Factors Influencing Risk In Investment Portfolios

"𝗠𝗼𝘀𝘁 𝗽𝗲𝗼𝗽𝗹𝗲 𝗼𝗻𝗹𝘆 𝗹𝗼𝗼𝗸 𝗮𝘁 𝗿𝗲𝘁𝘂𝗿𝗻𝘀. 𝗕𝘂𝘁 𝗶𝘀 𝘁𝗵𝗮𝘁 𝗿𝗲𝗮𝗹𝗹𝘆 𝘁𝗵𝗲 𝘄𝗵𝗼𝗹𝗲 𝗽𝗶𝗰𝘁𝘂𝗿𝗲?" 🤔 Chasing only high returns is like focusing only on the speed of your car without checking fuel levels, engine health, or your final destination. 🚗💨 In long-term investing, wealth creation hinges on several key factors. Here are the seven most important factors: 𝟭. 𝗖𝗹𝗲𝗮𝗿 𝗙𝗶𝗻𝗮𝗻𝗰𝗶𝗮𝗹 𝗚𝗼𝗮𝗹𝘀 Setting specific financial goals (like buying a house, retirement, or children’s education) helps you plan and stay focused. Example: Knowing you need ₹1 crore for your child's education in 15 years helps you choose the right investments to meet this target. 𝟮. 𝗧𝗶𝗺𝗲 𝗛𝗼𝗿𝗶𝘇𝗼𝗻 The duration you plan to stay invested impacts your investment choices. Longer horizons can handle more risk for potentially higher returns. Example: If you have 20+ years until retirement, you can afford to invest heavily in equity, as you have time to ride out market volatility. 𝟯. 𝗔𝘀𝘀𝗲𝘁 𝗔𝗹𝗹𝗼𝗰𝗮𝘁𝗶𝗼𝗻 Diversifying across asset classes (equity, debt, gold etc.) reduces risk and optimizes returns. Example: A mix of 60% equities, 30% debt, and 10% gold can help you diversify and stabilize your portfolio, catering to different market conditions. 𝟰. 𝗥𝗲𝗴𝘂𝗹𝗮𝗿 𝗜𝗻𝘃𝗲𝘀𝘁𝗺𝗲𝗻𝘁𝘀 Consistent investing, such as via SIPs (Systematic Investment Plans), leverages the power of compounding and reduces market timing risks. Example: Investing ₹10,000 monthly in an equity mutual fund over 20 years can grow significantly through the compounding effect. 𝟱. 𝗥𝗶𝘀𝗸 𝗠𝗮𝗻𝗮𝗴𝗲𝗺𝗲𝗻𝘁 Understanding your risk tolerance and adjusting your investments accordingly protects you from making panic decisions during market downturns. Example: If you can't handle the volatility of equity, balancing with safer debt funds can help maintain peace of mind. 𝟲. 𝗣𝗮𝘁𝗶𝗲𝗻𝗰𝗲 𝗮𝗻𝗱 𝗗𝗶𝘀𝗰𝗶𝗽𝗹𝗶𝗻𝗲 Wealth creation is a long journey. Staying invested through market ups and downs is key to compounding returns. Example: Investors who stayed invested during market crashes and didn't panic sell (like in 2008 or 2020) benefited from subsequent market recoveries. 𝟳. 𝗥𝗲𝘁𝘂𝗿𝗻𝘀: 𝗙𝗼𝗰𝘂𝘀 𝗼𝗻 𝗖𝗼𝗻𝘀𝗶𝘀𝘁𝗲𝗻𝗰𝘆 Chasing high returns can lead to risky decisions, but aiming for steady, consistent returns helps build wealth over time without unnecessary stress. Example: Aiming for consistent returns of 10-12% annually in a diversified portfolio can help you achieve your financial goals without any stress, even if it means avoiding trendy but volatile investments. Focusing on these seven pillars can set you on a path to long-term financial success. Instead of chasing quick gains, build a sustainable, well-rounded strategy that stands the test of time. Are you focusing on high returns or building a resilient investment strategy for the long haul? Take a moment to rethink your approach. 💭

Your pension portfolio should give you zen like calm, poise and balance. However, the essence of successful investing lies not merely in picking winning stocks but in how these stocks interact within a portfolio. A well-constructed portfolio should include stocks that rise and fall at different times, creating a smoother, more stable return over time. This concept, known as diversification, is crucial for mitigating risk and achieving consistent long-term investment success. Understanding the Nature of Market Volatility Stock markets are inherently volatile, driven by a complex interplay of factors such as economic cycles, interest rates, geopolitical events, and investor sentiment. For instance, technology stocks might surge during periods of innovation and economic expansion but could suffer during market downturns or regulatory challenges. Conversely, stocks in more defensive sectors, such as consumer staples or utilities, tend to remain stable or even appreciate when the economy slows, as the demand for their products is less sensitive to economic forces. The Role of Correlation in Diversification Correlation is a statistical measure that describes how two assets move in relation to each other, with a correlation coefficient ranging from +1 to -1. A correlation of +1 indicates that the assets move in perfect sync, while a correlation of -1 means they move in opposite directions. A correlation of 0 suggests no relationship between the movements of the assets. In a well-diversified portfolio, the goal is to include assets with low or negative correlations. For example, when technology stocks like Microsoft rise due to an economic boom driven by innovation, energy stocks like ExxonMobil might fall if the same boom suppresses oil prices. Conversely, during periods of economic contraction, energy stocks might perform well due to rising oil prices, even as tech stocks decline. This dynamic allows for a more stable overall portfolio performance, as the opposing movements of non-correlated assets help to smooth out returns. The Evolution of Diversification Theory The concept of diversification through non-correlated assets is not new. It dates back to the work of Harry Markowitz, who introduced Modern Portfolio Theory (MPT) in 1952. In his seminal paper “Portfolio Selection,” Markowitz demonstrated how combining assets with low or negative correlations could reduce portfolio risk while maintaining expected returns. His work laid the foundation for the idea that a diversified portfolio offers the best risk-return trade-off, a principle that remains central to investment theory today (Markowitz, 1952).

𝐓𝐡𝐢𝐧𝐠𝐬 𝐭𝐨 𝐊𝐞𝐞𝐩 𝐢𝐧 𝐌𝐢𝐧𝐝 𝐃𝐮𝐫𝐢𝐧𝐠 𝐏𝐨𝐫𝐭𝐟𝐨𝐥𝐢𝐨 𝐀𝐧𝐚𝐥𝐲𝐬𝐢𝐬: 1. 𝐀𝐬𝐬𝐞𝐭 𝐀𝐥𝐥𝐨𝐜𝐚𝐭𝐢𝐨𝐧 Is the portfolio diversified across asset classes (equity, debt, gold, etc.)? Proper allocation reduces risk and improves stability. 2. 𝐑𝐢𝐬𝐤 𝐯𝐬. 𝐑𝐞𝐭𝐮𝐫𝐧 Look beyond just returns. Assess risk-adjusted returns using Sharpe Ratio, Treynor Ratio, and Jensen’s Alpha. 3. 𝐏𝐨𝐫𝐭𝐟𝐨𝐥𝐢𝐨 𝐁𝐞𝐭𝐚 Understand the portfolio’s sensitivity to market movements. High beta = higher volatility. 4. 𝐏𝐞𝐫𝐟𝐨𝐫𝐦𝐚𝐧𝐜𝐞 𝐁𝐞𝐧𝐜𝐡𝐦𝐚𝐫𝐤𝐢𝐧𝐠 Compare returns against relevant benchmarks (like Nifty 50, Sensex, etc.). Outperformance or underperformance gives valuable insights. 5. 𝐆𝐨𝐚𝐥 𝐀𝐥𝐢𝐠𝐧𝐦𝐞𝐧𝐭 Does the portfolio align with the investor’s financial goals, time horizon, and risk appetite? A high-return portfolio isn’t useful if it doesn’t meet the purpose. 6. 𝐑𝐞𝐛𝐚𝐥𝐚𝐧𝐜𝐢𝐧𝐠 𝐅𝐫𝐞𝐪𝐮𝐞𝐧𝐜𝐲 Check if the portfolio is rebalanced regularly to maintain desired allocation. Market movements can distort the original strategy. 7. 𝐄𝐱𝐩𝐞𝐧𝐬𝐞 𝐑𝐚𝐭𝐢𝐨𝐬 𝐚𝐧𝐝 𝐂𝐨𝐬𝐭𝐬 High expense ratios or hidden charges can eat into your returns. Analyze net returns after costs. 8. 𝐓𝐚𝐱 𝐄𝐟𝐟𝐢𝐜𝐢𝐞𝐧𝐜𝐲 Understand the tax implications of short-term and long-term capital gains. Opt for instruments that are more tax-efficient, where possible. 9. 𝐋𝐢𝐪𝐮𝐢𝐝𝐢𝐭𝐲 𝐨𝐟 𝐈𝐧𝐯𝐞𝐬𝐭𝐦𝐞𝐧𝐭𝐬 Can the investments be liquidated quickly in case of emergencies? Illiquid assets may pose a problem during urgent needs. 10. 𝐂𝐨𝐧𝐬𝐢𝐬𝐭𝐞𝐧𝐜𝐲 𝐨𝐟 𝐏𝐞𝐫𝐟𝐨𝐫𝐦𝐚𝐧𝐜𝐞 Is the portfolio consistently delivering returns over time? Avoid portfolios that rely on one-off gains. Follow: Priyanshu Pandey #PortfolioAnalysis #InvestmentTips #FinancialPlanning #AssetAllocation #RiskManagement #PersonalFinance #WealthManagement

Tail risk-aware investors: 1. Don’t blindly rely on full-sample correlations for portfolio construction 2. Give scenario analysis a meaningful role in asset allocation decisions 3. Use these downside scenarios to estimate the investors’ risk tolerance 4. Use portfolio optimization tools that account directly for left-tail risks 5. Beware of “diversification free lunches” in privately held asset classes 6. Evaluate interest rate risk and its impact on stock-bond diversification 7. Seek asset classes that provide upside “unification”/anti-diversification 8. Consider active risk management strategies: ▪️ Hedges with put options and proxies ▪️ Strategies that embed short positions ▪️ Momentum-based factors or strategies ▪️ Actively-managed absolute return alts ▪️ Managed volatility overlays/strategies ▪️ Strategic or tactical cash allocations [From the book Beyond Diversification. This is not investment advice.]

A new paper from IFM Investors on the role private market assets can play in supporting risk adjusted returns through unanticipated swings in the economic cycle. Summary: Elevated geopolitical risks and heightened uncertainty have made it increasingly difficult to anticipate the future and invest accordingly. In our view, traditional portfolio construction approaches yield portfolios that are sub-optimally positioned to navigate this new investment paradigm. We apply advanced machine learning techniques to assess the relationship between key macro factors and asset performance to identify strategies to build more robust portfolios. Our approach significantly outperforms traditional factor estimation methods, includes both private and public markets, and takes into account the returns smoothing of private assets to improve comparability across private and public markets. We find clear evidence that higher private market exposures are desirable and result in increased portfolio resilience to broad macro volatility, better insulation against specific macro risks, improved overall portfolio robustness, and enhanced through-the cycle risk-adjusted returns. IFM Investors Economics & Research Frans van den Bogaerde, CFA and Christopher Skondreas. With Matthew Tsiglopoulos #privatemarkets #unlistedinfrastructure #investment #portfolio #assetallocation #macroalpha #macrobeta #machinelearning

It is perhaps surprising that even today, MACRO RISK accounts for over 50% of total portfolio risk for a representative US equity portfolio 👉 As the chart shows, the macro risk % of total risk has moved sharply higher in times of macro volatility The recent peak was 2022 (macro risk was 65% of total risk) and since late 2023 macro risk has been declining as idiosyncratic forces (#nvidia #ai #mag7) started to rise and as the #fed finished hiking rates 🚨 But macro risk still accounts for over 50% of the total risk of a portfolio made up of the #GoldmanSachs Very Important Positions ETF (#GVIP) constituents 👉 Macro still matters It is possible to break down this Macro Risk into its pieces and run a full attribution. The risk model underneath this chart is very similar to traditional equity factor risk models. In fact, it is entirely interoperable with these types of models. The difference is that macro factors (macro factor returns) are used. These are de-correlated and then related to portfolio (or indeed single stock) returns. A wide range of macro factors are used (including daily real GDP estimates). A variance -covariance matrix is used to generate Total Risk. The result is the "macro DNA" of your porfolio. 👉 And the message here is that macro is still impacting daily returns and overall risk. It is interesting to look at return attribution (not shown) - where you can see what part of returns was explained by macro factors ("non-specific") and what portion came from other sources ("specific risk") A greater focus on macro factor risk seems to be an emerging trend in among equity investors and equity long/short funds in particular over the last few years. Many funds have started to implement macro risk solutions. 👉 It would be very interesting to get any thoughts from equity investors on whether they feel understanding their macro risk is a challenge, how this is being handled and how best practice in this area is evolving

How much risk you take with your investments is one of the most reliable determinants of your expected investment returns. But how much risk should you take? And what even is risk? Risk in this context is typically framed as volatility, or the chance of an investment declining in value. I'll revisit this definition later. Assessing how much risk (volatility/downside) you should take has three main dimensions: 1. Behavioral loss tolerance 2. Ability to take risk 3. Need to take risk Behavioral loss tolerance breaks down into six elements: 1. Risk tolerance: your willingness to engage in financial behavior with an uncertain outcome and the potential for loss. 2. Risk preference: your general preference to take more or less risk. 3. Financial knowledge: greater financial knowledge is associated with a higher behavioral loss tolerance. 4. Investing experience: investment experience is generally associated with being more comfortable with risk. 5. Risk perception: your subjective assessment of the risk of investing, separate from the objective reality of it. 6. Risk composure: your actual behavior during past difficult market conditions. The only way to know your risk composure is to have lived through market crashes and the accompanying narratives that exacerbate investor worries. Best practice for establishing risk tolerance is using a psychometric assessment like the Grable-Lytton assessment. https://lnkd.in/eE96zUNF The other constraint on asset allocation is your ability to take risk. Ability to take risk breaks down into 3 elements: 1. The time horizon for the goal. 2. The ongoing need for liquidity from the portfolio. 3. The capacity to absorb a financial loss. Longer time horizon, lower liquidity needs, and higher risk capacity imply higher risk ability. The last dimension is the need to take risk. Someone with high loss tolerance and risk ability may not need to take a lot of risk, while someone with a low loss tolerance and risk ability who needs to take a lot of risk may need to reconsider their goals. Risk profiling frames risk as volatility, but that’s not the only relevant measure of risk for for long-term investors. Stocks are more volatile than nominal bonds, but they have been historically much less likely to lose purchasing power at long horizons. Long-term investors concerned with their inflation-adjusted wealth and spending may find that a higher allocation to stocks is, contrary to popular wisdom, safer than a more bond-heavy portfolio. Your psychological constitution and your financial situation are constraints on how much risk you can take. Even if you can handle taking a lot of risk, you may not want to if you don’t need to take much to meet your goals. Finally, and importantly, the nature of risk (volatility vs. funding long-term real consumption) changes with time horizon.

Quants should consider a variety of portfolio measures to assess the performance, risk, and characteristics of their portfolios. ♥️♥️♥️ Here are some key measures📚📚 1. Expected Return: The average return that the portfolio is expected to generate over a specific period. 2. Volatility (Standard Deviation): A measure of the dispersion of returns, indicating the portfolio's risk. 3. Sharpe Ratio: The ratio of the portfolio's excess return over the risk-free rate to its standard deviation, assessing risk-adjusted performance. 4. Beta: A measure of the portfolio's sensitivity to market movements, indicating systematic risk. 5. Alpha: The excess return of the portfolio relative to the return predicted by the CAPM, indicating the value added by active management. 6. Value at Risk (VaR): The maximum potential loss over a specified time period at a given confidence level. 7. Expected Shortfall (ES) or Conditional VaR: The expected loss given that the loss exceeds the VaR threshold, providing insight into tail risk. 8. Drawdown: The peak-to-trough decline in the value of the portfolio, indicating the maximum potential loss. 9. Sortino Ratio: Similar to the Sharpe ratio but only considers downside volatility, providing a measure of risk-adjusted return that focuses on negative returns. 10. Information Ratio: The ratio of the portfolio's excess return over a benchmark to the standard deviation of this excess return, assessing the efficiency of active management. 11. Tracking Error: The standard deviation of the portfolio's excess return relative to a benchmark, indicating the degree of deviation from the benchmark. 12. Jensen's Alpha: The difference between the actual return of the portfolio and the return predicted by the CAPM, adjusted for the risk-free rate. 13. Treynor Ratio: The ratio of the portfolio's excess return over the risk-free rate to its beta, assessing risk-adjusted performance relative to systematic risk. 14. Portfolio Turnover: A measure of the frequency with which assets in the portfolio are bought and sold, indicating trading activity and associated costs. 15. Correlation: The degree to which the returns of the portfolio move in relation to other assets or benchmarks, indicating diversification benefits. 16. Skewness: A measure of the asymmetry of the return distribution, indicating the likelihood of extreme positive or negative returns. 17. Kurtosis: A measure of the "tailedness" of the return distribution, indicating the likelihood of extreme returns. 18. Duration: The sensitivity of the portfolio's bond holdings to changes in interest rates, indicating interest rate risk. 19. Convexity: A measure of the curvature in the relationship between bond prices and yields, providing insight into interest rate risk. 20. Maximum Drawdown: The maximum observed loss from a peak to a trough of a portfolio, before a new peak is attained, providing insight into potential downside risk. #quantitativefinance #portfoliomanagement

According to a recent study by Allianz, nearly two in three Americans worry more about running out of money in retirement than death! No doubt many of your clients share this concern. I addressed this issue in a clip from my interview on Tom Hegna's new show, "Financial Freedom," which aired on CNBC. In this segment, I discussed the factors that contribute to the risk of portfolio depletion in retirement. The risk of clients outliving their money is exacerbated by an aging population with increased longevity and sequence of returns risk (market losses early in retirement), which make it difficult to determine a “safe” withdrawal rate. In addition, I provided some strategies clients can utilize to prevent it from happening. These include delaying Social Security to increase monthly benefit amounts and using income annuities which can provide a guaranteed retirement paycheck for life without the risk of running out. If your clients like Social Security, they’ll love a SPIA! Ultimately, asset depletion is a balancing act between your clients’ enjoying their retirement and preserving their financial security. With the right planning, you can make sure they protect rather than break their hard-earned nest egg!

Risk and reward go hand and hand. If you decrease your risk exposure, you decrease your expected return. But if you combine two assets with similar risk profiles, but whose correlations do not match, you can lower portfolio risk without necessarily lowering expected returns. GLD launched in 2004. Its standard deviation has been 16.83% versus 16.54% for that of the S&P 500, and their drawdowns have been -45% and -55% respectively. Both the S&P 500 and GLD have returned an identical 9.7% per year over this period. It is not a coincidence that two assets with similar risk profiles produced similar returns. A portfolio of 50% GLD and 50% SPY would therefore have also produced 9.7% over this period (10.4% if you rebalanced annually back to the target weightings), but the standard deviation of the portfolio drops to 11.79% and the portfolio drawdown drops to 32%. This represents a 28% reduction in std. deviation, and a 40% reduction in drawdown, with no corresponding reduction in returns as illustrated by the Blue line in the graph below. The reason why AGG bonds are a poor diversifier is that they have a much lower std. deviation than stocks. So while they lower risk, they lower return at essentially the same rate. Meaning you are no further along on a risk-adjusted basis. The way to reduce the systematic risk of equities in a portfolio is to find diversifiers with similar risk profiles to stocks. You WANT their higher volatility to offset stock risk. If you're looking for ways to add value to your portfolio, drop the low risk bonds for true diversifiers.