Proportion Of Risky Assets Research Articles

Fund Price Analysis Using Convolutional Neural Networks for Multiple Variables

Investing in funds has the effect of indirectly employing asset management professionals with specialized knowledge and experience, which can result in a diversified investment through the use of a portfolio. In this study, we focus on learning the patterns of prices rather than time points to predict Korean fund prices. We convert time-series data into 2-dimensional images and analyze them using a convolutional neural network. To improve the fund price forecasting performance, we consider the following aspects. A Korean fund should be recommended according to the level of risk aversion. The risk level of the fund is determined by the proportion of risky assets. Therefore, when estimating the fund price, the risk level of the fund needs to be considered. In this study, we use 15 additional variables, such as foreign stock indexes, foreign exchange rates, and Korean stock indices, in addition to the fund price data. The appropriate filter size, which plays an important role in this process, is proposed. In addition, types of networks and architectures are selected as suitable for forecasting the fund price. We also demonstrate that the number of output classes can be adjusted to increase the future return of the fund. Through this methodology with multiple variables, we can achieve a 25% cumulative profit for 2 years. This means that multi-variable models have a higher cumulative return than the single-variable model and KOSPI and thus a higher average of all funds for active investors.

Benchmarking superannuation funds based on relative performance

In this article, we assess fund performance using data envelopment analysis (DEA). For each inefficient fund, DEA provides a set of role model funds whose best practices may be emulated for performance improvement. We find that the role models of most inefficient funds consist entirely of funds different from their own type. To overcome this situation, we suggest a multi-step DEA procedure. The procedure starts by categorizing funds on a hierarchical basis. We establish the hierarchy based on the frequency of efficient funds that belong to each fund type. Thereafter, a set of role model funds for each inefficient fund is found by pooling the funds in its own category and the funds that belongs to the categories at the lower levels in the hierarchy and applying DEA. This procedure is repeated by augmenting the pool with funds at the next higher level and so on until all the sampled funds are included. At each step, a set of role models is identified. An inefficient fund can thus reach the efficient frontier in stages. Statistical evidence suggests that membership and proportion of risky assets may have a negative association, and the fund size may have a positive association with fund performance.

Risk Preferences of Australian Households: A Panel Study

Using household panel data for Australia sourced from HILDA, we explore how household risk preferences in relation to portfolio holdings differ across wealth ranges and in relation to various household sociodemographic characteristics across the nation. Our measure of risk is based on the proportion of variance of the optimal household portfolio rather than the proportion of risky assets in the portfolio. Based on this measure, we estimate the coefficients of relative risk aversion for investors in various wealth ranges. In contrast to most studies, we find evidence of very high risk aversion amongst the majority of households. However, this is heavily concentrated amongst less wealthy households. We apply a first differences model across three survey waves spanning 2002 to 2010, and focus on the aggregate national level. We find that risk tolerance increases significantly with household wealth, the relationship is both statistically and economically significant. Liquidity contraints in the form of rental payments were found to diminish household appetite for risk. However, risk tolerance is positively associated with mortgage payments.

The Loan Herding of Chinese Banks for Industrial Lending and the Subsequent Economic Impact

By using a uniquely compiled dataset, this study first examines whether Chinese banks exhibit the inter-temporal loan herding in industrial lending during 2006-2011. We decompose the inter-temporal correlation in lending into the own following and other following. Our results find that the correlation in lending for joint-equity banks and city banks primarily result from their loan herding. Next, we clarify the reasons that affect and cause loan herding. Our results show that loan herding significantly occurs in banks with a higher proportion of risky assets, a higher proportion of non-performing loans, a lower capitalization and a lower ROE. The two motivations for loan herding include reputational herding and characteristic herding. Finally, we aggregately analyze whether and how the loan herding of the same type and different types affect the multiple dimensions in real economy. We find that loan herding cause bank lending to risky industrial firms, which leads to the significant harmful impacts on real economic activities such as the industrial GDP growth, stock prices, price-earnings ratios, bank non-performing loans and foreign direct investment in the following year.

An Asset Allocation Puzzle: Comment

Should the proportion of risky assets in the risky part of an investor’s portfolio depend on the investor’s risk aversion? According to basic financial theory, in particular the mutual-fund separation theorem with a riskless asset, the answer is no. The theorem states that rational investors should divide their assets between a riskless asset and a risky mutual fund, the composition of which is the same for all investors. Risk aversion affects only the allocation between the riskless asset and the fund. However, Niko Canner et al. (1997), CMW hereafter, observed that popular investment advice does not conform to this theory. They reported the stocks, bonds, and cash allocations recommended by four advisors for conservative, moderate, and aggressive investors. As shown in Table 1, which is reproduced from CMW, the advisors recommend a bond/stock ratio that varies directly with risk aversion. For example, Fidelity recommends a bond/stock ratio of 1.50 for a “conservative” (more riskaverse) investor, a ratio of 1.00 for a “moderate” (less risk-averse) investor, and a ratio of 0.46 for an “aggressive” (still less risk-averse) investor. The inconsistency between such advice and the separation theorem is called an asset allocation puzzle by CMW. They attempted to solve the puzzle by relaxing key assumptions in the theory, but finally reached a negative conclusion: “Although we cannot rule out the possibility that popular advice is consistent with some model of rational behavior, we have so far been unable to find such a model” (p. 181). However, they suggested that consideration of intertemporal trading might help resolve the puzzle. In the present paper, we provide theoretical support for the popular advice. The two key insights are that the investor’s horizon may exceed the maturity of the cash asset and that the investor rebalances the portfolio as time passes. If the investor’s horizon exceeds the maturity of cash, which might be a money-market security with maturity of one to six months, then cash is not the riskless asset as is commonly assumed in the basic theory. In a theory allowing portfolio rebalancing, as opposed to a buy-and-hold framework, it is not unreasonable to assume that the investor can synthesize a riskless asset (a zero-coupon bond maturing at the horizon) using a bond fund and cash. Then bonds will be both in the (synthetic) riskless asset and in the risky mutual fund and we show that in this case the theoretical bond/stock ratio varies directly with risk aversion for any hyperbolic absolute risk aversion (HARA) investor. As an example of the type of results that a specific model can produce, we provide a continuous-time model with closed-form solutions, which produces theoretical bond/stock ratios similar to the popular advice. The present paper is organized as follows: in the next section, we analyze the popular advice in terms of the theory of mutual-fund separation of David Cass and Joseph E. Stiglitz (1970). We show that this theory is relevant both in static and dynamic frameworks and use it to analyze the popular advice in complete and incomplete markets. In Section II, we analyze the popular advice in the context of Robert C. Merton’s (1971) continuous-time statement of mutualfund separation and present an illustrative model in which a CRRA investor makes continuous-time portfolio decisions under interest rate and stock price uncertainty. In Section III, numerical results are compared with the popular advice. Section IV is a conclusion. * Bajeux-Besnainou: Department of Finance, School of Business and Public Management, George Washington University, 2023 G Street NW, Washington, DC 20052; Jordan: National Economic Research Associates, 1255 23rd Street NW, Washington, DC 20037; Portait: CNAM and ESSEC, Finance Chair CNAM, 2 Rue Conte, Paris, France. This research was supported by a grant from the Institute for Quantitative Investment Research. We thank two anonymous referees for their comments. 1 HARA functions include quadratic utility, which is one way of justifying mean-variance preferences, and constant relative risk aversion (CRRA) utility. Both quadratic and CRRA utility were considered in the CMW analysis.

Risques financiers : juniors vs seniors

Financial risks : juniors vs. seniors We consider the proportion of risky assets (stocks, bonds,...) among the household portfolios as a function of householder age, using two surveys conducted in 1995 on the holdings of financial assets. Unlike a common idea, older households hold more risky assets than their younger counterparts, both for homeowners and non homeowners and also among all wealth classes. We present the datasets used, the chosen classification of risky and riskless assets and we consider some explanations of the obtained results : learning effects, behaviour towards risk, background risk. We investigate the hypothesis that the volatility of young households earnings is high and thus that they minimize their risky financial investments.

Relative risk aversion once more: An analysis of Japanese households' financial asset holding pattern

It is widely accepted that as the total assets increse, households tend to diversify their portfolios. In other words, absolute risk aversion is decreasing. On the other hand, the proportion of risky assets may increase or decrease depending on whether relative risk aversion (RRA) is decreasing or increasing, and its direction is still left open as an empirical question. This study examines the constancy of RRA from Japanese individual households' financial asset holding data collected in 1984. Constant RRA implies that the proportion of risky assets in one's portfolio is constant regardless of the amount of total assets. A casual observation of household portfolio holding pattern suggests that this implication is clearly violated by the data, because there are substantial proportion of households which do not hold any risky assets. Zero-holding, however, may be interpreted as a result of fixed transaction cost incurred by individual investors when they hold risky assets. Then, we pose a question, ‘Do investors hold constant proportion of risky assets, when they decide to hold them?’