Dynamic Execution of VWAP Orders with Short-Term Predictions

Lecture Notes in Business Information Processing, 2008

Gomber et al.

2012

This paper proposes a new dynamic approach to modelling intra-day trading volume based on factor models. It assumes that intra-day volume can be decomposed into two parts each predicted using separate time-series models. By enabling more accurate prediction of intra-day volume, this methodology allows for a significant reduction in the cost of executing Volume weighted Average Price orders.

2007

Volume Weighted Average Price (VWAP) for a stock is total traded value divided by total traded volume. It is a simple quality of execution measurement popular with institutional traders to measure the price impact of trading stock. This paper uses classic mean-variance optimization to develop VWAP strategies that attempt to trade at better than the market VWAP. These strategies exploit expected price drift by optimally 'front-loading' or 'back-loading' traded volume away from the minimum VWAP risk strategy.

… Working paper, Karlsruhe …, 2010

Svetlozar T. Rachev Chair of Statistics, Econometrics and Mathematical Finance, School of Economics and Business Engineering, KIT, and Department of Statistics and Applied Probability, University of California, Santa Barbara, and Chief-Scientist, FinAnalytica INC Kollegium am Schloss, ...

Journal of New Results in Science, 2022

Moving averages and indicators derived from these averages are used to predict the future direction the stocks will move. In manual and algorithmic trading, moving averages play a decisive role in decision-making. In this study, a new hybrid approach has been developed that can be used as an alternative to moving averages such as SMA, WMA, and EMA used in the literature. In BIST30 stocks in Turkey, the proposed method performs better than widely used indicators such as MACD, Stochastic, and RSI, commonly used in the literature.

Proceedings of the Seventh Ieee International Conference on E Commerce Technology, 2005

In this paper, we address the importance of efficient execution in electronic markets. Due to intense competition for profit opportunities, trading costs can represent a significant portion of overall return. They must be taken into account both when a specific trade is being executed, and when a general investment strategy is being designed. We empirically demonstrate that by combining market orders (which offer immediate execution regardless of price) and limit orders (which offer uncertain execution at a specified price), we are able to obtain a superior average price than by using market orders only. Our analysis highlights the trade-off between expected price improvement from limit orders and the risk of non-execution. We show how to determine the optimal limit order price in a simplified setting and suggest how this approach can be generalized to a complete solution. All of our experimental results are obtained on an extensive collection of NASDAQ limit order data.

Operations Research Proceedings 2008, 2009

Investors which trade in financial markets are interested in buying at low and selling at high prices. We suggest to solve this type of problem with an online algorithm. This active trading algorithm is based on reservation prices. The effectiveness of the algorithm is analyzed from a worst case and an average case point of view. We also compare the average case and the worst case bounds using simulation on historical data. Moreover, we want to give an answer to the question if the suggested active online trading algorithm shows a superior behaviour to buy-and-hold policies.

SSRN Electronic Journal, 2000

We investigate the information content of the limit order book (LOB) on the Tokyo Stock Exchange, the world's second largest order-driven exchange 1 . Microstructure parameters, such as the current cost-to-trade 1% of average daily volume and order book slope, consistently and significantly predict future price volatility, trade prices, and speed of trading. The shape of the LOB on the bid side carries more predictive power than that on the ask side. Next, we document that the average trade size is the driving force in the standard volume-volatility relationship.

SSRN Electronic Journal, 2000

VWAP is the Volume Weighted Average Price of traded stock over a defined period. It is a metric of trade execution quality used by institutional traders to minimize the execution cost of large trades. A riskless VWAP trading strategy is not possible without knowledge of final market volume. We formulate a mean-variance optimal VWAP strategy by assuming knowledge of final volume and then project this onto the space of strategies accessible to the VWAP trader. The mean variance optimal VWAP trading strategy is the sum of two distinct trading strategies, a minimum variance VWAP hedging strategy and a 'directional' price strategy independent of the hedging strategy and market VWAP. It is optimal for large volume VWAP traders to increase the size of the price 'directional' trade for additional return. *

We use high-frequency data from the Nasdaq exchange to build a measure of volume imbalance in the limit order book (LOB). We show that our measure is a good predictor of the sign of the next market order (MO), i.e. buy or sell, and also helps to predict price changes immediately after the arrival of an MO. Based on these empirical findings, we introduce and calibrate a Markov chain modulated pure jump model of price, spread, LO and MO arrivals, and volume imbalance. As an application of the model, we pose and solve a stochastic control problem for an agent who maximizes terminal wealth, subject to inventory penalties, by executing trades using LOs. We use in-sample-data (January to June 2014) to calibrate the model to ten equities traded in the Nasdaq exchange, and use out-of-sample data (July to December 2014) to test the performance of the strategy. We show that introducing our volume imbalance measure into the optimization problem considerably boosts the profits of the strategy. Profits increase because employing our imbalance measure reduces adverse selection costs and positions LOs in the book to take advantage of favorable price movements.