G10 - General Financial Markets: General (includes Measurement and Data)Return

Investment in various assets is associated with returns and risks. Especially precious metals are considered profitable and safe. Our analysis for the United States in 2005 - Q2 2015 demonstrates that it is very questionable. In this period, which included the US financial crisis, precious metals were coupled with a greater price volatility and lower real income than was the case with stocks in the DJIA index. Even over a sufficiently long period, gold and silver were not a good store of value with positive real returns. Moreover, demand deposits were also more profitable than gold in the longer term after 1980. In the long run, contrary to the beliefs, precious metals may not to keep good value in the physical form or in the form of securities linked to the price development of these assets. Commemorative and historical coins with a numismatic value are the most appropriate investment in precious metals. However, this investment is also associated with some risk.

By modifying and generalizing the wavelet-based approach of approximately simulating univariate long-memory processes that is available in the literature, we propose a methodology for simulating a bivariate stationary process, whose components exhibit different relationships at different scales. We derive the formulas for the autocovariance and cross-covariance sequences of the simulated bivariate process. We provide a setting for the parameters of the simulation which might generate a bivariate time series resembling that of stock log returns. Using this setting, we study the properties of our methodology via Monte Carlo simulation.

The paper deals with high-frequency algorithmic trading (HFT), which has recently come to dominate some financial markets, e.g. the US equity markets. The author first attempts to establish a clear definition of high-frequency trading. With the most important characteristics having been analysed, it is concluded that such a definition would not bring more clarity into the debate over HFT. Strategies pursued by traders should be given consideration instead. On this account, the text proceeds with the examination of the most common strategies. Afterwards, the question is raised whether the rise of high-frequency algorithmic traders has resulted in more efficient financial markets. Based on robust evidence from academic research, important market participants and exchanges, HFT indeed seems to improve market quality by narrowing spreads and providing additional liquidity - the market-making strategy is mainly responsible for the latter. Issues such as possible system risks (flash crashes, herd behaviour) are also discussed.

Percival and Walden (2002) present a wavelet methodology of the least squares estimation of the long memory parameter for fractionally differenced processes. We suggest that the general idea of using wavelets for estimating long memory could be used for the estimation of long memory in time series perturbed by noise. One prominent example thereof is the time series of log-Garman-Klass estimates of log volatility of financial markets. The estimator of Percival and Walden (2002) is biased if the long memory time series is perturbed by noise. We propose a new estimator of the long memory parameter which combines (in its construction) the frequency-domain approach of Sun & Phillips (2003) and the approach of Percival & Walden (2002). We illustrate the properties of the proposed estimator via Monte Carlo simulations. The results show that the estimator may be useful for the estimation of the long memory in volatility.

The article provides a basic description and taxonomy of sovereign wealth funds, rapidly gaining importance in the international monetary and financial systems. SFWs are pools of assets owned and managed directly or indirectly by governments to achieve specific objectives. Tentative estimates of foreign assets held by SWFs are between USD 1.9 trillion and USD 2.9 trillion. These amounts are about 10 times less than the assets under management of mature market institutional investors and modestly higher than those managed by hedge funds. Current IMF projections are that sovereign wealth funds will accumulate international assets under sovereign management up to about USD 12 trillion by 2012, but growth estimates are different. The author's estimate of the SWFs' growth by 2013 is between USD 3.9-5.4 trillion. These funds have raised concerns about financial stability, corporate governance and political interference and protectionism. The following analysis does not prove the negative distortions of these funds on global financial stability and capital flows. In response to these concerns, the IMF with SWFs have made public voluntary Generally Accepted Principles and Practices (GAPP) for SWF, and the OECD has published guidance on recepient country policies towards the SWFs. Recipient countries should strive to avoid protectionism and should uphold fair and transparent investment frameworks.

We examine whether it is rational to put limit orders in a limit order market. We find that limit orders are not needed and may be even disadvantageous given that the agent trades on-line. Further, we present a numerical study indicating that putting limit orders may be optimal given that the agent trades at discrete times but the benefit from using them in comparison with immediate buying and selling is negligible.