Microsoft Bullish Cup and Handle Microsoft - NASDAQ:MSFT
A bullish monthly and weekly chart:
✅Monthly MACD Cross
✅ Long Term parallel channel intact
✅ Above 200 day & week MA
✅ Cup and Handle (with a high handle - Preferred)
✅ Good Risk: Reward Ratio at 7.6 (51%+ vs -7% loss)
⚠️ Stop loss levels on chart 🫡
A great set up. Those that are patient could wait for a potential pull back (arrow on chart) as we are reaching into overbought levels on the RSI on the weekly. It would not be unusual for Microsoft to pull back 5-8%. The R:R would be significantly improved if you waited and if it led to an entry from approx. $350 (after a 5-8% pull back), this would line up with the 200 DSMA also. However there are no guarantees of a pull back.
Those half as cautious could enter half a position here and see what happens and place another entry at $350.
All in all the $330 - 335 red box area on the chart is an absolute stop loss level. If this level is lost I would be out of the trade fast.
So you have options with this set up:
1) Entry here with a tight 7% stop.
2) Half a position here and half at approx. $350 with a stop at $335.
3) You wait for $350 and you place your stop at $330.
These all result in a similar loss of 5 - 7% in the event the trade fails. The upside potential is always 50%+. You can always cut early also at target one and take something at the 26% profit level.
It important you take full responsibility for your trade, position accordingly and be ok with the small 5-7% loss as it will likely happen, we are only leaning on the probability that maybe 60-70% of the time these trade set up provide us the return we want.
I have not really ventured into the earnings or dividends however they are both positive contributors to this trade as earnings have been excellent and dividends whilst minimal, are dividends at the end of the day. We are here for the trade and play a set up off the chart. The fundamental's are just nice framing for the stock in our minds eye.
PUKA
Community ideas
Meta Might Break OutMeta Platforms has consolidated for several months, but now the social-media giant could be attempting a breakout.
The first pattern on today’s chart is the $328 level. It was the high on February 2, 2022, immediately before the stock’s biggest drop ever. (The selloff was prompted at that time by weak results and business challenges involving Apple.) META tested that zone on October 11-12 before pulling back. But last week it returned to close slightly above it for the first time. Remaining here or continuing higher may confirm a breakout.
Second, a series of higher weekly lows may suggest longer-term buyers are active.
Third, the stock has danced around its 50- and 100-day simple moving averages (SMAs). However the faster SMA remains above the slower one, a potential sign that the longer-term trend is still bullish. They’re also above the 200-day SMA.
Finally, you have fundamentals. META’s earnings, revenue and users topped estimates on October 25. The stock initially fell on worries that violence in the Middle East could hurt advertising. That may create potential for buyers to come off the sidelines if worst-case scenarios don’t pan out.
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If you could only use one indicator, what would you pick?Here's a question for you: pretend that you can only use one indicator from now until the end of time. What indicator would you pick?
Write it in the comments below.
Don't worry, this is just a hypothetical question. 🤗
The comments should make for a fascinating read for all of us. Remember: pick only one indicator and that's it. Bonus points if you provide a little explanation about that indicator and why it matters to you. In doing so, you may help some traders discover a new indicator for their needs.
So, let's hear it! Write your single favorite indicator, one that you could use forever, in the comments below!
XAUUSD | GOLDSPOT | New perspective | follow-up detailsIn this video, we delve into the recent surge in gold prices, driven by a combination of factors. On Friday, the U.S. dollar and Treasury yields experienced a decline following disappointing U.S. jobs data, solidifying expectations that the Federal Reserve will halt its interest rate hikes. The October job growth figures fell short of economists' projections, with only 150,000 jobs added compared to the anticipated 180,000. Additionally, wage inflation cooled, indicating a potential easing in labor market conditions.
It is crucial to note that if the labor market continues to deteriorate, the Federal Reserve will be unable to maintain its hawkish stance. This data reinforces the notion of a Fed pause, which has contributed to the rise in gold prices. Furthermore, the dollar index (.DXY) experienced a 1% drop, while the benchmark 10-year U.S. Treasury yields reached a low not seen in over a month, further bolstering gold's appeal.
In light of the ongoing Middle East conflict, investors are now pricing in a 95% chance that the U.S. central bank will keep interest rates unchanged in December, compared to the previous 80% prior to the release of this data. These insights are based on the CME FedWatch tool.
XAUUSD Technical Analysis:
In this video, we dissected the XAUUSD chart from a technical standpoint, analyzed the key levels, analyzed historical price moves, market behaviors, and buyer-seller dynamics, and uncovered potential trading opportunities.
The $2,010 zone will remain our center stage for this week. Its historical significance makes it a crucial point. If the bullish momentum is sustained then the breakout/retest of this zone will serve as a platform for new highs. However, if selling pressure persists below $2,010 just as it had done in the last 5 months, we could witness renewed selling pressure back into the demand zone at the $1,900 zone.
Dive into the latest Gold market dynamics! Discover how escalating Middle East tensions and renewed decline in 10-year Treasury yields and their impact. Stay informed for strategic investment decisions.
#GoldMarket #SafeHavenAssets #USDebt 📺🔔💼
Disclaimer Notice:
Please be aware that margin trading in the foreign exchange market, including commodity trading, CFDs, stocks, and other instruments, carries a high level of risk and may not be suitable for all investors. The content of this speculative material, including all data, is provided by me for educational purposes only and to assist in making independent investment decisions. All information presented here is for reference purposes only, and I do not assume any responsibility for its accuracy.
It is important that you carefully evaluate your investment experience, financial situation, investment objectives, and risk tolerance level. Before making any investment, it is advisable to consult with your independent financial advisor to assess the suitability of your circumstances.
Please note that I cannot guarantee the accuracy of the information provided, and I am not liable for any loss or damage that may directly or indirectly result from the content or the receipt of any instructions or notifications associated with it.
Remember that past performance is not necessarily indicative of future results. Keep this in mind while considering any investment opportunities.
The Bane of TradersPrice never gets faked out. Traders do.
A blow-off top, a black swan, a trend break.
All of these can easily become TRAPS-101.
The winter is coming.
Time to turn back your clocks.
November 1994
November 2015
November 2023
No more words are necessary.
No conclusions, no signatures.
Strategy Smarts Part 1: Opening Range BreakoutWelcome to our four-part Strategy Smarts series designed to give you some practical trading templates which build on the concepts outlined in our Day Traders Toolbox and Power Patterns series.
We’re kicking this series off with the Opening Range Breakout strategy because it is fundamental to the process of intra-day price discovery.
Strategy Overview:
At first glance, the Opening Range Breakout may appear as a straightforward range breakout trading setup. However, when executed with precision, it can become a potent instrument for harnessing the inherent dynamics of intra-day price action.
The initial minutes of a trading session are marked by frenzied activity, as overnight and pre-opening news gets rapidly factored into prices, and orders are executed. During this phase of early price discovery, a trading range often takes form, aptly termed the opening range.
The Opening Range Breakout strategy comes into play when the market establishes a well-defined range within the first hour of trading.
Here’s a simple 3-step process which can be used as a framework for trading the Opening Range Breakout:
Step 1: Define the Opening Range
The initial and critical step in this strategy is defining the opening range. The method for determining the opening range may vary for different assets, such as stocks and indices or the forex market.
For Stocks & Indices:
Stocks and cash indices with set opening and closing times make defining the opening range relatively straightforward. We are looking for a range to develop within the first hour of trading – the more obvious the range the better.
NOTE: It's important to acknowledge that a range may not always form within the first hour of trading. In such cases, the Opening Range Breakout strategy would not usually be applied by traders using this strategy.
Example: AAPL 5min Candle Chart
Past performance is not a reliable indicator of future results
For Forex:
Forex is the market that never sleeps, this means the New York close rolls straight into the Asian open – making defining the opening range much more subjective.
For most major forex pairs, volume will be lower during the Asian session, increase in early European trading, before away during late morning and increasing again during U.S. trading hours.
There are many interpretations and definitions of the opening range breakout strategy for forex pairs, but perhaps the cleanest method is using the lower volume Asian session as a window in which a range can form.
Example: EUR/USD 5min Candle Chart
Past performance is not a reliable indicator of future results
Step 2: Check Range Location
If you've read our Day Traders Toolbox Part 1 on Previous Day High and Low (PDH/PDL), you understand the significance of these levels in shaping day trading strategies. The location of the opening range concerning PDH/PDL plays a pivotal role in shaping the expectations and management of the Opening Range Breakout strategy.
Assuming PDH represents resistance and PDL signifies support, the relative distance between the opening range and PDH/PDL dictates whether long or short positions are more appealing.
Should an opening range form above the PDH, this strategy suggests longs will be more attractive as the market is consolidating in a position of strength. The opposite applies to when an opening range forms below the prior days low – the market is consolidating in a position of weakness and therefore shorts might look more attractive.
Example Part 1: SPX 5min Candle Chart
Past performance is not a reliable indicator of future results
Example Part 2: SPX 5min Candle Chart
Past performance is not a reliable indicator of future results
Step 3: Trade the Breakout
Once a clear range has emerged within your defined opening window, and you've assessed the range's location relative to PDH/PDL, it's a matter of waiting for and executing a breakout when it occurs.
A breakout can occur either to the upside or the downside. Consider placing price alerts on both sides of the range to ensure you capture the breakout.
Be aware that breakouts from opening ranges may not always be clean. Noise and false breakouts can occur. Therefore, one of the best entry techniques for trading the opening range breakout is the 'Break & Retest' method, as outlined in our Power Patterns series. This approach waits for the breakout to occur and enters during the first pullback.
Stop Placement: You may want to consider positioning your stop within the opening range to account for potential market noise. Advanced traders may consider employing the Average True Range (ATR) for more precise stop placement, as discussed in our Day Traders Toolbox: Part 3 on ATR.
Profit Target: A sound starting point for determining profit targets in the Opening Range Breakout strategy is using the PDH/PDL and daily ATR. If the breakout happens within the prior day's range, set PDH/PDL as initial targets. If the breakout extends beyond the prior day's range, consider using 1 x Daily ATR as your initial target.
Worked Example 1: Tesla Long Opening Range Breakout
Tesla establishes an opening range during the first hour of trading above the PDH, indicating strength. The range is broken to the upside, and the market retests the upper boundary, offering an entry opportunity. A stop is placed within the opening range, and an initial target of 1 x ATR is reached as the price climbs.
TSLA 5min Candle Chart:
Past performance is not a reliable indicator of future results
Worked Example 2: Tesla Short Opening Range Breakout
Tesla forms an opening range just above the PDL. A break and retest of the opening range triggers the entry. A stop is positioned above PDL and within the opening range to accommodate market noise. The initial target of 1 x ATR is achieved as the price descends.
TSLA 5min Candle Chart:
Past performance is not a reliable indicator of future results
Disclaimer: This is for information and learning purposes only. The information provided does not constitute investment advice nor take into account the individual financial circumstances or objectives of any investor. Any information that may be provided relating to past performance is not a reliable indicator of future results or performance.
Arbitrage, Co-Integration & Pairs If you are interested in quantitative trading (“quant” trading) or even if you’re only interested in investing, chances are you may have heard of arbitrage, co-integration and pairs trading. But chances are equally likely you have no idea what these truly mean and how to assess/measure and exploit these different concepts in your trading life and investment life. And it makes sense, these are really complex concepts and generally utilized by quantitative traders in institutional trading. But, why let them have all the fun. So I’m going to try to simplify these concepts and give you a working idea of:
a) What these things mean;
b) Why they are imported for traders and investors; and
c) How to start applying these concepts to your trading and/or investment portfolio.
First, let’s get started with the pesky definition details.
Arbitrage: Isn’t that a big bird?!
In finance, arbitrage generally refers to any short to mid term trading strategies that revolve around mean reversion models and the exploitation of pricing inefficiencies. Despite the fact that the “ Efficient market Hypothesis ” postulates that markets are efficient and thus unpredictable, I am going to show you that they are in fact very inefficient and all it takes is a little math to reveal these inefficiencies.
And Co-Integration?
Co-integration is kind of like co-habitation, perhaps more copulation. If two tickers were going to have a child together, it would be a co-integration. Essentially, co-integration refers to what a ticker would look like while integrated into another ticker. The official explanation of cointegration is essentially when two or more nonstationary time series move together in such a way that their linear combination results in a stationary time series. Now this is the involves modelling one ticker after another, so that you can essentially predict one ticker’s price or behaviour, from another.
It may help to show you some examples of co-integration via charts. So let’s take a look at some examples below, using the SPTS indicator to perform linear regression assessments:
In the chart above, I have placed a co-integration model of GOOG and MSFT through linear regression. Essentially, we use GOOG’s close price to calculate the respective fair value of MSFT. From this, we can see when MSFT is over-valued from GOOG and vice versa, and we can see when the two are fully integrated (a regression to the mean).
Now cointegration isn’t a natural order. Not everything can co-integrate. Sometimes, there just isn’t a significant relationship. For this, we must apply some statistical tests. There are many that can be used, such as the Engle Granger Test, but the most popular is the Dickey Fuller test or Augmented Dickey Fuller test. We will talk more about this later.
Pairs Trading
Pairs trading refers to trading both arbitrage and co-integration. Remember our GOOG/MSFT example above? Well, pairs trading involves assessing, modelling and trading this co-integrated relationship. Let me explain through charts:
In the chart above we can see both MSFT and GOOG are in an uptrend. However, MSFT is lagging below GOOG and GOOG is holding slightly above MSFT. Now, because they are both in an uptrend, you don’t want to short, but if you wanted to maximize your profits, you are going to long the stock that is under-performing its benchmark or “cointegrated” pair, i.e. GOOG.
We can see this translated into about a 6.18% gain on MSFT vs only a 4.75% gain had you longed GOOG.
Now, traditional pairs trading generally involves finding two stocks that are highly correlated but have extremely diverged, shorting the one that is overvalued and longing the one that is undervalued. But I can tell you, that is almost IMPOSSIBLE to find in the real world! So I settle for this as a pseudo-pairs trading fill in!
Here is an intra-day example between SPY and QQQ from Tuesday October 31st:
Do you notice anything in this chart?
During the morning sell down, SPY lagged QQQ and QQQ sold more starkly. SPY held higher above QQQ, which we can see from our co-integration model. So what would have made more sense, to long SPY or QQQ for the bounce?
If you said QQQ, you are correct:
From its lowest to highest point, SPY bounced 0.57%.
From its lowest to highest point, QQQ bounced 0.85%.
And we were able to see that QQQ had more upside room than SPY by looking at the co-integration model overlaid on the chart.
Now do you remember when I talked about arbitrage and how I said the market isn’t so efficient when you pull in these pesky math equations? This is why. There is arbitrage everywhere, everyday, on every stock. These small inconsistencies in pricing that can be exploited for profit. Now, as retail traders, we likely don’t have the computing and modelling power/setup necessary to scan millions of tickers, creating multiple co-integration models to look for these pricing anomalies and capitalize on them, but we can absolutely have our own co-integration model built on stocks that we trade frequently, or that we like to invest in.
But before we get into the how, let’s look at some different examples of co-integration and mean reversion. First, let’s look at an example of a “perfect integration” i.e. the same stock with SPY and SPX:
You can see that the blue lines align perfectly with the candles. But watch what happens when we overlay SPY and ES1! (the futures version):
Do you notice something.. strange ?
Despite ES1! And SPY being pretty identical, we can notice a few “drifts” or inconsistencies in the pricing. This is likely attributable to the extended trading time of ES1! Vs SPY which is limited in its trading times, but it does highlight how these inconsistencies can “pop up” on tickers/futures that are trading almost identical underlying assets (in this case, the S&P 500).
What about investments? How is this useful for investments?
This is actually a really great question and.. well friends… I’m going to show you how your investments can thrive with a little bit of quantitative love!
Let’s use a very straight forward example, SPY and QQQ. They are pretty similar, tend to follow each other. Over the past 75 days, SPY and QQQ have a Pearson Correlation of 0.94. That is a pretty substantial relationship!
If we look at what SPY looks like overlaid with QQQ, here we are:
In the chart above, you can see there are areas where SPY outperforms QQQ and QQQ outperforms SPY. If we were to export SPY and QQQ trading data since July 2020 into Excel and create a investment model based on the modelled relationship between SPY and QQQ, it would look something like this:
Column B has our SPY close Price, C our QQQ close price, E through G are how we calculate the Dickey Fuller statistic, H and I are our SPY and QQQ Returns respectively, and J is our investment of $100.
Now, if we create a SPY trading algorithm off this model and tell it to long and hold SPY as long as it is undervalued in comparison to QQQ, sell when its over-valued and re-buy when its undervalued, assuming an initial investment of 100$, between July 22nd, 2020 and October 31st, 2023, you would have made exactly $36.40 or 36%. Had you just held SPY for that time and not sold when SPY became over-valued against QQQ, you would have made $27.95, or around 28%. The difference seems marginal maybe, but it is quite a stark percent difference.
And if you change that 100 to, say, 10,000, the difference starts to add up.
So … How can do you do it?
So now for the technical stuff. I am going to try to keep this as easy and straight forward as possible.
In a nutshell, the steps involved in developing a co-integration model include the following:
a) Finding a rational basis for the integration: It is insufficient to think that one stock should relate to the other. You need a rationale basis as to why these stocks are similar, which can later be confirmed by some tests.
b) Reference a correlation table or matrix to compare the stocks of interest and identify the highest correlated stock pairs.
c) Once you have identified the highest correlated stock pairs, you can use an indicator such as SPTS to create a regression model, or you can use Excel to create a regression model (for simplicity, I am going to show you how to do it on the SPTS indicator).
d) Create your co-integration model in Excel by exporting your two stocks of interest and plotting in your linear regression formula.
e) Perform the Dickey Fuller test to ensure stationarity.
f) You’re done!
Now, let’s walk through the steps, using NVDA and SMH as our two basis.
Determine rationality:
NVDA is a subsector of chips, which is tracked by SMH.
Check Correlation:
We can see on this correlation matrix, NVDA has a 0.82 correlation to SMH. It is the strongest, even stronger than QQQ which has a 0.74 correlation. In general, you want a correlation >= 0.8. So SMH has passed the first and second step!
Create a Regression Model
For simplicity, let’s use SPTS.
Launching SPTS, it is going to ask us to set a start and end time. I am going to start from the beginning of 2018 till current (approx. 5 years). Then, in the settings, I am going to select “Linear Regression”
SPTS is going to output a linear regression model (green arrow):
We are going to take a look at the Significance or P value, which is 0.9, even better than our correlation matrix result! And our R squared which is 0.8. This is an excellent R2 reading! We generally will accept R2 of 0.5 or greater, so 0.8 is perfect! We can also see our Error is 138.59, which means the variance present between NVDA and SMH is around $138.59 in both directions.
The meat of our model is the equation y = 2.7994x + -114.15. We need this formula for the next step.
Export the data into Excel
We are going to click the dropdown menu in the top right hand corner by our chart title and click “ Export chart data ”:
We are going to do this for both our tickers.
Once we have the data, we are going to just leave the Time and the Close price for NVDA and copy over the close price for SMH so that our Excel file looks like this:
Now, we are going to create a column in D called “Co-Integration”. In this column, we are going to use our model equation that was generated by SPTS like so:
Remember, we are converting SMH to NVDA, so we take the SMH close price and substitute for X in the equation.
Once that is done, we can drag and drop the data to calculate the expected close for NVDA:
If we want to use Excel to calculate the equation, we can select an empty cell and use the formula =SLOPE(known ys (NVDA), Known_xs (SMH)):
Then, in another column, we use =INTERCEPT(known_ys (NVDA), known_xs (SMH)):
Perform Dickey Fuller Test
So now we have our data, we have to ensure there is stationarity. Stationarity refers to the principle that the statistical processes of a stock will remain the same. Stationarity is required for any time series analysis, without stationarity, time series would not work in the way we need it to for this.
Now don’t get confused by the term. Stationarity doesn’t mean that the stock price can’t change, just that its statistical attributes will remain the same. For example, say NVDA and SMH both gain 4% in one day, then following day they lose 2%. Now, say in two months, both gain 4.2% and lose 2.2% the next day. This is a simplistic example of stationarity. The statistical processes that are driving these two tickers remain constant, despite the price increase or decrease.
So to perform a stationarity analysis, we need to first do what is called “Differencing”. All this means, is we need to subtract NVDA from our Co-integration formula like so:
Then we drag down. (Notice we assigned this column X. This is for simplicity).
One thing you will notice is the value of X is negative. This implies that NVDA is actually OVERVALUED in comparison to SMH. We are going to be seeing a lot of negatives ;).
Now that we have created our X column, we can go ahead and calculate what is called delta x or x change. This is the difference between the second and first x value, calculated as such:
We simply subtracted the proceeding value from the previous value. Once we put in the formula once we can just drag and drop it:
Now the last thing we need to do is created a lagged value of X. This is because the Dickey Fuller test requires lagged values to assess stationarity. So we simply carry down the previous X like so:
Then… what do you think?..... we drag and drop :p.
So now we are ready to calculate the Dickey Fuller result. And this is actually really easy! All we do is use the formula =LINEST(known_ys, known_xs). Our known Y’s are going to be the delta x and our known x’s are going to be the lagged x.
But before we use this function, we are going to highlight 2 rows like so:
The top called coefficient and the bottom error. This will give us the regression coefficient (the same thing we multiplied our SMH value by), as well as the standard error. Once we have our two boxes highlighted, we will put in our command like so:
NOW BEFORE YOU PRESS ENTER!
You need to force the LINEST function to only print the two values we want, so to do this, after we put in our known Ys and Known Xs, we are going to use the comma “,” and put 0 then comma “,” and put “1”. This is going to tell Excel we want a negative coefficient (for the DF test) and to print our standard Error:
Then, we are going to press ctrl + shift + enter. Or command + shift + enter on a mac. This is going to force Excel to only print the two variables of interesting:
And there are our results! Now, to calculate the DF test, all we do is divide the coefficient by the error like so:
And here is the result:
So what does it mean? Well, there are 3 critical values on Dickey Fuller
T Critical at 10% confidence = -1.75
T Critical at 5% = - 1.616
T Critical at 1% = -2.567
To be significant, the t-statistic needs to be below a critical value.
As a vague rule of thumb, in general, the more negative a value is, the more confident we are to reject the null hypothesis, that the data is NOT stationary. Here, we fail to have a very negative value and we fail to come in lower than any of the critical values. As such, we have to accept the null hypothesis and the fact that this data is non-stationary.
If we take, by comparison, the t-statistic of SPY and QQQ since 2020, it is a value of -2.048 within a normal distribution. Thus, we can say that the data is stationary up until a confidence level of 5%. However it is not significant within a 1% confidence level.
A side note on distribution:
While the distribution type does not technically affect the DF results, we should pay attention to whether we are operating with a normal distribution or an abnormal distribution.
So we need to check the distribution, which we can do with SPTS:
So should we accept NVDA and SMH as stationary?
No. Unfortunately, it is not a stationary dataset and we cannot use SMH to determine the fair market value of NVDA. I wanted to use this example to show you that stationarity is not a rule and it can be a challenge ascertain it in your models. But if you are big into the indices, generally you will find stationarity if you are looking between 3 to 4 years back max.
To recap, stationarity depends on
a) The distribution type (a normal distribution should be ABOVE the critical values and a non-normal distribution should be below the critical values).
b) In both cases, the more negative a value is, the stronger we can reject the null hypothesis. For example, if we returned a value of -4 on a normal distribution, this would indicate strong evidence of stationarity and would create an extremely reliable model.
c) If the data distribution is non-normal, we need the value to fall below the critical values. So, for -1.75, we would need the value to be less that -1.75 for 10% confidence, less than -1.61 for 5%, etc.
That said, I went ahead and applied the algo despite nonstationary data, to see how it would have faired using SMH as its anchor point. The initial investment was $200 at the start of 2018 and it would only buy NVDA when the value of NVDA fell below the FMV based on SMH. The result?
Our $200 would be $734.85 as of today, assuming we bought when NVDA was below FMV and sold when it crossover the FMV according to SMH, for a total return of around 267%.
What about if we bought NVDA and just held it from 2018 till now?
Our investment would be up to $1636.52 for a total of around 718%.
This is why stationarity matters , because it will affect how our investment does! You see it worked well on SPY and QQQ because there was stationarity to ensure consistency, but NVDA does not have it, too erratic.
So what about if you have stationarity?
If you have stationarity, then good! The principle is, you want to long the stock when your X value is positive (indicating it is undervalued by comparison to your co-integrated pair) and get out and/or short the opposite stock when your x value is negative.
As an investment strategy, I generally recommend not shorting, but just getting out when the x value turns negative (i.e. is over-valued), or simply setting a stop-loss to maintain the bulk of your gains and letting it do what it do.
You can also apply this on the shorter timeframes, like the 1 hour or 2 hour or 4 hour, like the examples I showed above.
Concluding remarks
So that concludes my very lengthy post. I really hope you learned something from this, took something away. These are really complex topics and there are not a lot of good resources out there on how to do them properly. Even just finding resources on the Dickey Fuller test, which is predominately only used in economics, was difficult. So I wanted to provide some information on these more complex strategies and principles that I think most traders and investors should have some idea about.
Hope you enjoyed and safe trades to all!
Thanks for reading!
History is Repeating Itself, Just FasterA little brief before I start into this. I got started investing prior to the 1987 stock market crash and have always been amazed at the stock market for what it can do in a short period of time. People experience the market in so many different ways and I was fascinated by the mass-hysteria, psychology, economics and politics that surrounded the entire 1987 crash. I will say that since I experienced the crash of 1987 and there has still been nothing like it since. The flash crashes, the GFC and many other "sharp drops" are nothing like the speed and power and dislocation of the 1987 crash. So, with that in mind, here is a pattern to compare the 2020 crash with the 1987 crash in context to the massive upwave from 1974-2000 and 2007.
So, to begin, the 1987 crash lines up with the 2020 crash when you use the 1974 low as a comparison to the 2009 low. Then, as life has it, things happen a little faster so this pattern speeds up a little. You can copy it yourself, just then line up the 1987 crash to the 2020 crash.
And here we are, right on track. Post-1987 crash the world was a very scary place in so many ways. It was actually quite scary. The banking system was falling apart because of the 1986 tax law change which bankrupted the S&L's to the biggest bailout in US history.
George Bush Sr, was president and he was very similar to Biden, making mistakes domestically and internationally. He started up the Drug War which destroyed civil liberties in so many ways, much like the draconian lockdowns for Covid.
I did put this long term forecast on long term charts years back here at TradingView so you can review those. This would have been good to have right in front of us before. I missed that chance.
Reagan had one good term before he had trouble with Iran-Contra funding by selling drugs to finance wars in foreign countries. 1985-1987 was a bad time with trade frictions with Germany and Japan due to a strong dollar and major tax law changes which destroyed real estate, much like 2007 led to the 2009 GFC.
Then we had Bush follow Reagan and he wasn't effective as a leader. His famous "Read my lips, no new taxes" happened right before he raised taxes
Sadly, we then had Clinton come in and take over for 8 years and his first attack was on health care, which ended badly but moved him to be more centrist. Al Gore as VP helped to foster internet growth with tax advantages and boom, we had the technology boom leading into the bubble of 2000.
So, the future should write itself from here. Let's look ahead to 1992-2000 ahead with 1993-1994 being a sideways grind with a giant short squeeze in T-Bonds bankrupting Orange County and knocking Long Term Capital Mgmt (hedge fund) to its knees.
More correlations to follow and hopefully we have a new technology like the internet was at that time, to drive accelerating growth. It could be the electrification of vehicles and transportation for its massively more efficient energy consumption. Time will tell!
Enjoy.
Tim
November 8, 2023 11:17AM EST
How to Choose Stocks for TradingWhat stocks do day traders trade? What stock types are more appropriate for swing traders? Selecting suitable stocks for trading requires an amalgamation of keen market understanding and thorough research. This process, while complex, is fundamental for traders aiming to navigate the ever-evolving financial markets with precision. Platforms like FXOpen provide traders with the tools and resources necessary to facilitate this selection, with instruments like TickTrader aiding in a more refined analysis. This article offers a structured approach to stock selection, encompassing various analytical techniques and considerations.
Understanding Your Trading Goals
Every trader has unique objectives shaping their strategies. While a young trader might aim for aggressive growth, those nearing retirement might focus on capital safety.
Consequently:
Growth-oriented traders are drawn to emerging companies with promising revenue growth, even if earnings vary, as they provide a high level of volatility.
Those emphasising capital preservation opt for long-standing firms known for steady profits.
Defining Your Trading Approach
Your trading approach will determine the stocks you can trade:
Short-Term: This is where understanding how to research stocks for day trading becomes essential. This period, which can last anywhere from a few moments to a few days, is ideal for traders who are looking for rapid market movements. Emerging equities and penny stocks may be an ideal option.
Medium-Term: Traders who choose medium-term trading lasting anywhere from weeks to months pay attention to securities whose value highly depends on sector trends or company-specific developments that could affect their value in the near future.
Long-Term: This investment timeframe extends over years. Although it’s not common for traders to keep trades open for such long periods, they may choose stocks with promising growth potential supported by solid company fundamentals.
Are you scouting for the best day trading stocks today, or are you more intrigued by swing trading? With platforms like FXOpen, traders can optimally navigate the markets on chosen timeframes.
Risk Tolerance Assessment
If you are looking for the best stocks for trading, it's crucial to assess the level of risk you're comfortable with in relation to your entire trading capital. Risk tolerance can be categorised into different profiles, such as conservative, moderate, or aggressive:
Conservative approach: priority for capital preservation and lower-risk investments.
Moderate approach: a trader may take some risk but still prefer a balanced approach.
Aggressive approach: higher levels of risk for potentially higher returns.
Understand Stock Types
Stocks can be categorised into various types based on their risk profiles, such as:
Blue-chips: Generally considered less risky and associated with established financially stable companies.
Growth: Offers the potential for higher returns but comes with higher volatility and risk.
Value: Tend to be less volatile and may appeal to more conservative traders.
Fundamental Analysis
Fundamental analysis provides the map for a stock trading journey, using financial statements and key ratios to decode a company's performance and potential.
Evaluating Financial Statements
Income Statement: This vital document illuminates the revenue, expenses, and profits, acting as a window into a company's profitability over a specific period. By examining it, traders discern how the company generates profits and manages its operating expenses.
Balance Sheet: Acting as a financial snapshot, the balance sheet reveals a company's assets and liabilities at a particular point in time. It provides insights into the company's net worth and financial resilience.
Cash Flow Statement: A crucial tool for traders, it traces the journey of cash as it enters and exits the company. More than just profitability, this statement underscores the company's liquidity, showing how well it manages its cash resources.
Analysing Key Financial Ratios: Ratios like P/E, Debt-to-Equity, and ROE offer profound insights into a company's valuation, leverage, and profitability, respectively.
Assessing the Company's Industry and Market Position: Understanding the industry trends and the company's standing within its sector provides context. Does the company lead its peers, or does it follow?
Identifying Potential Catalysts: A product launch, merger, or even macroeconomic factors can serve as catalysts, inducing stock price movements.
Technical Analysis
Technical analysis deciphers stock price movements through historical trends and patterns, enabling traders to base decisions on past data over speculation.
Reading Stock Charts
By analysing chart patterns and technical indicators, you can identify the best stocks with precise entry and exit points, increasing the likelihood of effective trades. For example, if you're looking to learn how to find stocks to day trade, understanding and utilising candlestick patterns can be an incredibly useful tool.
Using Technical Indicators
Technical indicators allow traders to determine the assets with the most promising price movements. Whether you are a day trader or keep trades open for weeks, technical analysis tools will help build a strong trading strategy.
Volume Analysis
Every stock movement is driven by the forces of supply and demand. Volume analysis helps to understand this by shedding light on a stock's trading activity. A surge in volume could indicate a growing interest in a stock, while dwindling volumes could suggest fading enthusiasm. This metric is essential, especially when identifying the best stocks to day trade.
Market Sentiment Analysis
Market sentiment analysis offers a deep dive into traders' collective perceptions, providing insight into their outlook on particular stocks or the market as a whole. Such insights often serve as the vital link between analytical data and the real-world trading environment.
Understanding Market Sentiment: Recognising the market's overall sentiment can be invaluable. For instance, a predominantly bullish sentiment on a blue-chip stock after a strong earnings report might indicate a potential upward trend.
Monitoring News and Events: External events, such as an unexpected CEO resignation or geopolitical tensions, can drastically impact stock prices. Staying updated can prepare traders for sudden market shifts.
Social Media Sentiment Analysis: Platforms like Twitter can be goldmines of trader sentiment. A sudden spike in tweets about a tech company following a product launch, for example, might hint at market excitement.
Sentiment Indicators and Tools: Several tools, such as those on platforms like TickTrader, offer sentiment metrics. Tracking market volume is a logical way to measure market sentiment. Large market volumes are a good indicator of how the market feels about a particular security.
Screening for Trading Candidates
Traders need a systematic approach to identify the most suitable stocks for their strategy in order to navigate the vast sea of options available. Effective screening can be the difference between capitalising on an opportunity and missing it entirely.
Liquidity ensures traders can promptly enter or exit trades. Typically, blue-chip stocks have higher liquidity than small-cap stocks.
Volatility represents price fluctuations. High volatility can provide more short-term trading chances, but it comes with risks. For instance, emerging industry stocks tend to be more volatile.
Price Trends track stocks with steady trajectories. A stock frequently hitting its 52-week high may suggest a sustained bullish trend.
Stock Screeners and Tools: With modern tech, traders use stock screeners to filter stocks that match their criteria, streamlining the selection process.
Conclusion
Choosing stocks requires a careful mix of insight, study, and instinct. As markets change, being informed and adaptable remains crucial. Platforms such as TickTrader support traders, providing essential tools for their trading journey. If you are keen to further harness these approaches, consider opening an FXOpen account.
This article represents the opinion of the Companies operating under the FXOpen brand only. It is not to be construed as an offer, solicitation, or recommendation with respect to products and services provided by the Companies operating under the FXOpen brand, nor is it to be considered financial advice.
Pinefest #1 WinnersThe winner of Pinefest #1, our first Pine programming contest, is alexgrover with this script . Alex is one of our Pine Wizards , and a well-known Pine programmer in our TradingView community. Alex will receive 500 USD and TradingView merchandise.
The five runners-up are:
Trendoscope
ImmortalFreedom
SimpleCryptoLife
jason5480
SamRecio
They will receive TradingView merchandise.
Congratulations to all our winners, and warm thanks to all participants. Pinefest #1 was an unqualified success. We were very pleased to see our vibrant Pine community participate, and were impressed with the number of high-quality entries. Fractions decided the final outcome.
We will continue to issue Pinefest challenges periodically. You can expect a few every year. Upcoming challenges will explore a variety of aspects of Pine programming.
Participants to our next Pinefests should keep in mind that it's important to read the challenge very carefully, to ensure you understand it correctly. It's also essential to produce complete publications for your entries, including a useful description. We are looking for high-quality publications, where descriptions are as important as code.
— The PineCoders team
Why Is Gold Outpacing the Stock Market?Looking back to 1928, when the time series for the S&P 500 began, U.S. equities have had an average annual price return of 5.9%. But gold isn’t far behind with an average yearly gain of 4.9%.
It can be instructive to reprice equities in gold terms by dividing the S&P 500 index by the dollar price of gold.
The S&P 500 to gold ratio has been through broad swings over the past century, with stocks falling by 86% in gold terms between 1929 and 1942; rising by 1165% versus gold from 1942 to 1967; falling by 95% versus gold from 1967 to 1980; soaring 4000% versus gold between 1980 and 2000; and then falling by 89% between 2000 and 2011.
More recently, the S&P 500 rose by 350% versus gold between 2011 and 2021 but has since dropped back by around 15%.
Gold tends to outperform stocks during periods of fiscal and monetary expansion, price instability, and periods of geopolitical conflict and uncertainty. As such, one might wonder if gold might be the outperformer for the remainder of the 2020s.
If you have futures in your trading portfolio, you can check out on CME Group data plans available that suit your trading needs www.tradingview.com
By Erik Norland, Executive Director and Senior Economist, CME Group
*CME Group futures are not suitable for all investors and involve the risk of loss. Copyright © 2023 CME Group Inc.
**All examples in this report are hypothetical interpretations of situations and are used for explanation purposes only. The views in this report reflect solely those of the author and not necessarily those of CME Group or its affiliated institutions. This report and the information herein should not be considered investment advice or the results of actual market experience.
Bearish Dollar Breakdown, Fuel For A Year-End RallyKey to much of the market’s late 2022 and first-half of 2023 rally was a general move lower in the US Dollar Index (DXY). Mostly a short play on the euro, the DXY is a key macro indicator – when it’s rising, it is considered a ‘risk-off’ environment for stocks while significant equity bull markets have featured sideways or downward moves in the greenback. Nothing is set in stone, though, and there have certainly been periods where both the S&P 500 and the buck moved higher in tandem.
Today, though, it’s clear that the usual negative correlation is in play. Just take a look at last week. The SPX enjoyed its best week since November last year as the DXY suffered its worst weekly decline since July. The dollar had been on a great run for much of the second half – with the Invesco Bullish Dollar ETF (UUP) rising in 13 out of 14 weeks, undoubtedly inflicting pain on stock market bulls. That trend may have ended just in time for the usual November-December equity rally.
This week’s chart illustrates a bearish breakdown in the US Dollar Index. The DXY had steadied itself in a range between 105.50 and 107 during October. Last week, and so far this morning, the index is under the key 105-105.50 zone. There’s now a bearish measured move price objective to just under 104. Now, the dollar does not have to collapse to get stocks trending higher over the months ahead, but a bearish DXY bias would be another bullish piece of evidence for investors to consider as strong seasonal trends persist in the next two months.
Reading multi timeframe Secrethello everyone, this is my first video tutorial on this website. I hope I explained everything properly if I didn't let me know so I can make improvements...
I did have some people who contacted me how to trade, they liked my analysis so I made this video for them and also for people new to trading.. Or people who are already pro this will give a nice upgrade on there skills
for this tutorial I used DXY which is the most important index in trading and I think it's a good start for new traders so they can use DXY to trade major currencies..
please let me know how the video was?
thank you
SPX weekly preview and what to watch forAll in the video - 4400 is going to decide whether or not we continue the uptrend. For short term a little higher makes sense, but if this is a bear market rally, this is typical kind of movement. Sometimes they go a little higher, consolidate and pullback again. I cover everything in the video. Thank you for being patient and for your support.
Can DraftKings Overcome Key Technical Levels?Primary Chart : DraftKings Inc. Weekly Price Chart with Fibonacci Levels and Downward Trendline from All-Time Highs
DraftKings Inc., an innovative sports-betting company, has been one of the hottest stocks of this week after it beat earnings expectations and raised revenue guidance. Many are likely chasing the stock's price here without any discipline whatsoever, being driven by fear of missing out and the possibility of untold gains from a former darling of growth investors.
The magenta trendline on the primary chart, which is logarithmically scaled by the way, shows that the downtrend remains intact despite today's powerful rally. This downward trendline could be broken, by the way, if momentum is sustained by bullish seasonality and tailwinds into year end in a pre-election year. But a shorter-term down trendline has been decisively snapped with today's upside push, and this suggests near-term strength for DKNG.
Supplementary Chart A
And DKNG gapped above its key 50-day SMA today as well.
Supplementary Chart B
But this post does not recommend shorting or longing this stock; instead, its purpose is to analyze NASDAQ:DKNG and consider its current position in light of a severe bear market in 2021-2022 and a euphoric bull-market run in 2020-2021. With discipline, some trading profits might be made long or short given this stock's inherent volatility—the stock rose about 15% today and about 25% this week alone. But without risk management, this stock could easily obliterate anyone attempting to gather quick profits on a short-term to intermediate-term time frame.
The stock is extended here after it gapped above key moving averages. It also has reached critical resistance at the .618 Fibonacci retracement after breaking above the 50% retracement on October 31, 2023. The .618 Fibonacci retracement lies at $34.25, a few cents above the high of the week and the day today. A bit of consolidation of today's move may provide traders with a bullish view into the new year (a time frame of about 2 months) a reason to buy the dip.
But caution is warranted into 2024 and 2025—can technological innovation and earnings surprises be enough to sustain this stock? Your comments on this particular question are welcome. There may be room for some debate as macro headwinds cannot prevent rallies like the one seen in equity indices like SP:SPX and some growth stocks. But there is a decent likelihood that macro headwinds may work against DKNG as long as interest rates remain high and inflation does not disappear. The Federal Reserves funds rate is now at 5.25% to 5.50%, a 22-year high. And quick look at the TradingView's Financial overview shows that DKNG has not had positive net income yet. And its financial history is not that long yet: It was founded in 2011, and it has only been public since 2020. So despite the major earnings beat and positive guidance today, DKNG still lost $0.61 per share. Unprofitable growth stocks do not perform as well in high-rate environments.
________________________________________
Author's Comment: Thank you for reviewing this post and considering its charts and analysis. The author welcomes comments, discussion and debate (respectfully presented) in the comment section. Shared charts are especially helpful to support any opposing or alternative view. This article is intended to present an unbiased, technical view of the security or tradable risk asset discussed.
Please note further that this technical-analysis viewpoint is short-term in nature. This is not a trade recommendation but a technical-analysis overview and commentary with levels to watch for the near term. This technical-analysis viewpoint could change at a moment's notice should price move beyond a level of invalidation. Further, proper risk-management techniques are vital to trading success. And countertrend or mean-reversion trading, e.g., trading a rally in a bear market, is lower probability and is tricky and challenging even for the most experienced traders.
DISCLAIMER: This post contains commentary published solely for educational and informational purposes. This post's content (and any content available through links in this post) and its views do not constitute financial advice or an investment or trading recommendation, and they do not account for readers' personal financial circumstances, or their investing or trading objectives, time frame, and risk tolerance. Readers should perform their own due diligence, and consult a qualified financial adviser or other investment / financial professional before entering any trade, investment or other transaction.
TradingView Masterclass: Paper TradingIn this Masterclass, you’ll learn how to use our official paper trading tool. Paper trading gives trades the capability to test their trading skills in a simulated environment without risking real money. For all the new traders out there, you’ll want to make paper trading your best friend. Why? Have all the fun you want, practice endlessly, and never lose a dime.
Reminder: With Black Friday nearing (seriously… it’s coming soon), now is the time to master one of our most important tools. You’ll be ready to go the second you activate your upgraded account.
To get started, follow the steps below:
Step 1 - Click the ‘Trading Panel’ button located at the bottom of the chart.
Step 2 - Once you click the ‘Trading Panel’ button, a list of brokers in your region will appear, but also, at the very top, a Paper Trading account powered by yours truly, TradingView.
Step 3 - Click Paper Trading and you’ll now start the process of opening your free, simulated trading environment, entirely powered by us.
You made it! Time to celebrate! 🕺💃
Alright, let’s go a little deeper and talk about the buttons you’ll want to understand now that you’ve got your Paper Trading account opened.
While still having the Trading Panel open, click the button that says “Trade” and an order slip will appear. It’ll look like this:
As you get started, here are some tips to keep in mind:
Take Paper Trading seriously. Work Paper Trading as if it were a real account:
Record your trades, the reasons, the results obtained and the lessons learned.
Explore different approaches like intraday trading or swing trading.
Maintain emotional discipline, your trading strategy and risk management.
Practice, practice, practice - that’s what this is all about, getting better at trading through practice.
It gets better, because there are multiple ways to trade and customize your paper trading experience. Open the chart settings menu or right click on the chart, and you can add specific trading features to the chart as needed.
In-fact, we’ll explain all of the features available to you in the chart settings.
🟥🟦 Buy/Sell buttons :
When these are turned on, you’ll see a Buy and Sell button at the top right of the chart. When it comes to buying and selling, there are three primary order types:
Market (executed at the current market price),
Limit (executed at a defined specific value), and
Stop (executed when the price falls below a certain level).
👆 Instant Orders placement :
This option allows you to open positions at the market price by simply clicking the buy and sell buttons. You can choose the quantity by clicking on the number below the spread.
⏰ Play Sound for executions :
You can enable this option to receive an audible notification when a trade is executed, with eight different tones to choose from.
📲 Notifications :
Receive notifications for All events or Rejection orders only.
Tip : You can open the order panel by using the Shift + T shortcut or by right-clicking on a chart, then selectings Trade > Create a new order.
👁🗨 Positions :
Uncheck this box if you don’t want to see your active trading positions.
🔺🔻 Profit & loss :
This option allows you to view the profit and loss changes in your trades, which can displayed in both ticks and percentages.
🔃 Reverse button :
When enabled, a button is added to your active trading positions that allows you to reverse your trade.
👁 Orders :
See your current open unexecuted orders by checking this box.
🔺🔻👁 Brackets profit & loss :
It functions similarly to the Profit & Loss option, but for pending orders.
⏪ Executions :
It displays the past executed orders on the chart.
Execution labels :
Enable this option to view specific information about past execution orders, including trade direction, quantity, and executed price.
Extended price line for positions & orders :
It creates an extended horizontal line for your active trades.
⬅⬆➡ Orders & positions alignment :
You can move the alignment of your orders to Left, Center and Right in your charts.
🖥 Orders, Executions and Positions on screenshots :
Check this box if you want to download screenshots (shortcut: Ctrl + Alt + S) with active and pending orders.
Thanks for reading and we hope this tutorial helps you get started! We look forward to reading your feedback.
- TradingView Team
Revisiting Automatic Access Management API for VendorsThis video explains how to automate access management for vendors who build and sell invite only scripts based on subscription or one time fee. I have made videos about this earlier as well. But, due to high demand, I have been asked to make this video again.
🎲 Tools Required
Replit - Used for hosting the service that automates access management
Postman - To test the services hosted
🎲 Prerequisites
User should have premium tradingview account and be able to publish invite only scripts by following the house rules.
User should disable 2FA on their account in order to allow programs to login remotely and manage access.
🎲 Steps
All the steps are also mentioned in the githup repository: github.com
🎯 Run the access management service
Fork the replit repository: replit.com
Update Environment Variables tvusername and tvpassword
Run the repl
🎯 Use postman to test the service methods
Detailed explanation of the API calls are present in the github link provided above. The service is capable of doing following things.
Check if the given tradingview username is valid or not
Get the access details of given user to list of scripts identified by pub id.
Delete the access to given user to list of scripts identified by pub id.
Provide/Extend access to given user to list of scripts identified by pub id for specific duration.
🎲 Notes
Please follow house rules while publishing and selling subscriptions to invite only scripts.
Do not commercialize these API calls or do not turn it into product. The mechanism is built on backend calls that are not officially supported by tradingview. While tradingview is tolerant on individual use, any malicious activity may force them to shut this down for everyone.