Developing sustainable trading strategies using directional changes with high frequency data

Market prices are traditionally recorded in fixed time intervals. Directional Change is an alternative approach to summarize price movements in financial markets that is consistent with across all time scales. Unlike time series, directional change summarizes the big data in finance by focusing on the intrinsic time of the data. This captures deeper intrinsic data qualities and thus trading strategies based on directional change are more sustainable and less disruptive. In this paper, we propose four trading strategies using the concept of directional change and explore the combination with technical analysis. The trading strategies are tested using EUR/USD and GBP/USD high frequency FX market data. Empirical results show good performance of our trading strategies based on thresholds, and that combining with technical analysis brings further improvement

Review of blockchain-based distributed energy: Implications for institutional development

The future of energy is complex, with fluctuating renewable resources in increasingly distributed systems. It is suggested that blockchain technology is a timely innovation with potential to facilitate this future. Peer-to-peer (P2P) microgrids can support renewable energy as well as economically empower consumers and prosumers. However, the rapid development of blockchain and prospects for P2P energy networks is coupled with several grey areas in the institutional landscape. The purpose of this paper is to holistically explore potential challenges of blockchain-based P2P microgrids, and propose practical implications for institutional development as well as academia. An analytical framework for P2P microgrids is developed based on literature review as well as expert interviews. The framework incorporates 1) Technological, 2) Economic, 3) Social, 4) Environmental and 5) Institutional dimensions. Directions for future work in practical and academic contexts are identified. It is suggested that bridging the gap from technological to institutional readiness would require the incorporation of all dimensions as well as their inter-relatedness. Gradual institutional change leveraging community-building and regulatory sandbox approaches are proposed as potential pathways in incorporating this multi-dimensionality, reducing cross-sectoral silos, and facilitating interoperability between current and future systems. By offering insight through holistic conceptualization, this paper aims to contribute to expanding research in building the pillars of a more substantiated institutional arch for blockchain in the energy sector

Asset Pricing, Investment, and Trading Strategies

Asset pricing, investment, and trading strategies are very important in finance. They are useful in various situations, for example, supporting the decision-making process of choosing investments; determining the asset-specific required rate of return on the investment; pricing derivatives for trading or hedging; getting portfolios from fixed incomes or bonds, stocks, and other assets; evaluating diverse portfolios; determining macroeconomic variables affecting market prices; calculating option prices; and incorporating features such as mean reversion and volatility, etc. They can also be applied in financial forecast for assets, portfolios, business projects.Understanding, modeling, and using various asset pricing models, investment models, and models for different trading strategies is paramount in many different areas of finance and investment, including banking, stocks, bonds, currencies, and related financial derivatives. Different asset pricing models, investment models, and models for different trading strategies also allow us to compare the performances of different variables through the analysis of empirical real-world data.This Special Issue on "Asset Pricing, Investment, and Trading Strategies” will be devoted to advancements in the theoretical development of various asset pricing models, investment models, and models for different trading strategies as well as to their applications.The Special Issue will encompass innovative theoretical developments, challenging and exciting practical applications, and interesting case studies in the development and analysis of various asset pricing models, investment models, and models for different trading strategies in finance and cognate disciplines

Grain marketing policy changes and spatial efficiency of maize and wheat markets in Ethiopia

"In the context of on-going market reform in developing countries, there is a need for an improvement in the existing methods of spatial market efficiency analysis in order to better inform the debate toward designing and implementing new grain marketing policies, institutions, and infrastructure that facilitate the emergence of a well developed and competitive grain marketing system. The standard parity bounds model (PBM), while it overcomes many weaknesses of the conventional methods of spatial market efficiency analysis, it does not allow for the test of structural changes in spatial market efficiency as a result of policy changes. In this paper, building on the standard PBM, we develop an extended parity bounds model (EPBM). The EPBM is a stochastic gradual switching model with three trade regimes. The EPBM is estimated by maximum likelihood procedure and allows for tracing the time path and structural change in spatial market efficiency conditions due to the policy changes. We applied the EPBM to analyze the effect of grain marketing policy changes on spatial efficiency of maize and wheat markets in Ethiopia. The results show that the effect of policy changes on spatial market efficiency is not significant statistically in many cases; there is high probability of spatial inefficiency in maize and wheat markets before and after the policy changes. The implication of these results is that maize and wheat markets are characterized by periodic gluts and shortages, which can undermine the welfare of producers, grain traders and consumers. It is also observed that the nature of spatial inefficiency for maize and wheat markets is different implying that the two commodities might require different policy responses in order to improve spatial market efficiency. Maize traders made losses most of the time while wheat traders made excess profits most of the time covered by the study." Authors' AbstractStochastic analysis ,structural change ,

Challenges arising from alternative investment management.

Alternative investment management differs from traditional asset management in a number of respects. First, it is distinct in terms of both its targets – aiming to achieve an absolute performance, regardless of trends in underlying markets – and its strategies, in particular exploiting inefficiencies in the valuation of financial assets via opportunistic and discretionary positions. It also differs in terms of the financial techniques implemented, e.g. the extensive use made of leverage, derivatives and short selling, and the specific investment vehicles used (ad hoc structures such as hedge funds that are not bound by ordinary law in the way traditional investment vehicles are). These particularities, alongside the fact that the alternative investment universe is somewhat opaque, make it difficult to measure a fund’s risks or a fund manager’s performance. Specific measurement tools are therefore required, which differ from those commonly used in traditional asset management. Over the past few years, the alternative investment management, a diverse and rapidly-evolving universe, has enjoyed a spectacular development, which is illustrated by the sharp rise in the amounts under management and the proliferation of investment vehicles offered to an increasingly broad investor base. In view of the specific nature of alternative fund managers’ modus operandi, the flourishing of the alternative investment industry raises questions as to its implications in terms of financial stability. It also raises new issues regarding the division of roles between market participants and supervisory authorities in the organisation and monitoring of this asset management sector.

International Symposium on Evolutionary Breeding in Cereals

Evolutionary plant breeding has a long history, but has so far not become part of mainstream breeding research, nor has it been implemented in practice to any substantial degree. However, over the last decade, research in evolutionary plant breeding has markedly intensified. For example, there are currently major research projects on-going in this area, including the EU funded project SOLIBAM, the Wheat Breeding LINK project in the UK, and the Danish Biobreed project. Also, a new 3-year international research project called COBRA on this topic is due to start in March 2013. Funded by the CORE Organic 2 Eranet the project brings together over 40 partner organizations from 18 European countries. In addition, interest in evolutionary plant breeding is growing among farmers, breeders and policy makers. In fact, there are currently encouraging developments in the imminent revision of seed legislation in Europe that could lead to more room for evolutionary plant breeding approaches in the future. This renewed interest in evolutionary plant breeding is partly due to the recognition that mainstream plant breeding is limited in terms of its engagement with end users, i.e. farmers and growers. More urgently however, effects of climate change on agricultural production have become more noticeable and there is also a growing awareness of increasing resource constraints; together, these will create more stressful growing conditions for agricultural crops. With this background, it is now being recognized that crops need to be able to cope with more variable, contrasting, fluctuating, and generally more unpredictable growing conditions. To be able to deal with this large and increasing environmental variability, plant breeding needs to become more decentralized and diversified. Evolutionary plant breeding offers great potential in this respect. The contributions collated from this symposium explore this potential as well as the limitations of evolutionary plant breeding. While they only show a part of the on-going research activities in Europe, we hope that these proceedings provide inspiration both for further research and for implementation in practice

Integration of the international carbon market: A time-varying analysis

This is the final version. Available on open access from Elsevier via the DOI in this recordData availability: Data will be made available on request.Emission Trading Schemes (ETSs) have become vital for meeting global emission reduction targets. They are gaining momentum, as witnessed by increasing market size and improving information mechanisms. Examining key emission markets — European Union, New Zealand, California, and Hubei (China) — from April 2014 to December 2021, a Time-Varying Parameter Vector Autoregressive (TVP-VAR) model is applied to discern the markets' connectedness. In a novel approach to global carbon market research, this study uniquely combines the TVP-VAR with the connectedness approach, overcoming fixed parameters estimation and ensuring precise parameter estimates. The approach sheds light on patterns of total, directional, and net return/volatility spillovers, striving to identify which markets act as transmitters and which are receivers. Linking market spillovers to market characteristics, events, and policies offers insights for investors and policymakers. The total connectedness index of 10–12 % suggests a relatively low level of spillover, when compared to other market integration studies. The dynamic nature of return and volatility spillovers is evident, especially during the energy crisis and Covid-19 outbreak. The EU's ETS consistently acts as a net transmitter, predominantly in return connectedness, while New Zealand's ETS emerges as a major shock receiver in both return and volatility systems. Global climate negotiations and carbon market events have only a minor impact on the level of connectedness, in contrast to energy or financial crises and the Covid-19 outbreak. By highlighting the intricacies of carbon price volatility and market transmissions, the findings equip stakeholders with invaluable, actionable insights

Coordination in Networks Formation: Experimental Evidence on Learning and Salience

We present experiments on repeated non-cooperative network formation games, based on Bala and Goyal (2000). We treat the one-way and the two-ways flow models, each for high and low link costs. The models show both multiple equilibria and coordination problems. We conduct experiments under various conditions which control for salient labeling and learning dynamics. Contrary to previous experiments, we find that coordination on non-empty Strict Nash equilibria is not an easy task for subjects to achieve, even in the mono-directional model where the Strict Nash equilibria is a wheel. We find that salience significantly helps coordination, but only when subjects are pre-instructed to think of the wheel network as a reasonable way to play the networking game. Evidence on learning behavior provides support for subjects choosing strategies consistent with various learning rules, which include as the main ones Reinforcement and Fictitious Play.Experiments, Networks, Behavioral game theory, Salience, Learning dynamics

Financial Risk, Innovation and Alternative Pathways to Decarbonising the Energy System in 2050

There is a lot of forward looking work attempting to envisage the decarbonised energy system of the future as reflected with current interest in 'smart grids'. A central tenet behind most visions of the 'smart grids' of the future are the price signals that financial and commodity markets will deliver to facilitate effective and efficient resource allocation. Most of these visions take stylised and static views of financial and commodity markets despite the fact that these markets are experiencing dramatic change due to innovation and regulation. Accordingly, the paper maps the risks associated in the fusion of financial innovation with innovation in the energy system through a theoretical framework that draws on evolutionary models of paradigm shift. Risks to both the financial and energy systems are characterised as either emanating from primary or secondary markets and these are explored in terms of alternative visions of the energy system in the long run