Statistical Arbitrage Mining for Display Advertising

We study and formulate arbitrage in display advertising. Real-Time Bidding (RTB) mimics stock spot exchanges and utilises computers to algorithmically buy display ads per impression via a real-time auction. Despite the new automation, the ad markets are still informationally inefficient due to the heavily fragmented marketplaces. Two display impressions with similar or identical effectiveness (e.g., measured by conversion or click-through rates for a targeted audience) may sell for quite different prices at different market segments or pricing schemes. In this paper, we propose a novel data mining paradigm called Statistical Arbitrage Mining (SAM) focusing on mining and exploiting price discrepancies between two pricing schemes. In essence, our SAMer is a meta-bidder that hedges advertisers' risk between CPA (cost per action)-based campaigns and CPM (cost per mille impressions)-based ad inventories; it statistically assesses the potential profit and cost for an incoming CPM bid request against a portfolio of CPA campaigns based on the estimated conversion rate, bid landscape and other statistics learned from historical data. In SAM, (i) functional optimisation is utilised to seek for optimal bidding to maximise the expected arbitrage net profit, and (ii) a portfolio-based risk management solution is leveraged to reallocate bid volume and budget across the set of campaigns to make a risk and return trade-off. We propose to jointly optimise both components in an EM fashion with high efficiency to help the meta-bidder successfully catch the transient statistical arbitrage opportunities in RTB. Both the offline experiments on a real-world large-scale dataset and online A/B tests on a commercial platform demonstrate the effectiveness of our proposed solution in exploiting arbitrage in various model settings and market environments.Comment: In the proceedings of the 21st ACM SIGKDD international conference on Knowledge discovery and data mining (KDD 2015

Cross-Sectional Analysis of Stock Returns in Athens Stock Exchange for the Period 2004-2011

This study is an investigation of the factors affecting the average returns of stocks that were traded on the Athens Stock Exchange for the period July 2004 - June 2011. The methodological approach is similar to that applied by Fama and French (1992), in the first stage, stocks are grouped into portfolios with predefined criteria, and subsequently monthly cross sectional regressions are carried out, according to the Fama-MacBeth approach (1973). The main result of this study is that average stock returns in the ASE are not associated with the market beta (market risk) and there is not a strong relationship with any other risk factor for the stocks market value or book to market ratio

Combination Forecasts of Bond and Stock Returns: An Asset Allocation Perspective

We investigate the out-of-sample forecasting ability of the HML, SMB, momentum, short-term and long-term reversal factors along with their size and value decompositions on U.S. bond and stock returns for a variety of horizons ranging from the short run (1 month) to the long run (2 years). Our findings suggest that these factors contain significantly more information for future bond and stock market returns than the typically employed financial variables. Combination of forecasts of the empirical factors turns out to be particularly successful, especially from an an asset allocation perspective. Similar findings pertain to the European and Japanese markets

Evaluating Greek equity funds using data envelopment analysis

This study assesses the relative performance of Greek equity funds employing a non-parametric method, specifically Data Envelopment Analysis (DEA). Using an original sample of cost and operational attributes we explore the e¤ect of each variable on funds' operational efficiency for an oligopolistic and bank-dominated fund industry. Our results have significant implications for the investors' fund selection process since we are able to identify potential sources of inefficiencies for the funds. The most striking result is that the percentage of assets under management affects performance negatively, a conclusion which may be related to the structure of the domestic stock market. Furthermore, we provide evidence against the notion of funds' mean-variance efficiency

Double Exponential Instability of Triangular Arbitrage Systems

If financial markets displayed the informational efficiency postulated in the efficient markets hypothesis (EMH), arbitrage operations would be self-extinguishing. The present paper considers arbitrage sequences in foreign exchange (FX) markets, in which trading platforms and information are fragmented. In Kozyakin et al. (2010) and Cross et al. (2012) it was shown that sequences of triangular arbitrage operations in FX markets containing 4 currencies and trader-arbitrageurs tend to display periodicity or grow exponentially rather than being self-extinguishing. This paper extends the analysis to 5 or higher-order currency worlds. The key findings are that in a 5-currency world arbitrage sequences may also follow an exponential law as well as display periodicity, but that in higher-order currency worlds a double exponential law may additionally apply. There is an "inheritance of instability" in the higher-order currency worlds. Profitable arbitrage operations are thus endemic rather that displaying the self-extinguishing properties implied by the EMH.Comment: 22 pages, 22 bibliography references, expanded Introduction and Conclusion, added bibliohraphy reference

What Do the Fama-French Factors Add to C-CAPM?

This study extends standard C-CAPM by including two additional factors related to firm size (SMB) and book-to-market value ratio (HML) — the Fama–French factors. C-CAPM is least able to price firms with low book-to-market ratios. The explanation of these returns, as well as the returns on the SMB and HML portfolios, is significantly improved by the inclusion of the HML factor. The component of the risk premia explained by consumption varies across size. We suggest that a possible explanation for the role of HML is its association with the investment growth prospects of firms