Managed futures strategy

January 13, 2023 by Youssef LOURAOUI

In this article, Youssef LOURAOUI (Bayes Business School, MSc. Energy, Trade & Finance, 2021-2022) presents the managed futures strategy (also called CTAs or Commodity Trading Advisors). The objective of the managed futures strategy is to look for market trends across different markets.

This article is structured as follow: we introduce the managed futures strategy principle. Then, we present the different types of managed futures strategies available. We also present a performance analysis of this strategy and compare it a benchmark representing all hedge fund strategies (Credit Suisse Hedge Fund index) and a benchmark for the global equity market (MSCI All World Index).

Introduction

According to Credit Suisse (a financial institution publishing hedge fund indexes), a managed futures strategy can be defined as follows: “Managed Futures funds (often referred to as CTAs or Commodity Trading Advisors) focus on investing in listed bond, equity, commodity futures and currency markets, globally. Managers tend to employ systematic trading programs that largely rely upon historical price data and market trends. A significant amount of leverage is employed since the strategy involves the use of futures contracts. CTAs do not have a particular biased towards being net long or net short any particular market.”

Managed futures funds make money based on the points below:

Exploit market trends: trending markets tend to keep the same direction over time (either upwards or downwards)
Combine short-term and long-term indicators: use of short-term and long-term moving averages
Diversify across different markets: at least one market should move in trend
Leverage: the majority of managed futures funds are leveraged in order to get increased exposures to a certain market

Types of managed futures strategies

Managed futures may contain varying percentages of equity and derivative investments. In general, a diversified managed futures account will have exposure to multiple markets, including commodities, energy, agriculture, and currencies. The majority of managed futures accounts will have a trading programme that explains their market strategy. The market-neutral and trend-following strategies are two main methods.

Market-neutral strategy

Market-neutral methods look to profit from mispricing-induced spreads and arbitrage opportunities. Investors that utilise this strategy usually attempt to limit market risk by taking long and short positions in the same industry to profit from both price increases (for long positons) and decreases (for short positions).

Trend-following strategy

Trend-following strategies seek to generate profits by trading long or short based on fundamental and/or technical market indicators. When the price of an asset is falling, trend traders may decide to enter a short position on that asset. On the opposite, when the price of an asset is rising, trend traders may decide to enter a long position. The objective is to collect gains by examining multiple indicators, deciding an asset’s direction, and then executing the appropriate trade.

Methodolgical isuses

The methodology to define a managed futures strategy is described below:

Identify appropriate markets: concentrate on the markets that are of interest for this style of trading strategy
Identify technical indicators: use key technical indicators to assess if the market is trading on a trend
Backtesting: the hedge fund manager will test the indicators retained for the strategy on the market chosen using historical data and assess the profitability of the strategy across a sample data frame. The important point to mention is that the results can be prone to errors. The results obtained can be optimized to historical data, but don’t offer the returns computed historically.
Execute the strategy out of sample: see if the in-sample backtesting result is similar out of sample.

This strategy makes money by investing in trending markets. The strategy can potentially generate returns in both rising and falling markets. However, understanding the market in which this strategy is employed, coupled with a deep understanding of the key drivers behind the trending patterns and the rigorous quantitative approach to trading is of key concern since this is what makes this strategy profitable (or not!).

Performance of the managed futures strategy

Overall, the performance of the managed futures strategy was overall not correlated from equity returns, but volatile (Credit Suisse, 2022). To capture the performance of the managed futures strategy, we use the Credit Suisse hedge fund strategy index. To establish a comparison between the performance of the global equity market and the managed futures strategy, we examine the rebased performance of the Credit Suisse managed futures index with respect to the MSCI All-World Index.

Over a period from 2002 to 2022, the managed futures strategy index managed to generate an annualized return of 3.98% with an annualized volatility of 10.40%, leading to a Sharpe ratio of 0.077. Over the same period, the Credit Suisse Hedge Fund Index managed to generate an annualized return of 5.18% with an annualized volatility of 5.53%, leading to a Sharpe ratio of 0.208. The managed futures strategy had a negative correlation with the global equity index, just about -0.02 overall across the data analyzed. The results are in line with the idea of global diversification and decorrelation of returns derived of the managed futures strategy from global equity returns.

Figure 1 gives the performance of the managed futures funds (Credit Suisse Managed Futures Index) compared to the hedge funds (Credit Suisse Hedge Fund index) and the world equity funds (MSCI All-World Index) for the period from July 2002 to April 2021.

Figure 1. Performance of the managed futures strategy.

Source: computation by the author (Data: Bloomberg)

You can find below the Excel spreadsheet that complements the explanations about the Credit Suisse managed futures strategy.

Why should I be interested in this post?

Understanding the profits and risks of such a strategy might assist investors in incorporating this hedge fund strategy into their portfolio allocation.

Useful resources

Academic research

Pedersen, L. H., 2015. Efficiently Inefficient: How Smart Money Invests and Market Prices Are Determined. Princeton University Press.

Business Analysis

Credit Suisse Hedge fund strategy

Credit Suisse Hedge fund performance

Credit Suisse Managed futures strategy

Credit Suisse Managed futures performance benchmark

About the author

The article was written in January 2023 by Youssef LOURAOUI (Bayes Business School, MSc. Energy, Trade & Finance, 2021-2022).

Equity market neutral strategy

January 11, 2023 by Youssef LOURAOUI

In this article, Youssef LOURAOUI (Bayes Business School, MSc. Energy, Trade & Finance, 2021-2022) presents the equity market neutral strategy. The objective of the equity market neutral strategy is to benefit from both long and short positions while minimizing the exposure to the equity market fluctuations.

This article is structured as follow: we introduce the equity market neutral strategy. Then, we present a practical case study to grasp the overall methodology of this strategy. We conclude with a performance analysis of this strategy in comparison with a global benchmark (MSCI All World Index and the Credit Suisse Hedge Fund index).

Introduction

According to Credit Suisse (a financial institution publishing hedge fund indexes), an equity market neutral strategy can be defined as follows: “Equity Market Neutral funds take both long and short positions in stocks while minimizing exposure to the systematic risk of the market (i.e., a beta of zero is desired). Funds seek to exploit investment opportunities unique to a specific group of stocks, while maintaining a neutral exposure to broad groups of stocks defined for example by sector, industry, market capitalization, country, or region. There are a number of sub- sectors including statistical arbitrage, quantitative long/short, fundamental long/short and index arbitrage”. This strategy makes money by holding assets that are decorrelated from a specific benchmark. The strategy can potentially generate returns in falling markets.

Mathematical foundation for the beta

This strategy relies heavily on the beta, derived from the capital asset pricing model (CAPM). Under this framework, we can relate the expected return of a given asset and its risk:

Where :

E(r) represents the expected return of the asset
r_f the risk-free rate
β a measure of the risk of the asset
E(r_m) the expected return of the market
E(r_m) – r_f represents the market risk premium.

In this model, the beta (β) parameter is a key parameter and is defined as:

Where:

Cov(r, r_m) represents the covariance of the asset return with the market return
σ²(r_m) is the variance of market return.

The beta is a measure of how sensitive an asset is to market swings. This risk indicator aids investors in predicting the fluctuations of their asset in relation to the wider market. It compares the volatility of an asset to the systematic risk that exists in the market. The beta is a statistical term that denotes the slope of a line formed by a regression of data points comparing stock returns to market returns. It aids investors in understanding how the asset moves in relation to the market. According to Fama and French (2004), there are two ways to interpret the beta employed in the CAPM:

According to the CAPM formula, beta may be thought in mathematical terms as the slope of the regression of the asset return on the market return observed on different periods. Thus, beta quantifies the asset sensitivity to changes in the market return;
According to the beta formula, it may be understood as the risk that each dollar invested in an asset adds to the market portfolio. This is an economic explanation based on the observation that the market portfolio’s risk (measured by 〖σ(r_m)〗^2) is a weighted average of the covariance risks associated with the assets in the market portfolio, making beta a measure of the covariance risk associated with an asset in comparison to the variance of the market return.

Additionally, the CAPM makes a distinction between two forms of risk: systematic and specific risk. Systematic risk refers to the risk posed by all non-diversifiable elements such as monetary policy, political events, and natural disasters. By contrast, specific risk refers to the risk inherent in a particular asset and so is diversifiable. As a result, the CAPM solely captures systematic risk via the beta measure, with the market’s beta equal to one, lower-risk assets having a beta less than one, and higher-risk assets having a beta larger than one.

Application of an equity market neutral strategy

For the purposes of this example, let us assume that a portfolio manager wants to invest $100 million across a diverse equity portfolio while maintaining market-neutral exposure to market index changes. To create an equity market-neutral portfolio, we use five stocks from the US equity market: Apple, Amazon, Microsoft, Goldman Sachs, and Pfizer. Using monthly data from Bloomberg for the period from 1999 to 2022, we compute the returns of these stocks and their beta with the US equity index (S&P500). Using the solver function on Excel, we find the weights of the portfolio with the maximum expected return with a beta equal to zero.

Table 1 displays the target weights needed to build a portfolio with a neutral view on the equity market. As shown by the target allocation in Table 1, we can immediately see a substantial position of 186.7 million dollars on Pfizer while keeping a short position on the remaining equity positions of the portfolio totaling 86.7 million dollars in short positions. Given that the stocks on the short list have high beta values (more than one), this allocation makes sense. Pfizer is the only defensive stock and has a beta of 0.66 in relation to the S&P 500 index.

If the investment manager allocated capital in the following way, he would create an equity market neutral portfolio with a beta of zero:

Apple: -$4.6 million (-4.6% of the portfolio; a weighted-beta of -0.066)
Amazon: -$39.9 million (-39.9% of the portfolio; a weighted-beta of -0.592)
Microsoft: -$16.2 million (-16.2% of the portfolio; a weighted-beta of -0.192)
Goldman Sachs: -$26 million (-26% of the portfolio; a weighted-beta of -0.398)
Pfizer: $186.7 million (186.7% of the portfolio; a weighted-beta of 1.247)

Table 1. Target weights to achieve an equity market neutral portfolio.
Source: computation by the author (Data: Bloomberg)

You can find below the Excel spreadsheet that complements the explanations about the equity market neutral portfolio.

An extension of the equity market neutral strategy to other asset classes

A portfolio with a beta of zero, or zero systematic risk, is referred to as a zero-beta portfolio. A portfolio with a beta of zero would have an expected return equal to the risk-free rate. Given that its expected return is equal to the risk-free rate or is relatively low compared to portfolios with a higher beta. Such portfolio would have no correlation with market movements.

Since a zero-beta portfolio has no market exposure and would consequently underperform a diversified market portfolio, it is highly unlikely that investors will be interested in it during bull markets. During a bear market, it may garner some interest, but investors are likely to ask if investing in risk-free, short-term Treasuries is a better and less expensive alternative to a zero-beta portfolio.

For this example, we imagine the case of a portfolio manager wishing to invest 100M$ across a diversified portfolio, while holding a zero-beta portfolio with respect to a broad equity index benchmark. To recreate a diversified portfolio, we compiled a shortlist of trackers that would represent our investment universe. To maintain a balanced approach, we selected trackers that would represent the main asset classes: global stocks (VTI – Vanguard Total Stock Market ETF), bonds (IEF – iShares 7-10 Year Treasury Bond ETF and TLT – iShares 20+ Year Treasury Bond ETF), and commodities (DBC – Invesco DB Commodity Index Tracking Fund and GLD – SPDR Gold Shares).

To construct the zero-beta portfolio, we pulled a ten-year time series from Refinitiv Eikon and calculated the beta of each asset relative to the broad stock index benchmark (VTI tracker). The target weights to create a zero-beta portfolio are shown in Table 2. As captured by the target allocation in Table 2, we can clearly see an important weight for bonds of different maturities (56.7%), along with a 33.7% towards commodities and a small allocation towards global equity equivalent to 9.6% (because of the high beta value).

If the investment manager allocated capital in the following way, he would create a zero-beta portfolio with a beta of zero:

VTI: $9.69 million (9.69% of the portfolio; a weighted-beta of 0.097)
IEF: $18.99 million (18.99% of the portfolio; a weighted-beta of -0.029)
GLD: $18.12 million (18.12% of the portfolio; a weighted-beta of 0.005)
DBC: $15.5 million (15.50% of the portfolio; a weighted-beta of 0.070)
TLT: $37.7 million (37.7% of the portfolio; a weighted-beta of -0.143)

Table 2. Target weights to achieve a zero-beta portfolio.
Source: computation by the author. (Data: Reuters Eikon)

You can find below the Excel spreadsheet that complements the explanations about the zero beta portfolio.

Performance of the equity market neutral strategy

To capture the performance of the equity market neutral strategy, we use the Credit Suisse hedge fund strategy index. To establish a comparison between the performance of the global equity market and the equity market neutral strategy, we examine the rebased performance of the Credit Suisse managed futures index with respect to the MSCI All-World Index.

The equity market neutral strategy generated an annualized return of -0.18% with an annualized volatility of 7.5%, resulting in a Sharpe ratio of -0.053. During the same time period, the Credit Suisse Hedge Fund index had an annualized return of 4.34 percent with an annualized volatility of 5.64 percent, resulting in a Sharpe ratio of 0.174. With a neutral market beta exposure of 0.04, the results are consistent with the theory that this approach does not carry the equity risk premium. This aspect justifies the underperformance.

Figure 1 gives the performance of the equity market neutral funds (Credit Suisse Equity Market Neutral Index) compared to the hedge funds (Credit Suisse Hedge Fund index) and the world equity funds (MSCI All-World Index) for the period from July 2002 to April 2021.

Figure 1. Performance of the equity market neutral strategy.

Source: computation by the author (Data: Bloomberg)

You can find below the Excel spreadsheet that complements the explanations about the Credit Suisse equity market neutral strategy.

Why should I be interested in this post?

Understanding the performance and risk of the equity market neutral strategy might assist investors in incorporating this hedge fund strategy into their portfolio allocation.

Useful resources

Academic research

Pedersen, L. H., 2015. Efficiently Inefficient: How Smart Money Invests and Market Prices Are Determined. Princeton University Press.

Business Analysis

Credit Suisse Hedge fund strategy

Credit Suisse Hedge fund performance

Credit Suisse Equity market neutral strategy

Credit Suisse Equity market neutral performance benchmark

About the author

The article was written in January 2023 by Youssef LOURAOUI (Bayes Business School, MSc. Energy, Trade & Finance, 2021-2022).

Global macro strategy

January 9, 2023 by Youssef LOURAOUI

In this article, Youssef LOURAOUI (Bayes Business School, MSc. Energy, Trade & Finance, 2021-2022) presents the global macro equity strategy, one of the most widely known strategies in the hedge fund industry. The goal of the global macro strategy is to look for trends or disequilibrium in equity, bonds, currency or alternative assets based on broad economic data using a top-down approach.

This article is structured as follow: we introduce the global macro strategy principle. Then, we present a famous case study to grasp the overall methodology of this strategy. We conclude with a performance analysis of this strategy in comparison with a global benchmark (MSCI All World Index and the Credit Suisse Hedge Fund index).

Introduction

According to Credit Suisse, a global macro strategy can be defined as follows: “Global Macro funds focus on identifying extreme price valuations and leverage is often applied on the anticipated price movements in equity, currency, interest rate and commodity markets. Managers typically employ a top-down global approach to concentrate on forecasting how political trends and global macroeconomic events affect the valuation of financial instruments. Profits are made by correctly anticipating price movements in global markets and having the flexibility to use a broad investment mandate, with the ability to hold positions in practically any market with any instrument. These approaches may be systematic trend following models, or discretionary.”

This strategy can generate returns in both rising and falling markets. However, asset screening is of key concern, and the ability of the fund manager to capture the global macro picture that is driving all asset classes is what makes this strategy profitable (or not!).

The greatest trade in history

The greatest trade in history (before Michael Burry becomes famous for anticipating the Global financial crisis of 2008 linked to the US housing market) took place during the 1990’s when the UK was intending to join the Exchange Rate Mechanism (ERM) founded in 1979. This foreign exchange (FX) system involved eight countries with the intention to move towards a single currency (the Euro). The currencies of the countries involved would be adjustably pegged with a determined band in which they can fluctuate with respect to the Deutsche Mark (DEM), the currency of Germany considered as the reference of the ERM.

Later in 1992, the pace at which the countries adhering to the ERM mechanism were evolving at different rate of growth. The German government was in an intensive spending following the reunification of Berlin, with important stimulus from the German Central Bank to print more money. However, the German government was very keen on controlling inflation to satisfactory level, which was achieved by increasing interest rates in order to curb the inflationary pressure in the German economy.

In the United Kingdom (UK), another macroeconomic picture was taking place: there was a high unemployment coupled with already relatively high interest rates compared to other European economies. The Bank of England was put in a very tight spot because they were facing two main market scenarios:

To increase interest rates, which would worsen the economy and drive the UK into a recession
To devalue the British Pound (GBP) by defending actively in the FX market, which would cause the UK to leave the ERM mechanism.

The Bank of England decided to go with the second option by defending the British Pound in the FX market by actively buying pounds. However, this strategy would not be sustainable over time. Soros (and other investors) had seen this disequilibrium and shorted British Pound and bought Deutsche Mark. The situation got completely off control for the Bank of England that in September 1992, they decided to increase interest rates, which were already at 10% to more than 15% to calm the selling pressure. Eventually, the following day, the Bank of England announced the exit of the UK from the ERM mechanism and put a hold on the increase of interest rate to the 12% until the economic conditions get better. Figure 1 gives the evolution of the exchange rate between the British Pound (GBP) and the Deutsche Mark (DEM) over the period 1991-1992.

Figure 1. Evolution of the GBP-DEM (British Pound / Deutsche Mark FX rate).
Global macro performance
Source: Bloomberg.

It was reported that Soros amassed a position of $10 billion and gained a whopping $1 billion for this trade. This event put Soros in the scene as the “man who broke the Bank of England”. The good note about this market event is that the UK economy emerged much healthier than the European countries, with UK exports becoming much more competitive as a result of the pound devaluation, which led the Bank of England to cut rates cut down to the 5-6% level the years following the event, which ultimately helped the UK economy to get better.

Performance of the global macro strategy

Overall, the performance of the global macro funds between 1994-2020 was steady, with occasional large drawdowns (Asian crisis 1998, Dot-com bubble 2000’s, Great Financial Crisis of 2008, Covid-19 pandemic 2020). On a side note, the returns seem smaller and less volatile since 2000 onwards (Credit Suisse, 2022).

To capture the performance of the global macro strategy, we use the Credit Suisse hedge fund strategy index. To establish a comparison between the performance of the global equity market and the global macro hedge fund strategy, we examine the rebased performance of the Credit Suisse index with respect to the MSCI All-World Index. Over a period from 2002 to 2022, the global macro strategy index managed to generate an annualized return of 7.85% with an annualized volatility of 5.77%, leading to a Sharpe ratio of 0.33. Over the same period, the MSCI All World Index managed to generate an annualized return of 6.00% with an annualized volatility of 15.71%, leading to a Sharpe ratio of 0.08. The low correlation of the long-short equity strategy with the MSCI All World Index is equal to -0.02, which is close to zero. The results are in line with the idea of global diversification and decorrelation of returns derived from the global macro strategy from global equity returns. Overall, the Credit Suisse hedge fund strategy index performed better worse than the MSCI All World Index, leading to a higher Sharpe ratio (0.33 vs 0.08).

Figure 2 gives the performance of the global macro funds (Credit Suisse Global Macro Index) compared to the hedge funds (Credit Suisse Hedge Fund index) and the world equity funds (MSCI All-World Index) for the period from July 2002 to April 2021.

Figure 2. Performance of the global macro strategy.

Source: computation by the author (data: Bloomberg).

You can find below the Excel spreadsheet that complements the explanations about the global macro hedge fund strategy.

Why should I be interested in this post?

Global macro funds seek to profit from market dislocations across different asset classes. reduce negative risk while increasing market upside. They might, for example, invest in inexpensive assets that the fund managers believe will rise in price while simultaneously shorting overvalued assets to cut losses. Other strategies used by global macro funds to lessen market volatility can include leverage and derivatives. Understanding the profits and risks of such a strategy might assist investors in incorporating this hedge fund strategy into their portfolio allocation.

Useful resources

Academic research

Pedersen, L. H., 2015. Efficiently Inefficient: How Smart Money Invests and Market Prices Are Determined. Princeton University Press.

Business Analysis

Credit Suisse Hedge fund strategy

Credit Suisse Hedge fund performance

Credit Suisse Global macro strategy

Credit Suisse Global macro performance benchmark

About the author

The article was written in January 2023 by Youssef LOURAOUI (Bayes Business School, MSc. Energy, Trade & Finance, 2021-2022).

Asset allocation techniques

December 19, 2022 by Youssef LOURAOUI

In this article, Youssef LOURAOUI (Bayes Business School, MSc. Energy, Trade & Finance, 2021-2022) presents the concept of asset allocation, a pillar concept in portfolio management.

This article is structured as follows: we introduce the notion of asset allocation, and we use a practical example to illustrate this notion.

Introduction

An investment portfolio is a collection of assets that are owned by an investor. Individual assets, such as bonds and stocks, as well as asset baskets, such as mutual funds or exchange-traded funds, can be employed. When constructing a portfolio, investors often consider both the projected return and risk. A well-balanced portfolio includes a wide range of investments to benefit from diversification.

The asset allocation is one of the processes in the portfolio construction process. At this point, the investor (or fund manager) must divide the available capital into a number of assets that meet the criteria in terms of risk and return trade-off, while adhering to the investment policy, which specifies the amount of exposure an investor can have and the amount of risk the fund manager can hold in his or her portfolio.

The next phase in the process is to evaluate the risk and return characteristics of the various assets. The analyst develops economic and market expectations that can be used to develop a recommended asset allocation for the customer. The distribution of equities, fixed-income securities, and cash; sub asset classes, such as corporate and government bonds; and regional weightings within asset classes are all decisions that must be taken in the portfolio’s asset allocation. Real estate, commodities, hedge funds, and private equity are examples of alternative assets. Economists and market strategists may set the top-down view on economic conditions and broad market movements. The returns on various asset classes are likely to be altered by economic conditions; for example, equities may do well when economic growth has been surprisingly robust whereas bonds may do poorly if inflation soars. These situations will be forecasted by economists and strategists.

The top-down approach

A top-down approach begins with assessment of macroeconomic factors. The investor examines markets and sectors based on the existing and projected economic climate in order to invest in those that are predicted to perform well. Finally, funding is evaluated for specific companies within these categories.

The bottom up approach

A bottom-up approach focuses on company-specific variables such as management quality and business potential rather than economic cycles or industry analysis. It is less concerned with broad economic trends than top-down analysis is, and instead focuses on company particular.

Types of asset allocations

Arnott and Fabozzi (1992) divide asset allocation into three types: 1) policy asset allocation; 2) dynamic asset allocation; and 3) tactical asset allocation.

Policy asset allocation

The policy asset allocation decision is a long-term asset allocation decision in which the investor aims to assess a suitable long-term “normal” asset mix that represents an optimal mixture of controlled risk and enhanced return. The strategies that offer the best prospects of achieving strong long-term returns are inherently risky. The strategies that offer the greatest safety tend to offer very moderate return opportunities. The balancing of these opposing goals is known as policy asset allocation. The asset mix (i.e., the allocation among asset classes) is mechanistically altered in response to changing market conditions in dynamic asset allocation. Once the policy asset allocation has been established, the investor can focus on the possibility of active deviations from the regular asset mix established by policy. Assume the long-run asset mix is established to be 60% equities and 40% bonds. A variation from this mix under certain situations may be tolerated. A decision to diverge from this mix is generally referred to as tactical asset allocation if it is based on rigorous objective measurements of value. Tactical asset allocation does not consist of a single, well-defined strategy.

Dynamic asset allocation

The term “dynamic asset allocation” can refer to both long-term policy decisions and intermediate-term efforts to strategically position the portfolio to benefit from big market swings, as well as aggressive tactical strategies. As an investor’s risk expectations and tolerance for risk fluctuate, the normal or policy asset allocation may change. It is vital to understand what aspect of the asset allocation decision is being discussed and in what context the words “asset allocation” are being used when delving into asset allocation difficulties.

Tactical asset allocation

Tactical asset allocation broadly refers to active strategies that seek to enhance performance by opportunistically adjusting the asset mix of a port- folio in response to the changing patterns of reward available in the capi- tal markets. Notably, tactical asset allocation tends to refer to disciplined techniques for evaluating anticipated rates of return on various asset classes and constructing an asset allocation response intended to capture larger rewards.

Asset allocation application: an example

For this example, lets suppose the fictitious following scenario with real data involved:

Mr. Dubois recently sold his local home construction company in the south of France to a multinational homebuilder with a nationwide reach. He accepted a job as regional manager for that national homebuilder after selling his company. He is now thinking about the financial future for himself and his family. He is looking forward to his new job, where he enjoys his new role and where he will earn enough money to meet his family’s short- and medium-term liquidity demands. He feels strongly that he should not invest the profits of the sale of his company in real estate because his income currently rely on the state of the real estate market. He speaks with a financial adviser at his bank about how to invest his money so that he can retire comfortably in 20 years.

The initial portfolio objective they created seek a nominal return goal of 7% with a Sharpe ratio of at least 1 (for this example, we consider the risk-free rate to be equal to zero). The bank’s asset management division gives Mr Dubois and his adviser with the following data (Figure 1) on market expectations.

Figure 1. Risk, return and correlation estimates on market expectation.
Time-series regression
Source: computation by the author (Data: Refinitiv Eikon).

In order to replicate a global asset allocation approach, we shortlisted a number of trackers that would represent our investment universe. To keep a well-balanced approach, we took trackers that would represent the main asset classes: global equities (VTI – Vanguard Total Stock Market ETF), bonds (IEF – iShares 7-10 Year Treasury Bond ETF and TLT – iShares 20+ Year Treasury Bond ETF) and commodities (DBC – Invesco DB Commodity Index Tracking Fund and GLD – SPDR Gold Shares). To create the optimal asset allocation, we extracted the equivalent of a ten-year timeframe from Refinitiv Eikon to capture the overall performance of the portfolio in the long run. As captured in Figure 1, the global equities was the best performing asset class during the period covered (13.02% annualised return), followed by long term bond (4.78% annualised return) and by gold (4.65% annualised return).

Figure 2. Asset class performance (rebased to 100).
Time-series regression
Source: computation by the author (Data: Refinitiv Eikon).

After analyzing the historical return on the assets retained, as well as their volatility and covariance (and correlation), we can apply Mean-Variance portfolio optimization to determine the optimal portfolio. The optimal asset allocation would be the end outcome of the optimization procedure. The optimal portfolio, according to Markowitz’ seminal study on portfolio construction, will seek to create the best risk-return trade-off for an investor. After performing the calculations, we notice that investing 42.15% in the VTI fund, 30.69% in the IEF fund, 24.88% in the TLT fund, and 2.28% in the GLD fund yields the best asset allocation. As reflected in this asset allocation, the investor intends to invest his assets in a mix of equities (about 43%) and bonds (approximately 55%), with a marginal position (around 3%) in gold, which is widely employed in portfolio management as an asset diversifier due to its correlation with other asset classes. As captured by this asset allocation, we can clearly see the defensive nature of this portfolio, which relies significantly on the bond part of the allocation to operate as a hedge while relying on the equities part as the main driver of returns.

As shown in Figure 3, the optimal asset allocation has a better Sharpe ratio (1.27 vs 0.62) and is captured farther along the efficient frontier line than a naive equally-weighted allocation . The only portfolio with the needed characteristics is the optimal one, as the investor’s goal was to attain a 7% projected return with a minimum Sharpe ratio of 1.

Figure 3. Optimal asset allocation and the Efficient Frontier plot.
Time-series regression
Source: computation by the author (Data: Refinitiv Eikon).

Will this allocation, however, continue to perform well in the future? The market’s reliance on future expectations, return, volatility, and correlation predictions, as well as the market regime, will ultimately determine how much the performance predicted by this study will really change in the future.

Excel file for asset allocation

You can find below the Excel spreadsheet that complements the example above.

Why should I be interested in this post?

The purpose of portfolio management is to maximize (expected) returns on the entire portfolio, not just on one or two stocks for a given level of risk. By monitoring and maintaining your investment portfolio, you can build a substantial amount of wealth for a variety of financial goals, such as retirement planning. This post facilitates comprehension of the fundamentals underlying portfolio construction and investing.

Useful resources

Academic research

Arnott, R. D., and F. J. Fabozzi. 1992. The many dimensions of the asset allocation decision. In Active asset allocation, edited by R. Arnott and F. J. Fabozzi. Chicago: Probus Publishing.

Fabozzi, F.J., 2009. Institutional Investment Management: Equity and Bond Portfolio Strategies and Applications. I (4-6). John Wiley and Sons Edition.

Pamela, D. and Fabozzi, F., 2010. The Basics of Finance: An Introduction to Financial Markets, Business Finance, and Portfolio Management. John Wiley and Sons Edition.

About the author

The article was written in December 2022 by Youssef LOURAOUI (Bayes Business School, MSc. Energy, Trade & Finance, 2021-2022).

Art as an asset class

January 30, 2024November 2, 2022 by Nakul PANJABI

Art as an asset class

In this article, Nakul PANJABI (ESSEC Business School, Grande Ecole Program – Master in Management, 2021-2024) talks about the Art as an asset class.

Before delving into the economics of the art market and art’s significance as an asset class, let us first recollect the definition of an asset and an asset class. An asset broadly refers to a resource from which future economic benefits are expected to flow. An asset class is a group of assets that have similar characteristics and related risk and return behavior. Common examples of asset class would be equities, fixed-income investments, and real estate.

Why have you not invested in art yet?

Although an age-old investment, art as an investment has been available to only a minority of investors most of whom are high-net-worth individuals (HNWI) or even ultra-high-net-worth individuals (UHNWI). The prime reason is that the market faces an inelastic supply. In simple terms, there are very few goods in market to be traded which leads to higher prices of each item and therefore, at equilibrium, only few people with such means could afford the good. This economic explanation of the art market would be enough if there were very few art items available to buy. However, as intuition might suggest, that is not the case. The world is filled with pieces of art and people who own it. Does this fact weaken our previous argument? The answer is simply No. Even though there are lots of art item and anyone with some spare money can buy a piece of art, almost none of those items would be classified as an asset. Art as an Asset class has an extremely limited supply. Only a few pieces of art are purchased as Asset.

Features of the Art Market

Besides limited supply and consequently higher prices, there are few other factors as well that makes art an interesting asset class. Firstly, the investable art items are highly illiquid. Selling a collectible art item is a time-consuming complex process. It requires dealers, auctions and most importantly potential buyers who could afford such an expensive item that provides no economic benefits except capital appreciation. As one might guess, there are only a handful of individuals in the world who own a 50-million-dollar painting.

Secondly, the supply of this asset class is not closely related to the cost of producing it. Most goods’ supply is based on the cost of producing them. For example, it is cheap to produce toothpaste, so it has an elastic supply. If there is a strike at a toothpaste factory, then there would be less people to make the toothpaste. This will increase the wages (cost of production) paid to them. Now fewer toothpastes would be produced at a higher price. This will make the supply of toothpaste relatively inelastic. However, this economic phenomenon seems to be missing in the art market. The supply of this asset class is highly inelastic but the goods that represent investable art are very cheap to produce. The low cost of production does not dictate the supply of collectible art. It is the rarity of these goods that cause such an inelastic supply. A lot of Investable art items are works of deceased artists. Although they probably were very cheap to produce, it is impossible to create more of them. The rarity of such items makes them so valuable.

Art has a very high maintenance cost and most of the art do not provide any recurring cashflows. One source of art cashflows is the income generated from renting art to museums. Because there is a limit to the number of paintings that can be displayed in museums, most of the return from art investments is generated through capital appreciation. However, as we discussed before, it is not so easy to sell a piece of art. Then, why would anyone, let alone the most sophisticated of investors, buy such an asset? Well, there are a lot of reason why one might invest in art.

Reasons to invest in the art market

Low correlation

Art has a low correlation with traditional asset class. Fluctuations in Apple’s stock price would probably have little effect on the price of an authentic Picasso painting. Thanks to this low correlation, a collectible painting can act as a hedge against inflation and market crashes. According to a 2022 Citibank report, art has either a weak positive correlation or zero correlation with other asset classes.

Tax Benefits

Given the fact that the value of investable art does not derive from either its future cashflows or its cost of production, it is relatively easier to manipulate its price than it is for other assets. Manipulating the price of an asset is extremely useful to manipulate income and consequently taxes.

Money laundering

Art Investments have also been used for money laundering. The logic is straightforward. A 50-million-dollar painting can be much easily hidden than cash or gold of similar value.

Status Symbol

Art is a very efficient status symbol. The rarity of the collectible art items makes owning them a source of prestige. If your friend owns one of the only five paintings created by a famous renaissance painter, you don’t need to be an expert in art to judge the economic worth of the painting or of your friend.

What Future looks like for the art market

According to the annual report by Art Basel and UBS Global Art, the worldwide art sales crossed $65.1 billion in 2021. This reflects a 29% increase from the previous year.

Moreover, with increase in the trend of NFT trading, millennials are more interested in (digital) art than ever. According to 2021 study by Art Basel and UBS Global Art, millennials were the highest spenders on fine art in 2020.

Now, with an increase in art investing funds, the barriers for art investing have also been reduced tremendously. People, who could not invest in art because of high capital requirement and lack of expertise, can now do so by investing in an art fund.

Why should I be interested in this post?

As an (wealthy) investor, art represents an asset class which is not highly correlated with traditional assets. It then can be useful for asset allocation in terms of diversification. When you think of your personal portfolio, you may think of art.

About the author

The article was written in November 2022 by Nakul PANJABI (ESSEC Business School, Grande Ecole Program – Master in Management, 2021-2024).

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