A 1-Month Portfolio Analysis of a 3-Month £50,000 Mock Investment Fund

Introduction

This write-up is based on the first month of a 3-month project where I am testing if a £50,000 mock investment fund can outperform a chosen benchmark. Each week, I tracked the portfolio’s performance and linked it to market events to see how they affected results.

I decided on £50,000 as the starting amount because it felt like a realistic figure for a small fund. Even though one month is a short time, it has already given me the chance to practise building a portfolio, test diversification, and learn how risk and market changes play a role in investment performance.

Investment Strategy

My main goal when building this mock portfolio was to create a strategy that balanced growth opportunities with stability. Since I am still learning about investing, I wanted to focus on diversification across different asset classes rather than taking on too much risk with just one type of investment.

To do this, I decided to split the £50,000 across equities, ETFs, bonds, and REITs. Equities were chosen to capture growth potential, while bonds were included to provide stability and reduce volatility. ETFs gave me exposure to wider markets without having to pick too many individual stocks, and REITs added a different type of asset linked to property and income.

I also kept in mind that this was a short one-month project, so my aim wasn’t long-term growth but more about practising how to allocate assets and see how they behave together in different market conditions.

Performance Metrics (week 1)

This week I started tracking the portfolio by looking at three main things: the portfolio return %, the benchmark return %, and excess return (how much better or worse the portfolio did compared to the benchmark). I also used attribution to break down which assets helped or hurt the portfolio the most.

Return on investment basically shows how much the portfolio went up or down compared to where it started. For Week 1, the portfolio return was around -0.14%, which means it dropped slightly in value. Even though it’s only a small change, it gave me an idea of how the portfolio reacted in its first week.

It’s too early to judge volatility after just one week, but I could already see some patterns. Amazon, for example, had a bigger drop compared to other holdings, showing that growth stocks are more sensitive to market movements. On the other hand, bonds (AGG) were much steadier and actually helped reduce the overall loss. This confirmed to me why diversification is important.

For the same period, the benchmark (SPY) lost about -0.29%. Since my portfolio was down -0.14%, it actually did slightly better than the benchmark by about +0.15%. This suggests that the mix of assets I chose, especially having bonds, gave the portfolio a bit more protection than just being invested in the market index.

Using a benchmark like the S&P 500 makes it easier to judge whether performance is good or bad. Without it, I wouldn’t know if the small loss in the portfolio was normal or not. Comparing to SPY showed me that the portfolio is doing okay, because even though it lost value, it still did better than the wider market.

Figure 1. This chart shows which assets helped or hurt my portfolio in Week 1. AGG and USO added small gains, while Amazon and Unilever pulled the portfolio down.

Figure 2. Comparison of portfolio and benchmark cumulative returns for Week 1. The portfolio fell slightly but performed better than the benchmark overall.

Performance Metrics (weeks 1-4 Summary)

Over the past month, my £50,000 mock portfolio had a few ups and downs but ended slightly lower than where it started. The portfolio finished with a return of about -0.26 %, while the benchmark (S&P 500 - SPY) ended at -0.36 %. Even though both lost value, my portfolio performed a little better overall, which shows that spreading my investments across different assets helped reduce losses.

Each week was quite different. In Week 2, the portfolio went up by +0.36 %, mostly because of good results from technology and healthcare stocks. But in the next few weeks, the value dropped again, mainly because Amazon and the oil ETF (USO) fell in price. Even with those drops, my portfolio stayed more stable than the benchmark, which had a bigger fall of -1.61 % around mid-October before recovering a bit at the end.

When looking at individual assets, Johnson & Johnson (JNJ) and Nvidia (NVDA) did the best, returning +9.67 % and +3.71 %. JNJ made the biggest positive impact on the portfolio overall. However, Amazon (-7.97 %) and USO (-7.54 %) pulled the total value down the most. Bonds (AGG) and property investments like Realty Income (O) and VICI stayed quite steady and helped balance out some of the losses from the riskier assets.

Comparing my portfolio to the benchmark showed that my mix of assets helped protect against big losses. The benchmark moved up and down more sharply, while my portfolio stayed more even. This shows that having both growth and defensive investments makes performance smoother, even when the market is unpredictable.

Overall, this first month taught me how quickly the market can change and how important it is to have a balanced portfolio. The line chart comparing my portfolio and the benchmark shows that while the benchmark dropped more sharply, my portfolio held up better thanks to diversification.

Figure 3. Asset contribution to portfolio return in Week 4. JNJ and NVDA made the strongest positive contributions, while Amazon (AMZN) and USO were the main negative drivers.

Figure 4. Portfolio vs benchmark returns across all five weeks (weeks 0-4). The portfolio mostly followed market movements but stayed more stable overall, showing slightly lower volatility than the benchmark.

Market Overview

During the one-month period I was tracking the portfolio, the market was quite mixed. There were a few ups and downs each week, mainly caused by changing news around inflation and interest rates. Investors seemed to still be cautious, which led to some sectors doing better than others.

Technology stocks had a lot of attention throughout the month, especially companies like Nvidia, which continued to benefit from interest in artificial intelligence. However, the tech sector also remained sensitive to small shifts in interest rate expectations, which caused occasional dips in share prices. Amazon followed a similar pattern, performing well at times but pulling back when overall market sentiment turned more defensive.

On the other hand, more stable sectors such as healthcare and consumer staples, represented in my portfolio by Johnson & Johnson and Unilever, didn’t experience large swings but also didn’t show major gains. Bonds, like those in the AGG ETF, remained steady and acted as a safety net when equities became more volatile. This balance showed why it was important to hold a mix of assets rather than focusing on just one area.

Commodities also had their own movement during this period. Oil prices rose slightly at first but later settled, while agricultural products like wheat were quieter and didn’t have a big effect on the portfolio overall. REITs, such as VICI and Realty Income, stayed relatively stable but didn’t grow much because property-related investments are still sensitive to higher interest rates.

Looking at all of this together, the market reflected a cautious but active environment. Tech and energy showed short bursts of growth, while defensive assets helped balance things out. The mix of reactions across sectors made it clear that market conditions can shift quickly even in a short time frame, which is something I learned to pay attention to while tracking this fund.

Portfolio Performance Review

Over the five weeks (weeks 0-4) of this project, my mock £50,000 portfolio showed small ups and downs but stayed fairly steady overall. It finished slightly below its starting value, with a total return of around -0.26%, while the benchmark (S&P 500 - SPY) ended lower at -0.36%. This meant my portfolio performed a little better than the benchmark, which shows that diversification helped reduce losses during market downturns.

In Week 2, the portfolio saw its strongest rise of about +0.36%, supported by gains in technology and healthcare stocks. However, the following weeks were more volatile, with Week 4 showing the largest dip when both the market and my portfolio declined. Even then, the portfolio’s loss was smaller than the benchmark’s, suggesting that the mix of defensive and growth assets helped limit downside risk.

When comparing the two, the benchmark had more dramatic movements, while my portfolio stayed smoother overall. This pattern showed that diversification across equities, bonds, commodities, and REITs can make performance more stable, even if it limits some of the stronger gains during bullish weeks.

Looking at individual assets, Johnson & Johnson (JNJ) was the best performer, gaining around +9.7% and contributing positively to the overall return. NVIDIA (NVDA) and Unilever (UL) also added small but steady gains that helped balance out weaker areas. These assets reflected how large, established companies tend to stay resilient even when markets fluctuate.

On the other hand, Amazon (AMZN) and the United States Oil Fund (USO) were the most disappointing performers, falling by roughly -8% and -7.5%. These losses showed how growth and commodity-based assets can be more sensitive to short-term market conditions. Smaller declines also came from WEAT and VICI, but because they made up a smaller share of the portfolio, their effect was limited.

Overall, the portfolio’s performance over the month showed how diversification helps manage risk. While the fund didn’t make large gains, it successfully avoided steep losses, which was one of my main goals when building it. This experience showed me that even during a short time frame, a balanced portfolio can provide better protection than simply following the wider market.

Lessons Learned

Looking back on this first month, I learned a lot about how markets behave and how different assets respond to change. Tracking the portfolio each week helped me see that even small market movements can affect performance, especially when the portfolio includes a mix of assets like stocks, bonds, and commodities.

One of the key things I learned was how diversification really helps reduce risk. My portfolio didn’t grow much, but it also didn’t drop as sharply as the benchmark during market dips. This showed that spreading investments across asset types is an effective way to protect the overall value, especially when some sectors perform worse than others. My strategy of combining growth assets like Nvidia and Amazon with more defensive holdings such as bonds (AGG) and Johnson & Johnson (JNJ) worked well in keeping returns more stable.

The month also showed me how market conditions influence investment outcomes. For example, technology stocks reacted strongly to small changes in interest rate expectations, while bonds stayed relatively calm. Commodity prices, especially oil, were also sensitive to global news and economic data. Seeing these changes made me realise that keeping up with market updates is important when managing a portfolio, even over a short period.

If I were to make adjustments in the future, I would consider rebalancing the portfolio more actively. I might reduce the amount invested in high-volatility assets like Amazon and USO and increase exposure to areas that provided steady returns, such as healthcare and bonds. I would also pay closer attention to macroeconomic trends, since they clearly impact sector performance.

In terms of risk management, I learned that having too many assets in similar sectors can increase exposure to sudden market changes. For future portfolios, I would add more variety, perhaps including international ETFs or alternative assets that don’t move in the same direction as major markets.

Overall, this project taught me the importance of being balanced, observant, and flexible as an investor. Diversification is not just about having many assets, it’s about understanding how they interact under different conditions and adjusting them when needed to manage risk more effectively.

Conclusion

This project gave me a practical understanding of how investments behave over time and how portfolio management works in real situations. Over the five weeks, my mock £50,000 fund experienced small ups and downs but remained fairly steady overall. Even though the final return was slightly negative, it performed a little better than the benchmark, which showed that diversification helped protect the portfolio from larger losses.

Throughout the project, I realised how important it is to keep monitoring and reviewing investments regularly. Market conditions can change quickly, and even small news events can affect prices. By checking the portfolio each week, I was able to spot trends, notice which assets were performing well, and understand where the risks were. Continuous evaluation also helped me see when rebalancing might be needed to keep the portfolio aligned with my goals.

Overall, this experience improved my understanding of portfolio dynamics, how different assets interact, how diversification reduces volatility, and how market shifts influence returns. It taught me that successful investing isn’t just about picking the best stocks but also about maintaining balance, patience, and awareness. Even though this was a short project, it helped me see how disciplined decision-making and regular analysis are key parts of effective portfolio management.

Call to Action

Completing the first month of this project has made me realise how valuable it is to practise investing in a safe, simulated way before putting real money into the markets. I would encourage anyone interested in finance or investing to try building their own mock portfolio, even for a short period like a month. It’s one of the best ways to learn how different assets perform, how diversification works, and how emotions can influence decision-making when markets move up and down.

I’m still continuing this project until the full three months are complete, and I’m excited to see how the portfolio performs over a longer period. I think this will help me understand how short-term trends develop into longer-term patterns and how regular tracking can lead to better decision-making over time.

I also found that regularly reading market news and analysis helped me understand why certain sectors performed the way they did. Keeping up with updates on things like inflation, company earnings, and interest rate changes made it easier to connect what I saw in my portfolio to what was happening in the real world. For anyone starting out, staying informed and learning continuously is just as important as choosing the right investments.

Lastly, I’ve realised how helpful it is to talk about investing with others who share the same interest. Joining online communities or student investment groups can be a great way to exchange ideas, get feedback, and learn from different perspectives. The more discussions and shared insights there are, the better we can all understand how to build and manage portfolios effectively.