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.
Learning
Hidden Costs of Trading You Must Know
In this educational article, we will discuss the hidden costs of trading.
1 - Brokers' Commissions
Trading commission is the brokers' fee for opening a trading position.
Usually, it is calculated based on the size of the trade.
Though most of the traders believe that trading commissions are too low to even count them, the fact is that trading on consistent basis and opening a couple of trading positions weekly, the composite value of commissions may cut a substantial part of our profits.
2 - Education
Of course, most of the trading basics can be found on the Internet absolutely for free.
However, the more experienced you become, the harder it is to find the materials . So you typically should pay for the advanced training.
Moreover, there is no guarantee that the course/coaching that you purchase will improve your trading, quite often traders go through multiple courses/coaching programs before they become consistently profitable.
3 - Spreads
Spread is the difference between the sellers' and buyers' prices.
That difference must be compensated by a trader if one wished to open a trading position.
In highly liquid markets, the spreads are usually low and most of the traders ignore them.
However, being similar to commissions, spreads may cut the substantial part of the overall profits.
4 - Time
When you begin your trading journey, it is not possible to predict how much it will take to become a consistently profitable trader.
Moreover, there is no guarantee that you will become one.
One fact is true, you should spend a couple of years before you find a way to trade profitably, and as we know, the time is money. More time you sacrifice on trading, less time you have on something else.
5 - Swaps
Swap is the fee you pay for transferring a position overnight .
Swap is based on a difference between the interests rates of the currencies that are in a pair that you trade.
Occasionally, swaps can even be positive, and you can earn on holding such positions.
However, most of the time the swaps are negative and the longer you hold your trades, the more costly your trading becomes.
The brokers' commissions, spreads and swaps compose a substantial cost of our trading positions. Adding into the equation the expensive learning materials and time spent on practicing, trading becomes a very expensive game to play.
However, knowing in advance these hidden costs, the one can better prepare himself for a trading journey.
GBPUSD: Spotting the Next Big MoveKey Insights
Upward Trend: The overall trend for GBPUSD remains bullish.
Resistance Levels: 1.3200 and 1.3250 are significant resistance levels. A breakout above these levels could signal further upside potential.
Support Levels: 1.3000 is a key support level. A break below this level could indicate a potential reversal.
Economic Indicators: Keep an eye on economic indicators from both the UK and the US, as they can significantly impact the exchange rate.
Bearish Perspective
Key Points:
Overbought Conditions: GBPUSD might be approaching overbought conditions on certain technical indicators. A pullback could be expected.
Resistance Breakout Failure: If the pair fails to break above the 1.3200 resistance level multiple times, it could signal a potential reversal.
Economic Data: Weak economic data from the UK or strong data from the US could weaken the GBP.
Sell Levels:
1.3200 (resistance)
1.3300 (stronger resistance)
Potential Swing Trade:
Buy on Pullback: If the pair pulls back to the 1.3000 support level, consider buying with a stop-loss below the support. The target could be the next resistance level around 1.3250.
Bullish Perspective
Key Points:
Upward Trend: The overall trend remains bullish, and a breakout above the 1.3200 resistance level could trigger a significant rally.
Positive Economic Indicators: Strong economic data from the UK or weak data from the US could support the GBP.
Technical Indicators: A bullish crossover on a moving average or a positive divergence on an oscillator could reinforce the bullish outlook.
Buy Levels:
1.3000 (support)
1.2800 (stronger support)
Bullish Strategy:
Buy on Pullback: If the pair pulls back to the 1.3000 support level, consider buying with a stop-loss below the support. The target could be the next resistance level around 1.3250.
By combining technical analysis with fundamental factors, you can make more informed decisions about your GBPUSD trades.
Remember: [/b ]Swing trading involves holding positions for a few days or weeks. It's essential to have a well-defined risk management strategy in place. Remember to stay alert for potential market manipulations (Inducements), especially around support and resistance levels. These can often occur during significant events or flash news. Avoid getting caught in these traps by carefully analysing the market using price action.
Disclaimer: This analysis is based on current market conditions and may change. It's essential to conduct your own research before making any investment decisions.
$NSE:TATAELXSI Learnings - Time correction/opportunity costNSE:TATAELXSI
🔰Analyzing Tata Elxsi: A Case of Valuation & Earnings Stability ⤵️
🔰 PE Ratio Halved: From 100 to 50
✅ The PE ratio dropped from around 100 to 50, signaling a shift in market sentiment or correction from an overvalued state.
🔰 Timewise Correction, Not a Price Drop
✅ The stock has gone through a timewise correction with sideways movement instead of a steep decline.
↳ This often indicates consolidation after a significant rally.
🔰 Earnings Stability
✅ Despite the PE decline, EPS (Earnings Per Share) remains stable or slightly increasing.
↳ A positive indicator that the company’s earnings capacity is intact.
🔰 Market Sentiment vs. Fundamentals
✅ The PE ratio drop without a corresponding decrease in earnings shows a recalibration of growth expectations.
↳ Remember, valuation and market sentiment can diverge from a company’s actual performance.
🔰 Timing is Key
✅ Entering when valuation is high can lead to modest returns, even if the company performs well.
↳ Patience and strategic timing are crucial.
🔰 Long-Term Perspective
✅ Tata Elxsi’s stable earnings during a timewise correction show the benefits of holding strong fundamentals over short-term volatility.
🔰 Strategic Takeaway
✅ Look beyond PE ratios—understand the business, sector dynamics, and macroeconomic factors.
↳ Align your investment strategy with market conditions and company performance.
How to Identify Candlestick Strength | Trading Basics
Hey traders,
In this educational article, we will discuss
Please, note that the concepts that will be covered in this article can be applied on any time frame, however, higher is the time frame, more trustworthy are the candles.
Also, remember, that each individual candle is assessed in relation to other candles on the chart.
There are three types of candles depending on its direction:
🟢 Bullish candle
Such a candle has a closing price higher than the opening price.
🔴 Bearish candle
Such a candle has a closing price lower than the opening price.
🟡 Neutral candle
Such a candle has equal or close to equal opening and closing price.
There are three categories of the strength of the candle.
Please, note, the measurement of the strength of the candle is applicable only to bullish/bearish candles.
Neutral candle has no strength by definition. It signifies the absolute equilibrium between buyers and sellers.
1️⃣ Strong candle
Strong bullish candle signifies strong buying volumes and dominance of buyers without sellers resistance.
Above, you can see the example of a strong bullish candle on NZDCHF on a 4H.
Strong bearish candle means significant selling volumes and high bearish pressure without buyers resistance.
On the chart above, you can see a song bearish candle on EURUSD.
Usually, a strong bullish/bearish candle has a relatively big body and tiny wicks.
2️⃣ Medium candle
Medium bullish candle signifies a dominance of buyers with a rising resistance of sellers.
You can see the sequence of medium bullish candles on EURJPY pair on a daily time frame.
Medium bearish candle means a prevailing strength of sellers with a growing pressure of bulls.
Above is the example of a sequence of medium bearish candles on AUDUSD pair.
Usually, a medium bullish/bearish candle has its range (based on a wick) 2 times bigger than the body of the candle.
3️⃣ Weak candle
Weak bullish candle signifies the exhaustion of buyers and a substantial resistance of sellers.
Weak bearish candle signifies the exhaustion of sellers and a considerable bullish pressure.
Usually, such a candle has a relatively small body and a big wick.
Above is the sequence of weak bullish and bearish candles on NZDCHF pair on an hourly time frame.
Knowing how to read the strength of the candlestick, one can quite accurately spot the initiate of new waves, market reversals and consolidations. Watch how the price acts, follow the candlesticks and try to spot the change of momentum by yourself.
Profitable Triangle Trading Strategy Explained
Descending triangle formation is a classic reversal pattern . It signifies the weakness of buyers in a bullish trend and bearish accumulation .
In this article, I will teach you how to trade descending triangle pattern. I will explain how to identify the pattern properly and share my trading strategy.
⭐️ The pattern has a very peculiar price action structure :
1. Trading in a bullish trend, the price sets a higher high and retraces setting a higher low .
2. Then the market starts growing again but does not manage to set a new high, setting a lower high instead.
3. Then the price drops again perfectly respecting the level of the last higher low, setting an equal low .
4. After that, one more bullish movement and one more consequent lower high , bearish move, and equal low .
Based on the last three highs , a trend line can be drawn.
Based on the equal lows , a horizontal neckline is spotted.
❗What is peculiar about such price action is the fact that a set of lower highs signifies a weakening bullish momentum : fewer and fewer buyers are willing to buy from horizontal support based on equal lows.
🔔 Such price action is called a bearish accumulation .
Once the pattern is formed it is still not a trend reversal signal though. Remember that the price may set many lower highs and equal lows within the pattern.
The trigger that is applied to confirm a trend reversal is a bearish breakout of the neckline of the pattern.
📉Then a short position can be opened.
For conservative trading, a retest entry is suggested.
Safest stop is lying at least above the level of the last lower high.
However, in case the levels of the lower highs are almost equal it is highly recommendable to set a stop loss above them all.
🎯For targets look for the closest strong structure support.
Below, you can see the example of a descending triangle trade that I took on NZDCAD pair.
After I spotted the formation of the pattern, I was patiently waiting for a breakout of its neckline.
After a breakout, I set a sell limit order on a retest.
Stop loss above the last lower high.
TP - the closest key support.
90 pips of pure profit made.
Learn to identify and trade descending triangle. It is one of the most accurate price action patterns every trader should know.
Mastering Elliott Waves: Key Rules You Can't IgnoreEducational Idea : Understanding Key Principles of Elliott Wave Theory
Introduction
Elliott Wave Theory is a powerful tool used by traders to analyze market cycles and forecast future price movements. Understanding its core principles can help you make more informed trading decisions. In this article, we will delve into three fundamental principles of Elliott Wave Theory that cannot be violated. Remember, this video is purely for educational purposes and not intended as trading advice or tips.
1. Wave 2 Can Never Retrace More Than 100% of Wave 1
The first principle of Elliott Wave Theory is that Wave 2 can never retrace more than 100% of Wave 1. In other words, Wave 2 cannot go below the starting point of Wave 1. If it does, it invalidates the wave count and suggests that the initial impulse wave (Wave 1) was incorrectly identified. This rule ensures that Wave 2 is a correction wave within the larger trend and not a reversal of the trend itself.
Example Illustration:
- If Wave 1 starts at 100 and peaks at 150, Wave 2 can retrace to any level above 100, but not below it.
2. Wave 3 Can Never Be the Shortest Among All Three Impulse Waves (1-3-5)
The second principle states that Wave 3 can never be the shortest among the three impulse waves (Waves 1, 3, and 5). Typically, Wave 3 is the longest and most powerful wave, characterized by strong momentum and volume. If you find that Wave 3 is shorter than either Wave 1 or Wave 5, the wave count is incorrect, and you need to re-evaluate your analysis.
Example Illustration:
- If Wave 1 is 50 points and Wave 3 is only 30 points, while Wave 5 is 40 points, this violates the rule as Wave 3 is the shortest.
3. Wave 4 Cannot Enter the Territory of Wave 1 (Except in Diagonals & Triangles)
The third principle asserts that Wave 4 cannot enter the price territory of Wave 1. This means that the lowest point of Wave 4 should not overlap the highest point of Wave 1. An exception to this rule occurs in diagonal and triangle patterns, where some overlap is permissible. This rule helps maintain the integrity of the impulse wave structure.
Example Illustration:
- If Wave 1 peaks at $150 and Wave 4 retraces to $145, this overlaps and invalidates the wave count unless the pattern is a diagonal or triangle.
Conclusion
By following these principles, you can ensure that your Elliott Wave analysis remains robust and accurate, helping you navigate the complexities of the financial markets with greater confidence. Understanding and applying these key principles of Elliott Wave Theory can significantly enhance your market analysis and trading strategies. Keep these rules in mind as you study and apply Elliott Wave Theory in your trading journey. Remember, this video is purely for educational purposes and not any kind of trading advisory or tips.
This content is for educational purposes only and should not be considered as financial advice. Always do your own research before making any trading decisions.
I am not Sebi registered analyst.
My studies are for educational purpose only.
Please Consult your financial advisor before trading or investing.
I am not responsible for any kinds of your profits and your losses.
Most investors treat trading as a hobby because they have a full-time job doing something else.
However, If you treat trading like a business, it will pay you like a business.
If you treat like a hobby, hobbies don't pay, they cost you...!
Feel free to share your thoughts or questions in the comments below. Happy trading!
Hope this post is helpful to community
Thanks
RK💕
Disclaimer and Risk Warning.
The analysis and discussion provided on in.tradingview.com is intended for educational purposes only and should not be relied upon for trading decisions. RK_Charts is not an investment adviser and the information provided here should not be taken as professional investment advice. Before buying or selling any investments, securities, or precious metals, it is recommended that you conduct your own due diligence. RK_Charts does not share in your profits and will not take responsibility for any losses you may incur. So Please Consult your financial advisor before trading or investing.
why you should avoid trading after a trending marketHello traders,
I saw This learning post today in the London session(24-7-24).
you can go for 5 minutes to understand this concept better, you can see a clear pattern on the chart, trending -> sideways/choppy -> trending -> sideways/choppy.
in the trending market, you see fast movement; in the choppy market, you see lots of SL hunting and wicks.
try to avoid such a market so you can make money in trending.
Note : not a finance advice
Learn How to Apply Top-Down Multiple Time Frame Analysis
In this article, we will discuss how to apply Multiple Time Frame Analysis in trading .
I will teach you how to apply different time frames and will share with you some useful tips and example of a real trade that I take with Top-Down Analysis strategy.
Firstly, let's briefly define the classification of time frames that we will discuss:
There are 3 main categories of time frames:
1️⃣ Higher time frames
2️⃣ Trading time frames
3️⃣ Lower time frames
Higher Time Frames Analysis
1️⃣ Higher time frames are used for identification of the market trend and global picture. Weekly and daily time frames belong to this category.
The analysis of these time frames is the most important .
On these time frames, we make predictions and forecast the future direction of the market with trend analysis and we identify the levels , the areas from where we will trade our predictions with structure analysis .
Above is the example of a daily time frame analysis on NZDCAD.
We see that the market is trading in a strong bullish trend.
I underlined important support and resistance levels.
The supports will provide the safest zones to buy the market from anticipating a bullish trend continuation.
Trading Time Frames
2️⃣ Trading time frames are the time frames where the positions are opened . The analysis of these time frames initiates only after the market reaches the underlined trading levels, the areas on higher time frames.
My trading time frames are 4h/1h. There I am looking for a confirmation of the strength of the structures that I spotted on higher time frames. There are multiple ways to confirm that. My confirmations are the reversal price action patterns.
Once the confirmation is spotted, the position is opened.
Analyzing the reaction of the price to Support 1 on 1H time frame on NZDCAD pair, I spotted a strong bullish confirmation - a triple bottom formation.
A long position is opened on a retest of a broken neckline.
Lower Time Frames
3️⃣ Lower time frames are 30/15 minutes charts. Even though these time frames are NOT applied for trading, occasionally they provide some extra clues . Also, these time frames can be applied by riskier traders for opening trading positions before the confirmation is spotted on trading time frames.
Before the price broke a neckline of a triple bottom formation on an hourly time frame on NZDCAD, it broke a resistance line of a symmetrical triangle formation on 15 minutes time frame. It was an earlier and riskier confirmation to buy.
Learn to apply these 3 categories of time frames in a combination. Start your analysis with the highest time frame and steadily go lower, identifying more and more clues.
You will be impressed how efficient that strategy is.
xauusd analysis for 9/07/2024Last week our analyis on xauusd was perfect , we have predicted that if it cannot break the 2319-2312 zone then it will be bullish up to 2385.
Targets hit
2337 ✅✅✅
2347✅✅✅
2362✅✅✅
2385✅✅✅
our analyis for today:
it will be a ranging market from 2353 to 2371 , so buy the dip and sell the high.
▶️ if 2370 is broken then the market will fly upwards to 2385 2393 2404 2421 in extension
▶️ if 2353 support is broken then the market will fall towards
2342 2333 2321 2311 2306
.
we will make a detail analysis on fundamental technical and geopolitical scenarios.
LIKE US BOOST US FOLLOW US SHARE US
Liquidity is KEY to the MarketsIn this video I go through more about liquidity and why it is important.
The markets move because of liquidity. Without liquidity, there is no trading. The larger the trader, the larger the liquidity required. Understanding the concept of liquidity and the fractal nature of price, trading becomes very interesting. A whole new world opens up to you and you no longer have to keep guessing where price is going. You no longer have to keep chasing candles.
I hope you find this video insightful.
- R2F
Chart reset: drop down Gold analysis - WeeklySo I have hit a real brick wall. I have not hit it once, I have hit it over and over again and I need to reset and align myself to my strategy, edge and focus.
What is the idea? Well I need to do some more drop down analysis to ensure I am focused and know where the market is going and which direction I am because without it, I am just gambling and I can't do that anymore.
The strategy? Price action trading using confluence between the time frames and long term bias to set direction. Price structure is also considered as we need to know the strength of each push.
RULES FOR ENGAGEMENT:
- WEEKLY AND DAILY SET BIAS - ABOVE 200 BUYS (GREEN) BELOW 200 SELLS (RED)
- 4HR MUST AGREE WITH HIGHER TIMEFRAME
- BUY OR SELL WELL MARKET IS OVERSOLD OR OVERBOUGHT, AT SUPPORT/RESISTANCE AND MACD IS CROSSING
- LOOK FOR DIVERGENCE ON RSI
Further testing and changes to take place to ensure the changing of trend can be taken into consideration with both swing and intraday trades.
(Examples to follow)
ANALYSIS OF THE WEEKLY:
- Price broke to the upside back in mid March solidifying the bullish trend. We should have seen this from previous price action when price was in a long term range and opportunities to buy at the bottom were present.
- While price is continuing in this bull run, on the shorter time frames we have plenty of opportunities to enter long and compound (See following posts)
- Price is now consolidating in a range. Action for a range? Buy at the bottom (support) and sell at the top (resistance) - wait for the breakout for further confirmation.
What can we take from this chart?
- Price is bullish and above the 200 MA which give us buying permissions.
Onto the next chart.
FULL ANALYSIS GUIDE - (Using ICT's Concepts)Hey guys,
In this video I will show you my process for performing analysis. Yes, it takes some work, but generally once you get into the swing of it, it doesn't take long, and the higher timeframes only require analysis once in awhile. It allows me to have a higher win-rate and be more on side with how the market is predisposed to move. Whilst it is not required in order to be profitable, my personality and system requires me to make more frequent wins.
I hope you find this video insightful.
- R2F
xauusd analysis for the day 1/07/2024xauusd is following a neutral pattern for the day before European market opening.
we will provide major support and resistance for the recent market scenario. a further update will be given based on market momentum changes,
right now xauusd is following a ranging market.
Support
2321
2314
2306
2297
2288
2282
Resistance
2332
2337
2347
2362
2378
2396
these support and resistance can be used as bullish and bearish targets for your trades,
PLEASE BOOST US LIKE AND SHARE US SO THAT WE WILL BE MOTIVATED TO GIVE MORE UPDATES.