# How to Size Trades so One Loss Won't Ruin Your Account

To size a position so that a single losing trade cannot blow up your account, you must calculate your trade volume using a fixed percentage of your total trading capital—typically 1% to 2%. By dividing this predefined dollar risk amount by the distance to your stop-loss, you determine the exact number of shares or contracts to purchase. This mathematical framework ensures that even an extended streak of consecutive losses will only result in a manageable drawdown, allowing you to survive market volatility and trade another day.

## The Most Overlooked Skill in Financial Markets

When entering the financial markets, most participants obsess over identifying the perfect entry signal, studying complex chart patterns, and attempting to predict short-term market direction [cite: 1]. However, experienced professionals and institutional traders know that longevity in the markets relies almost entirely on position sizing. Position sizing is the systematic, mathematical process of determining exactly how much capital to allocate to a single trade relative to the total portfolio [cite: 2, 3]. It acts as the critical bridge between a theoretical trading strategy and real-world capital protection [cite: 4].

You can deploy a trading strategy that boasts a highly impressive 70% win rate, but if you size your positions incorrectly and allow your losses to outpace your gains, a few bad trades will still blow up your account [cite: 1, 3]. Conversely, a disciplined trader can win only 40% of the time and still build steady wealth, provided their losses are strictly capped through calculated sizing and their winners are allowed to run [cite: 1]. The financial markets do not reward conviction, hope, or confidence; they operate strictly on mathematical probabilities. If your risk mathematics are flawed, your trading career will inevitably be cut short [cite: 5].

Position sizing determines the ultimate magnitude of each loss, the depth of your account drawdowns, and whether your portfolio can mathematically recover from an inevitable losing streak [cite: 3]. A strategy with a modest edge can succeed brilliantly with proper position sizing, whereas a world-class strategy will ultimately fail if the sizing parameters are too aggressive [cite: 3].

### Deconstructing Expectancy and Win Rate Illusions

The mathematical concept that dictates long-term trading success is not the win rate, but rather the statistical expectancy of the trading system. Expectancy calculates the average amount a trader can expect to win or lose per trade over the long run, factoring in both the win rate and the average size of the wins and losses. The formula for expectancy multiplies the win rate by the average win size, and subtracts the product of the loss rate and the average loss size [cite: 6]. 

If a trader achieves an 80% win rate but averages a 0.5 unit gain on winning trades while suffering a massive 3.0 unit loss on losing trades, the expectancy of that system is negative [cite: 6]. Specifically, over one hundred trades, the mathematical drift of the account is downward despite winning eight out of ten trades. This is the precise reason why an aggressive position sizing strategy destroys high-win-rate accounts. Conversely, a trader with a mere 35% win rate who targets a 3.0 unit gain per win and strictly limits losses to 1.0 unit per trade will yield a robust positive expectancy [cite: 6]. Position sizing is the mechanism that enforces the 1.0 unit limit on the downside, ensuring that the structural math of the strategy remains intact.

## The Mathematics of Survival: Understanding Risk of Ruin

To comprehend why strict position sizing is non-negotiable, one must understand the statistical concept of the "risk of ruin." Risk of ruin is a probability-based metric that estimates the likelihood a trader will lose their entire trading capital, or at least draw down the account to a level where recovery is no longer mathematically realistic [cite: 7, 8]. Professional risk managers treat risk of ruin as a capital survival problem rather than a performance metric [cite: 7].

The core variables that dictate the risk of ruin include the strategy's win rate, the payoff ratio, and crucially, the percentage of capital risked per trade [cite: 7]. As the risk per trade increases, the risk of ruin does not rise linearly; it accelerates exponentially [cite: 7, 8]. 

Drawdown mathematics dictate that recovering from capital losses becomes disproportionately harder as the losses mount. If a trader's account drops by 10%, they need an 11% return to break even [cite: 9]. If the account drops by 25%, a 33% return is required to recover [cite: 9]. However, if poor position sizing leads to a 50% drawdown, the trader must achieve a staggering 100% gain just to return to their starting balance [cite: 8, 9]. Because generating a 100% return is exceedingly difficult, a 50% drawdown is often considered the point of practical ruin [cite: 8]. 

### The Inevitability of the Losing Streak

Every trading strategy, no matter how sophisticated, will experience losing streaks. Statistical variance dictates that even a system with a 60% win rate will eventually encounter periods where ten or more trades in a row hit their stop-losses [cite: 5, 8, 10]. The sequence of returns risk means that identical statistical strategies can perform very differently depending entirely on the order of wins and losses [cite: 7].

Consider two traders who both start with a $10,000 account and experience a statistically plausible ten-trade losing streak. Trader A utilizes the professional standard of risking exactly 1% of their current account balance per trade. Trader B, confident in their strategy, utilizes an aggressive 10% risk per trade. 

| Loss Number in Streak | Trader A (1% Risk per Trade) | Trader B (10% Risk per Trade) |
| :--- | :--- | :--- |
| 0 (Initial Capital) | $10,000.00 | $10,000.00 |
| 1 | $9,900.00 | $9,000.00 |
| 2 | $9,801.00 | $8,100.00 |
| 3 | $9,702.99 | $7,290.00 |
| 4 | $9,605.96 | $6,561.00 |
| 5 | $9,509.90 | $5,904.90 |
| 6 | $9,414.80 | $5,314.41 |
| 7 | $9,320.65 | $4,782.97 |
| 8 | $9,227.45 | $4,304.67 |
| 9 | $9,135.17 | $3,874.20 |
| 10 | $9,043.82 | $3,486.78 |

By the end of the streak, Trader A has lost just under 10% of their total capital [cite: 8, 11]. They possess over $9,000 in equity and can easily continue trading their system with clear emotional bandwidth [cite: 11]. Trader B, conversely, has lost roughly 65% of their account, dropping below $3,500 [cite: 8, 11]. Trader B is functionally ruined, as they now require nearly a 200% gain just to recover their initial capital [cite: 8].

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## The Foundation of Risk Control: The 1% Rule

The foundational guideline that governs professional position sizing is universally known as the "1% Rule." This rule dictates that a trader should never risk more than 1% of their total trading capital on any single trade [cite: 2, 10, 12]. It does not imply that the trader only invests 1% of their capital into the asset. Rather, it means that if the trade reaches the predetermined stop-loss level, the absolute dollar amount lost will be capped at exactly 1% of the total account balance [cite: 2].

The primary function of the 1% rule is to preserve capital for future opportunities and to mitigate the compounding damage of consecutive losses [cite: 2, 12]. For absolute beginners, some institutional educators recommend dropping the risk per trade to an even more conservative 0.5% to ensure maximum survival while navigating the steep learning curve of the markets [cite: 13, 14]. Conversely, more aggressive traders with proven, high-expectancy systems may push this boundary to the 2% rule, though doing so inherently magnifies the impact of mistakes during losing streaks [cite: 12, 15]. The 1% threshold is widely considered the optimal balance between meaningful portfolio growth and robust drawdown protection [cite: 15].

For a trader with a $5,000 account, the 1% rule limits the maximum risk per trade to $50 [cite: 13]. On a $25,000 account, the maximum risk is $250, and on a $100,000 portfolio, it scales to $1,000 [cite: 1]. By operating within this rigid boundary, the sizing framework inherently removes emotional decision-making from the heat of the moment, as the absolute maximum financial pain is both known and accepted before the trade is even executed [cite: 2, 15]. 

## The Step-by-Step Position Sizing Formula

Position sizing is not an arbitrary decision; it is derived from a clear, logical mathematical formula [cite: 2]. To determine exactly how many shares or units to purchase, traders execute a sequential calculation utilizing three core inputs: the total account size, the selected account risk percentage, and the distance to the invalidation point [cite: 2, 3].

### Defining the Invalidation Point (Stop-Loss)

Before calculating the size of the position, the trader must determine where the market would definitively prove their trade thesis wrong [cite: 2, 14]. This price level is the invalidation point, where a hard stop-loss order must be placed [cite: 2, 14]. A stop-loss is not designed to protect the individual trade; its sole purpose is to protect the overall trading account [cite: 15]. 

The placement of the stop-loss must be dictated by technical market structure, support and resistance levels, or historical volatility [cite: 15]. A common and devastating mistake made by novices is placing a stop-loss based on an arbitrary dollar amount they feel comfortable losing, rather than placing it at a logical structural level on the price chart [cite: 16]. If a stop-loss is placed arbitrarily tight just to allow for a larger position size, it will likely be triggered by normal market noise before the trade has a chance to play out in the desired direction. 

### Executing the Mathematical Calculation

Once the risk percentage and the stop-loss distance are established, the position size can be calculated using the following standard formula:

**Position Size = Account Risk Amount ÷ Trade Risk Per Share** [cite: 1, 14, 17]

The "Account Risk Amount" is the total dollar figure the trader is willing to lose, derived by multiplying the account size by the risk percentage [cite: 1]. The "Trade Risk Per Share" is the absolute distance between the planned entry price and the stop-loss price [cite: 1, 14].

Consider a practical example involving equity trading. A trader manages a $50,000 account and adheres strictly to the 1% rule, establishing a maximum Account Risk Amount of $500 per trade [cite: 18, 19]. They identify a compelling setup to purchase a stock at an entry price of $100.00 [cite: 19]. Based on their technical analysis, the logical invalidation point is below a recent support level at $95.00 [cite: 19]. 

The Trade Risk Per Share is calculated by subtracting the $95.00 stop-loss from the $100.00 entry price, resulting in a risk of $5.00 per share [cite: 19]. Finally, the trader divides the $500 Account Risk Amount by the $5.00 Trade Risk Per Share. The formula outputs a Position Size of precisely 100 shares [cite: 19]. If the market turns against the trader and hits the $95.00 stop-loss, the 100 shares will be sold for a $500 loss, perfectly honoring the 1% risk parameter [cite: 19].

This formula reveals the dynamic nature of position sizing. The number of shares purchased changes on every single trade depending on the distance to the stop-loss [cite: 1, 3]. If the trader in the previous example needed to place a wider stop-loss at $90.00 due to higher market volatility, the Trade Risk Per Share would increase to $10.00 [cite: 12]. To maintain the strict $500 Account Risk Limit, the formula ($500 ÷ $10.00) would demand a smaller position size of only 50 shares [cite: 12]. A wider stop-loss demands a smaller position size, while a tighter stop-loss allows for a larger position size, yet the total capital at risk remains a constant $500 in both scenarios [cite: 1, 2, 3].

## Leverage Versus Position Sizing: A Critical Distinction

A profound misunderstanding that routinely destroys retail trading accounts is the conflation of position sizing with leverage. Leverage is a credit mechanism provided by brokerage firms that allows traders to control a large notional position using a relatively small initial margin deposit [cite: 10, 20]. It is essentially a financial magnifying glass that amplifies both potential profits and potential losses [cite: 10, 21]. 

For example, a forex trader utilizing a 30:1 leverage ratio can control a $100,000 standard lot of currency by depositing just $3,333 in margin [cite: 21]. Inexperienced traders frequently assume that if they have $3,333 in their account, they should utilize the maximum allowable leverage to open the largest possible position. This reckless approach is known as sizing based on margin requirements, and it abandons the 1% rule entirely [cite: 20]. 

Leverage itself does not inherently destroy accounts; it provides capital efficiency [cite: 20]. What destroys accounts is the failure to apply the standard position sizing formula to leveraged instruments [cite: 20]. The dollar risk must still be calculated from the stop-loss distance, not the available margin. If the math dictates that the trader can only afford to control a $10,000 micro-lot to keep their risk under 1%, the fact that the broker's leverage would permit a $100,000 trade is completely irrelevant [cite: 10, 20]. Professional institutional traders running massive funds may use effective leverage for capital efficiency, but they still restrict the risk of any single position to a tiny fraction of their assets under management on a stop-loss basis [cite: 20].

### The Era of Global Regulatory Intervention

Historically, retail traders have proven so susceptible to the allure of over-leveraging that global regulatory bodies were forced to intervene to protect the public from catastrophic losses. Following the 2008 financial crisis, extensive data analysis revealed that between 74% and 89% of retail investor accounts were losing money rapidly when trading highly leveraged Contracts for Difference (CFDs) [cite: 22, 23]. Because small adverse price movements on oversized, over-leveraged positions can trigger margin calls that instantly wipe out an entire account, regulators recognized that excessive leverage was an acute systemic hazard to retail participants [cite: 23].

In 2018, the European Securities and Markets Authority (ESMA) implemented comprehensive product intervention measures across all EU member states [cite: 22, 24]. ESMA mandated strict leverage caps, limiting retail traders to a maximum of 30:1 for major currency pairs, 20:1 for non-major pairs and gold, 10:1 for commodities, and 2:1 for highly volatile cryptocurrencies [cite: 24, 25]. Furthermore, ESMA enforced a standardized margin close-out rule and mandatory negative balance protection, guaranteeing that retail clients could never lose more money than they had deposited in their accounts [cite: 24, 25, 26].

Regulatory bodies worldwide echoed this protective stance. The Australian Securities and Investments Commission (ASIC) adopted identical leverage limits, noting that retail traders frequently utilized 500:1 leverage to place massive directional bets without utilizing any formal position sizing framework [cite: 21, 27]. Similarly, Japan's Financial Services Agency (FSA), which had previously witnessed periods of extreme retail speculation, instituted a hard cap of 25:1 leverage on over-the-counter currency derivatives [cite: 28, 29]. 

These regulatory actions underscore a fundamental market truth: the average retail participant lacks the discipline to self-regulate their position sizes when offered unlimited buying power. By capping leverage, regulators installed a structural safety net that forces traders to reduce their notional exposure, inadvertently pushing them closer to mathematically sound position sizing [cite: 20].

## Advanced Position Sizing Methodologies

While the fixed percentage method of the 1% rule is the most universally applicable framework, professional traders and quantitative analysts employ several advanced methodologies to adapt their sizing to varying market environments.

### Fixed Fractional and Compounding Risk

The standard 1% rule is technically a form of Fixed Fractional position sizing. By risking a fixed percentage of the total account equity, the absolute dollar amount risked scales up and down dynamically as the account balance fluctuates [cite: 1, 14, 30]. If a trader starts with $10,000, their 1% risk is $100. If successful trading compounds the account to $15,000, the 1% risk automatically increases to $150, allowing the trader to systematically capitalize on their edge [cite: 14, 31]. Conversely, if the account draws down to $8,000, the risk parameter automatically tightens to $80 [cite: 30]. This self-adjusting mechanism inherently protects capital during losing streaks while aggressively compounding capital during winning streaks [cite: 1, 14].

An alternative approach is the Risk Multiple or Fixed Dollar Sizing method, where the trader risks a static dollar amount—often referred to as an "R-value"—on every single trade regardless of the fluctuating account balance [cite: 14, 19]. If the R-value is defined as $500, the trader risks exactly $500 on every setup. While this method offers extreme simplicity and consistency, it fails to capitalize on compounding growth and can result in disproportionate risk exposure if the account suffers a prolonged drawdown [cite: 14, 32].

### Volatility-Based Sizing and the Average True Range (ATR)

Market assets do not exhibit uniform behavior. A high-beta technology stock may routinely fluctuate by 5% in a single trading session, whereas a conservative utility stock or a major fiat currency pair may only move by fractions of a percent [cite: 14]. Sizing positions without accounting for these discrepancies in underlying volatility exposes the portfolio to hidden risks [cite: 19]. 

Volatility-Based Sizing solves this by systematically adjusting the position size relative to the asset's normal price fluctuations [cite: 14]. Quantitative traders frequently utilize the Average True Range (ATR) indicator, which measures the absolute price range of an asset over a defined historical period, typically 14 days [cite: 14, 31]. 

Rather than picking a stop-loss distance subjectively, the trader will set their stop-loss as a multiple of the current ATR—for example, 2x the ATR [cite: 4]. If the market enters a highly volatile phase, the ATR reading expands, forcing the calculated stop-loss to be placed further away from the entry price [cite: 4, 15]. According to the standard position sizing formula, this wider stop-loss directly results in a smaller share size [cite: 14, 33]. 

For instance, if the ATR-based stop-loss is $5 away from the entry, a $1,000 risk limit allows for 200 shares. If macroeconomic news doubles the volatility and pushes the ATR-based stop-loss to $10 away, the identical formula automatically restricts the trader to 100 shares [cite: 14]. This built-in mathematical shock absorber ensures that the portfolio is never overexposed to wild, erratic market conditions [cite: 14, 33]. 

### The Kelly Criterion and Fractional Kelly

For highly advanced, algorithmic, or quantitative trading systems, the Kelly Criterion is a mathematical formula designed to calculate the absolute optimal position size that maximizes the long-term compound growth rate of the portfolio [cite: 17, 32]. The formula relies heavily on the historical probability of winning and the exact ratio of the average win to the average loss [cite: 32]. 

For a strategy possessing a 60% win rate and a 1.5-to-1 reward-to-risk ratio, the pure Kelly calculation might suggest allocating an aggressive 40% of total capital to a single trade [cite: 32]. While mathematically optimal in a theoretical environment with infinite capital, trading full Kelly sizes in the real world almost guarantees catastrophic drawdowns due to inevitable statistical variance and "fat tail" market events [cite: 32]. Consequently, risk managers typically utilize a "Fractional Kelly" approach, deploying only 25% to 50% of the recommended Kelly output [cite: 31]. This significantly reduces volatility exposure while still capturing the vast majority of the mathematical growth curve [cite: 31].

## Portfolio-Level Risk and Institutional Exposure Limits

Position sizing cannot be evaluated solely in a vacuum on a trade-by-trade basis. If a trader utilizes strict 1% risk parameters on five separate trades, but all five trades involve highly correlated semiconductor stocks, the trader is functionally risking 5% of their account on the semiconductor sector. If an adverse macroeconomic event impacts the entire industry simultaneously, all five stop-losses may trigger concurrently [cite: 19].

To defend against this, comprehensive risk management frameworks incorporate total portfolio exposure limits, often referred to as limiting "portfolio heat" [cite: 1]. A standard safeguard is the 6% or 10% aggregate exposure rule, which strictly caps the total open risk across all simultaneous positions [cite: 1, 32]. If a trader reaches a 10% portfolio heat limit, the sizing algorithm or trading plan forbids the opening of any new positions until existing trades are either closed or their stop-losses are trailed to the break-even entry price, effectively removing their downside risk from the portfolio calculation [cite: 16, 32]. 

Institutional environments enforce these exposure limits with rigorous oversight. For example, the Canadian Investment Regulatory Organization (CIRO) publishes extensive best-practice guidelines for credit risk management among dealer members [cite: 34, 35]. CIRO expects firms to actively monitor individual account concentration limits, adjust margin rates dynamically based on the liquidity of the underlying security, and utilize sophisticated valuation models to measure both the current replacement value and the potential future market exposure of every position [cite: 34, 35]. 

Similarly, the Securities and Futures Commission (SFC) in Hong Kong imposes strict statutory position limits on futures and options contracts to prevent the accumulation of massive, market-destabilizing exposures [cite: 36, 37]. The SFC requires asset managers seeking exemptions to hold excess positions to demonstrate highly effective internal control procedures and risk management systems that actively monitor market risk and concentration risk [cite: 36, 38]. These vast institutional frameworks are essentially complex, macro-level applications of the same protective principles that govern the retail 1% rule.

## Psychological Traps That Destroy Trading Accounts

The mathematics governing position sizing are straightforward, utilizing simple division. The reason the overwhelming majority of retail participants fail to achieve long-term profitability is rarely due to mathematical illiteracy; it is deeply rooted in human psychology [cite: 1, 39]. Behavioral finance studies identify several pervasive cognitive biases that actively sabotage rational position sizing decisions [cite: 40, 41]. 

### Overconfidence Bias and Oversized Bets

Overconfidence bias occurs when individuals overestimate their own abilities, the accuracy of their analysis, or their control over future outcomes [cite: 40, 41]. In the context of trading, this often manifests after a brief winning streak. A trader experiencing temporary success will begin to believe they have developed superior market intuition, leading them to abandon their disciplined 1% risk parameters [cite: 42]. 

Convinced that a particular chart setup is a "sure thing," the overconfident trader will allocate 10%, 20%, or even 50% of their capital to a single position [cite: 43]. Because investing inherently involves forecasting complex future probabilities, unexpected variables—such as a surprise earnings miss or a sudden geopolitical event—can instantly invalidate the thesis. The resulting catastrophic loss wipes out months of accumulated gains in a matter of minutes, an outcome entirely preventable with proper sizing [cite: 41, 42, 43]. 

### Loss Aversion and the Disposition Effect

Pioneered by economists Daniel Kahneman and Amos Tversky through Prospect Theory, the concept of loss aversion reveals that humans experience the psychological pain of losing money approximately twice as intensely as the pleasure derived from gaining an equivalent amount [cite: 42, 44]. In trading, this intense fear of realizing a loss paralyzes decision-making [cite: 41, 44]. 

When a properly sized trade moves against an investor and approaches the predetermined 1% stop-loss, loss aversion triggers an emotional response [cite: 44]. Rather than accepting the small, calculated defeat, the trader will often cancel the stop-loss order entirely, hoping the market will eventually reverse [cite: 41]. This behavior directly causes the "disposition effect," where investors rapidly sell their winning positions to secure guaranteed joy, but stubbornly hold onto their losing positions to delay the pain of failure [cite: 41]. 

A secondary, equally destructive manifestation of loss aversion is "averaging down," where a trader buys more shares of a declining asset to lower their average entry price [cite: 1]. By doing so, they drastically increase the size of the position while the market is actively proving their original thesis wrong. By refusing to accept a tiny, mathematically planned loss, the trader allows a minor setback to mutate into a terminal portfolio drawdown. 

### Herd Mentality and Confirmation Bias

Herd mentality drives investors to follow the prevailing crowd, entering massively popular trades even when the sizing mathematics or risk-reward ratios no longer make logical sense [cite: 40, 42]. When combined with confirmation bias—the tendency to actively seek out only the information that supports a pre-existing belief while ignoring contradictory warning signs—traders become blind to risk [cite: 42]. A trader swept up in market euphoria will disregard their volatility-adjusted sizing formulas, heavily concentrating their portfolio into highly correlated, overextended assets simply because consensus sentiment deems them safe [cite: 40, 42]. 

## Conceptual Frameworks for Disciplined Sizing

To internalize the necessity of strict position sizing and override these psychological biases, professional market participants often rely on distinct conceptual analogies. 

### The Insurance Deductible Analogy

In the realms of corporate risk management and options trading, position sizing and stop-loss placement are conceptually treated like an insurance policy deductible [cite: 45]. When an individual purchases comprehensive automobile insurance, they agree to pay a small, fixed deductible out of pocket in the event of an accident [cite: 45, 46]. They willingly accept this minor, guaranteed loss to ensure that a catastrophic total loss of the vehicle does not lead to financial ruin [cite: 45]. 

In trading, the hard stop-loss acts as the insurance policy protecting the total account capital [cite: 15, 45]. The position size dictates the precise cost of the premium or the deductible [cite: 45, 46]. By utilizing the 1% rule, the trader is simply paying a minor, pre-calculated deductible to the market to find out if their trade thesis is correct [cite: 15, 46]. Recognizing a losing trade as a standard insurance premium, rather than a personal failure, helps neutralize loss aversion [cite: 47]. 

### The Business Inventory Limit Analogy

Retail businesses do not allocate their entire annual purchasing budget to acquire a massive stockpile of a single, unproven product. Doing so would consume all available capital, eliminate product diversification, and leave the business entirely dependent on a single outcome [cite: 3, 39]. If consumers reject the product, the business collapses. 

Instead, a prudent manager allocates small fractions of capital across various product lines to test consumer demand. Position sizing operates on the exact same premise. It is the practice of smart inventory management for financial assets, allocating only minor percentages of the portfolio to distinct, uncorrelated trade ideas [cite: 3, 39]. This ensures the trading enterprise always maintains sufficient operating capital to survive poor inventory decisions and successfully pivot toward profitable trends [cite: 3, 39].

## Bottom line

Proper position sizing is the absolute foundation of long-term survival in the financial markets, serving as a vital mathematical firewall against inherent volatility and inevitable losing streaks. By calculating trade volume based on a rigid 1% to 2% risk of total capital, and dynamically adjusting that size based on the distance to a structural stop-loss, traders can effortlessly absorb losses that would otherwise destroy a portfolio. While high broker leverage and psychological biases like overconfidence continually tempt participants to place outsized bets, enduring profitability is reserved exclusively for those who prioritize the defensive mathematics of capital preservation over the pursuit of maximum gains. 

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61. [St. Louis Fed: Portfolio Insurance](https://fraser.stlouisfed.org/files/docs/publications/frbatlreview/pages/67082_1985-1989.pdf)
62. [Newfound Research: Trend Following](https://blog.thinknewfound.com/tag/trend-following/)
70. [Curved Trading: Expectancy](https://curvedtrading.com/articles/en/trading/expected-value-trading-high-win-rate-losing-money/)
72. [Corporate Alliance: Leverage & Margin](https://corporatealliance.com/blog/fx-risk-management/understanding-leverage-margin-pips-forex-trading/)
73. [ASIC: CP322 Submissions](https://download.asic.gov.au/media/5829278/cp322-individual-submissions-1-50.pdf)
74. [KenMacro: Forex Leverage](https://kenmacro.com/what-is-leverage-in-forex-2026/)
75. [J2T: Leverage Interventions](https://j2t.com/solutions/blogview/what-is-leverage/)
77. [CIRO: Best Practices Credit Risk](https://www.ciro.ca/newsroom/publications/best-practices-credit-risk-management)
81. [CIRO: Credit Risk Guidance](https://www.ciro.ca/newsroom/publications/best-practices-credit-risk-management-0)
87. [St. Louis Fed Review: Options Sizing](https://fraser.stlouisfed.org/files/docs/publications/frbatlreview/pages/67082_1985-1989.pdf)
92. [StarTrader: Stop Loss Placement](https://www.startrader.com/knowledge-basics/trading-risk-management-rules-position-sizing-limits/)
93. [TradeFundrr: Kelly Criterion & ATR](https://tradefundrr.com/position-sizing-methods/)

**Sources:**
1. [chartguys.com](https://vertexaisearch.cloud.google.com/grounding-api-redirect/AUZIYQFylSdHw8-GTpFNevzUgVWhcuqkHHpkf1lCofooEMd0XAWpnRGQjXQNLM3eywhuzA6BMSBSojgdjUYLF3_3XdFXaBUaZy91NLHLRz-tC05ceDAUr0kkaYOTAck_uLLIOB4eFdAg-t3JGg==)
2. [binance.com](https://vertexaisearch.cloud.google.com/grounding-api-redirect/AUZIYQEEjMUvfiB56qVc6pHxMriV-RB8pQrOkcu3FdsBbiNZgIWR1-uwUo8mFu_bB2aa6zPjFlMnk2XpWHkY-boMcaxeDUk3FRUC-6d6IOtgoMhgcwM2Yyu_oGYUUwIpt8FV12G7qqYv8FzvCZg0CetBAuYGYkOtFXot0lC-5_92CDigvLzmUzQqXDs=)
3. [heygotrade.com](https://vertexaisearch.cloud.google.com/grounding-api-redirect/AUZIYQFBF1k9RALb_Ym8lJbkxy85gqgiMAVZGYyy8z8QaWjDnGQjzKioq5eagVC_6a7gmdLH7Kp4kFDisGv9VOqz4266w0yBBGsrkRmQLQkFo49fv_YtqQxctBFdcwt_eHBjHISaMuNaTqhLPAGau2CDgE_lC0Pd)
4. [tradingmetrics.com](https://vertexaisearch.cloud.google.com/grounding-api-redirect/AUZIYQHucNNw2TZMp_Q5RuY9aMyrHSh5rv1GPlYHvc0j2dILcdR4z5fyXA36T4GBGf2FdbAY2VqEakN6ovLmX5-cgAIJHcIo_g0pzXoe_S08F5PkZ1waWRYdtm6qMXQAp_gcqyqK4rYyInv9_NbEvvmf502jNQJYndssc1VQC18AIjC2rT1Abu3W5s4xx9jv)
5. [acy.com](https://vertexaisearch.cloud.google.com/grounding-api-redirect/AUZIYQGr-D6uakEeGwQGqyzlTqCIfv_q7z1fVTXyJpad8y5z-s6KpgusRbyFeXrZV97d0Lv-SomWTfccdBc6FSZO8wQ0G4LYYV0Qrn2tRSYG9h0Pw_YW7b5kTbslIfO8zeWds30qC6oapsiSTC3_r2E4snN7uoQ_BOHR5tFu0aq_eU286RfWk3Iq4Wl-Yw==)
6. [curvedtrading.com](https://vertexaisearch.cloud.google.com/grounding-api-redirect/AUZIYQEkv5De-8eFHY_PU_M9wlF5jlQG_VI2BNK5nJYEVFMgDoWIwBaXT8nF90wsE_1yFAmz2NT0j64bUnP9UitsXrL1E1iI3RiosxdURPhnqzrqLq_Yh4J1y1vDsm2cYeRQ3nbn4Up6RwppNZ2_sQO52PjaBdzKEJPWtTdi9hZsdnoyu_C2BE-2JBLxa4fTOExG1c7lTw-UEwM=)
7. [arongroups.co](https://vertexaisearch.cloud.google.com/grounding-api-redirect/AUZIYQFmN83LFxEVmlxt8Wj1XLoikYuU-de2ciS5cXsRuSsJUHw63Ep-GsYXX102K5h_GZzW8xJZgB_677pGCvqZL9ik12hNx5rj8hCVsMD25VYrsaOfClBcBblppiQKXZyr1_lYeyZr8rpfwZ1bkAQhJw==)
8. [heygotrade.com](https://vertexaisearch.cloud.google.com/grounding-api-redirect/AUZIYQG3dNGASsXXysegYAD1p4O_E1mjWSWJgFfLAZI-pm6SnqKPdVc_ZQUv3ctEQBGDlE0RatAFZOH6Mu3mqDJKDaCZ3Cv2QMVCmDc7NRBBKSHgOWBrbKgvUxEIUW1IwUOlrqQF0PUOvG771FLGhdUsQuk1fTw=)
9. [bookmap.com](https://vertexaisearch.cloud.google.com/grounding-api-redirect/AUZIYQGzr8ufGPm2_68EYD3rMtUO7Q7GL7gYGbcq5cvndrtBv3iWoixKnqbGalubqsNzxLcWXdlLYcw-FSVLBV3fHuPvY9yQKGI2Frf1f6MO4dm0YVmf5QVtL7bNng3qkMCFtpvt6hQc3FxdLpz-xplv)
10. [fxtm.com](https://vertexaisearch.cloud.google.com/grounding-api-redirect/AUZIYQEb40gDyaLwpJbd49W5BN2ztqMLMw6MAT0t5pHD6Hsqbl_26NT3wqBJ7JoOlkBf1PQ0asR4KR02NwYRJkIcVPtXthRMQ5Z4HFEmUJ_AA0mNG3Eknzo3Pw53Qsms7h7uTy3EkbW7eJQRyp1cOGn8y0Y=)
11. [Link](https://vertexaisearch.cloud.google.com/grounding-api-redirect/AUZIYQE3Hhzrmv9Ekrjzq3ztjwuads-mVfydrGwGQCQcTGO-Nm0ynbFg2CrSz30zxI84n_HT0ChWkfxWA1QIUvA3kCBH-A==)
12. [tastylive.com](https://vertexaisearch.cloud.google.com/grounding-api-redirect/AUZIYQGZY8cwP-rTIARnWqT_EDPXp-2yc5laY9sUGR11x0O6wiFQEfD8pa8JEMHJG_ULd2Z3NnPdnlH2kgyg6OpMzSSS9IWg2-zHiNxiERuQ3akOBqGYmpwMAjTV7KLo4TlgmW1-n67H0A2Zp1jZxVETRzDvJdp1)
13. [tradezella.com](https://vertexaisearch.cloud.google.com/grounding-api-redirect/AUZIYQFCIxGk1JcBjVfmdPaAuS1e_le7OF25wXwE6zf3czXGxdCRDCIDKFmK7aesssJb-2nK3UM45pytQFAtcd13s923d7zW7dxoA67vpSx89eAjdjT9oluyluFAfxl5Q5zPyfOyyVz25scK9E4ChsFNn7nSKw==)
14. [adventuresofgreg.com](https://vertexaisearch.cloud.google.com/grounding-api-redirect/AUZIYQF14H4h_MwMHMS0aIBHlJymUK5_mJMCmMfsfvSui6BFviiaROXhq6bZ7Lz8Di8pRceK5P1bQ1WB8ZOM2pt51Y5YADAEH1GJSHASc1zXBcir0qVSCvdt_P9D0vfK0YPEwTSYzztsbUXOPvCz5RA9Ds7ur4oOprPitqQCianiH5-SLwfwC7OvjZQkWkMmDA==)
15. [medium.com](https://vertexaisearch.cloud.google.com/grounding-api-redirect/AUZIYQES-QU-HuVjRxCzUoMeU8OW1sIuu_EmJ78eu9r2YuviZfqXPCV-wUWXSG78mk1eJC-jFdwYud4frNsz19gmn675GD4pbfArw8au2gNxjcTGZgZcs-_WAv5gznSZWDNgFkYeYkQrlkjOn24YfC-VEo8EgsUMaiHbDm6zzfCB9VEMJOtc8tAYXXIr0ayOCD8_Cuy3LEE=)
16. [startrader.com](https://vertexaisearch.cloud.google.com/grounding-api-redirect/AUZIYQEYF9kZ5bMR7r26gTTqTSf-Fub48RpZRaImn_WCHxy-HH_KsZZovnVcE3jwkCoVG6SxWVIsApY78HHn0olDIvzUMBD7HCjloOD8yQIJHVwrrvI2hVTJNSgLEasPY1-BVQgR4NGmN09a_B8IASalgt5FTQUxVmCdmwlccaT5XMolm330ZoEg5OOeAeE482inrPwD6kda1BSm)
17. [groww.in](https://vertexaisearch.cloud.google.com/grounding-api-redirect/AUZIYQEBgbcJI_a4kvm-KESM6qFsT_8U9ExXdX8ISStGeepNHjJsrKDTQCtrx7GhnWqjOjsvDvum3vjnhHNfG1WMWgOUehFEo0R3hbJyD_pMbs5poOHWfpi3yYo8zUuM)
18. [britannica.com](https://vertexaisearch.cloud.google.com/grounding-api-redirect/AUZIYQEoqbgLaT3919PYpM2mxwJkhKLPlVkJ5QRqlWwLOyIrs6hEyP-rBC6QqmEAgV8brpW_pWTs6_cpgJ7Hz4ap2GA-cZfAEJYr7x2SligwZkMX95Pd70z8K6j9SSQuhFArqNSuDNtnC6bdlf5Z00--8EtJ)
19. [lime.co](https://vertexaisearch.cloud.google.com/grounding-api-redirect/AUZIYQFeRDRoRp0TdLFXs8m7sWOTIITqaRhk5kSyg4zyvQPj-4-dyB5kA00c8scq7nX_8-NwnDZkzwETT3B-20NKeoYRktvlLsQtbkIP0dl1VOOPhTMMSXYA8JkEqdNIC5FexMW6vcw4xNlxuzkRt-ykMyplROlyBRuLWKuZvVTbbPGHKe7i8Sv81s-EISQCj5gMZGFjmX24fFY=)
20. [kenmacro.com](https://vertexaisearch.cloud.google.com/grounding-api-redirect/AUZIYQEE0-czeorVKLkB4T0DgMGimvbjkzjnKVGIFwYQUqyyL8DGnHvNpvIeXAbrfAshoIVbPmtAcrblRfiWNg2ab0eZTsyqehO6UqsXLh83vggjTEoJGYTvJPOH8Ul4WbERFRKaXWWA-cfQVaxq)
21. [corporatealliance.com](https://vertexaisearch.cloud.google.com/grounding-api-redirect/AUZIYQEiypYjkZQ023lTfKJrvrSMbaLPh4dg9FEdfL0i56LY5N39lkI-S_HcrB-fldyNfLrGEg81OpPKeoGbhBcthZc8te34s9xoouCDSg-W_iBvb59eW5bD01cQDxLSC54yKOnsnReXzNRErfWWqikXxPcr4-q5Ok_w9wTRVx5mqiksbawhmDrd63mYciu9kvc41n1UFQfILJfWdrx-448F)
22. [brokersreview.co.uk](https://vertexaisearch.cloud.google.com/grounding-api-redirect/AUZIYQF6g8zA1IevKi8A5ohdzOZffEMWpIbHlhNDcbWZg72bis7-9KdvDvjjc_kM7qXFjDQlyelasZrLTs3GUoPGPQXodPlbz4-exymLCqWM4Fw_K6ptD2o38-iGmqa2bfvAVoLIUJtag7SKco1jmayoH6P21-Q7ogQFE0nSvvRyU-3Ay6np3PUaUgQ=)
23. [j2t.com](https://vertexaisearch.cloud.google.com/grounding-api-redirect/AUZIYQGokU1c_OCYU5CmYwJu6X4JIoZXHVpuBlVC-6qgvA_-X3PVSrnCUGGTcbJmD_gx8Za3NGiqufRexzr1iTcbO6qpQM029jy0VFv0LcXWzIls7P9uJS0wFTd5dVP9Eak51PDm5ARMODCAr0Fz)
24. [forexchurch.com](https://vertexaisearch.cloud.google.com/grounding-api-redirect/AUZIYQEAN_hcTTdF8wraPFkHZmzyiKwZtJPWBYi2Hz7RseAbJTwzBbTqoLzHrvD4zutfVahtoAJNLIoQIHuPzD2QUU1uJAevT0pLk4KsjDiFTL5vcKOiPFI6NJG7fHp9ZWMw82UAqHKtYQg=)
25. [skilling.com](https://vertexaisearch.cloud.google.com/grounding-api-redirect/AUZIYQGnuA-Xrj-4_PgJUqwNqxJI8eCQLTWQWqlHgRx7guBt8Kehc2dJz3SCK2bCxZEIZ7e46Q0fCDIwTZNlcBQUfEBXh697Nr4HPkVXuSyVpMFe83gsPj3wEr4VVNzD7DXZ8i8Ux8i8zVBCw8U=)
26. [cms.law](https://vertexaisearch.cloud.google.com/grounding-api-redirect/AUZIYQEw8Z3QUDuEgvRwsok_AZodNGv5UqtupCY19hWa4fW3jofPzBUcEZ33sByg0KXrqiTQ2DT0i7E_NHZJ63BTgavPwjvZI---cfjcU754yOTLvlNI03dJSrtcxeBiGQhjyVZG-4qG6OhmKZ4SMarcew_nRVqzpJy1cWUn6hPKdoRMKDJQz72bhT2_3M23GP70JzsxiYtOsyFuhPSHcNoR-k-74VDzKQZjl6stp-JR4B58K-BXAGnG-HorqxDjjDTjE-P9Lqx-9h3bDTpOc6M=)
27. [asic.gov.au](https://vertexaisearch.cloud.google.com/grounding-api-redirect/AUZIYQFILdXVGkrCsnX1s2GrcIhGBLIXiSnf7Chfu8NnrfphkpxpX11ShQsNAHkKRMiV3Rynn6A_6ugJzIx-QoP6E-PHvxtjHM4eBQ8-rx87XJc5IV7Tna7tkaNLd-frYegOkP4hxjCfR-BYKYfd9NZD91d66IqWivVKHMFyUvo3hiDsshabTln8Fg==)
28. [westlaw.com](https://vertexaisearch.cloud.google.com/grounding-api-redirect/AUZIYQG3PAokW6c5tPESP_yMLM2tFyhKUE7NIlSwto0gExWMtoL_6w9n6h2d_-dEgrxroOzopzs0xP9DN_CRxb6wvLzppzlvh0QSlt2jSL9JvrYPKR04CQ0d2QRmqX5jYwgsS8TWYCw2IfBRM9cjVNGdVDJAfEX-kzBKfAy4-CQYaVnZnLcluuAxsA8HvGGFHbxBaSR13JwhDP3finGZ0oxJY_zlyUe9-DeSPStXOYEYMfPrj3POAyAih_Q02b0-iECwkm8cgGvRrGu_MemfQ6rpzYtR24DrjrhivR1oPicTZFksukbmILsMOAoIoLBAn0mlXBv5EbY-rshlG2e3QZIWYpo8ul0EjbaQScridZ0B0PeDmJ2abyOhj3gIeytL5w==)
29. [financemagnates.com](https://vertexaisearch.cloud.google.com/grounding-api-redirect/AUZIYQHJR47XmmXMF2qn91VRiqgy2AZL9mjDelp2shkQjHJ8JuUs3TrlmfAjh0F9IQBLSrHwe5tmviDKSaShZVIipkrlO3Gyh972H26ut1dEqfaVPeFlp1RT2HyjaDRTda1Lpyw3YLpgh6rMGSZQWSB-T-dAUNIWop8UPNtcw6RYoiwQzfpzPs179IqzVFuShU05fCV-9GqT)
30. [quantinsti.com](https://vertexaisearch.cloud.google.com/grounding-api-redirect/AUZIYQFDEl-CkgDTWf8AJ5-ptVQhpCyJNxeIwT_gpi_23lhicbQWFYcs4MPz0MaEfy0nMiI__-iwLGyFXeyq2PSmGfpsm1yVDV4WfLwiMk81VarFvDHfxcztHZM0NEWwZ2yp8Ni79A==)
31. [tradefundrr.com](https://vertexaisearch.cloud.google.com/grounding-api-redirect/AUZIYQGWatDOFqRciDTRBECbF1GXTVqkYGOcjDvVJP65DPjwM5Dvfy1pyRNcgPf-_-GzRhuiIzVqjMqZpTSW4y_o_rB5giuV9eIpM3PPxmDsrqVFIlmj_lFG0z-wDKnD6n2VwvlWr7rABK4=)
32. [traderspost.io](https://vertexaisearch.cloud.google.com/grounding-api-redirect/AUZIYQEKPCsofu0hLNHgzKe3h8Mw36vO0SiRVmpTuarm-rWsMFtZz3DvBQsjGrMrjRTZNmUYVTDZVKVs7bEDy4aTo3-Ro9LdEj1f_Q4PiExbFDexckMZprFizDHVE1Y4OEEkp82r2vQg0RGfT51J9_zEf7HFgyf5Ew==)
33. [luxalgo.com](https://vertexaisearch.cloud.google.com/grounding-api-redirect/AUZIYQEwv78X0RXWMcaTc4D75fzSoacyOCLe01kyT4YH3MOHO_N1DO7EFMj5ez3BtAV5jtJpBcMI136hRDaBsVGK_2HC2JT8489_eaOCDGvwgcMzvQlvOBCFyeDu5Go4fyJXngOLBGqvoQsauw_fylXN3ng8adh6jcxKTKg8BFg5c2ps3ROiUZsUdiELQgW_POhPT3tlfNHUPAbEhMCcbgkgNg==)
34. [ciro.ca](https://vertexaisearch.cloud.google.com/grounding-api-redirect/AUZIYQHtjlr4yGii1aFoBRihDiUP_BP2wiLfNydJIcg3e4GbFw27KCQSITnJeQGPRkZJVzBTXrYrYdtrmLmcB_5a_-yP62HAig6nNgKJ2hPSxhu0Lqrn-gqYH7VAu7WottUfWV5lOAMrddMPXfQSIVqY_4cVFog1rfxf3NqngFZ26Mg4fRwH5NHW)
35. [ciro.ca](https://vertexaisearch.cloud.google.com/grounding-api-redirect/AUZIYQFt5BxQFrskE2Fvfdxi5RAsqxpmn8mh17wcZ8M3wWrnNK1MHt0YF6HuLpk3AdSV6OXEdvLkuKb3ceEulQWyExKSzGItka4es6f6kit3-m3T2QP2XSNnp-ACZbAJ66vxKrmbupn2RUy2tnBCyu8Wu8eshTqMWsNSGwzzEzh6oomUrYNAiFaP7Do=)
36. [sfc.hk](https://vertexaisearch.cloud.google.com/grounding-api-redirect/AUZIYQGGRf1Spp_UNP8Q46vUXmr829ny2791RpGO56O1gEw9eqVIo0tdl_cmhfbbQpC1hKoyPdC7NI8B7gTXqZBZTdEAOhqOw-WOGgus8SWEtpyVOUzVizw367ANwe-Em_usEKUwTWReteR_bzUo1m7uKpuvEsLJrEGcxbcflV4zE250RDeGYWFd94nqmVsognIYrIUD-BWtQOhjBJE-S57vWBnPn3DNHTmMPEc08x5yd7PyglPl55P-P9Aum0mkdnAkEq2TeOJEeIAcDcaHGXsoIzZ6lXkB09XF54AxKgjrt_Y4ahP9E_8tde4irrD6deF5-yt6uw==)
37. [simmons-simmons.com](https://vertexaisearch.cloud.google.com/grounding-api-redirect/AUZIYQH3scalFF7FEC2phYprJ5z8LybKFZsBjE9UBNEGkw6CFeubf_QQC3nJf3DyfKbGQ6vxKtn7D3klnxx0V3d4KvNzDbYyFIN_ejhZ9HfajK-_NwZv0dWyNKAuoIzH0Sx2tgamWfT8y0cfVRcQccJp_Wb3wbBgc0-4QnD77HFx_sFPwArxlPekxakS2zRFKuKi36ZnRN4FcRU4AahyXoWp4_GsZ1NXlpyfmWUfkxTXf6YFxgMrf7WdUB0B)
38. [sfc.hk](https://vertexaisearch.cloud.google.com/grounding-api-redirect/AUZIYQH04wRzPbjgEsLaWKRGzfsbYj1a3W-dFfoz6pC3H2dW27rwBqwaWoq8CtBn4PHmqmu81d9WFN6sYabguI-S8M20USrhJ-Gbk-fZuzrXR_ZwSB__DUF1iefbdme6c_fJ6Tu5KEvpYJ07jF_mwmw9LmcK4OrvNAPAboJ7yJIxFBF4G-6QWqIIpSA-XSYTyNKcKPmxZ04POXnP0slSBrsM89wX3YQqQe5rUYhMGO2yQD4Ym-fCefzfOuKKUERenJdQnmqGmO_mUlKMsbFBgcmYPenM0D8fYfQlOatE5uR-C68fqrwanMekmosyTMhxAhTqLNRa1XU9hm1YCv0QOZwEbokEuQM=)
39. [sharescope.co.uk](https://vertexaisearch.cloud.google.com/grounding-api-redirect/AUZIYQEu3QPKdxrMZnoP6m_KpErSfLzBYD5LeGy4irxqj6DavA90y0WSu_9H0OVMJYjbqYk78KJpbFtLQUX4gV1LwsqmXVev4q2yMjNuA-t2cgjz-izyUKYh1t-2WmYyfxvY00gfR4m1nHRx5KzcZR97pmYdPqBAA3fu1D9TlaizcqARj6CKLBn7Tg==)
40. [providersandfamilies.com](https://vertexaisearch.cloud.google.com/grounding-api-redirect/AUZIYQGklUSGSdq42dppKzkG1kTBORuail80XEcbTUDkCG6agiZls_AAWQatT3XX_unfGuwBKij_NytmnHRzlIdyc2VGe-RI2Le3v8mEiuG_pm6qNx6x5CPZX20D4sc_vUtUYsJBTbf_iTt87aU_jVuz2fNqFdmZH8ph8IN3yNyqFUQCaqJ3_x_tpezoqG0=)
41. [toptal.com](https://vertexaisearch.cloud.google.com/grounding-api-redirect/AUZIYQFqyftJ7n5WexdLKLh9QL-Iwze2qmulsEd_TVeJHVJdQHwK2Mvak7h8TcIhdRsbZhXnTHZ4InoK4UOlA27vL15Wf5RBr6DlV4xrYDn5ppdaDTLudzuy9C7iaKZZxjPgU8hzprQZfj90xwrZ2SBcC_OqXREr-CHwop_jZCylpFwPd19LmxgKeq5V795rh2eGe7kaqPj3VQxmIPDc5Fc=)
42. [busey.com](https://vertexaisearch.cloud.google.com/grounding-api-redirect/AUZIYQHp-6q-6HH9VCzzzblfzrZm9HsfyiQYDWiOPhOLZpYju6azdiqKKT-HY9grCvW29ffuPh4wAsRidPq9sEaQUpoCYsemSchR6fFaLtA5PmXBkxFLVv4s4ULxCZZiMpwGxs4ngkCiqXqhnlTaIB1JkMqt2niOMC1_dBr_7RaMD_U4UAA1PE5D1TN_3QJ9tY36yg==)
43. [investingforever.com](https://vertexaisearch.cloud.google.com/grounding-api-redirect/AUZIYQFmTi_ysHVBZnBdZH2M4lJPgf-uDHfqXMXpHnXBuQIlm3r_b3Op3Qz5EmiEUmSVlEAt4u9NqxgWSlh2XGHRzFQm6iF8_v6LxdynRtaJDIv6oBVDHu4VKuD785M-b-XLp7fobjdsqoEY8iOu8fSl0--2J78e8GzTQPMLMygl)
44. [jasonapollovoss.com](https://vertexaisearch.cloud.google.com/grounding-api-redirect/AUZIYQGJS2JoT8Noxpi48D8W5qGHy8x3oRLGw_PZ4VNFSoe_HcLZGyrt0b4hmll3tizgv6UL8Ql7UHQ-lRRzsvPqi21P6xREaVWOBz15NJ_bIwNEM7fEnZ7xmR3N35G3ubm3Xr_J8xd8ar4Ehah2SSnzDmw86xDrqmnFM3OPqJ3LIw0w4CsKkJ79GG91IEP5ODCjmNbO)
45. [stlouisfed.org](https://vertexaisearch.cloud.google.com/grounding-api-redirect/AUZIYQGiC0QlgWmMQMIPo8CFF1sCWy16krx8o00TAKtPe_i1W3H2aNn6KZRx1IvfqIMjMUsYx5uY2X2V9qJS0eu3T5GWVbyN6xkc_GuRAVkH7Z-ivYQnzRBKfABtwA6SU-ZBqQXJzeXtnmE83WNiuH1PDnjiPBbKUKcssz8gb1ioxJ6YJ8fWS-rKRjYVclQYw0tbg9Lrew==)
46. [thinknewfound.com](https://vertexaisearch.cloud.google.com/grounding-api-redirect/AUZIYQE5W-GCb9P9OrW9qr5tKHnvWB0f_iJfESQPjyM6z51ZsouVSTLBCi31Jr1QJ1YxZ_9WWMIv30JElQQYktEbYh4bXR5-SEMwmGUGReXp5a7SbRYyrioTDlbwVGQDAbCdSBXx0YahDFepiMM=)
47. [alphametrixx.com](https://vertexaisearch.cloud.google.com/grounding-api-redirect/AUZIYQGLuM9aq44mcT5vzudzex_UIrwRQivCc1Hq-eIsIVGKg7hmGALxBotHFN9qe8K4voBCSpF3BkWyDfFx4DtSEwjlezE_IAqys0YcWlBZ55vfp1c8-nkUVqTg4ZFIwYXBRq-KP7yZgzZ80r60vQ7OaiIYETCCWXD1uNR-XjU=)