scholarly journals A study of efficiency in New Zealand election prediction markers

2021 ◽  
Author(s):  
◽  
Tram P. Cao
Keyword(s):  
Unit Root Test ◽  
Prediction Markets ◽  
Opinion Poll ◽  
Market Pricing ◽  
Market Prices ◽  
Arbitrage Opportunities ◽  
Election Prediction ◽  
Using Data ◽  
Abnormal Profits ◽  
Poll Data

<p>The development of prediction markets has naturally given rise to studies of their efficiency. Most studies of efficiency in prediction markets have focused on the speed with which they incorporate information. A necessary (but not sufficient) condition of efficiency is that arbitrage opportunities must non-existent or transitory in nature so that the systematic generation of abnormal profits is not possible. Using data from New Zealand’s first prediction market, iPredict, I examine the potential for arbitrage in the contracts for the party vote for the 2011 General Election. Relative to the risk-free interest rate, the returns from arbitrage are generally low, consistent with an efficient market. Regression analysis requires that the data not be subject to the possibility of spurious regressions - something that is not addressed in the literature. After confirming the non-stationarity of the price level and the stationarity of the price changes by the unit root test, I use the iPredict data in conjunction with opinion poll data to test whether the polls impact on market pricing behaviour. Using a number of different model types, I find that the opinion poll data has a very limited impact on market prices, suggesting that the information contained in the poll is largely already incorporated into market prices.</p>

scholarly journals A study of efficiency in New Zealand election prediction markers

2021 ◽  
Author(s):  
◽  
Tram P. Cao
Keyword(s):  
Unit Root Test ◽  
Prediction Markets ◽  
Opinion Poll ◽  
Market Pricing ◽  
Market Prices ◽  
Arbitrage Opportunities ◽  
Election Prediction ◽  
Using Data ◽  
Abnormal Profits ◽  
Poll Data

<p>The development of prediction markets has naturally given rise to studies of their efficiency. Most studies of efficiency in prediction markets have focused on the speed with which they incorporate information. A necessary (but not sufficient) condition of efficiency is that arbitrage opportunities must non-existent or transitory in nature so that the systematic generation of abnormal profits is not possible. Using data from New Zealand’s first prediction market, iPredict, I examine the potential for arbitrage in the contracts for the party vote for the 2011 General Election. Relative to the risk-free interest rate, the returns from arbitrage are generally low, consistent with an efficient market. Regression analysis requires that the data not be subject to the possibility of spurious regressions - something that is not addressed in the literature. After confirming the non-stationarity of the price level and the stationarity of the price changes by the unit root test, I use the iPredict data in conjunction with opinion poll data to test whether the polls impact on market pricing behaviour. Using a number of different model types, I find that the opinion poll data has a very limited impact on market prices, suggesting that the information contained in the poll is largely already incorporated into market prices.</p>

Using Prediction Market Prices to Differentiate Factors that Influence the Highest and Lowest Priced Tickets in Dynamic Pricing for Major League Baseball

2015 ◽  
Vol 9 (2) ◽  
pp. 43-63
Author(s):  
Rodney Paul ◽  
Andrew Weinbach
Keyword(s):  
Dynamic Pricing ◽  
Major League Baseball ◽  
Prediction Markets ◽  
Market Prices ◽  
Betting Market ◽  
Major League ◽  
Similarities And Differences ◽  
Using Data ◽  
Ticket Prices ◽  
Uncertainty Of Outcome

The use of prediction markets is extended to explain differences in preferences of fans that purchase different price levels of tickets under dynamic pricing for Major League Baseball.  Using data from eleven teams, this research investigates similarities and differences in variables that affect ticket prices for the highest-priced and lowest-priced tickets.  Key contrasts between the groups are found to stem from distinct preferences for uncertainty of outcome, measured by betting market odds, and team quality.  It is also shown that differences between the groups are attributable to sensitivity to factors such as key opponents, weekend games, opening day, and temperature.

ARBITRAGE TRADE IN PREDICTION MARKETS

2013 ◽  
Vol 6 (3) ◽  
pp. 14-26
Author(s):  
O Bergfjord ◽  
P. Kildal ◽  
T.A. McPherson ◽  
L.R. Loftaas ◽  
K. Valvik
Keyword(s):  
Presidential Election ◽  
Prediction Markets ◽  
Prediction Market ◽  
Political Opinion ◽  
Arbitrage Opportunities ◽  
Political Events ◽  
The Us ◽  
Time Zones ◽  
Using Data

By using data from five similar prediction market (PM) contracts on the 2008 American presidential election in two different market places targeted at investors of different nationalities, we investigate whether arbitrage opportunities across borders and market places exist in these markets. We find that arbitrage opportunities are rare and difficult to exploit.  Markets in these political events seem to be fairly efficient, even if they are located in different countries, time zones and are relatively small. However, inter-market arbitrage opportunities exist, and we hypothesize that this can be explained by differences in political opinion between the US and other countries.

CALL WARRANTS IN CHINA'S SECURITIES MARKET: PRICING BIASES AND INVESTORS' CONFUSION

2011 ◽  
Vol 07 (02) ◽  
pp. 333-345 ◽  
Author(s):  
WEI FAN ◽  
XINYI YUAN
Keyword(s):  
Lower Bounds ◽  
Securities Market ◽  
Market Pricing ◽  
Market Prices ◽  
No Arbitrage ◽  
Black Scholes Model ◽  
Price Performance ◽  
Black Scholes ◽  
Trading Mechanism ◽  
Using Data

This paper examines the price performance of call warrants in China's securities market. A recent sample of daily call warrant prices observed during the period from August 2005 to March 2007 is used. To the best of our knowledge this is the only recent study to using data from China and as such it greatly enhances our understanding of this particular market. On average, we find that the observed market prices are irrationally higher than the Black-Scholes model prices by 80.38% (using 180-day historical volatility) and 140.50% (using EGARCH volatility). However, we find another anomalous phenomenon that some of the call warrants prices are not only lower than the model prices, but have also recently been anomalously under their lower bounds. This finding seems to violate the "no arbitrage" principle. Among the convincing reasons, our findings indicate that trading mechanism constraints in China's securities market prevent rational investors from driving the prices of these call warrants to a reasonable level. Arbitrage chances are found to exist in some specific cases when the call warrant prices are below their lower bounds.

A Behaviorally Informed Survey-Powered Market Agent

2014 ◽  
Vol 8 (2) ◽  
pp. 1-28
Author(s):  
Jessica Inchauspe ◽  
Pavel Atanasov ◽  
Barbara Mellers ◽  
Philip Tetlock ◽  
Lyle Ungar
Keyword(s):  
Prediction Markets ◽  
Opinion Poll ◽  
Large Set ◽  
Prediction Market ◽  
Probability Estimates ◽  
Individual Probability ◽  
Continuous Double Auction ◽  
Zero Intelligence ◽  
Poll Data ◽  
Independent Probability

We introduce a new method for converting individual probability estimates (obtained through surveys) into market orders for use in a Continuous Double Auction prediction market. Our Survey-Powered Market Agent (SPMA) algorithm is based on actual forecaster behavior, and offers notable advantages over existing market agent algorithms such as Zero Intelligence Plus (ZIP) agents: SPMAs only require probability estimates (and not bid direction nor quantity), are more behaviorally realistic, and work well when probabilities change over time. We validate SPMA using prediction market data and probability estimates elicited through surveys from a large set of forecasters on 88 individual forecasting problems over the course of a year. SPMA outperforms simple averages of the same probability forecasts and is competitive with sophisticated opinion poll aggregation methods and prediction markets. We use a rich set of market and poll data to empirically test the assumptions behind SPMA’s operation. In addition to aggregation efficiency, SPMA provides a framework for studying how forecasters convert probability estimates into trading orders, and offers a foundation for building hybrid markets which mix market traders and individuals producing independent probability estimates.

scholarly journals Trade in Conflict Minerals -- Congolese Warlords, MNC’s, and Dodd-Frank 1502

Perceptions ◽  
2019 ◽  
Vol 5 (2) ◽  
Author(s):  
Ankit Deshmukh
Keyword(s):  
Supply Chain ◽  
Multinational Corporations ◽  
Primary Source ◽  
Market Prices ◽  
News Sources ◽  
Conflict Minerals ◽  
The Us ◽  
Face Threats ◽  
Using Data ◽  
The Eu

This paper seeks to provide an overview of conflict mineral trade by analyzing it through an economic lens. Using data gathered from news sources, the memo first defines the term “conflict minerals” and identifies that the primary actors involved in the conflict mineral market are rebel militia groups and multinational corporations. The trade is mutually beneficial for these actors as it serves as the primary source of revenue for militia groups and allows multinational corporations to buy minerals at low costs. The memo also highlights the struggles legitimate Congolese miners face, as they face threats from militia groups and low market prices Also identified is Section 1502 of the Dodd Frank act, legislation which forces multinational corporations to list their mineral suppliers, thereby increasing supply chain transparency. While implemented with good intentions, it is extremely unsuccessful in stifling the conflict mineral trade as it lacks substantive regulatory measures. Furthermore, the EU and US plan to implement opposing conflict mineral trade policies — the EU looks to increase supply chain transparency while the US looks to repeal Section 1502 of Dodd Frank (an action which would decrease supply chain transparency). This paper believes that coordinated and homogenous action on the part of both federal governments and IGOs is necessary in order to concretely enforce restrictions on conflict mineral trade.

Market Pricing of Bank M&As and Efficiency in Europe

2021 ◽  
pp. 91-110
Author(s):  
Sailesh Tanna ◽  
Hodian Urio ◽  
Ibrahim Yousef
Keyword(s):  
Stochastic Frontier Analysis ◽  
Shareholder Value ◽  
Stochastic Frontier ◽  
Abnormal Returns ◽  
Positive Influence ◽  
Bank Efficiency ◽  
Market Pricing ◽  
Frontier Analysis ◽  
Using Data ◽  
Merger Announcements

This study investigates the impact of bank mergers and acquisitions (M&As) on bank efficiency and how such efficiencies are expected to influence bank shareholder value upon merger announcements. It employs stochastic frontier analysis and event study methods along with regression analysis to account for the influences of pre-merger and post-merger efficiencies of bidders and targets in assessing their impact on bidder abnormal returns. Using data for a sample of large commercial bank M&As from 22 European countries, the authors find that bank bidders achieve short-term shareholder value gains from merger announcements, and this could be associated with the perceived efficiencies of bidders and targets. More generally, the evidence supports the view that bank profit efficiency has a positive influence on bidder returns from merger announcements, and therefore markets do take into account the importance of efficiency in value creation. This suggests that stock markets price operational efficiency of banks in predicting value gains from European Bank M&As.

Speculators and Middlemen: The Strategy and Performance of Investors in the Housing Market

2020 ◽  
Vol 33 (11) ◽  
pp. 5212-5247 ◽  
Author(s):  
Patrick Bayer ◽  
Christopher Geissler ◽  
Kyle Mangum ◽  
James W Roberts
Keyword(s):  
Los Angeles ◽  
Housing Market ◽  
Capital Stock ◽  
Individual Investors ◽  
Market Prices ◽  
And Performance ◽  
Using Data

Abstract Using data from the Los Angeles area from 1988 to 2012, we study the behavior and sources of returns of individual investors in the housing market. We document the existence of two distinct investor types. The first act as middlemen, purchasing substantially below and reselling above market prices throughout the cycle, improving liquidity and the existing capital stock in the process. The second act as speculators, who primarily enter during the boom, buying and selling at essentially market prices. Neither type anticipated the housing bust. We document similar behavior by speculators and middlemen in 96 other U.S. metro areas.

Analysis and Forecast of Tracking Performance of Hong Kong Exchange-Traded Funds: Evidence from Tracker Fund and X iShares A50

2016 ◽  
Vol 19 (04) ◽  
pp. 1650022 ◽  
Author(s):  
Patrick Kuok-Kun Chu
Keyword(s):  
Hong Kong ◽  
Trading Volume ◽  
Tracking Performance ◽  
Exchange Traded Funds ◽  
Time Series Regression ◽  
Market Prices ◽  
Bid Ask Spread ◽  
Arbitrage Opportunities ◽  
Relative Inability ◽  
Total Turnover

This study examines the tracking performance of two Hong Kong exchange-traded funds (ETFs): Tracker Fund and X iShares A50. The turnover of these two ETFs was more than half the total turnover of the 141 ETFs in the Hong Kong market during 2005–2013. Tracking performance is assessed using pricing deviation, which is found to be nonzero and predictable. This indicates that the premium paid by investors is of considerable economic interest. The significant differences in the tracking performance of physical ETFs and synthetic ETFs highlight the relative inability of synthetic ETF to track the market. Additionally, we document the existence of co-integration between the ETF prices and stock market prices. An econometric model is estimated to forecast the pricing deviation, which shows different price dynamics between the two ETFs, but an absence of arbitrage opportunities. The time series regression model of pricing deviation is significantly influenced by market value, dividend yield, trading volume, bid-ask spread, and market risk. The size of the regression coefficients indicates that synthetic ETFs have relatively poor ability to track the market during market fluctuations.

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