (Time-Weighted Average Price)

An algorithm that equalizes in time and places an order . Place an order by dividing the quantity you want to trade at equal time intervals.


VWAP (Volume-Weighted Average price)

An algorithm that aims to bring your VWAP closer to the market VWAP . In many cases , the volume is normalized by the volume distribution during the day and the quantity is sliced ​​before ordering.POW


POV(Percentage of Volume)

Place an order so that it accounts for a certain percentage of the market volume .


PI (Price Inline)

A modified version of VWAP. If the current price is smaller than VWAP, order a larger quantity, and if it is larger, order a smaller quantity.


MOC (Market on Close)

An algorithm that aims to bring its VWAP closer to the closing price of the market .


IS (Implementation Shortfall)

An algorithm that benchmarks the market price at the time of buying and selling decisions .




See market mid-market price

Determine your order price by referring to the market mid-market price.


Market price interlocking

Take the limit order left behind when the board situation changes and the price moves to either side .


Utilization of market liquidity

If there is a large order for another participant on the board, place an order in front of it.




Same product arbitrage

If the same product is traded in multiple markets, the price difference is determined.


Theoretical ruling

For objects such as derivatives for which the theoretical price can be calculated according to a model such as the financial price, the price difference from the theoretical price is determined.


Statistical ruling

Arbitrate statistical distortions that other market participants are unaware of.




Trend Following

We will trade with the expectation that the trends that occurred at the past will continue in the future.


Momentum Traing

Make transactions that take advantage of short-term momentum.




Range Trading

Trade with the expectation that the price will move within a certain range.


News / Event Driven

Transactions are triggered by stock price movements such as corporate news and announcements of indicators.



Front Running

The broker uses the order information from the customer to buy and sell in his own favor .



Place large orders at multiple prices and mislead other investors' forecasts.


Strike robbing (Strobing)

Placing an order on the board for a moment misleads other participants' predictions.


Momentum Ignition

Placing an order in a specific direction misleads other participants' predictions.


Stop Loss Ignition

Induce price movements by aiming for stop loss orders from other investors.


Push the Elephant

When there is a large order on the board that seems to be willing to buy or sell, induce a large order by updating the best quote with your own order.



Update the best quote on your order and manipulate the price of the dark pool referring to the quote.

Swing Trading With Three Indicators by Donald Pendergarst

Swing Trading With Three Indicators by Donald Pendergarst

Hello folks

Today I want to show u system of Donald Prendergast that was explained in in the December 2013 in journal "Stocks and Commodities "

Donald Pendergast

Donald Pendergast has studied technical price charts and market dynamics for more than 30 years and has had more than 1,000 articles on technical analysis, trading system development, and high-probability chart setups published at several trading/investing publications since 2008. Pendergast offers real-world trading signals for a basket of eight gold/silver mining stocks/ETFs and also offers high-quality, customized analysis for US stocks. 


Here's a look at my simple, visually based "trading with the trend" system that is nonoptimized, noncurve-fitted and is a no-brainer to construct and maintain. The key ingredient for success in trading with this template is you, because there are no secret market indicators or forecasting tools that can guarantee you trading success. But this no-cost trading template that is easy to construct will help you stay on track with the mental and emotional discipline needed to learn to trade profitably. After that, you may want to further fine-tune it by obtaining education in other market dynamics like relative strength analysis, money management techniques, price cycle studies, or wave analysis.

Before you begin, you first need to locate stocks and ETFs that tend to make relatively smooth, regular swing and/or trending moves (up or down, and preferably balanced over long periods of time) if you expect to achieve success with this system. In other words, look for volatile (high-beta), high-volume stocks from sectors and industry groups that tend to go on a bullish/bearish tear several times per year, and which don't spend too much time chopping around in directionless funks. Fast-moving, news-driven technology, mining, financial, or energy stocks are likely to be good hunting grounds for such desirable issues; you'll likely want to avoid sluggish markets like electric utility stocks or other highly regulated public service issues that tend to trade within small ranges most of the time.




The daily chart of Citigroup (C) in Figure 1 shows the three-indicator trading template; this was created using three standard indicators in TradeStation 9.1 (see Figure 2):

 A 50-day exponential moving average (EMA; blue line)
A five-day simple moving average of the daily highs (SMA; gold line)
A five-day simple moving average of the daily lows (SMA; red line)


The trading logic is very simple:

Long entry:

Go long when price exceeds the upper (gold) moving average of the daily highs by five ticks (0.05) and the price bar prior to the break of the upper moving average has closed above the blue 50-day EMA. (Note: If trading low-priced or high-priced stocks, you may want to decrease/increase the five-tick parameter as needed, since five ticks in a $300 stock is a much smaller entry filter amount than five ticks in a $40 stock, so adjust accordingly).
Once you are in a long trade, use the lower (red) moving average of the daily lows as your initial/trailing stop-loss for the life of the trade. Aggressive traders can use the low of the entry bar as the initial stop, but this will sometimes result in premature stop-outs and will entail extra commissions and effort; newer traders should just use the red line as the initial/trailing stop to keep things simple.

Short entry:

The rules for short entry are simply the inverse of the long entry setup.


The simulated test results aren't too shabby overall; the system made money on both sides of the market, although more on the long side. The closed trade drawdown was decent, and the profit factor was exceptionally good. Winners were much larger than losers on average, and there were no "catastrophic" losing trades -- a major plus. This means the model has good overall risk control even as it allows winning trades sufficient breathing room to develop.
Of course, this is just a sample trading strategy and no one knows if it will continue to perform as well as this in the future, but you can alter it, fine-tune it, automate it, add multiple exits, or just run it as-is, being sure to select a suitable, diverse universe of stocks or ETFs to trade it with.
Try using a longer or shorter EMA as your trend-confirmation line. Consider using, for example, a 21- or 30-day EMA to generate more trading opportunities, or perhaps an 80- or 100-day EMA to slow things down a bit. You can accomplish much of the same thing by lengthening/shortening the moving averages of the daily highs and lows, too. You can even control the dollar/share allocations by limiting your maximum account risk to perhaps 2% per trade or 0.75% to 1% per trade if you are trading it with a portfolio of six or more stocks. The possibilities for further development of this system are limited only by your understanding of the financial markets, trading skills, imagination, creativity, account size, and confidence level.


 Original and full story:



Buy and sell stocks in conjunction with President Trump's Twitter words

Buy and sell stocks in conjunction with President Trump's Twitter words

"ALGO-TRUMP"- the algorithm

One of the algorithmic trading that has become popular in recent years is to buy and sell stocks in conjunction with President Trump's Twitter words.

This is based on the fact that the stock price of a company that President Trump criticized by name on Twitter goes down, and when Prsident Trump tweeted a specific keyword, the system automatically reacts and buys and sells stocks.
In this way, it is also a feature that algorithms that match the trends of the times continue to be developed.


Although it is an algorithmic trading with great merits, it is not widely used among general investors because it costs a lot to introduce the system.

On the contrary, institutional investors and foreign investors who have financial power are actively using it, and it is also regarded as a problem that the gap with general investors is widening.

Harding phenomena in behavioral  trading

Harding phenomena in behavioral trading

Harding phenomenon


What is the ''Harding phenomenon''?
The harding phenomenon is a word that comes from the English word "Herd" (flock), and means that human beings tend to act according to the thoughts of others and many people.    Speaking of phenomena that are familiar to us, we buy products that are in fashion, and the queues call for more queues.The Harding phenomenon is known as one of the insights in "behavioral economics", but a synonym in behavioral economics may be the "bandwagon effect".   Behavioral economics has the perspective that "humans seem to be rational and behave irrationally" and "the economy created by humans also has irrationality born from such a psychological aspect", and stock investment and economy It can be said that it is one of the academic fields that are attracting attention in economics. We can see this tape of irrational behavioral action lots of times in financial markets when we see when price makes big divergence  agains company fundamentals. 


Is behavioral finance useful for investment?


Behavioral finance is the study of the influence of psychology on the behavior of investors or financial analysts. It also includes the subsequent effects on the markets. It focuses on the fact that investors are not always rational, have limits to their self-control, and are influenced by their own biases.

An example of the harding phenomenon in stock investment is the case where the stocks being bought are bought further and the high price is renewed.  In addition, it can be said that the irrationality of the harding phenomenon was glimpsed in the bubble formation of the subprime loan market that started the Lehman shock.   

Especially if you are a beginner in investment, you may intuitively think that the stocks that are going up will go up even more, and you may buy them and grab a high price. Behavioral economics proposes that human beings have the property of "heuristics" in which they make decisions based on past experience, apart from making logical thoughts when making decisions.  For example, this heuristic works well when multiplying and when making daily habits, but when it comes to investing, that thought can be a nuisance. Emotional investment decisions that are not based on rules do not have a statistical advantage and the method does not always work.   It is often said that "90% of individual investors lose", but many of them include failures due to lack of understanding of human irrationality and psychology. Isn't it?     Then, what kind of attitude should we take in investing so that we do not lose 90%?


Metacognition is important

In trading, it can be said that there is no way of thinking or method that "if you do this, you will definitely win", but what is important is "metacognition".  "Meta" is a prefix that means "beyond" and "contains", and "metacognition" means "recognizing cognition."   It is confusing to write cognition as cognition, but it can be said that it refers to the state of being able to see oneself objectively, what one is thinking.
What I am doing now can only be expressed from my own experience.   However, by reading a book or learning a new concept, you will be able to express that behavior in a new way.

Behavioral economics focuses on human scientific psychology, and human psychology such as "status quo bias" and "loss effect" will help us to see our thoughts and actions objectively.
If you are an investor, you will understand that you can trade calmly when you are winning, but you will panic or your mentality will be shaken when you are losing and you will make an appropriate trade. I think you have some experience.   Of course, everyone suffers failures and losses, but in order to reflect on them and improve them, it is of course important to omit "why did they fail?"   In the process, metacognition may be useful for verbalizing and embodying failure.   How to acquire metacognition   As a way to acquire metacognition, as I wrote earlier, reading a book to acquire new knowledge and making it a habit to draw a cycle to improve one's behavior can be mentioned. It may be a good idea to notice ideas and habits that you are not aware of and try to live while being aware of how to correct them.

If you know the word "harding phenomenon", you should have the perspective of "because it is a harding phenomenon, isn't it profitable to make a contrarian here?" Can be done.  It will be possible to broaden the range of investment and thinking by not only synchronizing with the way of thinking around you, but also by firmly holding your own investment axis.   Learning the knowledge of behavioral economics, not limited to the Harding phenomenon, is useful for making investments, so it may be good to learn it.









The random walk theory is a theory that explains that "the movement of stock prices cannot be predicted." Simply put, no matter what has happened in the past, there is always a 5: 5 chance that tomorrow's market will go up or down.



The random walk theory is a concept in finance that suggests that stock prices follow a random and unpredictable pattern, making it difficult to predict future price movements. This theory is based on the idea that past market trends and performance are not reliable indicators of future market performance. Despite this, the theory of random walks does not mean that it is impossible to make a profit in the stock market, as the share price of a company is ultimately tied to its future performance and profitability.

In contrast to random walks, speculative trading involves aggressive buying and selling of stocks in order to generate a profit that exceeds the average market return. This often requires expert knowledge and analysis of market trends, but it can also involve significant risk. In contrast, passive investing aims to achieve returns that are in line with the market average, and this typically involves a more straightforward investment strategy, such as buying stocks in a market index.

The theory of random walks suggests that it is difficult for active traders to outperform passive investors, as the unpredictable nature of the stock market makes it difficult to consistently generate higher returns. To mitigate the impact of random walks, traders can focus on more predictable and liquid markets, trade in blue-chip stocks, follow market flows, trade based on news events, and trade during market openings or mid-day. However, even with these strategies, it is important to recognize that the stock market remains inherently unpredictable and that there is always some degree of risk involved in trading.

The theory of random walks has been widely researched by economists and financial researchers. One of the earliest and most influential proponents of the random walk theory was French mathematician Louis Bachelier, who published a PhD thesis on the subject in 1900. In the decades since, many economists and financial experts have conducted research on the random walk theory and its implications for financial markets. Some of the notable scientists and economists who have contributed to the research on random walks include Paul Samuelson, Eugene Fama, and Burton Malkiel. Today, the concept of random walks remains a central topic in the field of finance and continues to be studied by researchers in universities and financial institutions around the world.


Much less room for human judgment right?

So why can't active trading outperform passive investing? In active trading, the professional manager makes full use of theory and data to determine when to buy and when to sell. However, using the theory of random walks based on the theory of probability, it is impossible to predict the market price no matter which method is used. Sometimes it succeeds, and sometimes it does not, and the result is at the level of the market average. However, active trading is more expensive for managers and inventory analysis, so the results are worse than passive investing.


While the theory of random walks suggests that stock prices follow a random and unpredictable pattern, there are a few strategies that traders can use to mitigate the impact of random walks and potentially improve their returns:

  1. Trade only in liquid markets: Liquid markets are markets that have high trading volumes, which can make it easier to buy and sell stocks quickly and at reasonable prices.

  2. Focus on blue-chip stocks: Blue-chip stocks are stocks of well-established companies with a history of stability and steady growth, which may be less susceptible to the effects of random walks.

  3. Trade based on market flows: Monitoring market trends and flows can help traders to identify trends and make more informed trading decisions.

  4. Trade based on news events: Following news events related to the stock market and individual companies can help traders to stay informed about market conditions and make informed trading decisions.

  5. Trade during market openings or mid-day: Trading during these periods may offer more opportunities to trade and take advantage of market fluctuations.

It is important to note that while these strategies may help to reduce the impact of random walks, they are not guarantees of success and there is always some degree of risk involved in trading. Additionally, it is important to have a well-informed and diversified investment strategy in order to mitigate risk and achieve long-term success in the stock market.


Tokmurzin Askar
Tokmurzin AskarOwner of
PROFILE: Stock and bond trader. In-depth knowledge of market making and running client prop book. Algorithmic trader and trading systems developer. SPECIALITY: London GDR’s & Kazakh cash equities, Eurobonds and international future contracts on indices & currencies. Proprietary trader, long/short for maximum returns. More than 14 years of International career in front office positions, as head trader and head of trading in Investment banks. Experienced market maker for more than 50 emerging market securities.

Past performance is not necessarily an indicator of future performance.

These results are based on simulated or hypothetical work results, which have certain inherent limitations. Unlike the results shown in the real performance report, these results do not reflect real trading. In addition, since these transactions have not actually been completed, the results may not be adequately or excessively offset by the influence, if any, of certain market factors, such as lack of liquidity. Modeled or hypothetical trading programs in general are also subject to the fact that they are developed based on previous indicators. None of the reported system performance reports guarantee that any account will achieve the same profit or loss ratio close to those shown.

 In addition, hypothetical trading does not involve financial risk, and the indicators of a non-hypothetical trading report cannot fully take into account the impact of financial risk in actual trading. For example, the ability to sustain losses or adhere to a certain trading program, despite trade losses, is a significant factor that can adversely affect the actual results of trading. There are many other factors related to the markets as a whole or to the implementation of any particular trading program that cannot be fully taken into account when preparing hypothetical results, each of which can adversely affect the actual results of trading.

Futures and forex trading contains substantial risk and is not for every investor. An investor could potentially lose all or more than the initial investment. Risk capital is money that can be lost without jeopardizing ones’ financial security or life style. Only risk capital should be used for trading and only those with sufficient risk capital should consider trading. Past performance is not necessarily indicative of future results.