Ernest N. Biktimirov

Relationship Between Use of Online Support Materials and Student Performance in an Introductory Finance Course

The authors examined the relationship between student online activity, including access to specific course materials, and performance in a traditional face-to-face introductory finance course that a class Web site supported. The authors used 6 measures: (a) total hits, (b) hit consistency, (c) number of unique files that the students accessed, (d) accesses to homework solutions, (e) accesses to PowerPoint slides, and (f) accesses to exam solutions. Results indicated that access to homework solutions and, to lesser extent, hit consistency, were both positively related to student performance. In addition, results showed that access to specific files, rather than access to online course materials in general, was associated with better student performance.

Mapping Your Course: Designing a Graphic Syllabus for Introductory Finance

Abstract In this article, the authors offer a powerful teaching tool, the graphic syllabus, to help instructors meet the unique challenges of teaching introductory finance. This tool, a visual representation of the topical organization of the course, supplements and clarifies the text syllabus. The authors explain the instructional advantages of graphics, describe how to design a graphic syllabus, and provide an example of one for the introductory finance course. In the Appendix, they enumerate the available graphics software for composing a graphic syllabus.

The Effect of Demand on Stock Prices: Evidence from the S&P Index Float Adjustment

I examine the effect of demand on stock prices by analyzing the transition of the S&P 500 index from market capitalization to free float weighting, which occurred in 2005. I find that a decrease in demand produced a permanent stock price decline, which was accompanied by significant abnormal trading volume. The results provide support for the downward-sloping demand curve hypothesis.

Model-Based versus Model-Free Implied Volatility: Evidence from North American, European, and Asian Index Option Markets

The Black–Scholes (BS) implied volatility is well known to be a rather noisy forecast of future volatility. On the one hand, it has the advantage of potentially incorporating current information that cannot be captured by any statistical technique that relies on historical data. On the other hand, it is “risk neutral,” meaning that the market’s true volatility forecasts are distorted by risk preferences. But no other pricing model has taken the place of BS, so the forecasting performance “horse race” has been between BS IVs versus statistical models such as GARCH. In recent years, “model-free” implied volatility (MFIV) is becoming more common. MFIV is extracted from the entire set of current option prices without the need to assume any specific pricing model. That is certainly a desirable property, but there are a variety of methodological issues in calculating and using MFIV. In this article, Biktimirov and Wang conduct a serious horse race among these models, looking at how much each one contributes to forecast accuracy in predicting future volatility in 13 major international stock markets over a 10-year period. The winner, somewhat surprisingly, is BS IV, both in terms of in-sample “encompassing” models that include several forecasts in the same combined specification and also in out-of-sample forecasting.

Market reactions to corporate name changes: evidence from the Toronto Stock Exchange

Purpose The purpose of this paper is to examine stock price and trading volume reactions to name changes of the Toronto Stock Exchange listed companies. Previous studies present conflicting evidence on reactions to corporate name changes in US and other capital markets. Design/methodology/approach This study uses the event study methodology to calculate abnormal returns and trading volume around the announcement, approval, and effective dates of corporate name changes. It also contrasts abnormal returns between major and minor name changes, signaling focused and diversified strategies, accompanied with a ticker symbol change and without a ticker change, structural and pure name changes, as well as brand adoption and radical name changes. Findings Companies tend to experience a significant run-up in stock price in the period preceding the announcement of a name change. The stocks also show a significant positive abnormal return around the effective date. In addition, corporate name changes are associated with significant increases in trading volume for several days starting from the approval date. Most importantly, the type of a name change matters, as reflected in significance levels of abnormal return and trading volume reactions to various types of corporate name changes. Research limitations/implications The limitation of this study comes from the difficulty to precisely identify the date when the market learns about a possible corporate name change. Originality/value This study is the first to examine market reactions to name changes of Toronto Stock Exchange listed companies. Most importantly, whereas previous studies focus on the announcement day, this paper also considers the approval and effective days. It also contrasts responses between name changes accompanied with a new ticker and name changes without a ticker change.

Market Reactions to Changes in the S&P/TSX SmallCap Index

Stocks added to major indexes generally experience positive abnormal returns. However, researchers disagree on whether these abnormal returns are permanent or temporary, and offer competing explanations. We examine stock price and trading volume reactions to changes in the Canadian S&P/TSX SmallCap Index. Our primary finding is that significant changes in prices and trading volume occur for stocks added to or deleted from the S&P/TSX SmallCap Index. The effect depends on whether a stock is a pure addition or deletion as opposed to being shifted between S&P/TSX indexes.