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The CORRECT way to trade MAsMost people have traded with moving averages. They end up being frustrated and losing money. That’s because they’re not using them correctly. I’m going to show you how to use moving averages the right way. Where it works and where it doesn’t To get good trades using moving averages, there’s just 1 thing to do. The thing you need to do is move to a higher timeframe. Stick to 1H, 4H and Daily charts. Sounds simple, right? It is simple but extremely effective. When this strategy is used on higher timeframes, it works amazingly. But on lower timeframes, you end up getting a lot of false signals. Also, use this strategy for potential reversals and trend continuation entries. Avoid using them in a sideways market. (I’ll talk about how to avoid a sideways market) Remember, the higher the time frame is, the better and more reliable the signal is. MA pairings These are the best MA pairings you can use: - 13 EMA & 21 SMA - 5 & 20 SMA - 10 & 50 SMA The big secret Now, after using the moving averages to trade, you will still get fake outs. You will still get caught in sideways markets. But there is a way to make the signals extremely reliable and filter out false signals. You can use the Death cross and the Golden cross. A Death cross is used for a sell. It happens when the longer period MA is ALREADY sloping downward and the shorter period MA crosses below it. Example: A Golden cross is used for a buy. It happens when the longer period MA is ALREADY sloping upward and the shorter period MA crosses above it. Example: These are used to avoid sideways markets. Summary This strategy is supposed to be used on high timeframes like the 4H and Daily chart. Rules for a buy: - The shorter period MA crosses above the longer period MA - The longer period MA should be either flat or already be sloping up (this is important) - Never take a buy if the longer period MA is sloping downward Rules for a sell: - The shorter period MA crosses below the longer period MA - The longer period MA should be either flat or already be sloping down (this is important) - Never take a sell if the longer period MA is sloping upward Please do not use this on lower timeframes like 1M, 5M, 15M and 1H. I hope you got value from this!
Education
by SamaaraDas
37
New Chips From Nvidia! Another growth cycle for the stock?Nvidia Corp unveiled its new H200 Tensor Core GPU yesterday, 13 November 2023. This chip boasts a 60-90% productivity increase compared to current models, with Nvidia's main competitors still in the process of developing analogs. The H200 Tensor Core is scheduled for general sale in Q2 2024. It may lead to a future rise in revenue and net profit of the issuer. Consequently, today, our focus is on the Nvidia Corp (NASDAQ: NVDA) stock chart. On the D1 timeframe, support has formed at 398.80, but resistance has not yet developed. Following a prolonged growth cycle, a correction to 476.52 is most likely. On the H1 timeframe, if the asset's upward trend persists, a short-term target for a price increase might be around 502.67. In the medium term, the target for a price increase could hover around 532.55. — Ideas and other content presented on this page should not be considered as guidance for trading or an investment advice. RoboMarkets bears no responsibility for trading results based on trading opinions described in these analytical reviews. The material presented and the information contained herein is for information purposes only and in no way should be considered as the provision of investment advice for the purposes of Investment Firms Law L. 87(I)/2017 of the Republic of Cyprus or any other form of personal advice or recommendation, which relates to certain types of transactions with certain types of financial instruments. Risk Warning: CFDs are complex instruments and come with a high risk of losing money rapidly due to leverage. 67.85% of retail investor accounts lose money when trading CFDs with this provider. You should consider whether you understand how CFDs work and whether you can afford to take the high risk of losing your money.
NASDAQ:NVDA
by RoboMarkets
18
$QQQ: Long term trend turning up?A pattern similar to the one that took place after the 2003 and 2009 bottoms is surfacing in mega cap tech and in index charts now... Low risk buy signal suggesting we might get a substantial rally from here within the coming months, but potentially also for a couple years if the quarterly chart triggers here. This quarterly signal is visible in names like NASDAQ:AAPL and NASDAQ:MSFT , to name a few, so I think it will also trigger here. It also comes on the heels of rates potentially having peaked for the time being, and the Dollar turning down after rallying substantially as of late. And after Oil has come down off the highs, which gives the market a bullish boost with some lag...it will be visible in the next quarterly report or two. Best of luck! Cheers, Ivan 'risk on' Labrie.
NASDAQ:QQQLong
by IvanLabrie
22
Slippery Slope: What is Slippage? With the unfortunate demise of the prop firm My Forex Funds, the issue of slippage has recently become a hot topic. This educational post takes a look at the slippery issue of slippage, beginning with the basics all the way to addressing popular theories and speculations about slippage. Something to remember is that every trader, regardless of expertise, will encounter slippage during their trading activity. What exactly is slippage? Slippage is the term used in the forex market to describe the difference between the requested price at which you expect to fill your order and the actual price that you end up paying. Slippage most often occurs during periods of high market volatility, when market conditions are very thin due to low volumes traded or when the market gaps; all of these scenarios then lead to market conditions being such that orders cannot be executed at the price quoted. Therefore, when this happens, your order will be filled at the next available price, which may be either higher or lower than you had anticipated. Understanding how forex slippage occurs can enable a trader to minimise negative slippage while potentially maximising positive slippage. Market Gap High Market Volatility Slippage is part of trading and cannot be avoided. This is due to forex market volatility and execution speeds. When a market experiences high volatility, it generally means there’s low liquidity. The reason for this is that during this time, market prices fluctuate very quickly. Where this affects forex traders is when there’s not enough FX liquidity to fill an order at the requested price. When this happens, the liquidity provider will complete the trade at the next best available price. Another cause of slippage is execution speed. This is how fast your Electronic Communication Network (ECN) can complete a trade at your requested price. With market prices changing in fractions of a second, having faster execution times can make a difference, especially on large trades. What is the difference between positive slippage, no slippage, and negative slippage? When slippage occurs, it is usually negative, meaning you paid more for the asset than you wanted to, though at some times it can also be positive. When slippage is positive, it means you paid less for the trade than you expected and therefore got a better price. To get a better understanding of this, let's see the image below. How do you calculate slippage? Let's assume that the price of the EUR/USD is 1.05000. After doing your research and analysing the market, you speculate that it’s on an upward trend and long a one-standard lot trade at the current price of EUR/USD 1.05100, expecting to execute at the same price of 1.05100. The market follows the trend; however, it goes past your execution price and up to 1.05105 very quickly—quicker than a second. Because your expected price of 1.05100 is not available in the market, you’re offered the next best available price. For the sake of the example, let's assume that the best next price is 1.05105. In this case, you would experience negative slippage (positive for the broker), as you got in at a worse price than you wanted: 1.05100 – 1.05105 = -0.00005, or -0.5 pips. On the other hand, let’s say your trade was executed at 1.05095. You would then experience positive slippage (negative for the broker), as you got in at a cheaper price than you wanted: 1.05100 – 1.05095 = +0.00005, or +0.5 pips. Negative Slippage Example Is slippage a technical glitch in a broker’s software, or is it built and designed to bring in extra revenue? There are popular beliefs that slippage is a software glitch or that it is made just to give brokers and liquidity providers extra revenue. This is not true, as slippage is something that is unavoidable. There are times when the markets are extremely volatile and price movements are too quick due to a lack of liquidity. Slippage does bring in extra revenue for brokers and liquidity providers, but you need to remember that slippage goes both ways; while brokers and liquidity providers will generate profits from negative slippage, they will also generate losses from positive slippage. Though there are times when brokers (very rare) use price manipulation on their clients to generate additional revenue (more on this later).  How can a trader avoid or minimise slippage? While slippage is impossible to fully avoid, there are a few things you can do to minimise the impact of slippage and protect yourself as much as possible in the markets, including using stop-loss orders to limit their exposure and placing orders during less volatile times. Stop-loss orders are instructions to your broker to immediately exit a trade if it reaches a certain price. By using stop-loss orders, you can limit your losses if the market moves against you. High liquid markets such as Forex enable you to take advantage of market swings to enter and exit trades rapidly, limiting your exposure to the market but also increasing the risk that your stop-loss order may not be executed at the price you expect if the market moves quickly against you. Additionally, there are some brokers that offer traders guaranteed stop-loss orders called 'Guaranteed Stop Orders' (GSOs), meaning that the stop-loss price is guaranteed, which makes the trader unaffected by slippage when getting stopped out. Another way to reduce the impact of slippage is to trade during less volatile times. The forex market is open 24 hours a day, but not all hours are equal. There are times when there are hardly any trading volumes being generated, and you want to avoid trading during this time at all costs as trading spreads will be wider and you will most likely get slipped due to the lack of liquidity in the markets. The best times to trade are usually when the market is most active, which is typically during specific trading sessions such as the Eurpoean or US trading sessions. To summarise, to minimise slippage, you should: What is slippage tolerance, and how should you factor that into account with regard to your stop-loss and risk-to-reward calculations? Some brokers will enable a feature called the 'Market Order Deviation Range' where the trader can adjust the slippage's maximum deviation. This is done so a trader can estimate his or her tolerance to slippage. For example, if you set the maximum deviation to 3 pips, the order will be filled as long as the slippage equals 3 or below. If the price slips beyond the set maximum, the order won't be filled. This is an effective way of managing your risk-to-reward calculations because if you have a strict risk-to-reward set-up and do not have much leeway to give in terms of slippage, you can adjust the slippage tolerance setting so that if the trade comes with more slippage than your trade can afford, it will not enter you in the trade. How can a trader tell if his or her broker is being predatory with regard to slippage? Although rare and illegal now that regulators are prevalent in the industry, in some cases, brokers may manipulate prices to cause slippage. This usually happens during times of high volatility when there are a lot of market orders. By creating a large amount of slippage, brokers can increase their profits. Forex brokers that are not regulated by the major governing bodies are more likely to do this. For a broker to gain the regulation of a major governing body, they must adhere to very strict guidelines set out by the regulating authority. Firstly, if you suspect that your broker is manipulating prices, you should immediately look for another broker. If you have evidence of your broker manipulating prices, you should report that broker to the financial authorities. A good way to gauge if a broker is potentially manipulating prices is by requesting a trade journal from them. A good and reputable broker usually offers trade journals to their clients. Trade journals show execution times of trades and will have a comment on the journal if the trade was slipped. On a standard trade journal, slippage comments should not appear there often (unless you are trading at times when the market is volatile, thin, or trading outside liquid hours). A broker that manipulates prices to their clients is usually hesitant to offer trade journals to their clients because it shows this on the trade journals. So if your broker is not willing to share the trade journals with you, you might want to think twice about continuing to trade with them. To add to that, you can also check if your broker is either a market maker or directly connected to the interbank market, as they will handle slippage differently. To recap, slippage is a part of forex, and no trader is immune to getting it. It occurs most often during periods of high market volatility. Though slippage is almost impossible to avoid and can impact your profit and losses, there are a few things you can do to minimise slippage and its impact. This includes the use of limit and stop-loss orders, placing orders outside of volatile market times, avoiding major economic and news events, and only using brokers that are regulated by the major governing bodies. BluetonaFX
Education
by BluetonaFX
14
Primer on Crude Oil Crack SpreadEver dreamt of being an oil refiner? Fret not. You can operate a virtual refinery using a combination of energy derivatives that replicates oil refiner returns. Crude oil is the world’s most traded commodity. Oil consumption fuels the global economy. Crude is refined into gasoline and distillates. Refining is the process of cracking crude into its usable by-products. Gross Processing Margin (GPM) guides refineries to modulate their output. Crack spread defines GPM in oil refining. This primer provides an overview of factors affecting the crack spread. It delves into the mechanics of harnessing refining spread gains using CME suite of energy products. UNPACKING THE CRACK SPREAD Crack spread is the difference between price of outputs (gasoline & distillate prices) and the inputs (crude oil price). Cracking is an industry term pointing to breaking apart crude oil into its component products. Portfolio managers can use CME energy futures to gain exposure to the GPM for US refiners. CME offers contracts that provide exposure to WTI Crude Oil ( CL ) as well as the most liquid refined product contracts namely NY Harbor ULSD ( HO ) and RBOB Gasoline ( RB ). Crude Prices Crude oil prices play a significant role in determining the crack spread. Refining profitability is directly impacted by crude oil price volatility which is influenced by geopolitics, supply-demand dynamics, and macroeconomic conditions. Higher oil prices lead to a narrowing crack spread. Lower crude prices result in wider margins. Expectedly, one leg of the crack spread comprises of crude oil. Gasoline Prices Gasoline is arguably the most important refined product of crude oil. Gasoline is not a direct byproduct of the distillation process. It is a blend of distilled products that provides the most consistent motor fuel. Gasoline prices at the pump in the US vary by region. Price differs due to differences in state taxes, distance from supply sources, competition among gasoline retailers, operating costs in the region, and state-specific regulations. CME’s RBOB Gasoline contract provides exposure to Reformulated Blendstock for Oxygenate Blending (RBOB). It is procured by local retailers, who blend in their own additives and sell the final product at pumps. RBOB is blended with ethanol to create reformulated gasoline. It produces less smog than other blends. Consequently, it is mandated by about 30% of the US market. RBOB price is thus representative of US gasoline demand. Each CME RBOB Gasoline contract provides exposure to 42,000 gallons. It is quoted in gallons instead of barrels. The contract size is equivalent to one thousand barrels like the crude oil contract. Distillate Prices Distillate or Heating Oil is another important refined product of crude oil. Distillate is used to make jet fuel and diesel. Demand for distillate products is distinct from gasoline demand. A substantial portion of the North-East US lack adequate connection to natural gas. Hence, the region depends on HO for energy during winters making HO sensitive to weather. CME NY Harbor ULSD contract ("ULSD”) provides exposure to 42,000 gallons of Ultra-low sulphur diesel which is a type of HO. ULSD contract is also equivalent to one thousand barrels. Chart: ULSD Price Performance Over the Last Twenty Years. TRADING THE CRACK SPREAD The crack spread can be expressed using the above contracts in three distinct ways: 1) 1:1 SPREAD This spread consists of a single contract of CL on one leg and a single contract of one of the refined products on the other. This spread helps traders to express their view on the relationship between single type of refined product against crude oil. It is useful when price of one of the refined products diverges from crude oil prices. 1:1 spread is also useful when there are distinct conditions affecting each of the refined products. 2) 3:2:1 SPREAD This spread consists of (3 contracts of CL) on one leg and (2 contracts RBOB + 1 contract of ULSD) on the other leg. The entire position thus consists of six contracts. It assumes that three barrels of crude can be used to create two barrels of RBOB and one barrel of HO. This trade is better at capturing the actual refining margin. It is commonly used by refiners to hedge their market exposure to crude and refined products. 3:2:1 spread is used by investors to express views on conditions affecting refineries. 3) 5:3:2 SPREAD Spread consists of (5 contracts of CL) on one leg and (3 contracts of RBOB + 2 contracts of heating oil) on the other leg. This spread captures the actual proportions from the refining process. However, it is much more capital-intensive. FACTORS IMPACTING CRACK SPREAD Seasonality, supply-demand dynamics, and inventory levels collectively impact crack spreads. Seasonality Mint Finance covered seasonal factors affecting crude oil prices in a previous paper . In that paper, we described that crude seasonality is influenced by variation in refined products demand. In summer, gasoline demand is higher, and, in the winter, distillate demand is higher. Seasonal price performance of the three contracts is distinct leading to a unique seasonal variation in various crack spreads. Summary performance of the three spreads is provided below. Chart: Seasonal price performance of Crude, its refined products, and their spread (excluding years 2008, 2009 and 2020 in which extreme price moves were observed) Refiners strategically time their operations based on seasonal trends, ramping up refinery capacity ahead of peak demand in summer and winter. This involves building up inventories to meet anticipated high demand. However, this preparation often results in a narrowed spread just before peak utilization. As the spread reaches its lowest point, refiners take capacity offline for maintenance. Subsequently, crack margins begin to expand as refined product supplies dwindle, aligning with decreased crude oil consumption. This results in a gradually increasing spread through high consumption periods. Supply/Inventories Supply and inventories of crude oil and refined products influence crack spreads. When inventories of refined products remain elevated, their prices decline narrowing the spread. When the production and inventory of crude oil is elevated, its price declines leading to a widening spread. On the contrary, low inventories of refined products can lead to a wider crack spread and low inventories of crude oil leads to a narrower crack spread. Demand Refinery demand has a self-balancing effect as higher refining requires higher consumption of crude which acts to increase crude oil prices. Demand for crude oil and refined products is broadly correlated. However, there are often periods when demand diverges on a short-term scale. Economic activity and available supplies drive demand for refined products. During periods of high economic growth, refined product consumption is robust pushing their price higher. Demand for refined products can precede or lag demand for crude oil from seasonal as well as trend-based factors. This lag can be identified using the crack spread. Sharp moves in crack spread pre-empt moves in the underlying which act to normalize the spread. CURRENT CONDITIONS There are two trends defining the crack spread currently: 1) Divergence in demand & inventories of gasoline and distillates: Low demand for gasoline is evident due to expectations of an economic slowdown while gasoline inventories remain elevated. Though, distillate consumption remains high as inventories are declining and lower than the 5-year average range. Chart: Divergence in inventories of distillate and gasoline (Source – EIA 1 , 2 ). Moreover, inventories of gasoline and distillates are higher than usual. Both factors together have led to a gloomy outlook for refined product demand. Gasoline stocks have started to increase while distillate stocks are still declining. When refined product inventories are elevated investors can position short on the crack spread in anticipation of ample supply. Conversely, if refined product inventories are low, investors can position long on the crack spread. Chart: Divergence in refined product inventories in US (gasoline rising and distillate declining). 2) Declining crude price and tight supplies: In September, Saudi Arabia and Russia announced supply cuts extending into January. Globally, this led to a supply deficit of crude oil. Supplies of crude in the US was particularly stressed as refiners increased utilization to build up inventories while margins were high and exacerbated by a pipeline outage. Chart: Crude Oil inventories in US have stabilized in September and October. Following increase in oil prices, refining activity has slowed, and supplies have become more stable. When inventories of crude are stable or elevated, it indicates less demand from refiners. Investors can opt to position long on the crack spread anticipating ample crude supply. Chart: US Refinery Utilization and Crude Inputs have slowed in October. Although, crude oil supply cuts from Saudi are going to continue until January 2024, there is no longer a deficit as consumption has slowed down. Together, both trends have caused a sharp collapse in the crack spread. Value of the 3:2:1 crack spread has declined by 50% over the past month. Prices of refined products have been affected more negatively by low demand than crude oil. Inventories and supply situation for refined products is more secure than crude oil. Still, seasonal trends suggest an expansion in crack spread once refined product inventories start to be depleted. HARNESSING GAINS FROM CHANGES IN CRACK SPREAD Two hypothetical trade setups are described below which can be used to take positions on the crack spread based on assessment of current conditions. LONG 3:2:1 SPREAD Based on (a) sharp decline in crack spread which is likely to revert, and (b) seasonal trend pointing to increase in the crack spread, investors can take a long position in the crack spread. This consists of: • Long position in 2 x RBF2024 and 1 x HOF2024 • Short position in 3 x CLF2024 The position profits when: 1) Price of RBOB and ULSD rise faster than Crude. 2) Price of Crude declines faster than RBOB and ULSD. The position looses when: 1) Price of Crude rises faster than RBOB and ULSD. 2) Price of RBOB and ULSD declines faster than Crude. • Entry: 63.81 • Target: 79.12 • Stop Loss: 55.73 • Profit at Target: USD 45,930 ((Target-Entry) x 1000 x 3) • Loss at Stop: USD 24,240 ((Stop-Entry) x 1000 x 3) • Reward/Risk: 1.89x LONG 1:1 HEATING OIL SPREAD Based on relative bullishness in distillate inventories plus stronger seasonal demand for distillates during winter, margins for refining heating oil will likely rise faster than gasoline refining margins. Focusing the expanding crack margin on a 1:1 heating oil margin spread can lead to a stronger payoff. This position consists of Long 1 x HOF2024 and Short 1 x CLF2024 . The position profits when: 1) Price of ULSD rises faster than Crude. 2) Price of Crude declines faster than ULSD. The position will endure losses when: 1) Price of Crude rises faster than ULSD. 2) Price of ULSD declines faster than Crude. • Entry: 36.15 • Target: 42.79 • Stop Loss: 32.3 • Profit at Target: USD 6,640 ((Target-Entry) x 1000) • Loss at Stop: USD 3,850 ((Stop-Entry) x 1000) • Reward/Risk: 1.72x KEY TAKEAWAYS Crack spread refers to the gross processing margin of refining (“cracking”) crude oil into its by-products. Refined products RBOB and ULSD can be traded on the CME as separate commodities. Both are representative of demand for crude oil from distinct sources. There are three types of crack spread: 1:1, 3:2:1, and 5:3:2. a. 1:1 can be used to express views on the relationship between one of the refined products and crude. b. 3:2:1 can be used to express views on the refining margin of refineries. c. 5:4:3 can give a more granular view of proportions of refined products produced at refineries but is far more capital-intensive. Crack spreads are affected by seasonality, supply, and inventory levels of crude and refined products, as well as demand for each refined product. A low-demand outlook for refined products of crude is prevalent due to expectations of an economic slowdown. MARKET DATA CME Real-time Market Data helps identify trading set-ups and express market views better. 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 DISCLAIMER This case study is for educational purposes only and does not constitute investment recommendations or advice. Nor are they used to promote any specific products, or services. Trading or investment ideas cited here are for illustration only, as an integral part of a case study to demonstrate the fundamental concepts in risk management or trading under the market scenarios being discussed. Please read the FULL DISCLAIMER the link to which is provided in our profile description.
NYMEX:RB1!Long
by mintdotfinance
12
Gold: Shining Bright with OpportunitiesGold is once again in the spotlight, and here’s why! Economic Cycles, PMI & Gold The US Purchasing Managers Index (PMI) is a leading indicator often used to identify turns in the economic cycle. A below 50 PMI print indicates contraction in the US manufacturing cycle, while a print above 50 suggests expansion. Generally speaking, expanding manufacturing cycles spell a boost for industrial materials, like copper, while contractionary periods spell downturns in the economy and a preference for 'flight to safety', boosting gold holdings. An interesting observation from the chart above is the correlation between the Gold/Copper ratio and the inverted US PMI, moving in tandem over the last decade. However, looking at the current scenario, the PMI has turned lower, yet the Gold/Copper ratio has remained relatively muted, suggesting that gold may currently be underpriced. Similarly, the Gold/Silver ratio shows a less pronounced but similar effect. Significant drops in the PMI below the 50 level have historically triggered notable increases in the Gold/Copper ratio. With the PMI currently below 50 for a sustained period, this might be priming the ratio for a potential upward surge. Yields, Fed Expectation & Gold As a non-interest-bearing asset, gold loses its appeal when interest rates rise, leading investors to prefer interest-yielding products. We covered the effect of a Fed rate cut on gold in a previous article here . While the Fed remains steadfast in holding rates, even the act of pausing rate hikes positively impacts gold. This effect is observed via the Gold/US10Y Yields ratio. The previous pause in rate hikes preceded a significant run-up in this ratio. Additionally, this ratio is currently near its resistance level, which it has respected multiple times over the last decade. With the Fed expected to continue holding rates, now could be an opportune time to consider adding gold to your portfolio. Gold Price Action Gold’s current price action also shows a completed cup-and-handle pattern. With an initial attempt to break higher halted, it now trades right above the handle. Additionally, gold could arguably be trading in an ascending triangle pattern, as noted by its price action as well as generally declining volume, potentially signaling a bullish continuation pattern. In summary, given the Fed's stance on holding rates, the correlation between PMI and the Gold/Copper ratio, and the bullish technical indicators in gold's price action, a positive outlook on gold seems reasonable. To express our view, we can buy the CME Gold Futures at the current level of 1962. Using the cup and handle pattern to guide the take profit level, at 2400 and stop at 1890. Each 0.10 point move in gold futures is for 10 USD. The same view can also be expressed with greater precision using the CME Micro Gold contract where the notional is one-tenth of the regular size gold contract. Here, each 0.10 point move is for 1 USD. The charts above were generated using CME’s Real-Time data available on TradingView. Inspirante Trading Solutions is subscribed to both TradingView Premium and CME Real-time Market Data which allows us to identify trading set-ups in real-time and express our market opinions. 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 Disclaimer: The contents in this Idea are intended for information purpose only and do not constitute investment recommendation or advice. Nor are they used to promote any specific products or services. They serve as an integral part of a case study to demonstrate fundamental concepts in risk management under given market scenarios. A full version of the disclaimer is available in our profile description. Reference: www.cmegroup.com www.cmegroup.com www.cmegroup.com
COMEX:GC1!Long
by inspirante
9
Bitcoin - A Small Or Big Pullback?Bitcoin has had an explosive month of price discovery, as over the course of the last four weeks we've climbed above our previous consolidation range and reached new yearly highs. Data from Glassnode indicates that we are still in the third wave of investor accumulation. Research has shown that in all previous market cycles, there was a pattern of Bitcoin accumulation. 1. The first wave occurs shortly after the All-Time High of Bitcoin in a Market Cycle, when price rapidly moves away (down) from that high level. 2. The second wave occurs during the depths of the Bear Market, when the price floor for that cycle is being discovered and tested. 3. Third third wave occurs after the cycle bottom, when prices begin ticking up in anticipation of the Bitcoin halving. It's important to note that in the last market cycle, there was a significant correction following the third wave of accumulation, which ultimately led to prices trending down until March of that year of the halving. Bitcoin has currently reached a High-Volume Node on our Volume Profile, indicating that this is an area of heavy potential supply or selling pressure. Our Senior Analyst Alexander had originally called for a $35,000 top for Bitcoin prices in 2023. Putting this together, we notice that a large gap was created in Bitcoin's price movement over the last four weeks. We anticipate a good chance for a short-term reversal to re-visit those price levels. This will give us an opportunity to gauge whether: 1. Bitcoin establishes previous resistance as support, and ranges in anticipation of a further breakout. 2. Bitcoin fails to establish previous resistance as support, and decisively breaks back down into a previous trading range. Conservative traders can consider taking profits on BTC long positions, and waiting for confirmation of flipped resistance before establishing a new tranche of long interest. Should Bitocin break previous resistance, we reccomend short-selling positions into the end of the year and potentially much of Q1 '24. Aggressive traders can also consider taking profits on BTC long positions, and establishing short-positions early, whether just for the re-test of the Fair-Value Gap, or to attempt to time the big swing of Bitcoin's correction.
BITSTAMP:BTCUSD
by CrackingCryptocurrency
27
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
NASDAQ:MSFTLong
by PukaCharts
38
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. TradeStation has, for decades, advanced the trading industry, providing access to stocks, options, futures and cryptocurrencies. See our Overview for more. Important Information TradeStation Securities, Inc., TradeStation Crypto, Inc., and TradeStation Technologies, Inc. are each wholly owned subsidiaries of TradeStation Group, Inc., all operating, and providing products and services, under the TradeStation brand and trademark. TradeStation Crypto, Inc. offers to self-directed investors and traders cryptocurrency brokerage services. It is neither licensed with the SEC or the CFTC nor is it a Member of NFA. When applying for, or purchasing, accounts, subscriptions, products, and services, it is important that you know which company you will be dealing with. Please click here for further important information explaining what this means. This content is for informational and educational purposes only. This is not a recommendation regarding any investment or investment strategy. Any opinions expressed herein are those of the author and do not represent the views or opinions of TradeStation or any of its affiliates. Investing involves risks. Past performance, whether actual or indicated by historical tests of strategies, is no guarantee of future performance or success. There is a possibility that you may sustain a loss equal to or greater than your entire investment regardless of which asset class you trade (equities, options, futures, or digital assets); therefore, you should not invest or risk money that you cannot afford to lose. Before trading any asset class, first read the relevant risk disclosure statements on the Important Documents page, found here: www.tradestation.com .
NASDAQ:META
by TradeStation
8
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!
SP:SPX
by TradingView
402
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.
PEPPERSTONE:XAUUSD
by darcsherry
14
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.
Education
by Capitalcom
7
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!
NASDAQ:NVDAEducation
by Steversteves
20
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
SP:SPXLong
by timwest
79
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.
NASDAQ:TSLAEducation
by FXOpen
9
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
AMEX:SPY
by PineCoders
22
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.
COMEX:GC1!
by CME_Group
15