How to Design a Portfolio
Designing a portfolio is a complex and multifaceted process that requires careful consideration of numerous factors.
At least it can be.
For long-term passive investors, it might involve regularly contributing to some index funds, with the main driver of success being their savings rate.
For an amateur trader, it might first be experimenting, trading off gut judgments, and using the process of being knocked around to learn how to do it differently.
But when a portfolio is designed well – i.e., at an institutional level – what does that look like?
Let’s look into the key elements that go into creating a well-structured and effective portfolio.
Key Takeaways – How to Design a Portfolio
- Define clear objectives – return targets, risk tolerance, and constraints.
- Consider various factors – allocation, investment products, markets, and regulations.
- Manage risk through proper measurement and budgeting.
- Address operational aspects – collateral, liquidity, and trade execution.
- Assess resource requirements and talent needs.
- Extensively test using historical, live, and synthetic data.
- Fine-tune the structure once the basics are right.
- Ensure cohesive integration of the various components.
- Most institutional portfolios these days – at least those with a more quantitative bent – will have various forms of balance in order to increase the return relative to the risk.
- Recognize the complexity and interconnectedness of portfolio elements.
- Understand trade-offs and second-/third-/nth-order effects.
- Iterate and optimize before live deployment.
- Ultimately, judge success by real-world results.
Defining Objectives and Constraints
The first step in designing a portfolio is to clearly define its objectives and constraints.
This involves answering several crucial questions:
Purpose
What is the portfolio trying to achieve?
Is it for retirement savings, wealth preservation, aggressive growth, income generation, designed to generate gains in all market/economic environments?
Return Target
How much return is needed to meet the portfolio’s objectives?
This should be expressed in both absolute terms and potentially relative to benchmarks.
One trader might target 15% annualized returns per year (absolute).
For another, it might be CPI + 500bps (basically 5% above inflation, thus indexed to a specific benchmark).
Risk Tolerance
How much risk can be realistically taken to achieve the desired returns?
This involves assessing the trader/investor’s psychological comfort with volatility as well as their financial capacity to withstand losses.
There are also various ways of assessing risk.
For example, one trader might define it as volatility, another might focus more on tail risk, which brings us to…
Risk Measurement
Decide on the appropriate risk metrics.
Will you use volatility-based approaches like standard deviation and Sharpe ratio, or focus more on tail risk measures like Value at Risk (VaR) or Expected Shortfall?
Portfolio Size
The size of the portfolio can impact one’s choices, diversification possibilities, and access to certain instruments.
Smaller portfolios tend to have fairly narrow market access, while larger portfolios run by more sophisticated traders/investors tend to have much wider access.
Drawdown Limits
Establish the maximum acceptable drawdown.
This helps in setting stop-loss levels, the types of options that are used in a portfolio to manage tail risk, and managing overall portfolio risk.
Regulatory Restrictions
Consider any legal or regulatory constraints that may apply, especially for institutional investors or those in specific jurisdictions.
For example, a pension fund, sovereign wealth fund, foundation, or endowment typically has little to no leverage.
A hedge fund or private investment firm is different.
Environmental, Social, and Governance (ESG) Considerations
Determine if there are any ESG-related constraints or preferences that need to be incorporated into the portfolio design.
Taxes
Taxes impact after-tax returns significantly.
Consider tax-efficient strategies, asset location, and harvesting losses.
Transaction Costs
Include commissions, bid-ask spreads, and market impact.
Can erode returns, especially in high-turnover strategies.
Minimizing their impact is essential for optimizing net returns and achieving long-term goals.
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All of these latter factors influence asset selection, trading frequency, and overall portfolio structure.
Asset Allocation and Product Selection
Once the basic parameters are established, the next step is to determine the asset allocation and select appropriate investment products for the goals of the portfolio:
Asset Classes
Decide on the mix of asset classes (e.g., stocks, bonds, commodities) that aligns with the portfolio objectives.
Geographic Diversification
Consider exposure to different markets and geographies to spread risk and capture global opportunities.
Currency Exposure
Determine whether to hedge currency risk or use it as an additional source of diversification or returns.
Product Types
Choose between individual securities, ETFs, derivatives, or alternative investments based on the portfolio’s needs and constraints.
Allocation Ranges
Set minimum and maximum allocation ranges for each asset class, sub-strategy, or sub-portfolio* to allow for some tactical flexibility while maintaining the overall strategic direction.
* An example sub-portfolio might be one that’s designed to outperform when discounted growth and discounted inflation are below expectations. That then gets 25% of the risk in the portfolio relative to the other three combinations.
Correlation Analysis
Examine correlations between different assets and strategies to ensure proper diversification and risk management.
Risk Management and Optimization
Effective risk management is important for portfolio success:
Risk Budgeting
Allocate risk across different trades, investments, and strategies to achieve the desired overall portfolio risk profile.
Optimization Methods
Use various optimization techniques (e.g., mean-variance–skew–kurtosis optimization, Black-Litterman model, risk parity) to find the most efficient portfolio allocation.
There are various mathematical optimization tools that we cover in more detail here.
Stress Testing
Subject the portfolio to various stress scenarios to understand how it might perform under extreme market conditions.
This includes customized simulations, backtesting, and synthetic data environments.
Tail Risk Hedging
Consider implementing tail risk hedging strategies to protect against severe market downturns.
Rebalancing Rules
Establish rules for when and how to rebalance the portfolio to maintain the target allocation and risk profile.
Implementation and Operational Considerations
The practical aspects of running the portfolio must also be carefully planned:
Collateral Management
For portfolios using derivatives or leveraged strategies, efficient collateral management is essential.
Liquidity Management
Be sure the portfolio has sufficient liquidity to meet any potential redemptions, cash flow needs, drawdowns, and variance in the portfolio.
Trade Execution
Develop a strategy for efficient trade execution to minimize transaction costs and market impact.
Leverage
Decide whether to use leverage and, if so, how much and in what form (e.g., margin, derivatives, structured products).
Operational Complexity
Assess the level of complexity in setting up and managing the portfolio.
More complex strategies may require specialized skills and resources.
Ongoing Research
Determine the level of ongoing research and analysis required to maintain and update the portfolio strategy.
Backtesting and Simulation
Before implementing a portfolio strategy, extensive testing is critical:
Historical Backtesting
Test the portfolio strategy using historical data across different time periods, market environments, and geographies.
Synthetic Data
Generate synthetic data to test the portfolio’s performance in scenarios that may not have occurred historically but are theoretically possible.
Is very helpful when it comes to stress testing to get a better view of the range of outcomes that are hypothetically feasible.
Monte Carlo Simulations
Use probabilistic modeling to generate a range of potential outcomes and assess the portfolio’s risk-return characteristics.
You’re always dealing with distributions in outcomes, not certainty.
Sensitivity Analysis
Examine how changes in various assumptions or parameters affect the portfolio’s performance.
Out-of-Sample Testing
Validate the strategy using data that was not used in the initial design process to avoid overfitting.
Fine-Tuning and Integration
Once the basic structure is in place, the portfolio needs to be fine-tuned:
Cohesive Integration
Ensure all elements of the portfolio (return streams, trade structures, hedging components) work together harmoniously.
Interdependencies
Recognize that changing one aspect of the portfolio can have ripple effects on other components.
For example, if one part of the portfolio is expressed as a specific type of options structure rather than the underlying asset, how does that impact the rest of the portfolio?
Trade-offs
Balance various objectives and constraints, which often involve trade-offs (e.g., risk vs. return, liquidity vs. yield).
Consider Higher-Order Effects
Higher-order effects in portfolio design involve considering the cascading impacts of trading/investment decisions:
Risk transformation
Hedges often shift risk rather than eliminate it.
For example, delta hedging may increase gamma or vega risk.
Market impact
Large trades can affect asset prices, potentially altering correlations or liquidity dynamics.
LTCM famously blew up because they failed to consider the correlations in their positions associated with their own influence.
Feedback loops
Portfolio actions may trigger responses from other market participants, creating unexpected consequences.
The use of certain analytical techniques in markets that become widely adopted can change the course of future financial data.
Systemic effects
Widespread adoption of similar strategies can lead to crowded trades or amplify market movements.
Regulatory responses
Financial decisions by large players may prompt regulatory changes.
Iteration
Be prepared to go through multiple iterations, refinements, and tests before arriving at the final portfolio design before deployment.
Ongoing Monitoring and Adaptation
Portfolio design is not a one-time event but an ongoing process:
Performance Monitoring
Regularly measure the portfolio’s performance against its objectives and benchmarks.
Risk Monitoring
Monitor risk metrics to make sure they remain within acceptable limits.
Market Changes
Stay alert to changes in markets, correlations, or other factors that might require portfolio adjustments.
Strategy Evolution
Be prepared to evolve the strategy over time as market dynamics change, goals change, new opportunities emerge, and/or based on new research or learning.
Balancing Exploitation and Exploration
Decide when to stick with proven strategies and when to explore new ideas or approaches.
Talent and Resources
The human element in portfolio design and management is important:
Skill Requirements
Assess the level of expertise required to manage the portfolio effectively.
More active or complex strategies typically demand higher skill levels or specific types of skill sets to manage.
Team Structure
Determine the optimal team structure and roles needed to implement and manage the portfolio strategy.
Technology Infrastructure
Be sure the necessary technological tools and systems are in place to support portfolio management, risk analysis, and reporting.
Continuing Education
Ongoing training and education to keep the team’s skills current with evolving market dynamics and trading/investment techniques.
Overall
More tactical, active approaches will require more skill and human resource commitments relative to approaches that are more strategic and passive.
Regulatory and Compliance Considerations
Staying compliant with relevant regulations is essential:
Regulatory Framework
Understand and adhere to all applicable regulations governing the portfolio’s activities.
This varies by the type of trader or investor.
Reporting Requirements
Implement systems to meet any regulatory reporting obligations.
Risk Disclosure
Proper risk disclosure to investors or stakeholders.
Communication and Reporting
Effective communication with stakeholders is important:
Reporting Framework
Develop a comprehensive reporting framework that provides clear insights into the portfolio’s performance, risk, and adherence to objectives.
Examples might include:
- Monthly returns
- Annualized returns
- Sharpe ratio
- Sortino ratio
- Beta
- Alpha
- Maximum drawdown
- Value at Risk (VaR)
- Standard deviation
- Portfolio allocation
Stakeholder Education
Educate stakeholders about the portfolio strategy, its potential outcomes, and any limitations.
But don’t give out proprietary information.
Transparency
Maintain transparency about the portfolio’s activities, especially during periods of underperformance or market stress.
Conclusion
Designing a portfolio is a complex process that requires a deep understanding of finance, economics, and risk management, combined with practical implementation skills.
It involves balancing numerous factors and making trade-offs between competing objectives.
The process is iterative and ongoing, requiring constant monitoring and adaptation to changing markets and stakeholder needs.
Ultimately, the success of a portfolio design is measured by its real-world results.
Thorough planning and analysis are important, but the true test comes when the portfolio is implemented and faces the real world.
A well-designed portfolio should be robust enough to weather various market environments while still achieving its stated objectives.
The complexity and depth of knowledge required for effective portfolio design underscore the value of professional investment management.
However, even for individual investors, understanding these principles can lead to more informed decision-making and better alignment of trading or investment strategies with personal financial goals.
It also helps for those who believe that trading is easy money. It’s not easy and you are up against a lot of sophisticated people and institutions involved in markets.