Why Large Language Models Struggle with Financial Analysis.Large language models revolutionized areas where text generation, analysis, and interpretation were applied. They perform fabulously with volumes of textual data by drawing logical and interesting inferences from such data. But it is precisely when these models are tasked with the analysis of numerical, or any other, more-complex mathematical relationships that are inevitable in the world of financial analysis that obvious limitations start to appear.
Let's break it down in simpler terms.
Problem in Math and Numerical Data Now, imagine a very complicated mathematical formula, with hundreds of variables involved. All ChatGPT would actually do, if you asked it to solve this, is not really a calculation in the truest sense; it would be an educated guess based on the patterns it learned from training.
That could be used to predict, for example, after reading through several thousand symbols, that the most probable digit after the equals sign is 4, based on statistical probability, but not because there's a good deal of serious mathematical reason for it. This, in short, is a consequence of the fact indicated above, namely that LLMs are created to predict patterns in a language rather than solve equations or carry out logical reasoning through problems. To put it better, consider the difference between an English major and a math major: the English major can read and understand text very well, but if you hand him a complicated derivative problem, he's likely to make an educated guess and check it with a numerical solver, rather than actually solve it step by step.
That is precisely how ChatGPT and similar models tackle a math problem. They just haven't had the underlying training in how to reason through numbers in the way a mathematics major would do.
Financial Analysis and Applying It
Okay, so why does this matter for financial analysis? Suppose you were engaging in some financial analytics on the performance of a stock based on two major data sets: 1) a corpus of tweets about the company and 2) movements of the stock. ChatGPT would be great at doing some sentiment analysis on tweets.
This is able to scan through thousands of tweets and provide a sentiment score, telling if the public opinion about the company is positive, negative, or neutral. Since text understanding is one of the major functionalities of LLMs, it is possible to effectively conduct the latter task.
It gets a bit more challenging when you want it to take a decision based on numerical data. For example, you might ask, "Given the above sentiment scores across tweets and additional data on stock prices, should I buy or sell the stock at this point in time?" It's for this that ChatGPT lets you down. Interpreting raw numbers in the form of something like price data or sentiment score correlations just isn't what LLMs were originally built for.
In this case, ChatGPT will not be able to judge the estimation of relationship between the sentiment scores and prices. If it guesses, the answer could just be entirely random. Such unreliable prediction would be not only of no help but actually dangerous, given that in financial markets, real monetary decisions might be based on the data decisions.
Why Causation and Correlation are Problematic for LLMs More than a math problem, a lot of financial analysis is really trying to figure out which way the correlation runs—between one set of data and another. Say, for example, market sentiment vs. stock prices. But then again, if A and B move together, that does not automatically mean that A causes B to do so because correlation is not causation. Determination of causality requires orders of logical reasoning that LLMs are absolutely incapable of.
One recent paper asked whether LLMs can separate causation from correlation. The researchers developed a data set of 400,000 samples and injected known causal relationships to it. They also tested 17 other pre-trained language models, including ChatGPT, on whether it can be told to determine what is cause and what is effect. The results were shocking: the LLMs performed close to random in their ability to infer causation, meaning they often couldn't distinguish mere correlation from true cause-and-effect relationships. Translated back into our example with the stock market, one might see much more clearly why that would be a problem. If sentiment towards a stock is bullish and the price of a stock does go up, LLM simply wouldn't understand what the two things have to do with each other—let alone if it knew a stock was going to continue to go up. The model may as well say "sell the stock" as give a better answer than flipping a coin would provide.
Will Fine-Tuning Be the Answer
Fine-tuning might be a one-time way out. It will let the model be better at handling such datasets through retraining on the given data. The fine-tuned model for sentiment analysis of textual stock prices should, in fact, be made to pick up the trend between those latter two features.
However, there's a catch.
While this is also supported by the same research, this capability is refined to support only similar operating data on which the models train. The immediate effect of the model on completely new data, which involves sentiment sources or new market conditions, will always put its performance down.
In other words, even fine-tuned models are not generalizable; thus, they can work with data which they have already seen, but they cannot adapt to new or evolving datasets.
Plug-ins and External Tools: One Potential Answer Integration of such systems with domain-specific tooling is one way to overcome this weakness. This is quite akin to the way that ChatGPT now integrates Wolfram Alpha for maths problems. Since ChatGPT is incapable of solving a math problem, it sends the problem further to Wolfram Alpha—a system set up and put in place exclusively for complex calculations—and then relays the answer back to them.
The exact same approach could be replicated in the case of financial analysis: Once the LLM realizes it's working with numerical data or that it has had to infer causality, then work on the general problem can be outsourced to those prepared models or algorithms that have been developed for those particular tasks. Once these analyses are done, the LLM will be able to synthesize and lastly provide an enhanced recommendation or insight. Such a hybrid approach of combining LLMs with specialized analytical tools holds the key to better performance in financial decision-making contexts. What does that mean for a financial analyst and a trader? Thus, if you plan to use ChatGPT or other LLMs in your financial flow of analysis, such limitations shall not be left unattended. Powerful the models may be for sentiment analysis, news analysis, or any type of textual data analysis, numerical analysis should not be relayed on by such models, nor correlational or causality inference-at least not without additional tools or techniques. If you want to do quantitative analysis using LLMs or trading strategies, be prepared to carry out a lot of fine-tuning and many integrations of third-party tools that will surely be able to process numerical data and more sophisticated logical reasoning. That said, one of the most exciting challenges for the future is perhaps that as research continues to sharpen their capability with numbers, causality, and correlation, the ability to use LLMs robustly within financial analysis may improve.
Study
$PFENot financial advice.
Per the STRAT system
NYSE:PFE
Scenario #1 in the monthly candle already went bullish reversal. If we break yellow line will go on a PMG (pivot machine gun) target on small yellow lines.
Scenario #2
we reverse and break white line will go to the bottom of the channel.
Like and follow for more ideas
EURUSD Trade study short/longTrade study using Asian range.
Trade went below opening candle in London session indicating bullish but wasn't noticed. Price also took the Asian lows before moving up. Price then consolidated before taking the Asian high, then took the recent swing low at lower timeframe indicating out POI. Price then eventually achieved our target Price Asian range low then took Thursdays (Asian high +4) before taking our initial Target (Asian range -1). Trading in Friday is complicated but with proper risk management we was able to take a 1:1.2rr trade
Using proper risk management is always necessary which I didn't do for some reason
NOTE : PRICE ALWAYS MOVES FOR A REASON
Weekend Research 2 Birla Cable Ltd. CMP 293.4Birla Cable Limited (Formerly known as Birla Ericsson Optical Limited) is a premier company in the field of Telecommunication Cables, which offers one of widest portfolio of Copper and Fibre Optic cables under its umbrella.
The negative aspect of the company is high promoter stock pledging, decline in net profit and fall in profit margin of the company. The positive aspect of the company is technical momentum is shifting towards positive and the company chart shows that the company is trying to build a firm base between 260 to 290. MACD is also indicating positive momentum.
Entry in the stock can be taken after closing above 295. Targets will be 312 and 335. Long term targets in the stock will be 354 and 375. Stop loss in stock can be maintained at a weekly closing below 250.
The above information is provided for educational purpose, analysis and paper trading only. Please don't treat this as a buy or sell recommendation for the stock. We do not guarantee any success in highly volatile market or otherwise. Stock market investment is subject to market risks which include global and regional risks. We will not be responsible for any Profit or loss that may occur due to any financial decision taken based on any data provided in this message.
Understanding the "Dead Cat Bounce" in TradingIn the dynamic world of trading, one peculiar phenomenon that often catches investors' attention is the "Dead Cat Bounce." This term, as bizarre as it sounds, is a crucial concept in technical analysis and market psychology. It refers to a temporary recovery in the price of a declining stock, followed by a continuation of the downtrend. This article delves into the nuances of the Dead Cat Bounce, helping traders recognize and navigate this pattern effectively.
What is a Dead Cat Bounce?
Originating from the saying, "even a dead cat will bounce if it falls from a great height," this metaphor is used to describe a brief and false recovery in a bear market. Essentially, it's a short-lived rally in the price of a stock or an index following a substantial decline, misleading some into believing that the downtrend has reversed.
Characteristics of a Dead Cat Bounce
Precipitating Sharp Decline: Typically, a Dead Cat Bounce occurs after a significant and rapid drop in price.
Temporary Rebound: The stock or index experiences a brief period of recovery, which may be mistaken for a trend reversal.
Resumption of Downtrend: The initial downtrend resumes, often eroding the gains made during the bounce.
Identifying a Dead Cat Bounce
The key challenge for traders is differentiating between a true market recovery and a Dead Cat Bounce. Here are some indicators:
Volume Analysis: A genuine recovery often accompanies increasing trade volumes, whereas a Dead Cat Bounce may occur on lower volumes.
Duration: Dead Cat Bounces are usually short-lived, lasting from a few days to a couple of weeks.
Technical Indicators: Tools like moving averages, RSI (Relative Strength Index), and Fibonacci retracements can aid in identifying these patterns.
Trading Strategies for Dead Cat Bounces
Short Selling: Traders might short sell a stock during a Dead Cat Bounce, anticipating the resumption of the downtrend.
Stop-Loss Orders: Setting strict stop-loss orders can mitigate risks if the bounce turns out to be a genuine reversal.
Patient Observation: Sometimes, the best strategy is to wait and observe the price action for clearer trend confirmation.
Case Studies and Examples
Analyzing past instances of Dead Cat Bounces can be educational. For instance, examining the 2008 financial crisis or the dot-com bubble burst reveals classic examples of this phenomenon.
Conclusion
The Dead Cat Bounce is a fascinating aspect of market behavior, representing the constant battle between optimism and reality in trading. Understanding this concept is not just about recognizing a pattern but also about grasping the underlying market psychology. As always, traders should approach these scenarios with caution, equipped with sound research and a well-thought-out strategy.
[STUDY] Bond Rates VS Real RatesSplit view showing the previous real rate of Bonds study along now with the actual Bond Yields. This is to gain insight into Demand dynamics for Bonds and what happens to yields when real yields are positive (expectation is that positive real yields will increase demand, reducing supply, and allowing Treasury to increase Bond prices and reduce yields.
Understanding Scarcity, Choice, and Resource AllocationWelcome to our third ever blog in our economics masterclass. Today we will be going over and Understanding Scarcity, Choice, and Resource Allocation.
[Section 1.4: Scarcity, Choice, and Allocation of Resources
The basic economic problem stems from scarcity, where wants are unlimited, but resources are finite, necessitating choices. Optimal utilization and distribution of resources are crucial.
For example, when you have only £1 to spend at a shop, you must choose between buying a chocolate bar or a packet of crisps due to the scarcity of money. This leads to the concept of opportunity cost, which is the value of the next best alternative foregone. The opportunity cost of choosing the crisps, in this case, would be the chocolate bar. Economic agents such as consumers, producers, and governments must consider opportunity costs when making decisions. Finite resources require careful allocation to achieve the best outcomes.
This section leads on nicely to our first ever some what complex economic theory.
Production Possibility Frontiers (PPFs)
Production Possibility Frontiers (PPFs) depict the maximum productive potential of an economy by using a combination of two goods or services when resources are fully and efficiently employed. PPF curves illustrate the opportunity cost associated with using scarce resources.
Below is an example of a PPF curve for Cheese and yoghurt
(tradingview dot com /chart/AAPL/rNnd689O-PPC-GRAPH)
An example could be, if milk is a scarce resource, there is a trade-off between producing more cheese or more yogurt from the milk. The PPF showcases the most efficient combinations of output (points A and B), where producing more yogurt incurs an opportunity cost of producing less cheese.
The law of diminishing returns states that as more yogurt is produced, the opportunity cost in terms of lost cheese units increases. Points C and D on the PPF represent inefficient production, where resources are not fully utilized. Point E is currently unattainable with the existing resources.
(tradingview dot com /chart/AAPL/YRb7mwU2-ppc-grpah-aks/)
This PPF shows the opportunity cost of producing each product. Producing 100 units of cheese means that only 40 units of yoghurt can be produced instead of the
potential of 90. Therefore, the opportunity cost is 90 - 40 = 50 units of yoghurt.
The PPF not only illustrates opportunity costs but can also indicate economic growth or decline. Economic growth is depicted by an outward shift of the PPF curve, indicating an increase in the economy's productive potential.
A decline in the economy is represented by an inward shift of the curve.
Economic growth can be achieved by increasing the quantity or quality of resources, resulting in an outward shift of the PPF curve.
Supply-side policies can facilitate this. Moving along the PPF incurs opportunity costs, while shifting the PPF curve outward reduces the opportunity cost of producing different goods.
Productive efficiency is achieved when resources are utilized optimally along the PPF curve, while allocative efficiency involves the optimal distribution of goods in society.
We have now covered every section for the first topic behind the A level spec for microeconomics!
4.1 Individuals, firms, markets and market failure ✅
4.1.1.1 Economic methodology ✅
4.1.1.2 The nature and purpose of economic activity ✅
4.1.1.3 Economic resources ✅
4.1.1.4 Scarcity, choice and the allocation of resources✅
4.1.1.5 Production possibility diagrams✅
$SE #SE how low is going this week .. #opportunity being with NYSE:SE from IPO times one could guess importance of this company on many other levels , not just trading it to profit , but to grow your position on every dip
I use to my advantage simple indicators to achieve just that , using similar to DRIP account I was able to accumulate 677% , with kind free" cash anyone can play this stock as a reserve bank for other use in trade larger cups
Nas100 long 1h 1hr chart entry, long till the previous break of structure. normally i would put my TP a bit under but close to the 21 Moving average but I have a feeling it will wick past it and come back down if anything or just go up noting on the 4hr the price is above the 200 Moving average still
What is the golden stop-loss rule?
For trades such as stocks, futures, or forex, stop loss is a part of the trade, and it only works for investors if there is a stop loss in each transaction and it is adhered to. Today, I bring you a 3:1 gold stop loss rule, hoping to help with your investments.
Stop loss is a way to minimize losses in current market trades and is frequently mentioned. However, the essence of stop loss is not just setting a stop loss price. In particular, in markets such as forex and futures where long and short positions can be taken, too many stop losses will undoubtedly cause significant loss of capital. Market leaders use people's fear to cause repeated shocks, even unilateral rises or falls to trigger short-term traders' stop loss prices, and then quickly retract. The normal daily volatility of the stock market is also around 5%, so if your stop loss is set at 5%, won't it often be hit?
This requires attention to two issues: first, judging the trend of the market, whether it is a volatile market or a clear trend market; second, setting a reasonable stop loss position.
First of all, it's important to understand that the most notable characteristic of the trading market is volatility, and most of the time it's in a volatile trend, regardless of whether it's in a larger time frame or a shorter time frame. Therefore, the investment strategy for a volatile market should be the preferred strategy for short-term traders.
Secondly, identifying the range of volatility is crucial. Find the highest and lowest prices in recent price fluctuations. After a sharp rise or fall in the market, a corrective wave will form between these highest and lowest prices, sometimes lasting a long time. For example, commonly seen patterns such as triangle consolidation or box consolidation require a longer period of time before forming a new breakthrough. As for what prices to choose as the range, it depends on your trading period, whether it's daily, weekly, 60-minute, or even minute-by-minute. By using price analysis to determine the operational cycle, you will find a clear pattern of fluctuation range. The stop-loss price for such fluctuations should be set outside the highest or lowest points, and smaller stop-loss or trailing stop-loss should not be used.
When the price breaks through the highest point, it is necessary to observe its sustainability. In most cases, it will return to the range-bound area again. However, if the sustainability is strong, it continuously sets new highs, and trading volume continues to increase, a new trend can be determined, and the stop-loss can be changed to a trailing stop. Its price should be set at a price that falls more than one time period beyond the highest or lowest price, and there is no new high or low in three consecutive time periods. At this time, it can be judged that the trend has stopped and entered a range-bound market. For example, if the time period is a 5-minute candlestick chart, then the trailing stop should be set at a price formed by a relatively large 5-minute candlestick chart. But generally, it should not exceed two candlestick chart prices, because beyond this price, the profit left is often very small.
The 3:1 golden stop-loss rule in trading skills means that the profit of the take-profit point is three times the loss of the stop-loss point. For example, if you buy a stock and it falls by 7% or 8%, you should close your position in a timely manner. When your stock rises by 20% to 25%, you should consider selling some of it, and not be greedy and wait for it to rise further. Of course, the percentage values here can be changed according to the market situation, but the ratio should always be maintained at 3:1.
Some investors may have doubts, what if I set a stop loss at 8% and then the stock rises significantly, even by more than 50%, after I sell it? It seems like a big mistake to sell it, and many investors may no longer believe in the 3:1 rule. Actually, the reason why we set a stop loss at 8% is to prevent it from falling by 10%, 20%, 25%, 40% or even more. You can think of it as a small insurance premium to ensure that an 8% loss doesn't turn into a 60% loss. Isn't it easier to handle that way? For most investors, an 8% loss is manageable, but a 60% loss is a burden that many cannot afford.
In the market, human weaknesses will be reflected. When you hold a stock that falls, you will lose some capital, and you will fear that it will continue to fall, rather than hoping it will rebound to make up for previous losses. As a defensive measure, trading systems should still follow the 3:1 rule for stop losses. Finally, I wish everyone a happy investment journey.
Gongmyeong's Knowledge Sharing - Step 5
< Let's just watch it for three minutes! Zhuge Gongmyeong's Knowledge Sharing >
Step 5. Types of bearish candles
Let's talk about the types of bullish candles yesterday and the types of bearish candles today.
Likewise, let's classify the types based on the shape.
First, the hanging candle.
It's a candle that went down to a low price and then went up a little.
It's a bearish candle with a tail at the bottom.
The shorter the torso and longer the tail, the more likely the next movement is to rise.
Next is 'meteoric candle'.
It's a candle that goes up once and then rolls down all the gains and then goes down further.
Because both the torso and tail contain the drop, the longer the torso and tail, the greater the influence.
If these cans appear at the high point, they are likely to turn downward.
Lastly, "long stick - bearish candle".
The properties are similar except for the pole bullish candle and the bearish/bullish.
It's a light stick candle with only the body without a tail up and down.
In general, there is a very strong downward trend in the process of these cans appearing, and the longer the torso, the more the amount of decline, so it exerts a greater influence.
Today, we've looked at the typical types of bearish candles.
Likewise, when you look at the shape of the candle on the actual chart, let's review it so that the characteristics of the candle come to mind!
Gongmyeong's Knowledge Sharing - Step 4
< Let's just watch it for three minutes! Gongmyeong's Knowledge Sharing >
Step 4. Types of bullish candles
We've looked at the composition of the candles in the previous sections.
Today, we're going to classify the types of bullish candles based on their shapes.
First, it's a hammer-type candle.
It's a candle that went down to low prices and then went up.
The shape has a tail only on the bottom.
If these candles came out of the low point, you can expect a trend shift to an upward trend.
The shorter the body and the longer the tail, the more reliable the candle is.
Next is the reverse hammer type candle.
Although it is a bullish candle, it is a candle that is bent at the end and left the upper tail.
The shorter the torso and longer the tail, the higher the probability that the next move will be a drop.
Conversely, the longer the torso and shorter the tail, the stronger the upward force, so the next is the higher the probability of ascending.
The length of the tail and body is important.
Lastly, it's "a long-stick candle".
The shape itself is simple, but it's a beekeeping candle with only the body without the top and bottom tails.
In general, there's a very strong upward trend in the process of these cans appearing, and the longer the torso, the greater the amount of upward movement, so it exerts a greater influence.
Today, we've looked at a typical type of bullish candle, and the shape of the candle is very important because it represents the power to move up and down.
When you look at the shape of the candle on the actual chart, let's review it so that the characteristics of the candle come to mind!
Gongmyeong's Knowledge Sharing - Step 2
< Let's just watch it for three minutes! Zhuge Gongmyeong's Knowledge Sharing >
We learned the basic theory about the composition of candles yesterday, and today we're going to summarize the names of the candles while looking at the actual candles.
You can think of it as a review of yesterday's content!
First, let's look at the left candle.
The left candle is green, so it's bullish candle.
- Bullish candle is a candle with a higher closing price than the starting price, which means that the price was higher at the end than at the beginning of the candle formation.
The starting price and the closing price can be confusing, so let's find out the easiest high price and low price first.
The high price is the highest price in the candle. They don't care about bullish or bearish candle.
The low price is the lowest price in the candle, as opposed to the high price.
In these candle, the high price is around 22315 and the low price is around 22250.
In the bullish candle, the 'starting price' is 'below' the closing price.
So the red part is the beginning of the candle. It looks like 22265.
The closing price is the blue part located on the opposite side. It looks like it's about 22300.
This time, let's distinguish between the body and the tail.
*If you divide the bullish candle into tail and body, it can be divided into three categories: lower tail, body, and upper tail.
Lower tail (low price ~ market price)
Body (shiga to closing price)
Upper tail (Closing price ~ expensive)
We found low prices, starting prices, closing prices, and high prices earlier, so you can replace them as they are.
Lower tail (22250 to 22265)
Body (22265 to 22300)
Upper tail (22300 to 22315)
It's not hard, right?
In fact, the tail, the body, the top price, and the low price can be intuitively distinguished, so it is important to understand to the extent that "Closing price" and "Starting price" are not confused.
The candle on the right is a bar.
Check it out and let's understand why it's like that!
Let's just watch it for a minute! Gongmyeong's Knowledge Sharing
< Let's just watch it for a minute! Gongmyeong's Knowledge Sharing >
Today, we're going to talk about the most basic element that makes up the chart, the candle.
This is very important because you need to have a better understanding of the candles to flexibly access more in-depth theories.
As basic as it is, it's not hard!
Today, we will talk about the composition and its name among the candles.
First, candles are made up of Bullish candle and Bearish candle.
- Bullish candle : Candles with a higher closing price than the starting price
- Bearish candle : Candles with a higher starting price than the closing price
Here, the starting price and the closing price are:
- Starting price: the price at which the candle started
- Closing Price: Candle Ended Price
It's not that hard, right?
The ends and ends of the Icer Candles are called low-priced and high-priced.
- High-priced : Highest price in the candle
- Low-priced : Lowest price in the candle
So we looked into four important parts: starting price, closing price, high price, and low price. Finally, let's look at the concept of tail and body.
The tail can be classified into 'upper tail' and 'bottom tail'.
- Upper tail: The thin part above the candle.
- Bottom tail: A thin part that forms under the candle.
The body is the whole part except for the tails!
The criteria for dividing the tail and body are 'Closing price' and 'Strating price'.
This part becomes the tail,
and , this part becomes the body!
Today we talked about the components of candles.
Let's understand the names and components through today's content and learn more about the candles next time!
See you tomorrow!
Traders and Gamblers: Know the main differences!Hi guys, This is CryptoMojo, One of the most active trading view authors and fastest-growing communities.
Consider following me for the latest updates and Long /Short calls on almost every exchange.
I post short mid and long-term trade setups too.
Let’s get to the chart!
I have tried my best to bring the best possible outcome to this chart, Do not consider financial advice.
We are gonna go through 6 crucial points and elaborate how traders are different from gamblers.
1) As a trader, one’s aim is to focus on the next 100 trades instead of the next 10. Long-term success, profitability, and consistency are two of the main things traders should target. However, a gambler’s wish and desire is to make quick money.
2) A successful trader/investor has a backtested trading plan that he sticks to and optimizes along the way, adapting to changing market conditions. On the other hand, gamblers like to trade based off what other people think and tweet, or by simply opening a random Buy/Sell position and hoping it plays out successfully.
3) Profitable traders always diversify their portfolio and risk no more than 1-2% per trade. On the contrary, gamblers go “full margin mode” on a single trade without setting a Stop Loss and end up blowing their accounts and blaming the markets.
4) Chasing markets and rushing the process is not what real traders do. Instead, they follow their plan and wait for the price to play out and match their entry criteria before executing. Nonetheless, gamblers like to overtrade, open positions based on nothing, make biased decisions.
5) When enduring a loss or two (or three), traders neither get emotional nor try to revenge the markets. They know that if they obey risk management principles and open high risk-to-reward positions, they will cover all their previous losses and get back to making profits. Gamblers, on the other hand, get angry and start attempting to revenge the market by making foolish decisions and entering many illogical trades.
6) Last but not least, if you want to be successful and profitable in this field, you have to treat trading as a business and take things seriously. Those that think markets are a playground or a casino machine will never succeed in this space.
Gambling vs Trading
Gambling involves staking on the occurrence of an event that has an uncertain outcome for winning. For an action to be considered as gambling, three prerequisites must be present; the stake, the risk involved and the prize to be obtained upon the occurrence of the event.
Gambling has existed since records began. Early gambling involved six-sided die in Mesopotamia in 3000 BC. Around the 9th century, playing cards made their entrance, giving birth to the modern card games we know today. Over the years, gambling has taken several shapes and forms such as sports betting, parimutuel betting, and the gamut of casino bets.
Trading on the other hand, involves the buying and selling of financial instruments like cryptocurrencies, stocks, bonds, derivatives amongst others. There are several types of trading such as high-frequency trading, day trading, etc. each of which has its pros and cons.
Historically, the trading of financial instruments began in the 17th century after merchants banded together to form joint-stock companies. In 1602, the Dutch East India Co. issued the first recorded paper shares, allowing for the trading of stocks. This revolutionary concept spread through the world, leading to the creation of exchanges such as the London Stock Exchange which was founded in 1773.
This chart is likely to help you make better trade decisions if it does consider upvoting it.
I would also love to know your charts and views in the comment section.
Thank you
How to become a master trader?
First:Making Plans
Before trading every day, make a trading plan, so how to make a good plan?
Take XAUUSD for example,If you mainly focus on short-term operations, focus on the key support and key resistance within the day, buy up at the support level, buy down at the resistance level, sell high and buy low, if you cannot accurately determine where the support and resistance are , you can see my daily analysis articles.
In addition, when making a plan, you must set the stop profit and stop loss points. The stop profit must be greater than the stop loss. The reason for this is that even if your accuracy rate does not reach 50%, you can still make profits in the long run.
Second:Implement
After making a trading plan, what you have to do is to strictly implement it. You need to have confidence in your plan and don’t doubt your judgment because of the turmoil in the market. You need to know that the truth is often in the hands of a few people.
Third:review
Regardless of whether you are making a profit or a loss in today's transaction, you need to review the market. When you make a profit, you need to consider whether the take-profit position set this time is reasonable, and whether the profit can be enlarged next time. Of course, you also need to learn how to stop in moderation.
Of course, we can’t avoid the situation where we misjudged the direction. At this time, we need to consider whether we have strictly implemented the stop loss operation. In many cases, small losses are out, and keeping the principal is also a very correct operation. More people They will stop profit, but they can’t accept the loss, which leads to a mistake and loses the whole game. Therefore, it is said that those who can buy are apprentices, and those who can sell are masters.
Fourth:Summarize
Making a trading plan is a good habit, and it will accompany you throughout your life. Don’t think it’s a good habit just because you’ve made money for several days in a row, and you’ll feel that making a plan is useless because you’ve lost money for a few days in a row. The meaning, a simple summary is to make a good plan, strictly implement it, review it many times, and believe in yourself.
I will formulate my trading plan every day, and then share it with you, hoping to make progress together with you. At any time, we are in awe of the market and let ourselves go further through planning. This market will always eliminate some people. Don’t believe it Luck, that kind of thing will run out sooner or later, friends are welcome to discuss with me.
❤️Please, support my work with like, thank you!❤️
Everything I've learned about the RSI BINANCE:BTCUSDT
In this post, I'll make an attempt to share everything I've learned over the Relative Strength Index (RSI) Over the past 24 months.
Nothing described in this post is financial advice, it's just me, sharing thoughts and ideas with you.
nb: this post is more suited for traders and investors that are already educated about the RSI Indicators.
A brief introduction about the indicator itself :
The relative strength index (RSI) is a momentum indicator used in technical analysis. RSI measures the speed and magnitude of a security's recent price changes to evaluate whether it's better to buy, sell, or wait.
The RSI is displayed as an oscillator (a line graph) on a scale of zero to 100.
The RSI is probably the most used oscillator in finance nowadays, by both retail traders and institutions, hence meaning that when used well , it can be used as a great edge to profitability.
RSI popular uses :
- An asset is usually considered overbought when the RSI is above 70 and oversold when it is below 30.
- The RSI can give us insights on a potential trend's loss of momentum or validity when the price pivots levels are diverging with the RSI indicator (hidden and regular divergences)
- The most popular RSI length is 14 periods.
My findings
1. Overbought and oversold: myth or reality?
RSI's 30 and 70 levels never proved themselves to be a strong enough edge for me to be used as a standalone signal for trade entries.
As an example, just look at the irregularity of the results you would get when using just these zones :
My take on it is that as a price oscillator when it crosses into extremes, it simply means price momentum is at extreme levels. To me it's basically like a mountain cyclist in the middle of a race: he might very well go faster and higher, however, the quicker and higher he goes the more unlikely he is to keep up with that speed. Eventually, he might either decrease its speed or even go backward.
What does this tell us ?
The RSI 30 and 70 levels seem to be better used when used as timing indicators. For example, the 70 and 30 levels could be used as a filter for a trader to eliminate market noise when using a trend reversal strategy (mean-reversion). For trend traders, the levels could be used to timing signals where they'll start looking for price to do a pullback (consolidation) to get in the trend.
My experience using the 30 and 70 levels as exit signals however has been better (when it comes to using it as the only signal for a trade exit).
Say you are long on BTCUSD, in profit, and you get an RSI closure above 70. Well, in that case, you could exit 50% of your position and wait for the oscillator to cross down the 70 levels to exit the rest (as the overbought and oversold zones are rarely a defining factor for trend reversals and corrections).
2. Divergences in the overbought and oversold zones :
The lower the time frame you are trading on is, the higher the noise when it comes to divergences, especially with volatile assets such as BTCUSD. So you might want to filter out most of the ones you see to only take the best ones.
On the 15M and 5M timeframes, on BTCUSD, I find that on average about 1/3 of the divergences I see play out. However, we are not expected to take every divergence we see.
Here's what has helped me get better results with divergences :
- When approaching supply and demand zones, especially the higher timeframe ones, we might want to be more aggressive with the divergences we enter into. As the hit rate is not always amazing, the R:R is usually much better, and if the trade works out, it might give you great results which accounts for the low win rate.
- If you want to increase your win rate, I also find that going for higher timeframes is usually better when it comes to divergences.
- Take only divergences where RSI divergence's first pivot point is over 70 or under 30. Ideally, you don't want the noise to go below 60, or above 40, so that your trade has the necessary momentum to play out.
- For extra confirmation, wait for a break of the noise level to enter the trade.
- Regular and hidden divergences play hand in hand creating a form of momentum equilibrium. Hidden divergences always create regular divergences and vice versa. Hence a hidden divergence can be considered an early pullback warning to get in a bigger-picture trend.
- Regular divergences tend to play out better than hidden divergences. This is especially true when the volume is decreasing, or after a longer period of consolidation when volatility has been contracting and might be about to expand soon.
- Regular divergences in strong trends can be both a disaster and a treat. "The trend is your friend". This saying is especially true here. However, 2-3 drives of regular divergences are a great indication of a potential reversal, with enough confirmation factors to produce (often time) a great entry.
- The angle of the trend line between divergences pivot points, both on the price chart and the RSI, can be a good indication of the severity of the divergence occurring.
- The ideal lookback period for detecting divergences for me has proved to be between 5 and 28 bars. (Below 5 bars is not enough to confirm a true pivot point for me and above 28 bars has probably already played out in past price movements).
- Like all edges, using a divergence strategy always produces better results when used in confluence with other signals. I find the best confluences happen when divergences occur: alongside a stochastic cross, near medium-slow moving averages, near horizontal supply and demand zones, alongside volatility expansion, when the volume is decreasing (meaning market makes are in disagreement with the move occurring), near Bollinger bands 2.5 to 3 standard deviations (period 20).
- Convergence between your timeframes and higher timeframes is key to understanding how to better choose your trades. Try to play the big divergences but enter smaller timeframes divergences.
- When you lose a divergence trade, don't get disappointed. Jump back in because often time, and price will need to do several divergences before getting in your desired direction (however, be careful not to jump in tilt mod. Know your win rate and R:R and keep your money management serious. You'll get blown out if you start tilting on this, especially if you trade reversals with divergences, as it's difficult to get the right timing every time).
3. RSI as a trend filter?
- I've found that in trending markets, when RSI's Exponential Moving Average (EMA) crosses above the 50 line, it's an indication of an uptrend and vice versa. However, this is less effective in ranging markets as there's more noise, hence more invalid crosses.
- I've found that in trending markets when the RSI line crosses above the EMA (I use a 12 period), it's an indication of an uptrend and vice versa. However, this is less effective in ranging markets as there's more noise, hence more invalid crosses.
- As an indication of the trend's direction, I don't find any value in using bullish and bearish control zones. The only use I can find them is when using them for divergence levels filters.
This is the end of the first post of this 2 parts series. There's just so much more you can discover about this indicator that it simply cannot be constricted to a few lines of writing. However, you are welcome to take a few of my findings and go test them out using replay and backtesting. See for yourself, and find your balance.
Most of my learnings have been made through screentime, trial, and error, backtesting, mistakes, and research.
Have a good day,
Arthur Girard
Learning Wyckoff - Accumulation Wyckoff’s Accumulation Schematics
( EURUSD 9Nov 09:25 - 11NOV 16:50)
I am trying to learn Wyckoff’s Accumulation Schematics by finding and identifying them on different charts.
I found this one, and thought that looks like a textbook example. just sharing it so it maybe helps others.
feel free to correct me if there some error.
cheers