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Megaphone - BearishSPY weekly looking interesting heading into the week. Staying hedged with the SPY holding another megaphone. The SPY is being carried by buyer volume with some hidden bearish divergence on the RSI and nearing overbought territory yet again. With so many sectors and indexes flashing red and a massive bearish cipher on the weekly timeframe as further confirmation, looking forward to playing the downside. Some FIB levels and RSI-based supply and demand zones to keep an eye on in the meantime (Accompanying Charts Attached Below)
AMEX:SPYShort
by jacobosiason7
S&P sets new high but weakness is mountingLast week, the market traded within a narrow range, yet still managed to reach new highs. The bulls remain in control of both the daily and weekly timeframes, although I’m not entirely comfortable with the structure that has developed over the past five days. Most of the growth occurred during extended hours, while during regular trading hours, the market either remained in a tight range or moved downward. This structure is fragile and could easily break, though I’m not ready to call for shorts just yet. Firstly, it hasn’t broken. We're still in a bullish wave on the daily timeframe — in the past two weeks, none of the days have closed below the previous day's low. Secondly, even if the structure breaks, we should not expect significant follow-through, as the market remains very bullish. Here's a quick recap of the key points supporting the bullish thesis (you can find the rest in my previous review): 1. The Fed cut interest rates by 0.5 percentage points, which is positive for both the economy and the stock market for several reasons, such as cheaper borrowing costs. 2. The SPX has reached a new all-time high, which is highly bullish. 3. Both the weekly and daily charts show a strong uptrend. For the market to reverse, there would need to be a significant shift in sentiment, likely triggered by some fundamental event. From a technical standpoint, the uptrend remains intact as long as the bulls hold the previous major low ( 538 ). Until then, any "red" waves should be viewed as mere pullbacks within the broader upward movement.
AMEX:SPY
by hermes_trisme
Exploring Valkyrie Bitcoin Strategy ETF @BTFExploring the Valkyrie Bitcoin and Ethereum Strategy ETF. Bitcoin ( NASDAQ:BTF ).. strong monthly imbalance in control playing our with BTC cryptocurrency currently attempting to break its all-time high again, with a monthly demand level also in control. Long term investment opportunity. Both Bitcoin and Ethereum are trending upwards and have a significant monthly demand level in control, contributing to the rise of these cryptocurrencies and the
NASDAQ:BTFLong
by AlfonsoMoreno
Mastering Market Signals &How to Use the VX Algo? In this video, we'll break down how to maximize your success rate by using key indicators and strategies during the optimal trading window (9:00 AM - 2:00 PM EST). Learn how to identify high-probability buy and sell signals, manage risk effectively, and stay in the 'winning zone' like a pro. Whether you’re a beginner or an experienced trader, this guide will help you gain the edge you need to navigate the markets confidently. Don't miss out on these actionable insights!" Hashtags: #TradingStrategy #VXAlgo #StockMarket #DayTrading #AlgoTrading #MarketSignals #TradingSuccess #Investing #Finance #TradingTips #MarketAnalysis #Stocks #ESFutures #FinancialFreedom
AMEX:SPY
by WallSt007
SPY for TA Tomorrow 9/30. 1. Price Action Overview: Current Trend: The price appears to be in a downward movement after breaking a rising trendline. There is a consolidation phase near the lower end of today's range, which suggests indecision or a potential bounce near support. Volume Profile: The high concentration of volume is around the price levels between 570-572. This indicates that this area has been significant for both buyers and sellers and could act as a pivot zone. 2. Key Levels: Support: 570.42: Strong near-term support, highlighted by the red horizontal line. A breakdown below this level could lead to further downside pressure. 569.89: The lower end of this support zone. A break here could open the door for a test of the 560.79 level, which is another key support based on volume profile and recent lows. 560.79: This represents a significant lower support level. If the market becomes extremely bearish, this level may be tested. Resistance: 571.32: Immediate resistance, shown as a red line on the chart. The price has previously rejected this area, so a break and hold above could show bullish momentum. 574.21 - 575.01: This is a notable resistance zone (highlighted in blue). If the price manages to break through 571.32 and rally, this area could provide strong resistance, as it coincides with prior highs and a volume shelf. 575.50+: Beyond this level, SPY would likely experience some resistance due to prior highs from the 25th-26th. 3. Potential Entry/Exit Points: Bullish Scenario: Entry: A long position can be considered on a bounce from the 570-569.89 support zone. Wait for confirmation of support holding (e.g., bullish candle pattern, or volume surge). Exit: Target the 574-575 resistance area for profit-taking, but keep an eye on momentum to see if it can break further. If volume increases on the upside, you can look for targets beyond 575.50. Stop Loss: Place a stop below the 569.89 support to minimize risk if the price breaks down. Bearish Scenario: Entry: A short position can be considered if price fails to break above the 571.32 resistance level or on a breakdown below 570.42 with strong volume. Exit: First target would be 569.89, and the second target would be the key support level near 560.79. Beyond this, further downside may be possible if there’s continued selling pressure. Stop Loss: If shorting near 571.32, a stop just above this level (around 572 or 572.50) would protect against a reversal. 4. Indicators Analysis: Moving Averages: The price seems to be below key moving averages, indicating short-term bearish pressure. If it moves back above the MAs, it could indicate a bullish reversal. MACD: The MACD at the bottom suggests that bearish momentum is slowing down as the histogram is flattening. This could indicate a potential reversal if a bullish crossover occurs soon. 5. Overall Sentiment: Bearish Bias: As the price broke below the trendline and is currently below the key levels of 571.32, the short-term bias appears bearish. A further break below 570.42 and 569.89 could intensify this. Bullish Potential: If SPY holds the 570 level and shows strength tomorrow, it could attempt a rally toward the 574-575 resistance zone. Suggestion: Tomorrow, I would watch closely for price action around the 570-569.89 zone to determine if there is support holding or if further downside pressure is building. If support holds, look for a potential bounce, but if it fails, prepare for a bearish move.
AMEX:SPY
by BullBear-Insights
NAIL: Entry, Volume, Target, StopEntry: above 177.44 Volume: above 566k Target: 208.80 area (this is an area, no guarantees, you should be selling on the way up) Stop: Depending on your risk tolerance; Based on an entry of 177.45, 167.00 gets you 3/1 Reward to Risk Ratio. This LONG swing trade idea is not trade advice and is strictly based on my ideas and technical analysis. No due diligence or fundamental analysis was performed while evaluating this trade idea. Do not enter a trade based on my idea, do not follow anyone blindly, do your own analysis and due diligence. I am not a professional trader.
AMEX:NAILLong
by tradepatiently
1
Top 5 Weekly Trade Ideas #2 - QQQ S/R Flip + Trend TestQQQ is similar to SPY/ES as usual. The $485 level has proven to be important, bulls have been holding it on every retest since it broke above last week. In addition we have a minor downtrend that could lead to a breakout, but also have the ascending channel/wedge. The trendlines may help determine direction, but 485 is the most important to me and is the simplest way to approach this trade. Bullish above, bearish below. First downside target would a previous low around 479, upside target would be last week's high or the top end of its wedge.
NASDAQ:QQQ
by AdvancedPlays
Weekly Seasonality Dynamic Kelly (Indicator Discussion)# Enhancing Trading Strategies with the Weekly Seasonality Dynamic Kelly Criterion Indicator Amidst this pursuit to chase price, a common pitfall emerges: an overemphasis on price movements without adequate attention to risk management, probabilistic analysis, and strategic position sizing. To address these challenges, I developed the **Weekly Seasonality with Dynamic Kelly Criterion Indicator**. It is designed to refocus traders on essential aspects of trading, such as risk management and probabilistic returns, thereby catering to both short-term swing traders and long-term investors aiming for tax-efficient positions. ## The Motivation Behind the Indicator ### Overemphasis on Price: A Common Trading Pitfall Many traders concentrate heavily on price charts and technical indicators, often neglecting the underlying principles of risk management and probabilistic analysis. This overemphasis on price can lead to: - **Overtrading:** Making frequent trades based solely on price movements without considering the associated risks. - **Poor Risk Management:** Failing to set appropriate stop-loss levels or position sizes, increasing the potential for significant losses. - **Emotional Trading:** Letting emotions drive trading decisions rather than objective analysis, which can result in impulsive and irrational trades. ### The Need for Balanced Focus To achieve sustained trading success, it is crucial to balance price analysis with robust risk management and probabilistic strategies. Key areas of focus include: 1. **Risk Management:** Implementing strategies to protect capital, such as setting stop-loss orders and determining appropriate position sizes based on risk tolerance. 2. **Probabilistic Analysis:** Assessing the likelihood of various market outcomes to make informed trading decisions. 3. **Swing Trading Percent Returns:** Capitalizing on short- to medium-term price movements by buying assets below their average return and selling them above. ## Introducing the Weekly Seasonality with Dynamic Kelly Criterion Indicator The **Weekly Seasonality with Dynamic Kelly Criterion Indicator** is designed to integrate these essential elements into a comprehensive tool that aids traders in making informed, risk-aware decisions. Below, we explore the key components and functionalities of this indicator. ### Key Components of the Indicator 1. **Average Return (%)** - **Definition:** The mean percentage return for each week across multiple years. - **Purpose:** Serves as a benchmark to identify weeks with above or below-average performance, guiding buy and sell decisions. 2. **Positive Percentage (%)** - **Definition:** The proportion of weeks that yielded positive returns. - **Purpose:** Indicates the consistency of positive returns, helping traders gauge the reliability of certain weeks for trading. 3. **Volatility (%)** - **Definition:** The standard deviation of weekly returns. - **Purpose:** Measures the variability of returns, providing insights into the risk associated with trading during specific weeks. 4. **Kelly Ratio** - **Definition:** A mathematical formula used to determine the optimal size of a series of bets to maximize the logarithmic growth of capital. - **Purpose:** Balances potential returns against risks, guiding traders on the appropriate position size to take. 5. **Adjusted Kelly Fraction** - **Definition:** The Kelly Ratio adjusted based on user-defined risk tolerance and external factors like Federal Reserve (Fed) stance. - **Purpose:** Personalizes the Kelly Criterion to align with individual risk preferences and market conditions, enhancing risk management. 6. **Position Size ($)** - **Definition:** The calculated amount to invest based on the Adjusted Kelly Fraction. - **Purpose:** Ensures that position sizes are aligned with risk management strategies, preventing overexposure to any single trade. 7. **Max Drawdown (%)** - **Definition:** The maximum observed loss from a peak to a trough of a portfolio, before a new peak is attained. - **Purpose:** Assesses the worst-case scenario for losses, crucial for understanding potential capital erosion. ### Functionality and Benefits - **Weekly Data Aggregation:** Aggregates weekly returns across multiple years to provide a robust statistical foundation for decision-making. - **Quarterly Filtering:** Allows users to filter weeks based on quarters, enabling seasonality analysis and tailored strategies aligned with specific timeframes. - **Dynamic Risk Adjustment:** Incorporates the Dynamic Kelly Criterion to adjust position sizes in real-time based on changing risk profiles and market conditions. - **User-Friendly Visualization:** Presents all essential metrics in an organized Summary Table, facilitating quick and informed decision-making. ## The Origin of the Kelly Criterion and Addressing Its Limitations ### Understanding the Kelly Criterion The Kelly Criterion, developed by John L. Kelly Jr. in 1956, is a formula used to determine the optimal size of a series of bets to maximize the long-term growth of capital. The formula considers both the probability of winning and the payout ratio, balancing potential returns against the risk of loss. **Kelly Formula:** \ Where: - \( b \) = the net odds received on the wager ("b to 1") - \( p \) = probability of winning - \( q \) = probability of losing ( \( q = 1 - p \) ) ### The Risk of Ruin While the Kelly Criterion is effective in optimizing growth, it carries inherent risks: - **Overbetting:** If the input probabilities or payout ratios are misestimated, the Kelly Criterion can suggest overly aggressive position sizes, leading to significant losses. - **Assumption of Constant Probabilities:** The criterion assumes that probabilities remain constant, which is rarely the case in dynamic markets. - **Ignoring External Factors:** Traditional Kelly implementations do not account for external factors such as Federal Reserve rates, margin requirements, or market volatility, which can impact risk and returns. ### Addressing Traditional Limitations Recognizing these limitations, the **Weekly Seasonality with Dynamic Kelly Criterion Indicator** introduces enhancements to the traditional Kelly approach: - **Incorporation of Fed Stance:** Adjusts the Kelly Fraction based on the current stance of the Federal Reserve (neutral, dovish, or hawkish), reflecting broader economic conditions that influence market behavior. - **Margin and Leverage Considerations:** Accounts for margin rates and leverage, ensuring that position sizes remain within manageable risk parameters. - **Dynamic Adjustments:** Continuously updates position sizes based on real-time risk assessments and probabilistic analyses, mitigating the risk of ruin associated with static Kelly implementations. ## How the Indicator Aids Traders ### For Short-Term Swing Traders Short-term swing traders thrive on capitalizing over weekly price movements. The indicator aids them by: - **Identifying Favorable Weeks:** Highlights weeks with above-average returns and favorable volatility, guiding entry and exit points. - **Optimal Position Sizing:** Utilizes the Adjusted Kelly Fraction to determine the optimal amount to invest, balancing potential returns with risk exposure. - **Probabilistic Insights:** Provides metrics like Positive Percentage (%) and Kelly Ratio to assess the likelihood of favorable outcomes, enhancing decision-making. ### For Long-Term Tax-Free Investors This is effectively a drop-in replacement for DCA which uses fixed position size that doesn't change based on market conditions, as a result, it's like catching multiple falling knifes by the blade and smiling with blood on your hand... I don't know about you, but I'd rather juggle by the hilt and look like an actual professional... Long-term investors, especially those seeking tax-free positions (e.g., through retirement accounts), benefit from: - **Consistent Risk Management:** Ensures that position sizes are aligned with long-term capital preservation strategies. - **Seasonality Analysis:** Allows for strategic positioning based on historical performance trends across different weeks and quarters. - **Dynamic Adjustments:** Adapts to changing market conditions, maintaining optimal risk profiles over extended investment horizons. ### Developers Please double check the logic and functionality because I think there are a few issue and I need to crowd source solutions and be responsible about the code I publish. If you have corrections, please DM me or leave a respectful comment. I want to publish this by the end of the year and include other things like highlighting triple witching weeks, adding columns for volume % stats, VaR and CVaR, alpha, beta (to see the seasonal alpha and beta based off a benchmark ticker and risk free rate ticker and other little goodies. //@version=5 indicator("Weekly Seasonality with Dynamic Kelly Criterion", overlay=false, max_labels_count=500) //////////// // Inputs // //////////// // User Inputs int startYearInput = input.int(2015, "Starting Year for Analysis", minval=1900) float capitalInput = input.float(10000, "Available Capital ($)", minval=0) // User-defined inputs float riskToleranceInput = input.float(1.0, "Risk Tolerance (0-1)", minval=0, maxval=1) float maxDrawdownInput = input.float(20.0, "Maximum Drawdown (%)", minval=0) float marginRateInput = input.float(0.5, "Margin Rate (0-1)", minval=0.01, maxval=1) float maintenanceRateInput = input.float(0.25, "Maintenance Rate (0-1)", minval=0, maxval=1) string fedStanceInput = input.string("neutral", "Fed Stance", options= ) // Options to display the results bool showTableInput = input.bool(true, "Show Weekly Summary Table") // Quarter Inputs // Options to filter returns by specific quarters bool q1Input = input.bool(true, "Q1") bool q2Input = input.bool(false, "Q2") bool q3Input = input.bool(false, "Q3") bool q4Input = input.bool(false, "Q4") ///////////////////////// // Function Definitions // ///////////////////////// // Function to calculate adjusted Kelly Fraction based on Kelly Ratio, risk tolerance, and Fed stance calculateAdjustedKellyFraction(float kellyRatio, float riskTolerance, string fedStance) => // Adjust Kelly Fraction based on risk tolerance float adjustedKellyFraction = kellyRatio * riskTolerance // Adjust based on Fed stance float kellyAdjustment = fedStance == "dovish" ? 0.1 : fedStance == "hawkish" ? -0.1 : 0.0 adjustedKellyFraction := adjustedKellyFraction + kellyAdjustment // Ensure Kelly fraction is within bounds adjustedKellyFraction := math.max(math.min(adjustedKellyFraction, 1), -1) adjustedKellyFraction // Custom function to sum over an array sumArray(float arr) => float total = 0.0 for i = 0 to array.size(arr) - 1 total += array.get(arr, i) total // Function to calculate standard deviation for returns calculateStdDev(float returns) => int count = array.size(returns) if count > 1 float avg = sumArray(returns) / count float sumSqDiffs = 0.0 for i = 0 to count - 1 float val = array.get(returns, i) float diff = val - avg sumSqDiffs += diff * diff float variance = sumSqDiffs / (count - 1) math.sqrt(variance) else 0.0 // Function to calculate Kelly Ratio calculateKellyRatio(float returns) => float winCount = 0.0 float lossCount = 0.0 float totalWinReturn = 0.0 float totalLossReturn = 0.0 int n = array.size(returns) for i = 0 to n - 1 float ret = array.get(returns, i) if ret > 0 winCount += 1 totalWinReturn += ret else if ret < 0 lossCount += 1 totalLossReturn += math.abs(ret) float winProb = (winCount + lossCount) > 0 ? winCount / (winCount + lossCount) : 0.0 float lossProb = 1 - winProb float avgWinReturn = winCount > 0 ? totalWinReturn / winCount : 0.0 float avgLossReturn = lossCount > 0 ? totalLossReturn / lossCount : 0.0 float kellyRatio = 0.0 if avgLossReturn != 0 and avgWinReturn != 0 float odds = avgWinReturn / avgLossReturn if odds != 0 kellyRatio := winProb - (lossProb / odds) kellyRatio // Function to calculate Max Drawdown calculateMaxDrawdown(float returns) => if array.size(returns) == 0 0.0 else float peak = array.get(returns, 0) // Updated to use array.get float maxDD = 0.0 float cumulativeReturn = 0.0 for i = 0 to array.size(returns) - 1 cumulativeReturn += array.get(returns, i) // Updated to use array.get if cumulativeReturn > peak peak := cumulativeReturn float drawdown = peak - cumulativeReturn if drawdown > maxDD maxDD := drawdown maxDDPercent = peak != 0 ? (maxDD / peak) * 100 : 0.0 maxDDPercent ///////////////////////////////// // Data Retrieval and Processing // ///////////////////////////////// // Initialize variables var float weekReturnSums = array.new_float(52, 0.0) var int weekReturnCounts = array.new_int(52, 0) var int weekPositiveCounts = array.new_int(52, 0) var float weekReturnSquares = array.new_float(52, 0.0) var float allWeekReturns = array.new_float() var int allWeekNums = array.new_int() // Get weekly data using request.security = request.security(syminfo.tickerid, 'W', ) // Detect new week isNewWeek = ta.change(weeklyTime) if isNewWeek int weekNum = weekofyear(weeklyTime ) // Previous week number int yearNum = year(weeklyTime ) if yearNum >= startYearInput float prevWeeklyClose = weeklyClose float currWeeklyClose = weeklyClose float ret = (currWeeklyClose - prevWeeklyClose) / prevWeeklyClose * 100 // Update the arrays int idx = weekNum - 1 // index in arrays if idx >= 0 and idx < 52 // Sum of returns sum = array.get(weekReturnSums, idx) + ret array.set(weekReturnSums, idx, sum) // Count of returns count = array.get(weekReturnCounts, idx) + 1 array.set(weekReturnCounts, idx, count) // Sum of squared returns sumSq = array.get(weekReturnSquares, idx) + ret * ret array.set(weekReturnSquares, idx, sumSq) // Positive counts posCount = array.get(weekPositiveCounts, idx) if ret > 0 posCount += 1 array.set(weekPositiveCounts, idx, posCount) // Store all returns and week numbers array.push(allWeekReturns, ret) array.push(allWeekNums, weekNum) //////////////// // Visualization // //////////////// if showTableInput and barstate.islast // Prepare data for the table var int selectedWeekNumbers = array.new_int() var float avgReturnsArray = array.new_float() var float stdDevArray = array.new_float() var float posPercentsArray = array.new_float() var float kellyRatiosArray = array.new_float() var float adjustedKellyFractionsArray = array.new_float() var float positionSizesArray = array.new_float() var float maxDrawdownsArray = array.new_float() for idx = 0 to 51 int weekNum = idx + 1 // Check if the week number is in the specified quarters bool isInQuarter = (weekNum >= 1 and weekNum <= 13 and q1Input) or (weekNum >= 14 and weekNum <= 26 and q2Input) or (weekNum >= 27 and weekNum <= 39 and q3Input) or (weekNum >= 40 and weekNum <= 52 and q4Input) if isInQuarter int count = array.get(weekReturnCounts, idx) if count > 0 array.push(selectedWeekNumbers, weekNum) float sum = array.get(weekReturnSums, idx) float avgRet = sum / count array.push(avgReturnsArray, avgRet) float sumSq = array.get(weekReturnSquares, idx) float variance = (sumSq - (sum * sum) / count) / (count - 1) float stdDev = variance > 0 ? math.sqrt(variance) : 0.0 array.push(stdDevArray, stdDev) // Positive percentage int posCount = array.get(weekPositiveCounts, idx) float posPercent = posCount / count * 100 array.push(posPercentsArray, posPercent) // Extract returns for this week float returnsArray = array.new_float() for i = 0 to array.size(allWeekReturns) - 1 if array.get(allWeekNums, i) == weekNum array.push(returnsArray, array.get(allWeekReturns, i)) // Kelly Ratio float kellyRatio = calculateKellyRatio(returnsArray) array.push(kellyRatiosArray, kellyRatio) // Adjusted Kelly Fraction float adjustedKellyFraction = calculateAdjustedKellyFraction(kellyRatio, riskToleranceInput, fedStanceInput) array.push(adjustedKellyFractionsArray, adjustedKellyFraction) // Leverage factor float leverageFactor = marginRateInput > 0 ? 1 / marginRateInput : 1.0 // Max position size float maxPositionSize = capitalInput * leverageFactor // Position size float positionSize = maxPositionSize * adjustedKellyFraction // Ensure position size does not exceed max position size positionSize := math.min(positionSize, maxPositionSize) // Max Drawdown float maxDD = calculateMaxDrawdown(returnsArray) // Adjust position size if max drawdown exceeds maxDrawdownInput if maxDD > maxDrawdownInput and maxDD != 0 positionSize := positionSize * (maxDrawdownInput / maxDD) array.push(positionSizesArray, positionSize) array.push(maxDrawdownsArray, maxDD) // Limit the number of rows to fit within the table size limit int maxRows = 49 // 49 data rows + 1 header row = 50 total rows int totalRows = array.size(selectedWeekNumbers) int numRows = math.min(totalRows, maxRows) int startIndex = 0 // Display from the first selected week // Create table var table returnsTable = table.new(position.top_right, 8, numRows + 1, border_width=1) // Set table headers table.cell(returnsTable, 0, 0, "Week", bgcolor=color.gray, text_color=color.white) table.cell(returnsTable, 1, 0, "Avg Return (%)", bgcolor=color.gray, text_color=color.white) table.cell(returnsTable, 2, 0, "Volatility (%)", bgcolor=color.gray, text_color=color.white) table.cell(returnsTable, 3, 0, "Pos %", bgcolor=color.gray, text_color=color.white) table.cell(returnsTable, 4, 0, "Kelly Ratio", bgcolor=color.gray, text_color=color.white) table.cell(returnsTable, 5, 0, "Adj Kelly Frac", bgcolor=color.gray, text_color=color.white) table.cell(returnsTable, 6, 0, "Position Size ($)", bgcolor=color.gray, text_color=color.white) table.cell(returnsTable, 7, 0, "Max Drawdown (%)", bgcolor=color.gray, text_color=color.white) // Populate table for idx = startIndex to numRows - 1 int row = idx + 1 // Adjust row index for the table int weekNum = array.get(selectedWeekNumbers, idx) float avgRet = array.get(avgReturnsArray, idx) float stdDev = array.get(stdDevArray, idx) float posPercent = array.get(posPercentsArray, idx) float kellyRatio = array.get(kellyRatiosArray, idx) float adjustedKellyFraction = array.get(adjustedKellyFractionsArray, idx) float posSize = array.get(positionSizesArray, idx) float maxDD = array.get(maxDrawdownsArray, idx) // Week Number table.cell(returnsTable, 0, row, str.tostring(weekNum)) // Avg Return (%) table.cell(returnsTable, 1, row, str.format("{0,number,#.##}", avgRet)) // Volatility (%) table.cell(returnsTable, 2, row, str.format("{0,number,#.##}", stdDev)) // Pos % table.cell(returnsTable, 3, row, str.format("{0,number,#.##}", posPercent)) // Kelly Ratio table.cell(returnsTable, 4, row, str.format("{0,number,#.####}", kellyRatio)) // Adj Kelly Frac table.cell(returnsTable, 5, row, str.format("{0,number,#.####}", adjustedKellyFraction)) // Position Size ($) table.cell(returnsTable, 6, row, str.format("{0,number,#.##}", posSize)) // Max Drawdown (%) table.cell(returnsTable, 7, row, str.format("{0,number,#.##}", maxDD))
NASDAQ:TQQQEducation
by livingdracula
"All-Time Highs" Finally! New Channel Unlocked ! what's next? Finally, we are at "All-Time Highs" and have unlocked a New Channel. What will happen next? Let’s just let the price follow its course. Last week, we correctly predicted the price movement by creating an "N3" and landing in the order block as support to gain upward momentum with the recent movements the price has made, we have unlocked a new upward channel in which we will be monitoring the price movement in the coming weeks (Yellow Channel). Here, we only need to focus on two things: 1. We can see that the last candle is an "Inside Candle." An inside bar can be bullish or bearish, depending on its context within price action. If it forms within a downtrend, it can be considered bearish, indicating a possible continuation. If it forms within an uptrend, it can be considered bullish, suggesting a possible continuation of the uptrend. (Look up this important candlestick pattern on Google.) In this case, the last two candles were bearish, so we might consider that the market could either drop or bounce again in our order block to continue the uptrend. This is the scenario I will be expecting if we have a bearish market on Monday. Now, if the price falls to the order block zone, notice how it will also respect the support of the yellow channel. This could mark the beginning of a bullish sequence. 2. Its Simple, the price stays within the yellow channel and follows an upward and orderly sequence. Thank you for supporting my analysis, and be very cautious when we are at all-time highs. The price can be highly unpredictable, so always make sure to mark your channels and consider institutional movements of supply and demand. Best regards.
AMEX:SPYLong
by RocketMike111
China MCHI small pullback before continuationI tend to ignore China since I really do not like their rampant painful policy changes. I tend to avoid single stocks for investing purposes in this region. The China sentiment however is very bullish and the stocks are undervalued. My plan here is to long an ETF instead which will reduce my single stock policy change risk. Between incentivized buybacks, reduction in down payments for second homes, and 500 billion dollar liquidity injection whales are looking to China. This ETF and China index have broken all 4 moving averages in a single week, this is what I call a pivot. I marked how much further the stochastic RSI has to run this is a decent amount and can take some time. My Plan: Entry point is marked as the dashed red hopefully we get a pullback TP 1 = 54$ TP 2 = 69$ (golden ratio correction thesis) I will be utilizing Jan long calls likely spreads between high open interest strikes
NASDAQ:MCHILong
by Apollo_21mil
5