Building a Successful Investment Framework as a PM

[HowardM1]

How to Create a Successful Investment Process

Imagine you are an investor who wants to grow your wealth and achieve your financial goals. You have a lot of options to choose from, but you also face a lot of uncertainty and complexity in the market. How do you make smart and consistent decisions that can help you (or your clients) reach your desired outcomes?

The answer is simple: you need a sound investment process. A sound investment process is like a roadmap that guides you through the journey of investing. It helps you navigate the twists and turns of the market, avoid pitfalls and traps, and discover opportunities and rewards.

In this post, I will show you how to create your own investment process using four simple steps:

1. Scenario building
2. Idea generation
3. Implementation
4. Portfolio management

I will also share with you my philosophy and principles that shape my investment process and how they can help you think critically, challenge yourself, and collaborate with others.

My philosophy is that a good process should be:

• Fundamentally driven
• Robust
• Transparent
• Iterative

It should always force you to ask the question "why" and invite cognitive strain. It should be collaborative in the initial stages but have clear responsibilities at the final stage, moving from a large group of people contributing ideas to a very small group to make decisions. It should also be flexible enough to change and evolve, as the best processes are always evolving.

This is the first post in a series that will take you through each step of my investment process in detail and give you practical examples and insights from my experience.

I hope you enjoy it!

Scenario Building

The first step of my investment process is to build scenarios that capture the potential future states of the world and their implications for the market. Scenarios are not predictions or forecasts, but rather plausible stories that describe how distinct factors and events could interact and affect the investment environment. Scenarios help me to:

• Anticipate risks and opportunities
• Test my assumptions and beliefs
• Prepare for different outcomes

To build scenarios, I use a macro top-down approach that considers the main drivers of the market, such as:

• Government policy
• Growth
• Inflation
• Central bank policy
• Geopolitics

I use various sources of information and analysis, such as:

• Investment bank research
• Internal economists and strategists
• External research

I also incorporate bottom-up views from stock pickers and credit managers who have local knowledge and insights from different regions and sectors. They are my eyes and ears on the ground and around the world.

I usually create a central base scenario that reflects the most likely outcome, an upside scenario that reflects a more optimistic outcome, and a downside scenario that reflects a more pessimistic outcome. I try not to assign probabilities to these scenarios because they will always be wrong. Instead, I try to filter my tail scenarios so that they have a greater than 10% probability by construction. My base scenario should be the most probable by default.

I also debate these scenarios with a large group of colleagues who can challenge my views and provide different perspectives. This helps me to refine my scenarios and make them more comprehensive and realistic. I update my scenarios over time as new information and events emerge.

Here is an example of three relevant scenarios that find this model:

• Base scenario: Higher interest rates and inflation for longer due to strong economic recovery and fiscal stimulus. This will keep regional banks in the US under pressure but if rate hikes are limited a hard landing should be avoided. Geopolitical tensions remain high but do not escalate into major conflicts.
• Upside scenario: Interest rates and inflation moderate as supply bottlenecks ease and demand cools down. This supports economic growth and corporate earnings. Geopolitical risks subside as the US and China cooperate on trade and climate issues.
• Downside scenario: Interest rates and inflation spike as supply shortages worsen and demand surges. This triggers a policy mistake by the Fed or a market crash. Regional US banks trigger a full-blown credit crunch, numerous banks fail. We are in uncharted waters as the Fed wants to cut but knows that will only stoke inflation further. Geopolitical risks flare up as China invades Taiwan or a new global pandemic emerges.

These scenarios inform my investment outlook and guide my idea generation in the next step of my investment process.

Idea Generation

The second step of my investment process is to generate ideas that can exploit the market opportunities and risks identified in the scenarios. Ideas are specific investment propositions that have a clear fundamental driver, a target return, and a time horizon. Ideas can be long or short, directional, or relative, single, or multi-asset.

To generate ideas, I challenge myself and my analysts to find ideas that the market is either not pricing or is pricing in an opposing fashion to my view. For example, in June 2020 my view was that the market was too pessimistic about the prospects of a Covid-19 vaccine, so an obvious idea was to be long biotech stocks and short travel stocks. Equally, in 2016 I felt the market was too complacent about the risks of Brexit, so short GBP an obvious idea. I also look for ideas that make money in each of my scenarios, so I need some risk-off ideas as well as optimistic upside bets.

Here are some of the key steps involved in idea generation:

Identify market opportunities and risks. This is done by building scenarios, as discussed in the previous section.

Find ideas that are mispriced or misvalued. This can be done by using fundamental analysis, technical analysis, or a combination of both.

Evaluate the ideas. This involves assessing the risk-reward profile of each idea and determining whether it meets your investment criteria.

Implement the ideas. This involves buying or selling the securities that make up the idea.

I evaluate ideas first on a qualitative level, using my fundamental analysis and judgment. I then use quantitative techniques at the implementation stage, such as back-testing, stress-testing, and scenario analysis. I do not like to rank ideas as it’s a way to introduce bias. I have minimum hurdles for liquidity and potential return. I always want to avoid risk of ruin and other pitfalls. I also assign conviction levels to each idea, which helps me in the next stage of my investment process.

Some examples of ideas that I used in the past are:

Long biotech stocks and short travel stocks: This idea reflected my view that the market was too pessimistic about the prospects of a Covid-19 vaccine in June 2020. I expected the vaccine development and distribution to be faster and more effective than anticipated, which should benefit biotech companies to a larger extent than travel companies. If I was wrong about the vaccine, it should hurt travel companies that rely on tourism and mobility much more than Biotech.

Short GBPUSD: This idea reflected my view that the market was too complacent about the risks of Brexit in 2016. I expected the UK to vote to leave the EU and trigger a political and economic turmoil, which should weaken the pound against the Dollar. I increased the trade on the day of the result as GBPUSD unexpectedly increased to erase most of its losses. This must have been flow related because after I put my trade on in subsequent days it fell to new lows.

Long US tech stocks and short US energy stocks: This idea reflected my view that the market was underestimating the impact of technological innovation and environmental awareness on different sectors in 2018. I expected tech companies to continue to dominate the market with their disruptive products and services, while energy companies would struggle with low oil prices and regulatory pressures.

These ideas fit into my scenarios and informed my implementation in the next step of my investment process.

Implementation

The third step of my investment process is to implement my ideas using various instruments and vehicles that can best express my views and optimize my returns. Implementation is where the rubber meets the road. It is where I translate my ideas into actual positions in my portfolio. It is also where I face the challenges of execution, such as timing, sizing, hedging, liquidity, and costs.

To implement my ideas, I tend to frequently use derivatives because they help me craft more precise and leveraged implementations and limit potential losses. Some types of instruments that I use are:

• Equity index futures
• FX forwards
• Interest rate futures
• ETFs
• ETNs
• ETCs
• Options on different asset classes
• Swaps
• Swaptions
• Volatility instruments

I occasionally build and invest in stock baskets. I do not buy other active funds because for me that is like cheating the investor by effectively charging them double fees. It is one reason I am very much against the fund of funds approach.

I will go into more detail on timing, sizing, and hedging in the deep dive articles, but at a high level I use the following:

• Technical triggers for entry and exit.
• Position sizing based on expected return and required return.
• Hedging to reduce unwanted risks or enhance returns.
• Collaborating with traders to find the best liquidity and the tightest execution.
• Building relationships with sell-side traders and understanding the market.

Another aspect of implementation that I use is machine learning to optimize execution. Machine learning is the use of algorithms and data to learn from experience and improve performance. I use machine learning to analyse market microstructure, which is the study of how markets operate at the level of individual trades and orders. Market microstructure affects the price, volume, liquidity, and volatility of securities. By using machine learning, I can identify patterns and anomalies in market microstructure that can help me improve my execution. For example, I can use machine learning to:

• Estimate the optimal time and size of my trades.
• Minimize market impact and slippage.
• Detect market inefficiencies and arbitrage opportunities.
• Adjust my execution strategy in real time based on market conditions.

A sound investment process is one that is flexible and adaptable to change. The market is constantly evolving, and so too must my investment process. I am always looking for new ways to improve my process and generate better returns for my investors.



Portfolio Management

The last step of my investment process is portfolio management. I oversee and adjust my portfolio in response to market movements and new information. I also measure and evaluate my portfolio performance and risk exposure.

I use risk as the primary tool to manage my portfolio. I understand the risk contribution of every position based on both a longer-term lookback window and a shorter-term one. I use a risk system that can manage the non-linear characteristics of options and the fat tails of financial markets. One approach is Monte Carlo techniques, which simulate thousands of scenarios and outcomes.

All my positions have target weights. If they deviate from those, I rebalance them. They also have upside and downside stops/review levels. If I hit one or get close to it, I close or rebalance the position. I rebalance my portfolio at least once a month or more frequently if needed.

I monitor my portfolio performance and risk exposure using various metrics and reports. I monitor my performance by:

• Time period
• Asset class
• Individual strategy
• Factor
• Scenario

I also use machine learning to cluster trades based on their similarities and correlations. I look for diversification and avoid big concentrations of risk. I use stress tests, both historical and hypothetical, to check how my portfolio performs under different scenarios.

I adapt my portfolio to changing market conditions and new information using a feedback loop that connects my portfolio management with my scenario building and idea generation. I look for information that invalidates my scenarios or markets that behave unexpectedly. If that happens, I update my scenarios and ideas accordingly. I also adjust my portfolio weights and hedges based on my conviction levels and risk appetite.

Portfolio management is the ultimate step of my investment process, but not the end of the journey. It is a continuous cycle of learning and improving that helps me achieve my financial goals.





Conclusion

In this post, I have shown you how to create your own investment process based off my approach, using four simple steps: scenario building, idea generation, implementation, and portfolio management. I have also shared with you my philosophy and principles that shape my investment process and how they can help you think critically, challenge yourself, and collaborate with others. My philosophy is that a good process should be:

• Fundamentally driven
• Robust
• Transparent
• Iterative

It should always force you to ask the question "why" and invite cognitive strain. It should be collaborative in the initial stages but have clear responsibilities at the final stage. It should also be flexible enough to change and evolve, as the best processes are always evolving.

I hope this post has helped you understand the importance and benefits of following a structured investment process. A sound investment process can help you or your clients achieve your financial goals by providing a framework for making consistent and rational decisions in the face of uncertainty and complexity.

In future posts, I will dive deeper into each of the four steps of the investment process and provide more insights and examples. I will also discuss some of the challenges and pitfalls of investing and how to overcome them.

I hope you will find this and subsequent posts interesting and informative please leave comments and questions below.

 

[JustAnotherHuman1]

Thanks for sharing your investment decision making framework, very thorough intro indeed, is this something you polished over the years and then took some inspiration from others to create something that works for you personally? Any good books to recommend (feel free to recommend classics)?

Is there a difference between an asset management PM seeking alpha vs a hedge fund manager trying to do the same?

 

[HowardM1]

Thanks for sharing your investment decision making framework, very thorough intro indeed, is this something you polished over the years and then took some inspiration from others to create something that works for you personally? Any good books to recommend (feel free to recommend classics)?

Is there a difference between an asset management PM seeking alpha vs a hedge fund manager trying to do the same?

I'm glad you found it interesting.

As for the origins of my approach, it's definitely a result of my experiences working in various firms, where I've seen both excellent and terrible processes. I've adapted, borrowed, and learned from these experiences along the way. However, I believe the foundation of an investment process is universal: it begins with an opinion and ends with an investment. In between, that opinion transforms into an idea, gets implemented, and then needs to be managed. There are numerous ways to approach this, such as top-down, bottom-up, qualitative, and quantitative methods, but the starting and ending points remain consistent.

Regarding book recommendations, there are so many that it could warrant a separate post, I will come back with some others but I personally really enjoyed Brent Donnelly's Alpha Trader. Its written to some extent from a day trading/traders viewpoint so its a bit short term, it wont help much with scenario generation but I think its excellent on the portfolio management side.

As for the differences between asset managers (AM) and hedge funds (HF), most asset managers generally manage beta, though some hedge funds do as well. In a broad sense, I think there is a difference, and my approach could work at either a hedge fund or a sophisticated asset management firm. The main distinctions likely lie in the implementation and portfolio management stages. A hedge fund manager, compared to an asset manager, may have a more extensive toolbox to choose from or may be highly focused on the microstructure of a specific market. However, they will almost certainly have a different risk framework, prioritizing maximizing returns while minimizing the risk of being stopped out. In contrast, an asset manager will likely be more focused on long-term returns and the volatility of those returns, aiming to maximize the probability of beating a benchmark or reaching a target while minimizing risk and drawdowns.

With some adjustments, the process I've outlined could work for a long-only multi-asset desk as well as a macro hedge fund, which, I suppose, reflects my career path in response to your initial question.

 

[Shane H Norman1]

I'm glad you found it interesting.

As for the origins of my approach, it's definitely a result of my experiences working in various firms, where I've seen both excellent and terrible processes. I've adapted, borrowed, and learned from these experiences along the way. However, I believe the foundation of an investment process is universal: it begins with an opinion and ends with an investment. In between, that opinion transforms into an idea, gets implemented, and then needs to be managed. There are numerous ways to approach this, such as top-down, bottom-up, qualitative, and quantitative methods, but the starting and ending points remain consistent.

Regarding book recommendations, there are so many that it could warrant a separate post, I will come back with some others but I personally really enjoyed Brent Donnelly's Alpha Trader. Its written to some extent from a day trading/traders viewpoint so its a bit short term, it wont help much with scenario generation but I think its excellent on the portfolio management side.

As for the differences between asset managers (AM) and hedge funds (HF), most asset managers generally manage beta, though some hedge funds do as well. In a broad sense, I think there is a difference, and my approach could work at either a hedge fund or a sophisticated asset management firm. The main distinctions likely lie in the implementation and portfolio management stages. A hedge fund manager, compared to an asset manager, may have a more extensive toolbox to choose from or may be highly focused on the microstructure of a specific market. However, they will almost certainly have a different risk framework, prioritizing maximizing returns while minimizing the risk of being stopped out. In contrast, an asset manager will likely be more focused on long-term returns and the volatility of those returns, aiming to maximize the probability of beating a benchmark or reaching a target while minimizing risk and drawdowns.

With some adjustments, the process I've outlined could work for a long-only multi-asset desk as well as a macro hedge fund, which, I suppose, reflects my career path in response to your initial question.

For any but the professional investor, this process will be difficult to adopt, not only because it requires access to top-flight information sources, but because of its reliance on peer challenges. That, in particular, will be impossible.

However, that is not to say that the post is irrelevant or useless. On the contrary, its detail reveals how challenging it is to succeed in active management and, therefore, why most individual investors should rely on professionally-managed funds and strategies, especially low-cost ETFs and similar passive vehicles - particularly, in developed markets.

But, the most important takeaway is the need for discipline. Without that, the investor is hostage to their own biases, doomed to fail at least as often as they succeed.

 

[HowardM1]

For any but the professional investor, this process will be difficult to adopt, not only because it requires access to top-flight information sources, but because of its reliance on peer challenges. That, in particular, will be impossible.

However, that is not to say that the post is irrelevant or useless. On the contrary, its detail reveals how challenging it is to succeed in active management and, therefore, why most individual investors should rely on professionally-managed funds and strategies, especially low-cost ETFs and similar passive vehicles - particularly, in developed markets.

But, the most important takeaway is the need for discipline. Without that, the investor is hostage to their own biases, doomed to fail at least as often as they succeed.

Hi,

Thanks for the comment, the process as I have outlined is close to the one I follow so yes if you wanted to use it as a roadmap it will be more suitable to someone that's working in the industry vs a retail investor. Part of that is information access and part is being able to collaborate with peers and invite challenge.

Is that impossible for the retail investor, I'm not sure I mean what's to stop you building a small group of like minded individuals and exchanging idea's. The challenge I guess is getting them all to buy into the process and having a common reference frame, that is actually not even that easy at an Asset Manager so I concede it maybe very hard to work out for a retail investor. The book I recommended by Brent is actually very relevant to the retail trader as he was a day trader himself so that's one to look at, he is also quite active on LinkedIn so would suggest following him.

Another book recommendation is "Thinking in Bets" by Annie Duke, she describes how she improved her poker game by building a group of people that all shared the same approach, and using them as a sounding board. Of course she and her friends are professionals but nevertheless I think the book has lots of great advice for decision making under uncertainty.

Your final point is key, for a retail investor my process would be form a view, generate ideas consistent with that view, implement and manage those ideas, its essential to have a consistent plan for each step and stick to it. If you can't explain your process in a few words you probably don't have one!

Be disciplined, try to understand why you made money and be honest if it was for the wrong reasons, equally don't beat yourself up about losing money if you stuck to the plan. Simply make sure you avoid risk of ruin and think about how you can make the wins bigger than the losses, finally be aware of transaction costs and leverage do not overtrade. Final book recommendation here is anything by Robert Carver as he has a great explanation of why transaction costs really do matter. Again many of his books are very much directed towards the retail investor.

 

[Shane H Norman1]

Hi,

Thanks for the comment, the process as I have outlined is close to the one I follow so yes if you wanted to use it as a roadmap it will be more suitable to someone that's working in the industry vs a retail investor. Part of that is information access and part is being able to collaborate with peers and invite challenge.

Is that impossible for the retail investor, I'm not sure I mean what's to stop you building a small group of like minded individuals and exchanging idea's. The challenge I guess is getting them all to buy into the process and having a common reference frame, that is actually not even that easy at an Asset Manager so I concede it maybe very hard to work out for a retail investor. The book I recommended by Brent is actually very relevant to the retail trader as he was a day trader himself so that's one to look at, he is also quite active on LinkedIn so would suggest following him.

Another book recommendation is "Thinking in Bets" by Annie Duke, she describes how she improved her poker game by building a group of people that all shared the same approach, and using them as a sounding board. Of course she and her friends are professionals but nevertheless I think the book has lots of great advice for decision making under uncertainty.

Your final point is key, for a retail investor my process would be form a view, generate ideas consistent with that view, implement and manage those ideas, its essential to have a consistent plan for each step and stick to it. If you can't explain your process in a few words you probably don't have one!

Be disciplined, try to understand why you made money and be honest if it was for the wrong reasons, equally don't beat yourself up about losing money if you stuck to the plan. Simply make sure you avoid risk of ruin and think about how you can make the wins bigger than the losses, finally be aware of transaction costs and leverage do not overtrade. Final book recommendation here is anything by Robert Carver as he has a great explanation of why transaction costs really do matter. Again many of his books are very much directed towards the retail investor.

We are completely on the same page. As property investment is location, location, location, so securities investment is discipline, discipline, discipline.

 

[magellan1]

I agree that one should exchange ideas with peers but one should not agree with the crowd easily. Some time ago, I come across research showing investment returns of funds by the number of investment committee members. I don't remember the exact data but the main message was that performance is worse, the higher the number of decision-makers is. This is because big groups need to reach a consensus and consensus decisions by design lead to average performance. You can have clarity of thought if you stay away from the crowd like Warren Buffet does by living in a small city far from New York.
I highly recommend the books of Nassim Taleb (Fooled by Randomness, Antifragile). He is a former First Boston trader and a very smart person who has had a huge influence on my approach to life and investing. Some of the most important ideas that he covers are fat tails, the barbell strategy, the role of randomness in investing and the imprudence of bank CEOs.

 

[Shane H Norman1]

I agree that one should exchange ideas with peers but one should not agree with the crowd easily. Some time ago, I come across research showing investment returns of funds by the number of investment committee members. I don't remember the exact data but the main message was that performance is worse, the higher the number of decision-makers is. This is because big groups need to reach a consensus and consensus decisions by design lead to average performance. You can have clarity of thought if you stay away from the crowd like Warren Buffet does by living in a small city far from New York.
I highly recommend the books of Nassim Taleb (Fooled by Randomness, Antifragile). He is a former First Boston trader and a very smart person who has had a huge influence on my approach to life and investing. Some of the most important ideas that he covers are fat tails, the barbell strategy, the role of randomness in investing and the imprudence of bank CEOs.

Interesting information about the size of investment committees. It confirms the wisdom of an old investment adage: the market will do whatever is necessary to prove the greatest number of people wrong.

Another book to read, and one that long predates Nassim Taleb is 'Extraordinary Popular Delusions and the Madness of Crowds', by Charles Mackay, published in 1841. Economic and market bubbles are among of his main topics.

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[HowardM1]

Interesting information about the size of investment committees. It confirms the wisdom of an old investment adage: the market will do whatever is necessary to prove the greatest number of people wrong.

Another book to read, and one that long predates Nassim Taleb is 'Extraordinary Popular Delusions and the Madness of Crowds', by Charles Mackay, published in 1841. Economic and market bubbles are among of his main topics.

​

Yes we would always tell clients, start with a large, diverse group of individuals, ideally those with a strong intellectual capacity, to generate and debate ideas. Then, a smaller, selected group should assess the ideas in greater depth. Lastly, a maximum of three decision-makers should determine how and when to invest.

Issues can arise with large numbers of people involved, particularly groupthink, which can stifle individual creativity and decision-making. Another associated issue is the lack of ownership, as it becomes easy to assign blame to others when something goes wrong. This dynamic can also contribute to inertia or slow decision-making in times of stress.

Decision-making under uncertainty is a fascinating topic, "Thinking, Fast and Slow" by Daniel Kahneman is obviously a classic and a good introduction but there are many other good books out there. To that end I will be kicking off a series of reading list posts on various topics, first one later this week hopefully.

I own the Charles Mackay book but I have to admit the style is a bit dry, its a great book but you need to be in the right frame of mind to get into it!