When it comes to software for wealth-management platforms, development experience is not the only must-have for developers. Domain knowledge is a crucial factor in the successful execution of software. If developers understand terminology and processes in capital markets, they will better appreciate tasks and won’t need to spend time acquiring basic knowledge in the domain and redoing poor work caused by misunderstanding of terms.
Here, I provide some basic financial and investment terminology that will be useful to software developers who want to better understand robo-advisory. To dig even deeper, it is important to learn more about capital markets and financial engineering.
Robo-advisors are software platforms that provide an online service to generate financial advice according to clients’ preferences and portfolio, and market trends. Advice is generated automatically based on mathematical algorithms that depend on the selected investment model or a mixture of several models, such as Modern Portfolio Theory (MPT), Capital Asset Pricing Model (CAPM), the Black Litterman Model, the Fama–French Model, etc. The mathematical algorithm used considers three main aspects:
- The historical long-term performance data of assets;
- Information that clients have provided about their investing goals, timeline, and earnings;
- A menu of investments.
The main purpose of robo-advisors is to meet clients’ financial objectives by analyzing their status and setting a program to achieve their goals. Robo-advisers suggest an appropriate proportion of stocks, bonds, and cash; then, over time, they buy and sell specific investments to achieve clients’ goals.
Assets and securities
An asset is an investment instrument that can be bought and sold. The return of an asset is the percentage value increase from the time it was bought to the time it is sold (realized gain) or may be sold (unrealized gain). This can be shown as:
R = return of an asset;
Vcur = current value of an asset;
Vin = initial value of an asset.
A security is an asset that represents the ownership of a stock, the credit from a bond, or the right to ownership from an option.
A stock is a type of security that signifies ownership in a corporation and represents a claim to part of the corporation’s assets and earnings.
A bond is a debt investment in which an investor loans money to an entity (typically corporate or governmental) which borrows the funds for a defined period of time at a variable or fixed interest rate.
An option is the right, but not the obligation, to buy (or sell) an asset under specified terms.
The set of all financial assets held by a client, including stocks, bonds, mutual funds, ETFs and cash, is known as their portfolio. The client’s wealth is a function of their entire portfolio. The return of the portfolio is a weighted average of each asset’s returns.
Portfolios should be built in accordance with the clients’ objectives and risk tolerance. Robo-advisors allow clients to accomplish long-term financial objectives by developing a model of portfolio allocations.
The portfolio return is the monetary yield experienced by the portfolio holder. Expected portfolio return is calculated as the weighted average of the likely profits of assets in the portfolio, weighted by the likely profits of each asset class, or:
E[R] = expected return of n asset allocations;
Ri = weight of portfolio allocation to a particular asset (specifies how much money is invested in a particular asset related to the total amount invested in the entire portfolio);
Pi = potential profit of the particular asset.
Portfolio return can be calculated through various methodologies, such as time-weighted (the compounded growth rate of assets over the period being measured) and money-weighted (the measure of profitability of assets) returns.
Portfolio variance (or portfolio risk)
Portfolio variance is a measurement of how the aggregate returns of a set of assets making up a portfolio fluctuate over time. It may be defined as a function of potential portfolio returns and associated probabilities, as follows:
A variance analysis is the process of weighing risk (variance) against expected return. However, unlike risk, which indicates the possibility of losing some or all of the investment, variance measures the variability from an average. A variance value can help to determine the risk of a particular asset and the entire portfolio. Generally, portfolio variance is less than the weighted average of individual asset variances.
In investment, risk tolerance is the degree of variability in returns that a client is willing to absorb. The client’s degree of risk tolerance can be assessed by taking a risk-related questionnaire, wherein they define how much money they would feel comfortable losing if their investments were to have a bad period. Risk tolerance is affected by factors such as time horizon, earning capacity, current assets, and purpose of savings.
Portfolio management entails the making decisions about the investment mix and policy, matching investments to objectives, allocating assets for individuals and institutions, and balancing risk against performance. Portfolio holders typically wish to maximize their return with the least amount of risk possible. When faced with two investment opportunities with similar returns, a portfolio manager (or robo-advisor) will always choose the investment with the least risk as there is no benefit to choosing a higher level of risk unless there is also an increased level of return.
The portfolio-management process is followed by robo-advisors to aid portfolio holders in meeting their investment goals. The procedure is as follows:
- Creating a Policy Statement—The policy statement details the portfolio holder’s goals, risk tolerance and timeline. To create it, the client completes a questionnaire provided by the robo-advisor.
- Developing an Investment Strategy—The robo-advisor creates a strategy that combines the client’s goals and objectives with current financial market and economic conditions.
- Implementing the Plan Created—The robo-advisor puts the investment strategy to work, investing in a portfolio that meets the client’s goals and constraint requirements.
- Monitoring and Updating the Plan—The robo-advisor monitors market changes as they occur, updates the plan, and rebalances the client’s portfolio according to the updated plan.
The time horizon is the length of time over which an investment is made or held before it is liquidated. The time horizon generally depends on the client’s savings objectives (retirement, college, etc.). Time horizons are usually expressed in years. Time horizons of less than three years determine short-term planning, while time horizons of 10 and more years determine long-term horizons. As the liquidation date approaches, the time horizon shortens, which leads to a change in the algorithm for generating advice.
Asset allocation is the investment strategy, or combination of strategies, that aims to reduce risk and improve portfolio returns. According to the client’s objectives, risk tolerance and time horizon, robo-advisors apportion of portfolio assets to balance risk and return. There is no simple formula to find the best asset allocation; each strategy has its own approach. Key strategies include the following:
- Strategic asset allocation distributes a proportional combination of assets based on the expected return for each asset class. This approach provides the optimal balance between expected risk and return for a long-term investment horizon. However, this approach does not change the client’s allocation according to changing market or economic conditions.
- Dynamic asset allocation builds portfolios by providing the optimal balance between expected risk and return for a long-term investment horizon. However, unlike strategic asset allocation, this approach adjusts apportionment over time relative to changes in the economic environment. With this strategy, assets in decline should be sold while assets that are increasing should be purchased.
- Tactical asset allocation creates extra value by taking advantage of certain situations in the market. With this strategy, the client should be more active in positioning their portfolio based on those assets, sectors, or individual stocks that show the most potential for perceived gains.
- Insured asset allocation allows the portfolio to be increased as much as possible; however, the portfolio does not drop under the base portfolio value established by the client. This strategy ideally suits clients who desire active portfolio management.
- Integrated asset allocation includes aspects of different strategies and accounts for expectations, risk tolerance, and actual changes in markets.
The cost basis is the original cost of an asset, which is usually the purchase price. This value is used for tax purposes to determine the capital gain or loss, which equals the difference between the asset’s cost basis and the current market value. Using the correct cost basis is extremely important when the client reinvests dividends instead of taking the earnings in cash. As dividends are reinvested, the adjusted cost basis should be increased by the amount of reinvested dividends; otherwise, taxes will be paid twice on the reinvested earnings.
The total assets owned by a client are known as their asset base. The value of the asset base is not fixed, but may increase or decrease according to appreciation or depreciation in asset value, which is shaped by market forces. The asset base may be computed for a particular moment in time; data needed for computing it is received from data aggregators such as Quovo, MorningStar, Yodlee, TD Ameritrade, etc.
Capital Asset Pricing Model
CAPM calculates expected return based on expected rate of return on the market, the risk-free rate and the beta coefficient of the stock. According to CAPM, the formula for calculating the expected return of an asset is as follows:
E[R] = expected return of the asset;
Rf = risk-free rate;
β = beta coefficient (risk measure) of the asset;
Rm = expected rate of return on the market.
The general idea behind CAPM is that investors need to be compensated in two ways: time value of money (represented by the risk-free rate Rf) and risk (represented by the other half of the formula). If the expected return does not meet or beat the required return, the investment should not be undertaken.
To optimize the expected return, MPT is used. MPT shows that specific risk can be removed through diversification; it allows robo-advisors to construct portfolios to optimize or maximize expected return based on a given level of market risk, emphasizing that risk is an inherent part of higher reward. However, diversification doesn’t solve the problem of systematic risk; even a portfolio with all the shares in the stock market cannot eliminate that risk.
Optimal portfolios that offer the highest expected return for a defined level of risk, or the lowest risk for a given level of expected return, are said to have an efficient frontier. Optimal portfolios that comprise the efficient frontier tend to have a higher degree of diversification compared to suboptimal ones, which are typically less diversified.
One end of the efficient frontier includes securities that are expected to have a high degree of risk coupled with high potential returns, which is suitable for highly risk-tolerant investors. Conversely, securities that lie on the other end of the efficient frontier are expected to have a low degree of risk coupled with low potential returns, and are suitable for risk-averse investors.
The efficient frontier concept was introduced by Nobel Laureate Harry Markowitz in 1952, and is a cornerstone of MPT.
The Sharpe ratio is one of the most referenced risk/return measures used in finance. The ratio describes how much excess return a client receives for the extra volatility that they endure for holding a riskier asset. The formula for calculating the Sharpe ratio of an asset is as follows:
S(x) = Sharpe ratio of asset x;
Rx = average rate of return of x;
Rf = best available rate of return of a risk-free asset;
σ(x) = standard deviation (return volatility) of Rx.
The Sharpe ratio was developed by Nobel laureate William F. Sharpe.
The above are only few of the many terms that may be useful for developers of robo-advisor software. I have tried to make them clear for developers, and hope the descriptions will be helpful when creating robo-advisor platforms.
This first list of wealth-management terminology is mostly related to portfolio and asset aspects. Subsequent lists will concern other terms and features of robo-advising. I will also include some mathematical details of the terms and explain how they are used in robo-advising platforms.
In the second post of the series, I focus on the most popular mathematical models for portfolio optimization: Modern Portfolio Theory, Black–Litterman Model, and Fama–French Model.