Andrei Nikiforov

Improved Bounds in Stochastic Matching and Optimization

Real-world problems often have parameters that are uncertain during the optimization phase; stochastic optimization or stochastic programming is a key approach introduced by Beale and by Dantzig in the 1950s to address such uncertainty. Matching is a classical problem in combinatorial optimization. Modern stochastic versions of this problem model problems in kidney exchange, for instance. We improve upon the current-best approximation bound of 3.709 for stochastic matching due to Adamczyk et al. (in: Algorithms-ESA 2015, Springer, Berlin, 2015) to 3.224; we also present improvements on Bansal et al. (Algorithmica 63(4):733–762, 2012) for hypergraph matching and for relaxed versions of the problem. These results are obtained by improved analyses and/or algorithms for rounding linear-programming relaxations of these problems.

Macroeconomic Announcements and the Distribution of Price‐Endings in the U.S. Treasury Market

We investigate how new information impacts quote clustering in the bond market. We find that clustering, along with quote activity, price volatility and bid‐ask spreads, increases sharply in the minutes following releases of macroeconomic news. Each returns to near‐normal levels within the hour. Effects are strongest for more liquid on‐the‐run notes and for the announcements typically associated with substantial information flow. The strong positive comovement of clustering, quote activity, price volatility, and bid‐ask spreads supports the conclusion that innovations of these variables are endogenous to the arrival and incorporation of information into prices.

Security design, market risk and round quotes in the treasury bond market

ABSTRACT Prior literature finds that the tendency of price-endings to cluster on rounder fractions increases with price volatility. We estimate the separate influences and relative importance of the determinants of price volatility, security design and market risks. Our data is from a market setting that is ideal for isolating and studying the relations of interest. Results for both quote and trade prices indicate that the tendency to use round price-endings increases with both a security’s inherent risk, attributable to security design, and variation over time in market risks. Security design influences clustering more than market risks, but market risks are influential in determining clustering once security design is fixed. The estimated effects are strongest in the on-the-run market segment where liquidity facilitates the aggregation of information into price.

Practical Applications of Fear and Greed: A Returns-Based Trading Strategy around Earnings Announcements

Timing markets correctly is the key to profiting from Warren Buffet’s advice to “Be fearful when others are greedy and greedy when others are fearful.” But until now contrarian investors have had to follow their gut. Authors Ivo Jansen and Andrei Nikiforov of Rutgers School of Business have developed a strategy based on earnings announcements—specifically, the reversals in extreme abnormal returns that often follow their release. The price-reversal phenomenon has been documented in the literature, but Jansen and Nikiforov demonstrate that the reversal around the actual earnings announcement date is about 60% higher than around non-earnings announcement dates. Furthermore, a trading strategy that exploits this reversal was shown to be profitable in 40 of the last 42 years in their 1971–2012 sample period. This article offers insight into their analysis.

Quote activity and round quotes in a voice-brokered bond market

ABSTRACT We investigate the relation between quote activity and the precision with which prices are quoted. Where prior literature finds that the tendency of price-endings to cluster on rounder fractions declines monotonically with quote activity, we show that the decline is limited to an initial range of quote activity. Once a very high level of quote activity is reached, the use of rounder quotes increases with quote activity. Also contrary to the conventional view is our finding that round quotes are used more frequently in the more active of two market segments where equivalent assets are traded. We attribute our results to two opposing influences of activity on price clustering, the price resolution and negotiation effects, that reflect the cognitive limitations of humans when dealing with uncertain values.

Fear and Greed: A Returns-Based Trading Strategy around Earnings Announcements

This article documents that earnings announcements serve as a reality check on short-term, fear- and greed-driven price development. Stocks with extreme abnormal returns in the week before an earnings announcement experience strong price reversals around the announcement. Basedon the findings of the authors, a trading strategy that exploits this reversal would have been profitable in 40 of the last 42 years and earned abnormal returns in excess of 1.3% over a two day-window.

Do Earnings Announcements Affect Trading Volume? The Role of Speculators

This study documents that total market volume is almost entirely unrelated to intertemporal variation in the number of earnings announcements. Thus, while individual earnings announcements, on average, significantly impact trading volume (e.g., Beaver, 1968), in aggregate this impact is minimal. We provide evidence that this seeming inconsistency is reconciled by the very large presence of speculators in the market, who trade around information events not for what those say about intrinsic values, but for the short-term price momentum they generate.

Human Bias in Algorithmic Trading

This paper documents a stark periodicity in intraday volume and in the number of trades. We find activity in both variables spikes by about 20% at regular intervals of 5 or 10 minutes throughout the trading day. We argue that this activity is the result of algorithmic trading influenced by human traders/programmers’ behavioral bias to transact on round time marks. An alternative explanation, that algorithms choose to concentrate their trades in time to take advantage of lower costs or to protect themselves from better informed traders, is not supported.

Practice Summaries: An Optimization Mathematical Model for Concentrated Solar Power Financing Decisions at Lockheed Martin

Concentrated solar power plants are an alternative to natural gas turbine plants in the portfolios of utilities and independent power producers (IPPs). To obtain financing for a new plant, an IPP must rigorously establish plant production guarantees. We developed an optimization model that maximizes annual profits by generating an optimal hour-by-hour production schedule. We use a fast greedy heuristic to solve this mathematical model. This work has enabled Lockheed Martin and its developer partners to be successful in project negotiations with major utility companies, resulting in 725 megawatts of power plants in development and over

Aggregate short selling during earnings seasons

5 billion in predicted sales.