Master Risk Management: 7 Steps to Protect Your Success

Economic

Summary:

Learn how to effectively manage risk with these seven essential steps. From identifying potential hazards to implementing safeguards, ensure the safety of your ventures and investments.

Risk is an inevitable part of any personal, professional, or financial endeavor. While it cannot be entirely eliminated, it can be managed effectively to minimize potential downsides. Risk management ensures that you are prepared for uncertainties, protecting your resources and goals. This article outlines a practical 7-step guide to managing risk and maintaining control over unpredictable situations.

Step 1: Identify the Risks

The first step to managing risk is recognizing it. Risks can stem from various areas, including market fluctuations, operational mishaps, or unforeseen circumstances.

How to Identify Risks

Brainstorming: Gather your team or use personal reflection to list potential threats.

Historical Data: Analyze past projects or ventures to identify common issues.

Industry Analysis: Review risks inherent to your sector or activity.

Example: A financial trader may face risks from market volatility, while a business might encounter risks in supply chain disruptions.

Step 2: Assess the Risks

Once identified, assess each risk based on two factors: likelihood and impact.

Tools to Assess Risk

Risk Matrix: Plot risks on a matrix to visualize which are high, medium, or low priority.

Quantitative Analysis: Assign numerical probabilities to risks and potential losses.

Example: A high-probability, high-impact risk (e.g., a key supplier going bankrupt) should be prioritized over a low-probability, low-impact risk.

Step 3: Prioritize Risks

Not all risks are equally urgent. Focus your resources on those that could cause the most damage.

Criteria for Prioritization:

Critical Risks: High-impact events that are likely to occur.

Moderate Risks: Manageable risks with moderate impacts or low probabilities.

Low Risks: Risks that require minimal attention but should still be monitored.

Tip: Use the Pareto Principle—address the 20% of risks that could lead to 80% of the issues.

Step 4: Develop Risk Mitigation Strategies

Create plans to reduce the likelihood or impact of risks. These strategies may include preventive measures or contingency plans.

Mitigation Methods:

Avoidance: Eliminate the activity causing the risk.

Reduction: Implement measures to lower risk exposure.

Transfer: Use insurance or contracts to shift risk to a third party.

Acceptance: Recognize and prepare for risks that cannot be avoided.

Example: A company may reduce cybersecurity risks by investing in robust firewall protection and employee training.

Step 5: Implement Safeguards

Put your risk mitigation strategies into action. Ensure every plan is communicated clearly to all stakeholders involved.

Examples of Safeguards:

Financial Safeguards: Maintain emergency funds or set stop-loss orders in trading.

Operational Safeguards: Install safety protocols and train staff to follow them.

Tip: Use project management tools to track the progress and implementation of safeguards.

Step 6: Monitor and Review

Risks evolve, and so should your strategies. Regularly monitor your environment and adjust your plans as needed.

How to Monitor Effectively:

Key Risk Indicators (KRIs): Use metrics to signal changes in risk levels.

Regular Audits: Periodically review strategies and their effectiveness.

Feedback Loops: Collect input from stakeholders to improve processes.

Step 7: Plan for Recovery

Despite your best efforts, some risks may materialize. A recovery plan ensures minimal disruption and swift resolution.

Elements of a Recovery Plan:

Crisis Communication: Keep all stakeholders informed during a risk event.

Contingency Funds: Reserve resources to manage unexpected costs.

Resilience Measures: Build adaptability into your processes to bounce back quickly.

Example: Companies often establish disaster recovery plans to restore operations after a natural disaster.

Conclusion

Risk management is a continuous process that protects your goals and ensures resilience against uncertainties. By following these seven steps—identifying, assessing, prioritizing, mitigating, implementing, monitoring, and planning for recovery—you can minimize risks and position yourself for sustained success.

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Risk Warnings and Disclaimers

You understand and acknowledge that there is a high degree of risk involved in trading. Following any strategies or investment methods may lead to potential losses. The content on the site is provided by our contributors and analysts for information purposes only. You are solely responsible for determining whether any trading assets, securities, strategy, or any other product is suitable for investing based on your own investment objectives and financial situation.

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Glendon

Economic

Drawdown is a critical concept in forex trading, directly linked to the performance and risk management of a trading account. Understanding drawdown helps traders evaluate their risk tolerance and adapt strategies for long-term success. Whether you’re a seasoned trader or a beginner, mastering the nuances of drawdown can mean the difference between sustained profits and financial setbacks.

What is Drawdown?

Drawdown in forex trading refers to the reduction in the capital of a trading account, measured as the difference between the account's highest point (peak) and its subsequent lowest point (trough). It is typically expressed as a percentage of the peak balance.

Types of Drawdown:

Absolute Drawdown: The difference between the initial account balance and the lowest point reached.

Example: Starting with $10,000, if your account drops to $9,000, the absolute drawdown is $1,000.

Relative Drawdown: A percentage that shows the account's maximum loss compared to its peak balance.

Example: If your account peaks at $20,000 and drops to $15,000, the relative drawdown is 25%.

Maximum Drawdown: The largest observed drop from a peak to a trough during the account's lifetime.

Significance: Used as a benchmark for evaluating a trader’s risk tolerance and strategy robustness.

Why is Drawdown Important in Forex?

Drawdown highlights the risk exposure and recovery requirements for a trading account. It serves as a key metric for evaluating trading performance and psychological resilience.

Impacts of Drawdown:

Capital Management: Excessive drawdowns can deplete account balances, reducing trading opportunities.

Psychological Pressure: Large drawdowns can cause emotional stress, leading to impulsive decisions or abandoning strategies.

Recovery Challenge: Higher drawdowns require exponential gains for recovery.

For instance: A 10% drawdown requires an 11.1% gain to recover.

A 50% drawdown demands a 100% gain.

Key Insight: Limiting drawdowns is essential to maintaining consistent trading momentum.

How to Manage Drawdown in Forex Trading

Managing drawdowns involves combining robust risk management techniques with disciplined trading.

1. Use Proper Position Sizing:

Trade only with an amount that aligns with your risk tolerance. Typically, traders risk 1-2% of their account per trade.

2. Apply Stop-Loss Orders:

Set stop-loss levels to cap potential losses and safeguard against excessive drawdowns.

3. Diversify Your Trades:

Avoid over-concentration by spreading your investments across different currency pairs or trading strategies.

4. Monitor Risk-to-Reward Ratios:

Aim for trades with a favorable risk-to-reward ratio, such as 1:2 or higher. This ensures potential gains outweigh possible losses.

5. Limit Leverage Usage:

While leverage amplifies gains, it also magnifies losses. Use it cautiously to avoid significant drawdowns.

6. Review and Adjust Strategies:

Regularly assess your trading approach to identify weaknesses and adjust for market conditions.

Recovering from Drawdowns

While minimizing drawdowns is ideal, recovery is equally important.

Steps for Recovery:

Pause Trading:

Analyze the reasons for the drawdown without rushing into new trades.

Reassess Your Strategy:

Identify and rectify flaws in your trading plan.

Reduce Position Sizes:

Trade smaller volumes to rebuild confidence and account balance.

Focus on Consistency:

Prioritize steady gains over risky, high-return trades.

Pro Tip: Recovery is a gradual process; patience is key to avoiding compounding losses.

Examples of Drawdown Scenarios

Scenario 1: Conservative Trader

Peak Balance: $10,000Drawdown: 5% ($500)

Recovery Required: 5.3%

Scenario 2: Aggressive Trader

Peak Balance: $10,000Drawdown: 50% ($5,000)

Recovery Required: 100%

Conservative strategies often outperform aggressive ones in sustaining long-term profitability.

Conclusion

Drawdown is more than just a financial metric—it is a reflection of trading discipline and risk management capabilities. By understanding, managing, and recovering from drawdowns, traders can safeguard their capital and build a sustainable trading career. Whether you are trading forex as a hobby or a profession, keeping drawdowns under control is paramount to achieving long-term success.

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Warren Takunda

Economic

Businesses are bracing for the economic impact of a second Trump presidency, which, if his campaign promises are to be believed, will mean tariffs across nearly all imports to the US, especially those from China.

But amid the gloom over the spectre of a renewed global trade war, some manufacturers may be looking to those who already have a playbook on dealing with aggressive US levies, such as China’s solar companies.

China all but owns the global solar market. Its share in every stage of the solar panel manufacturing chain exceeds 80%, according to the International Energy Agency. Last year it exported a record high of 227 gigawatts (GW) of solar panels – more than the entire installed solar capacity of the United States.

But virtually none of those panels were destined for the US. Less than 1% of the 54 GW of solar panels the US imported last year came from China.

More than a decade of US duties on Chinese solar cells and panels – which are expected to be ramped up further by Trump – have all but eliminated Chinese solar equipment from the US.

This has spurred some Chinese companies to rapidly shift and expand their supply chains overseas in what US government agencies allege is an attempt to dodge US levies – an alleged approach that may be setting an example for other manufacturers.

Because although less than 1% of the US’s solar imports come from China, more than 80% of them come from four countries in south-east Asia: Cambodia, Malaysia, Thailand and Vietnam. Last year, the US Commerce Department concluded that certain Chinese photovoltaic (PV) companies had been re-routing their supply chains through those countries in order to avoid US tariffs.

China’s major PV technology companies have been opening factories in south-east Asia since at least 2016. That year, the world’s third-largest solar manufacturer, Longi, expanded to Malaysia with its first overseas production base, and the launch of a Thai subsidiary. It also has a facility in Vietnam, and this year began construction of another Malaysian project and a joint-venture factory in the US. “The company’s shipment capabilities in the US market are expected to be enhanced,” it said in its 2023 annual report.

In 2022, Longi denied findings by the US Department of Commerce that a Vietnam subsidiary, Vina Solar, was among a number of Chinese companies circumventing tariffs by finishing products in south-east Asia, and said it was obeying US law.

But decision-makers in Washington see the expansions into south-east Asia very specifically as “an attempt to circumvent antidumping and countervailing duties”, said Cory Combs, associate director at Trivium China, a research company.

Longi denied the commerce department’s findings in 2022, and in its interim annual report this year said the “trade barriers” imposed on PV producers had “increased uncertainty” for companies, appearing to suggest that the global expansions were aimed at diversifying supply chains.

Last month, the commerce department announced new preliminary duties on several Chinese solar manufacturers that were exporting from Cambodia, Malaysia, Thailand and Vietnam. The decision follows a complaint from US solar panel companies that alleged Chinese companies were using their factories in those four countries to flood the US market with panels priced below their cost of production.

Longi was not among the solar manufacturers on the list, and it is not clear if the list includes one of its subsidiaries. Longi did not respond to repeated requests for clarification or comment.

Various US tariffs and antidumping duties have since been levied on the industry in the region at either country or company level, or in some cases both, and eyes are on the movements of Chinese industries.

Speaking generally, tariffs “are a bit like whack-a-mole”, said Marius Mordal Bakke, a senior analyst at Rystad Energy, a business intelligence company. As soon as import duties are targeted at one country, companies will up sticks and move to another. Rerouting supply chains costs money, “but as long as you can sell your product for three to four times as much in the US market, then it’s probably likely worth it.”

Next stop: the Middle East

The game of whack-a-mole now seems to be spreading to other parts of south-east Asia, such as Laos and Indonesia. In the first eight months of this year, US imports of solar goods from Indonesia reportedly nearly doubled to $246m, while shipments from Laos have also been surging.

The industry is also moving to the Middle East, said Combs.

“As south-east Asia gets hit harder and harder by these tariffs a lot of Chinese investors are moving into the [Gulf Cooperation Council, or GCC], particularly Saudi Arabia and the UAE and Oman. Does this happen quickly enough that the GCC becomes the next south-east Asia and then also gets hit with anti dumping and all that stuff? That’s already where the conversation is in DC.”

Chinese companies are well aware of the need to tariff-proof their businesses, and there are signs of plans being made to get ahead of Trump’s promised tariffs, on China and elsewhere.

Tongwei, China’s biggest solar company, said in its annual report that many Chinese photovoltaic companies have “started exploring new avenues for growth, including establishing manufacturing facilities overseas”, citing the US, the Middle East and Vietnam as examples, without elaborating on the company’s own plans.

The US solar market is relatively small. In 2023, it accounted for less than 10% of the solar panel global market, according to analysis by Lauri Myllyvirta, the lead analyst at the Centre for Research on Energy and Clean Air. Given over 93% of global production capacity for polysillicon – the raw material to make solar panels – is in China, it will be nearly impossible for the US solar industry to fully extricate itself from Chinese companies.

Indeed, the biggest risk to the Chinese solar industry from the incoming Trump administration may not be tariffs, but politics. “The solar industry in China has positioned itself to supply the solar equipment needed for a rapid global energy transition,” Myllyvirta said. “And it’s quite clear that the Trump administration is going to try and slow down that transition”.

Source: TheGuardian

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ING

Economic

Bunds in demand as Ukraine faces uncertain times

Over the past month, markets have rapidly adjusted to the realities of post-QE and QT. This is most evident in Bund swap spreads, but similar trends were also seen in the USD/EUR cross-currency basis, which has shared the same pattern as risk-premia into the looming year-end was reassessed. The shared trends suggest that concerns about German credit amid political instability were less influential, though they likely contributed to the overall movement.

Tuesday’s market reaction to headlines pointing to an escalation in the Ukraine conflict showed that the risk-off reflexes are still working. Bunds were the main recipient of safe-haven flows, outperforming other European government bonds with the 10y initially outperforming versus swaps by almost 4bp. The 10Y yield still sits slightly above swaps and time will tell how lasting the move will be or whether it is seen as an opportunity to jump back on the Bund underperformance trade. So far, the spread performance has been more resilient than the immediate reaction to headlines. However, recent history has shown that Bunds have had a weaker and shorter-lived response to risk-off events, such as the French election turmoil.

We still think that the levels broadly around 5bp above swaps could mark an equilibrium around which 10y Bund spreads evolve with risk-off episodes and supply as well as political turmoil continuing to add volatility. Recall that the equivalent spread of around 20bp above OIS was last observed in 2014 ahead of the European Central Bank's QE.

Today’s events and market view

UK October CPI data this morning came in hotter than expected with services inflation at 5% year-on-year and core CPI at 3.3% versus an estimated 3.1%. However, leaving out categories the Bank has told us it cares less about, our economist calculates that this "core-services" measure fell from 4.8% to 4.5%.

The data calendar remains lighter after the release of the UK CPI in the morning, although the ECB will release its indicator for negotiated wages in the third quarter today. A rise here, mainly given developments in Germany, is likely to garner some headlines amid markets that have become a tad more cautious about pricing aggressive easing from the ECB. We still think Friday’s PMIs will be key. Also look out for more commentary from ECB members, including de Guindos and Stournaras, while the ECB will also release its Financial Stability Review.

In primary markets, Germany will tap two bonds in the 30Y part of the curve for €1bn each. Later the US Treasury will sell a new 20Y bond for US$16bn.

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Warren Takunda

Cryptocurrency

Bitcoin’s potential climb to the $100,000 price level has captivated investors for years. While retail participants often celebrate such psychological milestones, the key impact should come from institutional adoption and advancements in the Bitcoin derivatives markets. Bitcoin to $100K: What Will Milestone Mean for Derivatives Markets?_1

Bitcoin to $100K: What Will Milestone Mean for Derivatives Markets?_1

Bitcoin futures aggregate open interest, BTC. Source: CoinGlass

Futures open interest on Bitcoin presently totals 626,520 BTC ($58 billion), a 15% increase in two months, signaling growing interest in derivatives. If Bitcoin reaches $100,000, this open interest would hit $62.5 billion, representing 3.1% of its $2 trillion market cap. This contrasts with the S&P 500, where $817 billion in futures open interest equals only 1.9% of its $43 trillion market cap.

A direct comparison between Bitcoin and S&P 500 futures is unfair, as over 65% of the cryptocurrency trading occurs on crypto-only exchanges such as Binance, OKX and Deribit. This number is expected to reduce as spot Bitcoin exchange-traded funds (ETFs) eventually launch their own futures markets, especially those offering in-kind creation that appeal to institutional investors.

However, regulation alone doesn’t guarantee adoption. For example, the CBOE offered Bitcoin futures from December 2017 to March 2019, only to discontinue the product due to low demand. Recent approvals for spot Bitcoin ETF options signal progress but underscore the need for deeper integration with traditional finance markets.

Institutional adoption: The key to $100,000 and higher

Institutional adoption is critical to translating Bitcoin's $100,000 milestone into meaningful derivatives market growth. Spot ETF options, for instance, could enable complex strategies like income generation through covered calls or hedging liquidity risks. As institutions grow more comfortable with Bitcoin as a reserve asset, the derivatives market will likely evolve to accommodate their sophisticated needs. Bitcoin to $100K: What Will Milestone Mean for Derivatives Markets?_2

Bitcoin to $100K: What Will Milestone Mean for Derivatives Markets?_2

Example of covered call expected return. Source: CME

Futures markets often confuse newcomers, particularly regarding the short positions. Many assume these positions signal bearish sentiment, but that’s not always the case. Strategies like cash and carry, where investors lock in a risk-free profit by selling futures while holding spot Bitcoin, create a large volume of short contracts. These strategies stabilize the market rather than betting on price declines.

A potential game-changing catalyst for Bitcoin's price surge could come from a shift in corporate governance. Microsoft shareholders recently voted to allocate funds toward Bitcoin, signaling a significant display of intention by influential investors. Even if the plans are not approved in 2025 or are disregarded by the board, the mere act of voting on Bitcoin allocation creates momentum that could pressure other companies to follow suit.

Additionally, Senator Cynthia Lummis’ proposal to convert US Treasury gold certificates into Bitcoin and create a “Strategic Bitcoin Reserve” offers another price catalyst. Her bill includes plans to acquire 5% of the total Bitcoin supply—1 million BTC—to be held for 20 years, further cementing Bitcoin’s potential as a reserve asset.

Bitcoin derivatives markets are a consequence, not a cause

Despite the excitement surrounding Bitcoin’s march toward $100,000, derivatives markets are more likely to react to broader adoption than drive it. Retail and corporate fears of fiat debasement remain the primary motivators pushing Bitcoin higher. This psychological shift—more than any futures product or spot ETF—will ultimately solidify Bitcoin’s role in institutional portfolios.

Lyn Alden’s research reinforces this narrative, showing a correlation between the global M2 money supply and Bitcoin's price. When governments accelerate monetary stimulus or reduce interest rates, investors increasingly seek scarce assets like Bitcoin as a hedge against debasement.

As a result, a liquid and mature derivatives market will emerge as a consequence, not a cause, of Bitcoin’s price breakthroughs.

Source: Cointelegraph

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UBS

Economic

Diversification is the beating heart of any multi-asset portfolio. Assets that have low or negative correlation move in different directions and help smooth overall returns; one part of a portfolio offsets and provides ballast against others. Understanding correlations is therefore essential.

From 1950 to 2000 US Treasuries were positively correlated with equities – only for that to flip negative for the next 20 years. Recently, the relationship has turned positive again.

A number of questions flow from this. Is there something about the current regime that means historical correlation relationships will continue to break down? If so, what does this mean for asset allocation? And is achieving natural diversification going to get harder?

In the case of the latter, there are many reasons to believe it might be. From rising geopolitical tensions, extreme US debt levels, demographic reversals with structural implications for higher inflation, and the move to a more multi-polar world order (one perhaps less reliant on the US dollar), there are several seismic shifts happening.

Before conjecturing on what this might mean for portfolio diversification and while also acknowledging that the past is not prologue, we crunched the data in search of asset correlations lessons at various stages of the market cycle. The results confirm that the relationship between ’risk assets’ and ’safe assets’ is not linear.

Non-linear correlations

We analyzed monthly data for a variety of indexes in listed assets between August 1994 and September 2024; for robustness, we also looked at the wider range of index returns at the weekly data frequency, although for a shorter period due to data limitations.

The following illustration shows the behavior of the asset classes in our sample. The top-left chart, a histogram, shows the distribution of the first asset class (namely, US equities). The chart below it, a scatterplot, shows the returns of US equities (horizontal axis) against developed market equities excluding the US. Clearly, the two indexes tend to move together, with positive correlation. In fact, in the mirror-opposite cell of the matrix, we see r=0.84, meaning that the correlation between the two asset classes is 84%. We organized the charts in two panels, 2a and 2b, for readability.

Figure 2a has plenty of unusual patterns. The bottom line represents gold (vertical axis). Gold seems to have little correlation with the other asset classes, and indeed its scatterplots look like clouds, with no pattern emerging. This suggests that gold prices move independently from returns to the other asset classes, and therefore may be a candidate for diversification.

The following line is cash. Cash has different regimes, as confirmed by the histogram at the right-hand side of the bottom row. It shows a bimodal distribution – i.e., a histogram where there are two peaks (left for loose money, right for tight money), and a valley (intermediate monetary conditions, which do not appear to have happened frequently in the last 30 years).

The row of charts above cash represents macro hedge funds (alternative strategies focused on macroeconomic themes and taking concentrated bets on specific markets). The purpose of these strategies is to produce returns without material correlation to the markets in the long term and the results imply they do a pretty good job on average. The same is true for equity market neutral strategies which buy and sell similar stocks if one is expected to go up and the other down.

With commodities, the left-most scatterplot depicts commodities vs. US equities, showing that when equity markets go down (horizontal axis) commodity prices often seem to dampen the fall. However, observing the scale of the vertical axis as well as the histogram to the right, we notice that more than half of the monthly returns to commodities during our sample period were negative. This suggests that, while commodities are a diversifier, a passive buy-and-hold commodity allocation would have lost money over the last 30 years.

Emerging market debt (EMD) denominated in hard currency is on the following row. The histogram is noticeably narrow, indicating low volatility. The beta of the regression line for the scatterplot in the first column is also positive, showing that EMD returns were positive on average when US equity returns were positive, and vice versa. It is therefore hardly surprising that EMD is seen by the market as a risky asset.

Figure 2b is like 2a in the sense that the first row shows US equities, but the remaining assets are new. Let us look at them, again starting from the bottom row, showing developed government bonds excluding the US, which appear to have little correlation to risk assets. Credit, high-yield and investment-grade bonds specifically, are clearly risk assets with a positive correlation to stocks. US government bonds show a slightly negative correlation to risk assets during the last 30 years, and therefore have worked as mitigators of market volatility.

To complete the chart, we have equities from emerging markets and from developed markets excluding the US, which both have a strong positive correlation to the US stock market, showing the existence of a global business cycle.

Segments of market performance

By segmenting our sample to only consider months where equity performance was particularly negative, we can now look at responses in different market conditions.

For the chart above, we only consider months in our sample that were in the bottom 2.5% of the distribution – i.e., when the stock market did worse than 97.5% of the cases. All betas are positive except for that of cash, which is negative but close to zero. This indicates that when stocks fell dramatically in the last 30 years or so, cash tended to remain stable. The only other asset class with a small beta is US credit (investment grade) bonds, a relatively safe asset during market panics.

As Figure 3 shows, both US and non-US government bonds (typically a good refuge during market panics) and hedge funds stand out as these zero-correlation strategies duringmarket routs.

Repeating the exercise with different percentiles offers similar results. However, the beta for US government bonds goes from zero to negative. This suggests the hedging effect may be more substantial for government bonds when the stock market fall is less extreme.

The analysis carried out shows clear diversification benefits in multi-asset portfolios. However, when stock market losses are severe, correlations between assets do appear to increase, muting the benefits of correlation in a traditional portfolio. Alternative asset classes such as hedge funds may help government bonds in achieving diversification benefits.

Importantly, illiquid asset classes such as direct real estate and private equity were excluded from the analysis. This is because their returns are generally quarterly and based on appraisals rather than on market transactions, making a proper statistical comparison impossible.

Inflation effects

The behavior of asset class correlations in different inflation regimes also matters. Inflation serves as both a barometer of economic health and a catalyst for market dynamics. In particular, we analyzed economic environments characterized by extreme inflation, since ordinary correlation patterns between asset classes are generally expected to break down.

As a proxy for inflation, we used the year-over-year changes of the United States Consumer Price Index for Urban Consumers (without seasonal adjustment and available as a monthly time series). Once again, we segment the data into quantiles.

On the left-hand side, we display the average monthly return of each asset class with its average quadratic error (one standard deviation of the mean). On average, independent of the inflation environment, all asset classes but commodities deliver a positive risk premium over cash.

On the right-hand side, the beta vs. US equities is positive and quite large for most risky assets. Cash and US government bonds represent the exception. Government bonds in foreign currencies display a small, yet slightly positive correlation to US equities, most probably coming from foreign currency risk exposures and global inflation cycles.

Next, we analyze asset class returns in the quantile corresponding to the 10% highest inflation environments – i.e., year-over-year changes of US Urban Consumers CPI higher than 4.13%. In such situations, the picture changes quite dramatically.

Does volatility matter?

Next, we analyze asset class returns in the quantile corresponding to the 10% highest inflation environments, that means year over year changes of US Urban Consumers CPI higher than 4.13%. In such situations, the picture changes quite dramatically.

The chart on the left-hand side shows average monthly returns becoming strongly negative for equity indexes. Riskier fixed income assets – such as US credit, US high yield and emerging market hard currency bonds – also show negative average monthly returns. Even ‘safe-haven’ assets, such as US government bonds, provide only a limited degree of diversification as they often have negative returns.

Asset class betas to US equities are again positive and quite large for most risky assets. Interestingly, defensive government bond assets become positive. Therefore, based on the assumption that government bonds should provide diversification to riskier asset classes, traditional multi-asset solutions will most probably encounter performance problems in high inflation environments.All is not lost, however: Figure 5 clearly shows that cash and alternative asset classes might provide diversification benefits. Average monthly returns are positive for cash, commodities, and two of the hedge fund styles designed to act as ’crisis hedge’ providers.

More specifically, commodities do seem to provide some hedge against inflation, whereas their beta vs. US equities decreases. However, the variability of average monthly return is the highest among all asset classes; the hedge therefore may not be as reliable and the effects on portfolio volatility may not be ideal.

The equity market neutral hedge fund style groups long/short portfolios with little market exposure, aiming to generate return mainly by taking idiosyncratic risk (as explained earlier). The second hedge fund style with diversification potential is the macro style, which groups strategies taking long or short positions in different equity, fixed income, currency and commodity markets, mainly with derivative securities, trying to profit from the economic and political outlook for different regions and countries. These strategies appear to provide good diversification.

The findings already discussed for the 10% highest inflation environment hold true for the 5% and the 2.5% equivalents.

Volatility effects

Another variable which influences asset class correlations is implied volatility, the volatility used in option pricing models, such as the Black-Scholes model. Figure 10 shows the historical distribution of VIX levels. We can see that the VIX level distribution is skewed to the right, with historical median at 18.33, and average at 20.06.

We look at the behavior of asset class correlations in different implied volatility regimes, keeping in mind the results earlier. First, we analyze asset class returns in the quantile corresponding to the 10% highest US equity implied volatility levels.

The diversification properties of government bonds continue to hold in high volatility regimes. Conversely, when volatility increases the betas to US equities of most asset classes increase significantly. The exceptions are cash, US government bonds, foreign government bonds and the macro hedge fund style.

Equity market neutral hedge funds appear to suffer in high volatility regimes, with a sharply increasing beta to US equities. This might happen because certain types of equity market neutral strategies, such as statistical arbitrage strategies, aim to identify pairs of correlated stocks and take opposing positions based on their historical relationship – and in high implied-volatility regimes such relationships tend to break.

When we analyzed asset class returns in the 5% and 2.5% quantiles the findings already discussed for the 10% highest inflation environment were mostly confirmed. However, when implied volatility levels become extreme, even the macro hedge fund style stops providing protection. The only ‘safe havens’ in this situation are cash and government bonds.

The future of diversification

Past performance is no guarantee of future results, yet past performance is all we can analyze, and it would be illogical not to. Both inflation and implied volatility clearly influence the behavior of asset class correlations, especially during extreme market conditions. Our observations indicate that in environments characterized by high inflation and elevated volatility, diversification – the primary rationale behind multi-asset strategies – is not constant.

‘Safe’ assets such as government bonds and low-beta hedge funds appear to provide diversification against fluctuations in risk assets. However, the extent of this diversification varies.

We can now ask which types of market stress we can expect in 2025 and beyond. Inflation appears to be retreating around the world, so we do not think this will be a likely trigger of volatility (at least in the short term). However, geopolitical tensions in Eastern Europe and the Middle East are a serious concern and so (from an investment point of view) is the high valuation of US mega-caps.

In the past when geopolitical events – such as the tragic 11 September 2001 events occurred – all risk assets such as stocks and high-yield bonds suffered, while ‘safe-haven’ assets such as government bonds outperformed. Even though the September 11 events had roots in the Middle East, commodity prices did not move very much. Meanwhile, in 2022 when Russian invaded Ukraine, risk assets suffered and ‘safe’ assets outperformed, but commodities had the highest gain due to supply concerns.

In terms of US stock valuations, the dot.com bubble (during a period of low inflation) illustrated the effects of a sudden fall from high stock valuations (note we are not suggesting that the current valuations of the largest US stocks is necessarily a bubble). In 2000-2002, after the market turned away from technology stocks, while risk assets lost en masse, traditional ‘safe’ assets such as government bonds performed quite well, providing good diversification.

Therefore, if investors are concerned about geopolitics and the possible overvaluation of stocks, they should consider a diversified allocation to ‘safe’ assets, starting with liquid (such as government bonds) and possibly extending to private assets. For those that fear an explosion in commodity prices due to geopolitics, a commodity exposure may be helpful, with a focus on energy.

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Warren Takunda

Economic

British inflation jumped by more than expected to go back above the Bank of England's 2% target last month and measures of underlying price growth gathered speed too, showing why the BoE is moving cautiously on interest rate cuts.

Consumer prices rose by an annual 2.3% in October, pushed up in large part by an increase in regulated domestic energy tariffs, after a 1.7% increase in September which was the first time the inflation rate had fallen below the BoE's target since 2021.

Sterling was up by almost a third of a cent against the U.S. dollar immediately after the data was published and interest rate futures priced in a slightly slower pace of rate cuts.

The BoE's most recent forecast and a Reuters poll of economists had both pointed to a CPI reading of 2.2% in October.

"These figures confirm a disappointing resurgence in inflation as the recent tailwind from lower energy costs turned into a headwind in October, following the increase in (regulator) Ofgem's price cap which drove a notable jump in household bills," Suren Thiru, Economics Director at accountancy body ICAEW, said.

The increase represented the biggest month-to-month rise in the annual CPI rate since October 2022.

Services inflation - which the BoE views as a key measure of domestically generated price pressure - rose to 5.0% in October from 4.9% in September, the Office for National Statistics said.

The BoE had expected it to rise to 5.0% in October.

Core inflation, which excludes energy, food, alcohol and tobacco, picked up to 3.3% from 3.2% in September.

"While the slight uptick in services price pressures confirms that it remains a significant hurdle to sustainably maintain inflation below target, slowing wage growth and a weakening labour market should help put it on a more consistent downward trajectory," Thiru said.

Chief Secretary to the Treasury Darren Jones said the government was trying to help reduce the cost of living "but we know there is more to do." Science minister Peter Kyle told Times Radio: "This does concern us."

BoE Governor Andrew Bailey on Tuesday stressed the central bank's message that borrowing costs are likely to come down only gradually as policymakers were awaiting clearer signs of how much inflation pressure remains in Britain's economy.

Earlier this month, the central bank said the first budget of Britain's new government was likely to add to inflation next year and beyond as higher taxes on companies were likely to translate into higher prices.

Source: Reuters

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