Risk Tolerance Of Investors Research Articles

Do Investment Risk Tolerance Attitudes Predict Portfolio Risk?

We investigated a new instrument designed to assess investment risk tolerance, the Risk Tolerance Questionnaire (RTQ). RTQ scores were positively correlated with scores on two other investment risk measures, but were not correlated with a measure of sensation-seeking (Zuckerman, 1994), suggesting that investment risk tolerance is not explainable by a general cross-domain appetite for risk. Importantly, RTQ scores were positively correlated with the riskiness of respondents’ actual investment portfolios, meaning that investors with high risk-tolerance score tend to have higher-risk portfolios. Finally, respondents with relatively more investment experience had more risk-tolerant responses and higher-risk portfolios than less experienced investors.

Risk Aversion and Personality Type

The finance literature supports an increasing role for behavioral aspects of investment decision-making. Among other factors such as demographics, personality type may influence risk tolerance as well. This paper explores the relationship between personality type dimensions of the Myers-Briggs Type Indicator (MBTI) and the moments approach to individual investor risk tolerance inherent in expected utility theory (EUT). Our study uses survey results to relate ex ante EUT tolerance for variance and skew to MBTI measures. Results indicate that personality type does explain individual ex ante EUT risk tolerance. Our results further suggest that the relationship between personality type and individual ex ante EUT risk tolerance is non-linear in form.

ASSESSING FINANCIAL RISK TOLERANCE OF PORTFOLIO INVESTORS USING DATA ENVELOPMENT ANALYSIS

For some investors their own personal investment counsellors address their investment strategy; for others automated means are used. To protect investors, the Canadian Government has enacted the "Know Your Client" Act requiring that all investment dealers and vendors of securities must know their clients and advise them on the appropriate investment strategy. This paper uses Data Envelopment Analysis (DEA) in a novel manner by applying it to a large data set of answers to a number of psychological questions. A Slacks Based Model was used to estimate investor risk tolerance. The model analyses the risk profile of the investor and can be used as a guide to match the risk rating of the investment vehicles for the client. Statistical comparisons were also carried out to show how risk tolerance relates to various demographic variables. Finally, the DEA results were validated through comparisons with the commercial system already in use.

Human Capital and Popular Investment Advice*

Popular investment advice recommends that the stock/bond and stock/wealth ratios should rise with investor risk tolerance and investment horizon respectively prescriptions that are difficult to reconcile with the simple mean-variance model. Canner et al. (1997) point out that the first piece of advice can potentially be explained by human capital considerations but only by invalidating the second piece of advice. We show that extending the mean-variance model to include human capital without any other modifications can simultaneously justify both recommendations so long as the correlation between human capital returns and stock market returns lies within a range determined by market and investor-specific parameters. Historical data from 11 countries generally satisfy this requirement although the statistical precision of our estimates is fairly weak.

The Only Game in Town: Stock-Price Consequences of Local Bias

Theory suggests that, in the presence of local bias, the price of a stock should be decreasing in the ratio of the aggregate book value of firms in its region to the aggregate risk tolerance of investors in its region. We test this proposition using data on U.S. Census regions and states, and find clear-cut support for it. Most of the variation in the ratio of interest comes from differences across regions in aggregate book value per capita. Regions with low population density - e.g., the Deep South - are home to relatively few firms per capita, which leads to higher stock prices via an only-game-in-town effect. This effect is especially pronounced for smaller, less visible firms, where the impact of location on stock prices is roughly 12 percent.

Human Capital and Popular Investment Advice

Popular investment advice recommends that the stock/bond and stock/wealth ratios should rise with investor risk tolerance and investment horizon respectively, prescriptions that are difficult to reconcile with standard models of portfolio choice. Canner et al. (1997) point out that the first piece of advice can potentially be explained by human capital considerations, but only by invalidating the second piece of advice. We show that extending the mean-variance model to include human capital can simultaneously justify both recommendations, so long as the correlation between human capital returns and stock market returns lies within a range determined by market and investor-specific parameters. Historical data from 11 countries generally satisfy this requirement, although the statistical precision of our estimates is fairly weak.

An Asset Allocation Sub-Puzzle

This paper documents a sub-puzzle in asset allocation. Canner, Mankiw and Weil (1997) point out that empirically the ratio of bond to stock holdings of a typical investor varies with her risk-averse attitude. This observation directly challenges the well-known mutual fund separation theorem of Tobin (1958) and Markowitz (1952). This paper reports additional evidence on investor's portfolio choice, finding that not only does the bonds to stocks ratio change, but within the stock portfolio, the ratio of high-risk stocks to low-risk stocks also changes with an investor's risk tolerance. This finding is important because most current literature attempts to solve the asset allocation puzzle by applying different interest rate models. Our finding shows that the puzzle involves more than just about interest rates, and needs a more fundamental examination from the perspective of an investors' risk attitude. Drawing on the loss aversion literature, we propose a general model that can solve both the Canner-Mankiw-Weil puzzle and the sub-puzzle. The key is that investors are loss averse and care about their expected worst-case returns. When an expected worst-return constraint is added to investors' utility maximization, the optimal ratio of low-risk to high-risk assets, be it bonds to stocks or low-risk stocks to high-risk stocks, changes with investors' risk attitudes.

Effects of Marriage and Children on Financial Risk Tolerance: A Synthesis of Family Development and Prospect Theory

Family development and prospect theory were used as a framework to predict variability in individuals' subjective financial risk tolerance within distinct family structures. Gender, age, and income were expected to interact with the main effects of family structure (marital status and children). Theory-generated hypotheses were examined in Study 1 (data from university housing respondents, n = 76) and Study 2 (the 1998 Survey of Consumer Finances, n = 4,305). One family structure main effect (child presence) was significant for investment risk tolerance in both studies. Family structure interactions (marital status × age and child × income) were significant for employment risk (Study 1), and child × age was significant for investment risk in Study 2.

Risk reduction in the United Kingdom property market

This paper investigates the potential benefits and limitations of equal and value-weighted diversification using as an example the UK institutional property market. To achieve this it uses the largest sample (392) of actual property returns that is currently available, over the period 1981 to 1996. To evaluate these issues two approaches are adopted; first, an analysis of the correlations within the sectors and regions and, second, simulations of property portfolios of increasing size constructed both naively and with value-weighting. Using these methods it is shown that the extent of possible risk reduction is limited because of the high positive correlations between assets in any portfolio, even when naively diversified. The results have implications for the development and maintenance of a property portfolio because they indicate that the achievable level of risk reduction depends upon the availability of assets, the weighting system used and the investor's risk tolerance.

Replication of Straddle Position and Evaluation of Its Performancein the Taiwan Stock Market

The purposes of this paper has twofold. One is to demonstate the replication of the Straddle position and the other is to examine its performance in the Taiwan stock market. We use the Taiwan Stock Exchange Index (TAIEX) and interest-rate of savings account to replicate Straddle position and compare its performance with dynamic portfolio insurance strategy and buy-and-hold strategy. The results indicate that (1) for synthetic Straddle strategy, the terminal values of assets are significantly reduced when transations costs are considered, but the influence between adjustment rules is insignificant; (2) Returns on synthetic Straddle strategy are relatively higher than those on synthetic puts or buy-and-hold strategies; (3) In bull markets, synthetic Straddle strategy performs best. In bear market, although synthetic put does provide insurance function, synthetic Straddle strategy can earn more positive returns. Finally, in correction markets, synthetic Straddle strategy performs worst; (4) The impact of stock price volatities on the performance of synthetic Straddle strategy is very significant; (5) Synthetic Straddle strategy obviously could not provide a stable return. inflow; And (6) the selection of investment strategies depends on the risk tolerance of investors. It seems that conservative investors will select portfolio insurance strategy, while only risk lovers can endure the Straddle strategy which is characterized by high risk and high return.

Equilibrium Exchange Rate Hedging

ABSTRACTWe assume a world like the one that gives the capital asset pricing model, but with many goods and many countries. We assume that investors in a given country have homothetic utility functions with the same weights, and a currency that has a sure end‐of‐period value using a price index with those weights. Siegel's paradox (derived from Jensen's inequality) makes investors want a positive amount of exchange risk. When average risk tolerance is the same across countries, every investor will hold the same mix of market risk (through the world market portfolio of all assets) and exchange risk (in a diversified basket of foreign currencies). In fact, the ratio of exchange risk to market risk is equal to the average investor's risk tolerance. We can write the ratio of exchange risk to market risk (and the fraction of the market's exchange risk that investors hedge) as depending on an average of world market risk premia, an average of world market volatilities, and an average of exchange rate volatilities. The weights in these averages are the same as the weights of the different countries in the currency basket. Given these averages, the ratio (and the fraction hedged) will not depend directly on exchange rate means or covariances. In equilibrium, we can use the ratio of exchange risk to market risk to measure average risk tolerance: in this model, risk tolerance is observable.

Equilibrium Exchange Rate Hedging

We assume a world like the one that gives the capital asset pricing model, but with many goods and many countries. We assume that investors in a given country have homothetic utility functions with the same weights, and a currency that has a sure end-of-period value using a price index with those weights. Siegel's paradox (derived from Jensen's inequality) makes investors want a positive amount of exchange risk. When average risk tolerance is the same across countries, every investor will hold the same mix of market risk (through the world market portfolio of all assets) and exchange risk (in a diversified basket of foreign currencies). In fact, the ratio of exchange risk to market risk is equal to the average investor's risk tolerance. We can write the ratio of exchange risk to market risk (and the fraction of the market's exchange risk that investors hedge) as depending on an average of world market risk premia, an average of world market volatilities, and an average of exchange rate volatilities. The weights in these averages are the same as the weights of the different countries in the currency basket. Given these averages, the ratio (and the fraction hedged) will not depend directly on exchange rate means or covariances. In equilibrium, we can use the ratio of exchange risk to market risk to measure average risk tolerance: in this model, risk tolerance is observable.

A Simple Solution for Optimal Currency Hedging

Rather than relying on historical experience to determine the optimal currency hedging strategy for portfolios that include foreign assets, one can use a simple procedure adapted from portfolio management theory. This procedure specifies the utility of a portfolio, given the investor's risk tolerance, asset and currency returns, standard deviations, weights and covariances. The sensitivity of the portfolio's utility can then be measured as a function of currency exposure. The portfolio's exposure to each currency to which utility is related positively is increased, and its exposure to each currency to which utility is related negatively is decreased. The portfolio's exposure to the currency with the largest sensitivity (in absolute terms) is iteratively adjusted until all the portfolio's sensitivities equal zero. This currency exposure represents the optimal portfolio-the one that offers the highest return for the chosen risk level. In some special cases, the optimal hedging strategy can be determined more directly. For example, the minimum-risk strategy for a single foreign asset can be identified by measuring the currency's beta relative to the underlying portfolio. For a portfolio with several foreign assets, the minimum-risk strategy can be defined by regressing the portfolio's returns on the currencies' returns. The basic procedure can also be adjusted to take inflation into account and to incorporate liabilities.