Performance 2023

Dear Readers,

At the beginning of the year, we introduced the optimized portfolio for 2023. The most efficient point on the curve is the one where, for a risk level of 51.87%, the return is 55.74%. However, given the assumed restrictions, the optimal portfolio would also achieve a expected return of 22.16% for a risk of 25.62%. 

The optimal portfolio in this case is composed of the following assets and their respective weights:

Microsoft - 22%
Tesla- 14%
Costco - 64%

Based on these considerations, you can find the year-by-year evaluation of this decision in terms of portfolio performance below. When we look at the portfolio, it is composed of 60% in the equity portfolio and 40% in Treasury bonds. Read more here: Optimized Portfolio 2023

Portfolio Composition and Performance

Risk-Free Asset: This makes up a significant portion of the portfolio at 40%.  Despite the slight increase in yield, the amount sold indicates a minor loss, resulting in a negative ROI of -0.72%.

Microsoft: With a 13% weight, the investment in Microsoft has shown a substantial increase in stock price from $237.47 to $376.04. This resulted in a high ROI of 58.27%, indicating strong performance.

Tesla: Representing 8% of the portfolio, Tesla has seen a remarkable price increase from $108.10 to $248.48. The ROI here is the highest among the assets at 129.73%, demonstrating an exceptional return.

Costco: Holding the largest share at 39%, Costco has also experienced significant growth in stock price from $439.87 to $660.08. The ROI is solid at 49.96%.

The total ROI pre-tax for the portfolio stands at 37.47%.

Risk Analysis

The portfolio's risk is measured by variance and standard deviation, with the risky portfolio showing a variance of 6.56% and a standard deviation of 25.62%. These figures suggest a moderate to high level of risk, which is corroborated by the substantial gains from high-volatility stocks like Tesla.
Benchmark Comparison:

Comparing the portfolio’s performance to benchmarks:

Standard Deviation: The portfolio's standard deviation of 25.62% is higher than the benchmark standard deviation of 17.34% from 2018. This indicates a higher risk taken by the portfolio compared to the benchmark.

Returns: The portfolio's return of 37.47% compares favorably to the benchmark return of 36.83% from 2023, suggesting the portfolio manager was successful in achieving returns above the benchmark, albeit with higher risk.
Conclusion:

The portfolio has performed well over the assessed period, outperforming the benchmark return in 2023 with substantial contributions from high-performing assets like Tesla and Microsoft. The higher standard deviation compared to the 2023 benchmark indicates a higher risk, but this has been rewarded with higher returns. The negative ROI on the risk-free asset, however, warrants a review of the assumptions regarding its stability and contribution to the portfolio.

Expect the optimized portfolio for 2024 in the next few days. 

Farfetch v Diversification & ML

 Farfetch & Diversification: how on earth do they converge you may ask?  

In my financial analysis postgraduate course, we scrutinized Farfetch’s financial state, focusing on the convertible bonds issued in April 2020. These bonds, totaling $350 million, were a strategic move to raise capital, coinciding with Farfetch’s stock surge of over 500% from 2020 to 2021 during the COVID-19 pandemic.

The significant price drop experienced by Farfetch stock was primarily attributed to the company not generating profits. Despite the increase in stock value following the convertible bonds issuance, the lack of profitability ultimately led to a decline in the stock price. This underscores the importance of sustainable financial health and profitability in maintaining investor confidence.

As an investor, I constantly seek stability in the capricious world of finance. I came across a research paper on Conditional Portfolio Optimization (CPO) using Machine Learning (ML) by Dr. Ernest Chan that adapts to markets regimes and it seems to be just the tip of the iceberg.

Imagine a tool that learns from market patterns and adapts your investment strategy accordingly. This is where ML in CPO comes in – it’s not just about data crunching but about understanding the nuances of market trends.

For me, the Farfetch case and this research intersect at a crucial point: the need for diversification and adaptability. It’s a lesson in not putting all your eggs in one basket and relying on smart, data-driven strategies to navigate market volatility. 

As I integrate these learnings into my investment approach where Machine Learning meets portfolio optimization, I see a path to a more secure financial future. I will publish a new post about the Portfolio Optimization Machine Learning Model I have been building this past year and the exciting news I have for you. 

Stay tuned & happy holidays! 

Incorporating AI and Active Portfolio Management: A Commentary on BlackRock's Market Outlook for 2024

BlackRock's Market Outlook for 2024 underscores the necessity, particularly under the theme "Steering Portfolio Outcomes", for an active approach to managing portfolios in the face of heightened volatility and market dispersion. This theme resonates deeply with my journey in portfolio management, which has evolved from leveraging Markowitz's theory to embracing AI models for optimized portfolio solutions.

BlackRock's emphasis on heightened volatility and dispersion in the current financial regime highlights the need for an active approach to managing portfolios. This perspective aligns with my belief in dynamic portfolio management, which has been a cornerstone of my strategy since the incorporation of AI models. The transition from static exposures to a more granular approach in portfolio allocations, as suggested by BlackRock, is a strategy I have advocated for, especially in my blog.

So, which approach is right for you?

The hypothetical scenario posed by BlackRock about accurately predicting U.S. equity sector returns highlights the potential of AI in investment strategy. My approach, using AI model, seeks to embody this hypothetical scenario in real-life applications. By processing and analyzing market data more efficiently and accurately, AI models provide a foundation for making informed decisions swiftly.

 

 

BlackRock'schart on the impact of rebalancing on U.S. equity returns illustrates the value of a dynamic investing approach. This is where I believe AI models play a crucial role. They enable a more frequent and “informed” rebalancing strategy, which, as per BlackRock's analysis, yields greater rewards compared to traditional buy-and-hold strategies.

Portfolio - AI model

In conclusion, BlackRock's Market Outlook for 2024 echoes many principles that I have incorporated into my investment strategy. A dynamic approach to portfolio management is not just a trend but a necessity in the current financial climate.

BlackRock Market Oulook 2024

Harnessing Machine Learning in Algorithmic Trading

Algorithmic trading's landscape has evolved with the integration of machine learning techniques, propelling the exploration of reinforcement learning (RL) models for financial decision-making.  Empirical findings reveal the model potential to adeptly navigate trading dynamics, achieving an impressive 263.38% return over the tested period, significantly outpacing the benchmark return of 43.22%.

Machine Learning: The New Frontier

Enter machine learning—a field that enables algorithms to learn from data and improve over time. In the context of trading, machine learning models, particularly those under the reinforcement learning umbrella, are game changers. They don't just react; they adapt, learning continuously from market feedback.

Data: The Fuel for Machine Learning

Our approach is deeply rooted in data. From stock prices and trading volumes to intricate financial metrics, our models ingest vast amounts of information. This data undergoes meticulous preprocessing, from computing daily returns to integrating expert financial insights, ensuring that the algorithms receive the richest possible input.

A Dynamic Trading Sandbox

To put our strategies to the test, we developed a custom trading environment. Think of it as a real-time market simulator where our machine learning-driven algorithm plays the role of a trader, navigating market shifts, making investment decisions, and continually refining its strategy.

Results

The empirical analysis underscored the model's robustness. The portfolio realized a remarkable 263.38% return over 981 trading days, with positive returns on 545 days. This performance, when juxtaposed against the benchmark's 43.22% return, illustrates the model's potential. Calmar Ratio at 0.8317 - this metric emphasizes the system's return efficiency relative to its maximum drawdown. A value nearing 1 showcases the system's capability to maximize returns while keeping potential losses in check.
    

However, real-world trading presents challenges like transaction costs, market slippages, and liquidity issues. Neglecting these factors could impact realized profitability.

Conclusion

The synergy between machine learning and finance is revolutionizing algorithmic trading. As we've seen, not only does it promise robust returns, but it also offers a dynamic risk management framework. As we continue to fine-tune our models and factor in real-world trading nuances, the horizon looks promising, filled with innovation and potential.

Optimizing Portfolio Performance with EVA Momentum

 Hello, dear readers! We are back with another insightful blog post, and today we're diving into an exciting financial performance measurement tool – the Economic Value Added Momentum, commonly known as EVA Momentum.

EVA Momentum, an evolution of the Economic Value Added (EVA) concept, was introduced as a modern measure of financial performance. This revolutionary tool was developed with the goal of providing a more accurate analysis and potentially improving firm performance.

But what is EVA, you ask? Economic Value Added is a measure of a company's financial performance based on the residual wealth calculated by deducting the cost of capital from its operating profit. In simpler terms, it calculates the value a company adds to its shareholders' investment.

Building upon the EVA concept, EVA Momentum goes a step further. It not only evaluates a company's current financial performance but also considers the change in EVA relative to the company's sales in the previous period. By calculating the EVA Momentum, investors can assess the rate at which a company's EVA is changing relative to its sales, providing insight into a company's operational efficiency and future performance potential. This measure can be particularly useful in identifying companies that are not only adding economic value but also doing so at an increasing rate.

One of the key highlights of EVA Momentum is its ability to improve and explain financial performance. It serves as an effective economic measure, providing a comprehensive overview of a firm's financial health. It is considered as one of the best measures for firm financial performance, as asserted by Stewart in 2009.

So, how can EVA Momentum benefit our portfolio?

EVA Momentum's focus on the rate of change in EVA relative to sales allows us to spot companies that are not just performing well now, but also show promise for future growth. This forward-looking aspect makes it an invaluable tool for constructing and managing our investment portfolio.

It enables us to identify potential winners early and adjust our portfolio, accordingly, potentially leading to higher returns. Furthermore, it provides a deeper understanding of a company's financial performance, helping us make more informed investment decisions.

In conclusion, EVA Momentum represents a significant advancement in financial performance measurement. Its potential to analyse and improve firm performance makes it a promising tool for portfolio management.

Source: Omneya, A. K., Ashraf, S., & Eldin, B. B. (2021). Is Economic Value Added Momentum (EVA Momentum) a Better Performance Measurement Tool? Evidence from Egyptian Listed Firms.

2023 Portfolio Performance: A Mid-Year Analysis

In the dynamic world of investing, a periodic review of your portfolio is crucial to assess performance, adjust strategies, and better plan for the future. As we stand at the midpoint of 2023, it's the perfect time to evaluate the performance of our investor's diversified portfolio, scrutinize its returns from a percentage perspective, and delve into risk management using metrics like the Sharpe Ratio.

At the start of 2023, we wisely diversified the portfolio across risk-free assets, Microsoft, Tesla, and Costco. The expected return was set ambitiously at 22.16%, while the risk, measured by standard deviation, was 25.62%. The initial risk-free rate was 3.79%.

Now, let's evaluate the mid-year performance of each asset. The risk-free assets, constituting 40% of the portfolio, are currently showing a slight negative return of -0.24%. This may be due to a minor increase in the risk-free rate to 3.82%.

Microsoft, which forms 13.2% of the portfolio, has performed well with an impressive return of 49.37%. The considerable rise in the asset price from 227.78 to 340.54 significantly bolstered this position.

Tesla, although holding only 8.4% of the portfolio, emerged as the star performer, boasting a remarkable return of 118.45%. This exceptional performance can be attributed to Tesla's share price jump from 119.77 to 261.77.

Costco, representing the largest weight in the portfolio at 38.4%, returned a respectable 12.16%. Despite its more moderate growth compared to Tesla, the significant allocation helped maintain a healthy overall portfolio return.

At this mid-year point, the portfolio value has grown by 21.04%, which would equate to an impressive 42.08% annualized return if the portfolio continues to perform at the same rate for the rest of the year. 

But returns are not the only key to a successful portfolio; risk management also plays a pivotal role. The Sharpe ratio of this portfolio stands at 1.68, a solid number that indicates the average return earned above the risk-free rate per unit of volatility or total risk. A Sharpe ratio of 1 or above is generally seen as favorable among investors.

Despite the promising returns, the portfolio is trailing the benchmark return of 28.32% at this mid-year review. Also, the portfolio has a lower standard deviation of 10.24% compared to the benchmark's 18.91%, indicating lower volatility but also lower returns.

In conclusion, the portfolio has demonstrated substantial percentage growth midway through 2023. The performance highlights the importance of strategic diversification, risk tolerance, and risk-adjusted returns. While some assets have not grown as anticipated, others like Tesla and Microsoft have shone, resulting in a positive overall portfolio performance. Moreover, the favorable Sharpe ratio indicates that the returns have been well-earned for the level of risk taken, affirming the efficacy of this investment strategy. We look forward to the end of the year with optimism, hoping for continued growth and success.

The EPS Elite: The 10 Best Performing Stocks for 2024 Portfolio Planning

   Upon rigorous analysis of the top 20 stocks featured in this blog, we have distilled our selection down to the final top 10 equities. This determination has been guided by a multi-factor approach, with key metrics such as Earnings Per Share (EPS), year-on-year growth, and overall company resilience and market stability being considered.

    Though each of the 20 assessed securities offered distinct value propositions, the subsequent 10 entities have emerged as outstanding performers, underpinning their selection for our strategic focus. These firms demonstrate compelling potential and remarkable financial performance, which are critical elements we seek as we construct our 2024 portfolio.

    Our curated selections lay the groundwork for a robust and diverse portfolio aimed at optimally positioning our strategy for 2024. Through sector diversification, our objective is to achieve an equilibrium between growth opportunities and risk mitigation, thus facilitating the generation of sustainable returns for our investors. Our commitment remains, as always, to deliver investment strategies that offer consistent value and market resilience.

    Now, let's delve deeper into the rationale behind each selection in our top 10 list.

·        Broadcom Inc (AVGO): Broadcom led the pack with an outstanding EPS of 31.96, demonstrating a 20% year-on-year growth. The company's robust finance performance positions it as a strong candidate for our 2024 portfolio.

·         Amgen Inc (AMGN): Amgen has shown significant promise with an EPS of 14.72, reflecting a 22% increase from the previous year. This growth underscores the company's potential for a solid presence in our 2024 portfolio.

·         Costco Wholesale Corp (COST): Costco secured a consistent EPS of 13.5, marking a 3% improvement year-on-year. The company's steady financial performance suggests it could continue as a reliable element within our portfolio.

·         Microsoft Corp (MSFT): Microsoft posted an EPS of 9.23, although this reflects a slight 4% dip from the previous year. Nevertheless, the resilience of its diverse product portfolio makes it an attractive consideration for our 2024 selection once again.

·         Adobe Inc (ADBE): Adobe achieved an EPS of 10.14, maintaining a consistent performance with no change year-on-year. This stability positions it as a potential candidate for our 2024 portfolio.

·         Honeywell International Inc (HON): Honeywell reported an EPS of 7.7, indicating a small decline of 3% from the previous year. Despite the slight dip, its strong industrial presence could make it a valuable addition to our portfolio.

·         Apple Inc (AAPL): Apple recorded an EPS of 5.89. However, it experienced a 4% drop from the prior year. Despite this, the enduring appeal of its product line and global brand recognition make it a viable contender for our future portfolio.

·         T-Mobile US Inc (TMUS): T-Mobile posted an EPS of 3.34. Yet, the telecom giant's performance saw a significant year-on-year jump of 62%. This substantial growth suggests promising prospects for our 2024 portfolio.

·         Cisco Systems Inc (CSCO): Cisco registered an EPS of 2.78, with a slight decline of 1% year-on-year. Still, its stable position within the tech industry could make it a steady contributor to our portfolio.

·         Comcast Corp Class A (CMCSA): Comcast finished our list with an EPS of 1.32. However, the media and technology company saw a year-on-year improvement of 9%, suggesting potential for growth within our 2024 portfolio.

In conclusion, this analysis provides insights into which companies could form part of our strategic portfolio selection for 2024. The EPS performance of these tech and retail giants, along with their year-on-year growth, offers a compelling snapshot of the potential investment opportunities.

Performance Backtesting

    Backtesting analysis is a crucial step in the portfolio management process. It involves analyzing the performance of a portfolio by applying a set of trading rules to historical market data. This analysis is used to evaluate the effectiveness of different investment strategies and to optimize portfolio performance. In this way, backtesting can help portfolio managers identify the most profitable strategies and minimize risk. By examining the historical performance of a portfolio, portfolio managers can gain valuable insights into how it may perform in the future, and adjust their investment strategies accordingly.

I have analyzed the performance of the portfolio for the years 2018 to 2022, and the results are as follows:

•  In 2018, the optimal portfolio obtained a return of 37.72% with a risk of 18.24%. The portfolio consisted of Microsoft (5%), Amazon (1%), Nvidia (11%), Meta (11%), Tesla (5%), PepsiCo (24%), T-Mobile (5%), Adobe (8%), Comcast (1%), and Netflix (10%). However, the portfolio's performance was negative, with a return of -6.62% compared to the benchmark (NASDAQ 100), which returned -3.96%. The M2 ratio was -1.6%, and the T2 ratio was -2.28%.

• In 2019, the optimal portfolio had a return of 34.07% with a risk of 25.40%. The portfolio consisted of Amazon (11%), Nvidia (29%), Broadcom (29%), Adobe (22%), and Netflix (8%). The portfolio's performance was 37.45%, outperforming the benchmark (NASDAQ 100), which returned 30.18%. The M2 ratio was -0.37%, and the T2 ratio was 3.23%.

• C. In 2020, the optimal portfolio had a return of 30.47% with a risk of 19.77%. The portfolio consisted of Microsoft (5%), Amazon (27%), Nvidia (21%), PepsiCo (9%), Costco (21%), T-Mobile (12%), and Netflix (6%). The portfolio's performance was 53.35%, outperforming the benchmark (NASDAQ 100), which returned 36.21%. The M2 ratio was 33.76%, and the T2 ratio was 42.8%.

• In 2021, the optimal portfolio had a return of 29.22% with a risk of 23.02%. The portfolio consisted of Apple (33%), Amazon (22%), Costco (28%), Adobe (15%), and Netflix (2%). The portfolio's performance was 21.69%, outperforming the benchmark (NASDAQ 100), which returned 19.38%. The M2 ratio was 7.04%, and the T2 ratio was -4.23%.

• In 2022, the optimal portfolio had a return of 42.29% with a risk of 29.41%. The portfolio consisted of Microsoft (44%), Apple (31%), and Netflix (20%). The portfolio's performance in this fifth year of fund activity is -27.73% compared to the benchmark's -40.2% (NASDAQ 100). In this fifth year, we obtained an M2 ratio of -5.98% and a T2 ratio of -52.06%.

The portfolio performed well in most years, outperforming the benchmark index. However, in 2018, the portfolio underperformed the benchmark, resulting in negative returns. The negative M2 and T2 ratios in 2018 indicate that the portfolio's performance was worse than the benchmark.

The optimal portfolio in 2019, 2020, 2021, and 2022 outperformed the benchmark, with positive M2 and T2 ratios, indicating superior risk-adjusted performance. The highest M2 and T2 ratios were observed in 2020, indicating that the portfolio's performance was significantly better than the benchmark.

Overall, as we can see here, the fund ended up with a very satisfactory performance, having achieved a holding period return of 45%, or an annualized return of 9.7%.

Do you think the current market trends will continue, and the portfolio will outperform the benchmark once again next year?

// M2, The Modigliani-Modigliani measure - is used to derive the risk-adjusted return of an investment.

// T2, indicates the excess return of the managed portfolio in comparison to the benchmark portfolio after adjusting for differences in the market risk.

So, which approach is right for you?

Passive vs active portfolio management

When it comes to managing your investment portfolio, there are two primary approaches: passive and active portfolio management. Passive portfolio management involves investing in a diversified mix of low-cost index funds or exchange-traded funds (ETFs) that track the performance of a specific market index, such as the Nasdaq. Active portfolio management, on the other hand, involves selecting individual stocks or funds and making trades in an attempt to outperform the market.

So, which approach is right for you? Let's take a closer look at the pros and cons of passive and active portfolio management:

Passive Portfolio Management

Pros:

Lower Fees: typically involves investing in low-cost index funds or ETFs, which have lower fees than actively managed funds. This means that more of your investment returns stay in your pocket.

Simplicity: With a passive portfolio, you don't need to spend time researching individual stocks or funds or monitoring the market on a daily basis. You simply invest in a diversified mix of index funds or ETFs and let the market do the work.

Consistent Returns: Over the long term, passive investments tend to provide consistent returns that closely track the performance of the market. This can help you avoid the ups and downs of individual stocks or funds and stay invested for the long haul.

Cons:

Limited Flexibility: you are limited to the returns of the index or market that you are tracking. You won't be able to outperform the market or take advantage of individual opportunities.

No Personalization: A passive portfolio doesn't take into account your personal investment goals or risk tolerance. You're investing in the same mix of funds as everyone else who is tracking the same index.

Active Portfolio Management

Pros:

Potential for Higher Returns: you have the potential to outperform the market and generate higher returns than passive investments.

Personalization: An actively managed portfolio can be customized to your specific investment goals and risk tolerance.

Flexibility: Active management allows you to take advantage of individual opportunities and make trades based on market conditions.

Cons:

Higher Fees: Active management typically involves higher fees than passive investments. This can eat into your investment returns over time.

Higher Risk: With active management, there is a higher risk of underperforming the market. In addition, it can be difficult to consistently outperform the market over the long term.

More Time-Consuming: Active management requires more time and effort than passive investing. You need to spend time researching individual stocks or funds and monitoring the market on a daily basis.

In conclusion, the choice between passive and active portfolio management ultimately depends on your personal investment goals, risk tolerance, and the amount of time and effort you're willing to put in. Passive investing can be a simple and effective way to invest in the market, while active management provides more flexibility and the potential for higher returns. It's important to do your research and carefully consider your options before making a decision.

PORTFOLIO 2023

To start our 2023 portfolio analysis, first we need to look at QQQ (Invesco QQQ Trust), an exchange-traded fund (ETF) designed to track the performance of the NASDAQ 100 index with low costs and tax efficiency. As a passive ETF, QQQ aims to replicate the performance of the underlying index, rather than outperform it.

If you want to identify the top 20 companies with the highest weight in the NASDAQ 100 using QQQ, you can first use the weight of each company in QQQ, and then choose the 20 companies with the highest weight. The following are the 20 companies with the highest weight in QQQ:

Earnings Per Share

EPS is a carefully examined metric that is often used as a barometer to measure a company's profitability per unit of shareholder ownership. As such, earnings per share are one of the key drivers of stock prices. It is also used as the denominator in the P/E ratio. EPS can be calculated using two different methods: basic and fully diluted.

Using this metric, a simple year-over-year average was used for 20 stocks, selecting the top ten companies with the highest earnings per share growth to participate in the portfolio.

Portfolio Selection

    Markowitz's principle of diversification tells us that investors can reduce the risk of their portfolio simply by holding combinations of instruments that are not perfectly positively correlated with each other. If all assets have a correlation of zero, then they are perfectly uncorrelated. The variance of the portfolio's return is the sum of the squares of all the assets held proportionally multiplied by the variance of the assets' return and their respective covariances, and therefore, the standard deviation of the portfolio is the square root of this variance.

Expected Returns 2023

    As a way to adjust the annual rebalancing, I chose to maximize the Sharpe ratio. This ratio, presented by Sharpe in 1966, is one of the measures used to evaluate the performance of a portfolio and shows that the assets in the portfolio are organized by their return above the risk-free asset of the portfolio, which can also be referred to as excess return.

    As the fund manager, I also consider that the risk-free asset that best served the purposes of the portfolio would be the ten-year US Treasury bonds. Therefore, the yields of these bonds were considered for the portfolio balancing in order to obtain the return of the risk-free asset. Finally, regarding the portfolio management, I made the decision not to engage in short selling and leveraging, thus placing an additional restriction on its performance.

2023

This year, the most efficient point on the curve is the one where, for a risk level of 51.87%, the return is 55.74%. However, given the assumed restrictions, the optimal portfolio also achieves a return of  22.16% for a risk of 25.62%. The optimal portfolio in this case is composed of the following assets and their respective weights: 

Microsoft - 22%

Tesla- 14%

Costco - 64%

Based on these considerations, I will present the year-by-year evaluation of the consequences of this decision in terms of portfolio performance. When we look at the portfolio, it is composed of 60% in the equity portfolio and 40% in Treasury bonds.

Please note that the information provided is for educational and informational purposes only and should not be construed as financial advice. It is important to consult with a licensed financial advisor or professional before making any investment decisions. The use of any information or materials in this context is solely at your own risk.

Introduction

    The purpose of this blog is to share my personal experiences, thoughts, or opinions. Also, provide informative content on the subject I am passionate about, building a community of like-minded individuals who share same interest and establishing myself as a leader in the PM industry.

This blog post will consider the following aspects:

• Playing the role of a manager of an investment fund.

• Companies that are part of the NASDAQ-100 index, as I understand it encompasses companies with strength in technological and electronic growth.

• The companies will be selected based on their annual EPS growth, with a maximum of 10 assets per period.

• The time horizon for the investment portfolio is a period of 60 months, starting in March 2023 and ending in February 2028.

• The portfolio management will follow the Markowitz model, where annual adjustments and balancing will be made based on the maximization of the Sharpe ratio. The performance of the portfolio will also be evaluated against the benchmark.

Finally, the annual performance of the fund will be taken into account.