Risk Management: Mortgage Vs. Cash Property Ownership – Risk management involves identifying, analyzing and accepting or minimizing uncertainty in investment decisions. Simply put, it is the process of monitoring and dealing with financial risks associated with investments. Risk management essentially occurs when an investor or fund manager attempts to analyze and determine the potential for loss in an investment, such as moral hazard, and then takes appropriate action (or inaction) to achieve their goals and assume risk.
Risk cannot be separated from return. Every investment has a certain amount of risk. It can be close to zero for US Treasury bills or very high for real estate in emerging market stocks or hyperinflationary markets. Risk is measured quantitatively in absolute and relative terms. A deeper understanding of risk in its various forms can help investors better understand the opportunities, trade-offs and costs associated with different investment approaches.
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Risk management involves identifying and analyzing where risks exist and making decisions about how to deal with them. This happens everywhere in the world of finance. For example:
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Diligent risk management can help reduce the likelihood of losses while ensuring financial goals are met. However, inadequate risk management can have serious consequences for companies, individuals and the economy. The subprime mortgage collapse that led to the Great Recession stemmed from poor risk management. Lenders gave mortgages to people with bad credit, and investment companies bought these loans, packaged them, and resold them to investors as risky, mortgage-backed securities (MBSs).
The word “risk” is often viewed negatively. But risk is an integral part of the investment world and cannot be separated from performance.
Investment risk is the deviation from expected results. This deviation is expressed in absolute terms or relative to something else, such as the market standard. Investment professionals generally agree that a deviation is some measure of the expected outcome of your investment, whether positive or negative.
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To get high returns, expect to accept a big risk. It is also recognized that increased risk means increased volatility. While investment professionals are constantly looking for and sometimes looking for ways to reduce volatility, there is no clear consensus on how to do it.
The amount of volatility an investor should accept depends entirely on his risk tolerance. For investment professionals, it depends on the tolerance of their investment goals. One of the most widely used measures of absolute risk is the standard deviation, which is a statistical measure of the dispersion around the central tendency.
Here’s how it works. Take the average investment return and find its average standard deviation over the same time period. The normal distribution (the familiar bell-shaped curve) dictates that the expected return on an investment can be one standard deviation from the mean 67% of the time and two standard deviations from the mean 95% of the time. It provides a numerical assessment of risk. If the risk is bearable (financially and emotionally), they may invest.
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Behavioral finance highlights the imbalance between people’s views of gain and loss. In probability theory, the field of behavioral finance introduced by Amos Tversky and Daniel Kahneman in 1979, investors avoid losses.
They note that investors place almost twice as much weight on pain associated with losses as they do on good feelings associated with gains.
Investors often want to know the losses that come with an investment as well as how much the asset deviates from its expected results. Value at risk (VAR) attempts to measure the amount of loss associated with an investment with a given level of confidence over a given period of time. For example, an investor can lose $200 on a $1,000 investment over a two-year period with a confidence level of 95%. Keep in mind that a measure like VAR does not guarantee that 5% of cases will be significantly worse.
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It also doesn’t take into account any of the unusual events that hit the Long Term Capital Management (LTCM) hedge fund in 1998. A default on the Russian government’s outstanding sovereign debt obligations threatened to bankrupt hedge funds, which took several valuable positions. $1. than a trillion dollars. Its failure could lead to the collapse of the global financial system. But the US government created a $3.65 billion loan fund to cover losses, enabling LTCM to avoid turmoil and liquidation in the early 2000s.
A confidence level is a probability statement based on the statistical characteristics of an investment and the shape of its distribution curve.
A measure of risk geared toward behavioral trends is the drawdown, which refers to any period in which an asset’s return is negative compared to a previous high. When measuring degradation, we try to address three things:
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For example, in addition to wanting to know whether a mutual fund has outperformed the S&P 500, we also want to know its relative risks. One solution to this is beta. Also called market risk, beta depends on the statistical properties of the covariance. A beta greater than 1 indicates greater risk from the market, while a beta less than 1 indicates less volatility.
Beta helps us understand the concepts of negative and positive risk. The chart below shows the time series of returns (each data point marked with a “+”) for a given portfolio R(p) versus the market return R(m). Returns are cash-adjusted, so the point where the x and y axes intersect is the cash-equivalent return. Drawing a line of best fit through the data points allows us to measure passive risk (beta) and active risk (alpha).
The gradient of the line is beta. So the formula of 1 implies that for every increase in the market return, the portfolio return also increases by one unit. A money manager using a passive management strategy can try to increase portfolio return by taking more market risk (ie a beta greater than 1) or alternatively reduce portfolio risk (and return) by reducing the portfolio beta to less than one.
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If market risk or systematic risk is the only influencing factor, the portfolio return will always equal the beta-adjusted market return. But this is not the case. Returns vary due to many factors unrelated to market risk. Investment managers following an active strategy assume other risks to achieve returns that exceed market performance, including:
Active managers look for alpha, which is a measure of excess return. In our chart example above, alpha is the amount of the portfolio’s return that is not explained by beta, which is represented by the distance between the intersection of the x and y axes and the intersection of the y axis. It can be positive or negative.
In their pursuit of excess returns, active managers expose investors to alpha risk, meaning their bets may turn out to be negative rather than positive. For example, a fund manager may believe that the energy sector will outperform the S&P 500 and overweight his portfolio in that sector. If unexpected economic developments cause energy stocks to fall sharply, the manager will underperform the benchmark index.
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The more alpha an active fund and its managers can generate, the higher the fees they charge. For purely passive vehicles like index funds or exchange traded funds (ETFs), you’ll pay between 1 and 10 basis points (bps) in annual management fees. Investors can pay 200 basis points in annual fees for a high-octane hedge fund with complex trading strategies, high capital commitments, and transaction costs. They may also have to return 20% of the profits to the manager.
The pricing difference between passive strategies (beta risk) and active strategies (alpha risk) encourages many investors to try to isolate these risks, such as paying low fees for estimated beta risk and concentrating expensive exposures on specifically defined alpha opportunities. This is commonly referred to as carry alpha, which is the assumption that the alpha component of the total return is separated from the beta component.
For example, a fund manager may claim to have an active sector rotation strategy to beat the S&P 500 with a track record of beating the index by 1.5% on an average annual basis. This excess return is the manager’s value (alpha) and the investor is willing to pay a higher fee to obtain it. Of course, residual total return (what the S&P 500 earned by itself) has nothing to do with a manager’s unique ability. Portable alpha strategies use derivatives and other instruments to optimize how the alpha and beta components of their exposure are acquired and paid.
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During the fifteen year period from August 1, 1992 to July 31, 2007, the average annual total return for the S&P 500 was 10.7%. This number tells what happened throughout the period, but it doesn’t show what happened along the way.
The average standard deviation of the S&P 500 for the same period was 13.5%. It is the difference between the average return and the actual return at several specific points over a 15-year period.
Applying the bell curve model, any result falls within one standard deviation of the mean approximately 67% of the time and within two standard deviations approximately 95% of the time. Thus, an S&P 500 investor can expect a return of 10.7% plus or minus any time during this period.
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