|
on Market Microstructure |
| By: | Ledenyov, Dimitri O.; Ledenyov, Viktor O. |
| Abstract: | In the Schumpeterian creative disruption age, the authors firmly believe that an increasing application of electronic technologies in the finances opens a big number of new unlimited opportunities toward a new era of the ultra high frequency electronic trading in the foreign currencies exchange markets in the conditions of the discrete information absorption processes in the diffusion - type financial systems with the induced nonlinearities. Going from the academic literature, we discuss the probability theory and the statistics theory application to accurately characterize the trends in the foreign currencies exchange rates dynamics in the short and long time periods. We consider the financial analysis methods, including the macroeconomic analysis, market microstructure analysis and order flow analysis, to forecast the volatility in the foreign currencies exchange rates dynamics in the short and long time periods. We discuss the application of the Stratanovich-Kalman-Bucy filtering algorithm in the Stratanovich – Kalman – Bucy filter and the particle filter to accurately estimate the time series and predict the trends in the foreign currencies exchange rates dynamics in the short and long time periods. We research the influence by discrete information absorption on the ultra high frequency electronic trading strategies creation and execution during the electronic trading in the foreign currencies exchange markets. We formulate the Ledenyov law on the limiting frequency (the cut-off frequency) for the ultra high frequency electronic trading in the foreign currencies exchange markets. |
| Keywords: | absorption of information, diffusion of information, transmission of information, information theory, ultra high frequency electronic trading, processing frequency, algorithmic trading, informed trading, noise trading, currencies exchange rate, vehicle currency, interest rate, retail aggregator, liquidity aggregator, interdealer trade orders flow direction, stop-loss order, bid - ask spreads, price discovery process, capital inflow, capital outflow, carry trade strategy, financial liquidity, foreign currencies exchange market micro structure, foreign currencies exchange rate dynamics, Wiener filtering theory, Stratanovich-Kalman-Bucy filtering algorithm, Stratanovich – Kalman – Bucy filter, particle filter, nonlinearities, Ledenyov law on limiting frequency for ultra high frequency electronic trading in foreign currencies exchange markets, econophysics, econometrics, global foreign exchange market, global capital market |
| JEL: | C0 C01 C02 C1 C15 C3 C32 C41 C46 C53 C58 C63 F17 F30 F31 F32 G1 G17 |
| Date: | 2014–07–03 |
| URL: | http://d.repec.org/n?u=RePEc:pra:mprapa:57084&r=mst |
| By: | David E. Allen (University of Sydney, and University of South Australia, Australia); Michael McAleer (National Tsing Hua University, Taiwan; Erasmus University Rotterdam, Tinbergen Institute, the Netherlands; Complutense University Madrid, Spain); and Marcel Scharth (University of New South Wales, Australia) |
| Abstract: | In this paper we document that realized variation measures constructed from high-frequency returns reveal a large degree of volatility risk in stock and index returns, where we characterize volatility risk by the extent to which forecasting errors in realized volatility are substantive. Even though returns standardized by ex post quadratic variation measures are nearly gaussian, this unpredictability brings considerably more uncertainty to the empirically relevant ex ante distribution of returns. Explicitly modeling this volatility risk is fundamental. We propose a dually asymmetric realized volatility model, which incorporates the fact that realized volatility series are systematically more volatile in high volatility periods. Returns in this framework display time varying volatility, skewness and kurtosis. We provide a detailed account of the empirical advantages of the model using data on the S&P 500 index and eight other indexes and stocks. |
| Keywords: | Realized volatility, volatility of volatility, volatility risk, value-at-risk, forecasting, conditional heteroskedasticity |
| JEL: | C58 G12 |
| Date: | 2014–06–23 |
| URL: | http://d.repec.org/n?u=RePEc:dgr:uvatin:20140075&r=mst |
| By: | Amal Aouadi; Mohamed Arouri; Frédéric Teulon |
| Abstract: | The aim of this paper is to study the influence of investor attention on the French stock market activity and volatility. Following an original way, we construct a non-standard proxy of investor attention on the basis of investors' online search behavior exclusively provided by “Google insights for search”. We find that Google search volume is a reliable proxy of investor attention. Interestingly, we show that investor attention is strongly correlated to trading volume and is a significant determinant of the stock market illiquidity and volatility. Most importantly, this evidence is maintained even after controlling for the financial crisis effect. |
| Keywords: | Google search volume, Information asymmetry, Stock illiquidity, Volatility |
| Date: | 2014–06–27 |
| URL: | http://d.repec.org/n?u=RePEc:ipg:wpaper:2014-405&r=mst |
| By: | Garnier, Ernesto (RWTH Aachen University); Madlener, Reinhard (E.ON Energy Research Center, Future Energy Consumer Needs and Behavior (FCN)) |
| Abstract: | Forecasting the production of photovoltaic (PV) and wind power systems inevitably implies inaccuracies. Therefore, sales made based on forecasts almost always require the vendor to make balancing efforts. In the absence of resources available within their own portfolios, operators can turn towards the intraday market in order to avoid an engagement in the imbalance market with the resulting surcharges and regulatory penalties. In this paper, we combine a novel trade value concept with options valuation and dynamic programming to optimize volume and timing decisions of an individual operator without market power when compensating PV or wind power forecast errors in the market. The model employs a multi-dimensional binomial lattice, with trade value maximized at every node to help formulating bids in view of correlated, uncertain production forecast and price patterns. Inspired by the German electricity market's characteristics, we test the sensitivity of the model's output – namely trade timing and trade volume – to changing uncertainty and transaction cost parameters in 50 different setups. It shows that the model effectively outbalances price against volumetric risks. Trades are executed early and with large batch sizes in the case of price volatility. In contrast, increasing forecast error uncertainty leads to trade delays. High transaction costs trigger batch size reductions and ultimately further trade delays. Running 10,000 simulations across ten scenarios, we find that the model translates its flexible trade execution into a competitive advantage vis-à-vis static bidding strategy alternatives. |
| Keywords: | Bidding strategy; Production forecast; Renewable energy; Options; Intraday market |
| JEL: | G12 Q42 Q47 |
| Date: | 2014–02 |
| URL: | http://d.repec.org/n?u=RePEc:ris:fcnwpa:2014_002&r=mst |