Learning how to analyse the financial markets has provided us with invaluable information about:

  • Economic and other events that can affect the financial markets
  • Trading opportunities and how to identify them
  • Price trends and how to describe and verify them  
  • Basic technical indicators which we can use to find price targets
  • Advanced technical indicators which we can use to find trading signals

We use this information to achieve our goal of profitability – our “why” to continue trading.

However, there is something even more important: risk management strategy.

Risk management strategy allows us to know “how” to continue trading. 


Many traders fall into the trap of greed in the beginning of their Forex trading career. 

Trying to capitalise on every price move, they open multiple large positions without limits. 

It doesn’t take too long before they realise that this is not a sustainable trading strategy

We will talk more about basic and advanced trading strategies in Lesson 9

Before that, we must learn: 

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Risk Management in Forex Trading

Our capital might be the heart of our portfolio, pumping blood into our trades. However, risk management is the brain, keeping it alive.  

Risk management is how we protect our portfolio when the market conditions are changing. Real success in trading is defined as creating a sustainable source of income. 

Thus, the quality of the risk management strategy is the true predictor of a successful trader. It is the most important section of our Forex trading plan.


Investing should be more like watching paint dry or watching grass grow. If you want excitement, take $800 and go to Las Vegas.

Paul Samuelson


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Forex markets change due to many factors like social, political, economic, and industrial events. As they shift the risk sentiment, new buy and sell decisions are made and prices rise or fall.

These events are often pre-scheduled, but unforeseen events also occur frequently. Unpredictable events cause investors to make on-the-spot decisions, reducing the predictability of market behaviour. 

Risk management strategy allows us to control for the impact of this unpredictability in the markets and works as a buffer to protect our portfolio when the markets are not working in our favour. 

As a vital part of our trading plan, it encompasses guidelines which can be divided into two main categories:

  • Determining the risks
  • Managing the risks


The market can stay irrational longer than you can stay solvent.

John Maynard Keynes


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How to Determine Risks in the Forex Markets?

Opportunity and risk are the two sides of the same coin. 

Whether a market movement is an opportunity or a risk, it’s based on where our investment is. 

To determine our risks in the Forex markets, we should first understand what risk is to us. Thus, we will personalise the description of risk and define the risk factors for our portfolio.

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What Is a Risk?

Risk in the financial markets refers to the potential of our actual return on investment (ROI) to deviate negatively from the expected return. 

Negative deviations occur when the price action in the market is against our investment.

There are three different types of negative deviations: 

  • A less-than-expected profit
  • A break-even
  • A loss – which can range anywhere from minor setbacks to portfolio wipe-outs 

Unfavourable price actions manifest usually in the wake of a full-scale economic event. Such events shift the investors’ risk sentiment and cause massive reactions. These reactions cause volatility – rapid changes in the speed and intensity of price movement.

Volatility can be assessed in four dimensions: 

  • Direction: Same or reversed 
  • Magnitude: Strong or weak
  • Duration: Transient or persistent
  • Generalisability: Market-specific or markets-wide

As Forex traders, we love volatility because it creates numerous new trading opportunities. However, volatility also creates threat; especially if our portfolio isn’t sure to endure the storm.

The capacity of our positions and portfolio to endure volatility is called risk tolerance. The stronger our risk tolerance is, the better we can resist volatility and sustain our investment. 

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What Are the Risk Factors?

Risk factors are the external and internal elements that cause the negative deviations. 

External elements are beyond our control – like market events and investor sentiment. The interaction of external elements is the underlying cause of market reactions which elicit price fluctuations and shift the markets’ course.

Internal elements are in our grip – like our trading strategy and risk management plan. The integration of internal elements provides us the response strategies which we employ to benefit from or guard against price movements.

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External Risk Factors

Our trading plan outlines the financial assets which will be a part of our Forex trading. The price of each asset can be affected by different external risk factors.  

We should identify our risk factors and classify the level of impact as major, moderate or minor. 

Risk Source External Risk Factors
Economy Monetary policy decisions, interest rates, economic indicators, regulations
Politics Political uncertainties, elections, regional conflicts, wars, natural disasters
Finance Market liquidity, investor risk sentiment, business confidence
Personal Portfolio composition, trading strategy, trading costs, leverage, psychology

The level of impact of each risk factor depends on the asset. For example, an interest rate decision can affect Forex pairs strongly, but not commodities. 

Or if we trade only Oil related assets, our portfolio can be very vulnerable to OPEC decisions.

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Internal Risk Factors

Internal elements of our trading plan outline how we will behave and respond in the markets. Their effectiveness depends on the details, comprehensiveness, diversity, and application.

Since the specifications are subjective, the risk comes from our level of knowledge and skills. 

Risk Source External Risk Factors
Asset Range Including similar assets or diversifying the portfolio
Risk Management Plan Level of detail, analysis methods, tools to employ
Trading Strategies Trading style, trading hours, position sizing, duration, different strategies depending on the asset or market conditions
Psychological Regulation Identifying personal strengths and weaknesses, knowing when to trade and when to not.

Risk aspect of internal elements of the trading plan would be based on two things: 

  1. the degree to which they are relevant to the current conditions in the market, and 
  2. the level of discipline we can demonstrate to stick to our plan. 

We should continuously assess the effectiveness of our trading plan to make sure that:

  • Our trading strategy yields significantly more profits than regular market returns.
  • Our risk management plan is efficient to protect the portfolio from external risks.

In case either one is underperforming, we should review our trading plan and adapt. However, if negative results come from our inability to stick to the plan, we must observe our feelings when trading and take measures to regulate them. 


The trick is not to learn to trust your gut feelings, but rather to discipline yourself to ignore them.

Peter Lynch


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How Risk Management Works?

The process of risk management has three main steps: identification, analysis and mitigation. 

Knowing the risk factors and their impact allows us to focus on the relevant variables. Within this scope, we can:

  • Identify the risks
  • Analyse our risk exposure with various methodologies and tools 
  • Employ relevant strategies to prevent or mitigate them.


The essence of risk management lies in maximizing the areas where we have some control over the outcome while minimizing the areas where we have absolutely no control over the outcome. 

Peter L. Bernstein


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Step 1: Identifying Risk

If we focus on only a few assets, then we can get a clear picture of the risk factors and probable situations. Risks emerge from the market events, and each one has a limited number of outcomes. 

We can study how markets have reacted in past incidences to find patterns and refine our predictions. Using this information, we can create scenarios to know what to expect in the next occurrence. Although exceptions may occur, we would still have a degree of control on potential adversities. 

Example: Interest Rate Decisions

A central bank has only three options in an interest rate decision: hike, cut, or unchanged. At the time of the announcement the investors’ sentiment can be positive, negative, or neutral.

The decision would interact with investors’ sentiment and have nine probable scenarios. Each interest rate decision would be responded to differently in each sentimental environment. Depending on the forecasts and the market conditions, one of these nine scenarios can happen. 

For example, after an interest rate cut: 

  • In normal market conditions, a high-valued currency’s price can drop
  • It can stimulate a stagnant economy, please the markets and raise the currency’s value

We identify such events in advance, match a scenario, and open positions accordingly. If we have counter trend positions, depending on the forecasted magnitude, we can adapt by:

  • Close the positions fully or partially 
  • Reconsider our Stop Loss and Take Profit levels
  • Add more funds to increase available margin. 

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Step 2: Analysing Risk

In step 1, we identified the possible market scenarios which can increase our risk exposure. 

In step 2, we analyse and quantify the risk factors to prepare ourselves to brace the impact. 

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External Risk Factors: Passive Risk and Beta

External risk factors are objective market variables that shift the asset prices. Since we don’t have control over them, we call them passive risks and calculate using beta (ß).

Beta compares an asset to a benchmark in terms of their volatility within a specific time period. Volatility level reveals the degree of price fluctuations. 

  • High volatility: prices are changing more rapidly, increasing both return and risk potentials. 
  • Low volatility: price fluctuations are minimal, a safer investment with smaller returns. 
How to Interpret Beta Value in Forex Risk Management
  • Beta baseline is 1, indicating that the asset and benchmark had the same level of volatility. 
  • If beta value is higher than 1 (ß>1), the asset had higher volatility than the benchmark.
  • If beta value is lower than 1 (ß<1), the asset had lower volatility than the benchmark. 

If the asset had higher volatility than the benchmark (ß > 1), its prices fluctuated more. Thus, this asset, compared to its benchmark, generated stronger but riskier opportunities. 

How to Use Beta in Forex Trading

Let’s say we want to trade AUD/USD and want to know our risk in comparison to its market. 

We choose a benchmark: the U.S. Dollar Index, which measures the performance of major pairs. Then, we choose a time period: last 12 months. Finally, we calculate the beta and find ß = 1.3. 

Conclusion: In the last 12 months, AUD/USD fluctuated 30% more than the U.S. Dollar Index.

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Internal Risk Factors: Active Risk and Alpha

Internal risk factors are subjective trading variables that define our responses to market events. Since we personally decide on them, we call them active risks and calculate using alpha (α).

Alpha compares an asset to a benchmark in terms of their return performance in a time period. Return levels show the profitability of trading a specific asset. 

  • Higher returns: trading this asset was more profitable, and our strategy was effective 
  • Lower returns: the opportunities were limited, and the trading strategy was not effective.
How to Interpret Alpha Value in Forex Risk Management
  • Alpha baseline is 0, indicating that the asset and the benchmark had the same return level. 
  • If alpha value is positive (α>0), the asset had higher returns than the benchmark.
  • If alpha value is negative (α<0), the asset had lower returns than the benchmark.
How to Use Alpha in Forex Trading

Let’s say, we are trading BHP Billiton stocks and wonder if our returns will be larger than market. 

We first choose a benchmark: S&P/ASX 200 index. Then, we choose a time period: last 12 months. Finally, we calculate the alpha and find α = 0.55.

Conclusion: In the last 12 months, trading BHP Billiton stocks returned 55% more than the ASX.

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Calculating Beta and Alpha

Beta and Alpha compare an asset to a benchmark to reveal risk and return differences. The calculations are as follows:

Beta (ß)

ß = Covariance (Rm, Re) / Variance (Rm) 

  • Rm: Market return % – the return % of the chosen benchmark in a time period
  • Re: Equity return % – the return % of the chosen asset in a time period

Step by step Beta calculation:

  1. We calculate the covariance (correlation) between the return percentages.
  2. Divide the covariance to the variance of the benchmark’s return percentage. 
  3. The variance of the asset’s return percentage gets isolated and reveals volatility.

Alpha (α) 

α = Rp – [Rf + ß(Rm – Rf)]

  • Rp: Portfolio return % – the return % of the entire portfolio in a time period
  • Rf: Risk-free return % – the return % of a low-risk investment option like bonds
  • Rm: Market return % – the return % of the chosen benchmark in a time period

Step by step Alpha calculation:

  1. Isolate the benchmark’s performance by subtracting the return of the low-risk investment.
  2. Multiply the difference with ß to adjust it to the asset with ß. 
  3. Then we add the adjusted value to the risk-free return.
  4. Subtract it from our portfolio return to understand the effectiveness of trading this asset.

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Combining Active and Passive Risk Analysis

Active and passive risk analysis informs us whether an asset’s profitability is worth its risk. Based on our conclusions, we can decide whether trading a specific asset is worthwhile or not.

Alpha Beta Conclusion
High (α > 0) High (ß > 1) More profit, more risk
High (α > 0) Low (ß < 1) More profit, less risk
Low (α < 0) High (ß > 1) Less profit, more risk
Low (α < 0) Low (ß < 1) Less profit, less risk
How to Use Alpha and Beta in Forex Trading

Let’s say Apple launched a new iPhone, and we expect Apple stocks to rise in the next 30 days. We can estimate risk and return of trading Apple stocks using α and ß in previous 30 days.

We choose NASDAQ 100 tech index as a benchmark and 1-Year U.S. Bond as low-risk investment.

Let’s say that in the past 30 days:

  • Market Return (Rm) was 10% for the NASDAQ 100 Index
  • Equity Return (Re) was 18% for Apple stocks
  • Risk-free Return (Rf) was 1% for 1-Year U.S. Treasury Note
  • Portfolio Return (Rp) was 12% for our trading portfolio

We start by calculating Beta (ß) first:

  1. Let’s say that the price covariance of Apple stocks and NASDAQ 100 futures was 80% (0.8).
  2. NASDAQ 100 Index had a price variance of 2% (0.2). 
  3. We divide asset-benchmark covariance to benchmark variance and find ß = 40% (0.4). 

Then, we calculate Alpha (α):

  1. We subtract risk-free return from the benchmark return, and multiply it with ß. 
  2. We add the risk-free return to adjust it to the asset risk.
  3. We subtract it from the portfolio return to find the asset return in 30-day period.

Interpreting the alpha and beta values, we can conclude that in the last 30 days: 

  • Apple stocks had 60% less volatility than the NASDAQ 100 Index
  • Apple stocks had 7.4% more return than the NASDAQ 100 Index. 

Thus, Apple stocks brought more profits with lower risk and can be a worthwhile investment.

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Improving Active and Passive Risk Analysis

We use active and passive risks to quantify the potential return and risk of an investment. However, the accuracy of our analysis can be compromised by outlier market events.

In order to control for the variance caused by such outliers, we can refine our analysis by using:

Corresponding Time Frames

In our example, we had analysed Apple stocks in the 30 days prior to the launch of the new iPhone.

Instead, we can take the 30-day period after the previous product launch as a reference. Calculating its α and ß, we can understand better how Apple stocks react to new iPhones.

Multiple Time Frames

The analysis can be further improved by including several previous launches. We can calculate their individual α and ß values, and then average them. The resulting α and ß can give us a post-launch behaviour pattern in Apple stocks.

However, market conditions for each time period may be different. To control for this, we can assign weights to each period and calculated weighted averages.

Confidence Interval

Another way to improve our prediction is to use a confidence interval (CI). We can calculate standard deviations (SD) of α and ß and establish a CI for each of them.

In accordance with normal distributions theory, we can suggest that: 

  • With 67% confidence, α and ß will be within 1 positive SD and 1 negative SD after launch. 
  • With 95% confidence, α and ß will be within 2 positive SD and 2 negative SD after launch.

Let’s say we found average α as 8% and alpha SD as 0.5%. 

We can predict that the post-launch 30-day α would be:

  • Between 7.5% and 8.5% (with 67% confidence)
  • Between 7% and 9% (with 95% confidence).

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Step 3: Mitigating Risk

We can decide on our risk management strategy only after we analyse our risk exposure. Market behaviour is out of our control, but how we will respond to them is up to us. 

Volatility and performance predictions inform us about what to expect in a specific time period. Using these, we can employ different risk mitigation tools and prevent unwanted outcomes.


Throughout my financial career, I have continually witnessed examples of other people that I have known being ruined by a failure to respect risk. 

If you don’t take a hard look at risk, it will take you.

Larry Hite


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Risk Tolerance

Risk tolerance is our endurance to suffer losses the markets are working against us. 

There are two types of risk tolerance: of the total portfolio and of a position. 

Portfolio Risk Tolerance

The portfolio’s risk tolerance is determined by the available margin in any given time. In Forex trading, leverage allows us to allocate only a small margin of our capital to a position.

The remaining available margin carries the load of the floating profit/loss of all open positions. When the losses become too big to sustain, we can get margin call from our broker.

Margin call is the automatic closure of our open positions, due to insufficient available margin.

Position Risk Tolerance

A position’s risk tolerance is based on the maximum loss limit we assign to the position. A position we opened can suffer losses due to market volatility before it moves in our favour.

Such adverse movements can turn out to be too large or prolonged for our portfolio to endure. In this case, we must exit the position in a timely fashion and cut the losses. 

Otherwise, we would be stuck with a losing position and might incur further damage. 

There are three primary components to consider when determining risk tolerance level: 

  • Position size & pip value
  • Risk/reward ratio (RRR)
  • Take profit & stop loss levels. 


I know this will sound like a cliché, but the single most important reason that people lose money in the financial markets is that they don’t cut their losses short.

Victor Sperandeo


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Position Size & Pip Value

Position sizing refers to the percentage of capital which we allocate as margin to each position. It also determines the pip value of a position. 

Most successful traders employ 1%-3% Rule as their position sizing strategy:

  • Maximum margin per position must be limited to 1% of total capital.
  • Maximum margin usage across all positions must be limited to 3% of total capital.

If we have $100,000 capital in our account, our total margin usage must not exceed $3,000. 

When we have no open positions, the margin usage of our next trade can be up to $1,000. 

How to apply Position Sizing rule

Let’s say our broker offers 400:1 leverage in GBP/USD currency pair. 

We can open Buy position in GBP/USD with a size up to 400,000 and have $40 pip value. 

Subsequent positions should also apply the 1% limit and must not exceed 3% of total capital. 

However, we are not required to open all positions with the maximum limit.

Key factors when choosing a Position Size

  • Goal – the amount we want to earn
  • Pip value – determining the speed of profits and losses
  • Asset type – each asset has different pip value with same margin usage
  • Volatility – price volatility of the asset and the market
  • Sentiment – current market conditions and expected events

Position Sizing in Different Markets

Assets in the highly volatile markets often experience large-scale price fluctuations. Thus, small position sizes can still bring significant profits while keeping the risk level low. We should set a profit goal before we open the position and strive to find the optimal pip value. 

For instance, if we are interested in earning $500 in the GBP/USD position with $40 pip value:

  • We need only 13 pips movement to achieve the profit target.
  • But, if GBP/USD drops 30 pips, we will have $1,200 loss and have to wait until it recovers. 

On the other hand, if we had kept our position size at 250,000 with $25 pip value:

  • We would have needed 20 pips movement to gain $500. 
  • If the currency pair had dropped 30 pips, our floating loss would be only $750. 

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Risk/Reward Ratio (RRR)

High winrate in trading doesn’t necessarily translate into earnings. We can accumulate small profits, but one big loss can wipe out all of it. 

The number of winning trades required to be profitable is based on the Risk/Reward Ratio. RRR is the ratio between the expected return and the potential risk of a position. 

It can be calculated in terms of pips or amount. 

Risk/Reward Ratio Required Winrate
1:3 25%
1:2 33%
1:1.5 40%
1:1 50%
1:0.7 60%
1:0.3 70%

For instance, if we our global RRR is 1:2, we need to close only 33% of our positions at profit. This ratio would apply specifically when setting Stop Loss and Take Profit targets. If we set our Take Profit level at 40 pips, then we set our Stop Loss level at 20 pips.

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Take Profit & Stop Loss

Before we trade an asset, we should analyse its trend and estimate how many pips it can move. Then, we should determine how much we are looking to earn. 

Dividing the profit goal to the potential number of pips, we can calculate the required pip value. 

Calculating Take Profit and Stop Loss Targets

Let’s say we expect AUD/USD to increase by 50 pips, and we want to earn $1,000 in this trade. 

Our pip value is going to be ($1,000) / (50 pips) = $20. 

So, position size must be 200,000 (2 Lots), which require $500 margin with 400:1 leverage. 

With RRR of 1:2, we set 50 pips Take Profit to earn $1,000 and 25 pips Stop Loss to risk $500. 

Improving Take Profit and Stop Loss Efficiency

Deviations from expectations occur regardless of the quality of analysis and risk management. For example, AUD/USD might move 46 pips instead of 50 pips and then recover.

In this case, our TP wouldn’t be activated, and we may miss the chance to consolidate profits. We can improve our chances by setting TP at a slightly lower level than the expected maximum. 

As a result, we either sacrifice some profits or increase our pip value to maintain profit goal. For example, for the AUD/USD trade above, we can set 40 pips TP and 20 pips SL to earn

  • $800 profit by risking $400, using the same position size, margin, and pip value
  • $1,000 profit by risking $500, but with 250,000 position size, $625 margin and $25 pip value

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Portfolio Diversification

You probably heard the phrase “don’t put all your eggs in one basket” before. Distributing investments across assets and markets is a very common risk management strategy.

If we trade only one market and similar assets, we are vulnerable to a single type of risk factor. Hence, we diversify our portfolio and reduce our exposure to this type of risk. 

Portfolio diversification strategy has three rules:

  • Limiting the number of positively correlated assets
  • Adding negatively correlated assets to hedge main assets of interest
  • Dividing the portfolio to uncorrelated asset categories

However, too much diversification would divide our attention and lead us astray. Finding the perfect balance using the assets we know can prove very effective.


Wide diversification is only required when

investors do not understand what they are doing.

Warren Buffett


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Positive Correlation

When two assets move in the same direction after an event, they are positively correlated. Trading positively correlated assets can yield high profits when our prediction is correct. However, losses can also accumulate rapidly if we are on the wrong side of the market.

Example: Forex Trading With Positively Correlated Assets

For example, AUD/USD and NZD/USD are strongly correlated due to regional proximity and USD.

When USD gains or loses value after an event, two pairs react at similar speeds and magnitudes. If our prediction is correct, we would earn both from AUD/USD and NZD/USD.

However, in the opposite scenario, both positions would be losing and depleting our resources.

AUD/USD & USD/CAD Positive Correlation - Risk Management with CFD Trading
AUD/USD & USD/CAD Positive Correlation
Example: CFD Trading With Positively Correlated Assets

Another example of high positive correlation is found in the Oil market. Crude Oil prices have high positive correlation with: 

  • The stocks of Oil companies like ExxonMobil 
  • The currencies of Oil-producing countries like Canadian Dollar (CAD)
  • They are also moderately correlated with each other

Thus, any Oil market event that like production cut by OPEC, influence the prices of these assets. If we trade only Oil-related asset CFDs, our portfolio would be very vulnerable to such events. While it could yield large profits, any adverse price action could compromise our portfolio. 

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Negative Correlation

When two assets move in the opposite direction after an event, they are negatively correlated. Trading negatively correlated assets with a single event can be a profitable trading strategy.

If the US interest rates will rise, selling AUD/USD and buying USD/JPY can make double profits.

However, like in positive correlations, wrong predictions can lead to multiple losing positions.

AUD/USD & USD/CAD Negative Correlation - Risk Management with CFD Trading
AUD/USD & USD/CAD Negative Correlation
Hedging With Negatively Correlated Assets

Negative correlation is often used as a hedging strategy for the main trading position. For example, we can open Sell positions both on AUD/USD and USD/JPY.

Since they are negatively correlated, they will move in opposite directions after a USD event. As a result, one will generate profit and the other will generate loss. If we set our TP and SL levels properly, the hedge position can insure the main position. 

Example: Forex Trading With Negatively Correlated Assets

For example, if the Fed were to raise interest rates, we can predict USD to rise and AUD/USD to fall.

With a 1:2 RRR, we can open a Sell position on AUD/USD and set TP at 40 pips and SL at 20 pips. 

We can hedge this position by Selling USD/JPY and setting our TP and SL levels at 20 pips both. 

  • If Fed raises the interest rates, we will have 20 pips net profit.
    • AUD/USD will fall and hit 40 pips TP 
    • USD/JPY will rise and hit 20 pips SL
  • If Fed does not raise the interest rates, we will breakeven and lose only the spread.
    • AUD/USD can rise and hit 20 pips SL
    • USD/JPY can fall and hit 20 pips TP 

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Low or No Correlation

While no correlation is mathematically possible, practically it exists as low correlations. 

When two assets are affected by different factors, their prices would have low correlation. By dividing our capital to unrelated assets, we can limit our risk exposure in a particular market. As such, a single market event that affects one asset type won’t threat our entire portfolio.

However, comprising our portfolio from unrelated assets can have its own disadvantages. Our success largely depends on the time and effort we spend to learn the nature of our assets. The more we diversify, the more we will have to divide our attention to study unrelated factors. Thus, we should limit diversification to maximum 2-3 markets, and include only 4-5 assets each.

Low or No Correlation - Risk Management with CFD Trading
Low or No Correlation

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Hedging Strategies

Hedging is a trading strategy which is utilised specifically as a risk management method. We hedge by opening another position in the opposite direction of the main position.

If our prediction for a main position was wrong, the losses would be covered by the hedge profits. As explained earlier, we can use negatively correlated assets to the hedge our positions.

It’s also possible to hedge by opening a position in the opposite direction with the same asset. The main position’s RRR must be larger than the hedge position’s RRR to remain profitable.