Learning the CAPM through Bubbles

Bubbles are generally considered the outcome of investor irrationality or informational asymmetry, both objectionable in efficient markets with rational investors. We introduce an Intertemporal-CAPM with market clearing between high- and low-risk-averse rational investors who learn the CAPM under incomplete, yet symmetric information. Periodic equilibrium prices make a lognormal price process that nests the classic CAPM with a potential for endogenous bubbles through learning. The absence of comparables through the introductory phase of new technologies results in unstable return dynamics that might burst to bubbles or decline to near-zero, “pink-sheet†valuations. When the technology shifts phase to generate real profits the return dynamics is convergent, revealing the classic CAPM. Once the real technology return is observable, over- and under-pricing can be assessed, resulting in prompt positive or negative price adjustments toward the CAPM valuation. Correspondence with the Abreu and Brunnermeier (2003) model of bubbles with rational arbitrageurs is presented as well.ICAPM; Bubbles; New Technologies; Rational Expectations

Why Would Financial Bubbles Evolve After New Technologies?

This paper presents an equity market where the value of a new technology is infrequently observable while the equity claim of the asset is continuously traded. We clear the stock market between two optimal asset allocation strategies, speculative vs. fundamental, adopted by risk-averse investors who differ in their rist-aversion. The stock price path maintains a potential for endogenous bubbles or under-pricing vs. the asset as a function of total funds invested in the stock by each investor type. Bubbles grow exponentially if speculation dominates but if the fundamental strategy dominates, the stock\u27s growth rate and its volatility will decline

A Robust Valuation Model for Entrepreneurial Ventures

Pro forma estimation of financial statements often builds on constant ratios to sales revenue. While constant ratios may be relevant for established firms operating in predictable industries, they yield noninformative and possibly misleading information when applied to new firms, and particularly to technology ventures. Because new firms grow and change rapidly, a robust analysis should be based on intimate familiarity with the specific firm\u27s business plan. This paper presents an alternative approach that links the firm\u27s budget, as derived from its business plan, to pro forma financial statements, and to valuation models. The resulting estimated firm value is less sensitive to exogenous parameter assumptions than other methodologies

Price Bubbles of New-Technology IPOs

Asset pricing models with atomistic agents typically relax assumptions concerning rationality and/or homogenous information in order to track endogenous bubbles. In this model, identically informed rational agents hold a Perceived Law of Motion (PLM) for a single new technology asset at IPO, yet they differ with respect to risk aversion. By mapping risk preferences to strategies, we use marginal supply and demand functions to solve for the PLM if REE holds. By relaxing the assumption of complete knowledge of agent\u27s tastes and wealth, post-IPO bubbles emerge where the Actual Law of Motion is an amplification (bubble) of the price processes vs. the PLM

The Impact of Retail Investors Sentiment on Conditional Volatility of Stocks and Bonds

We measure bond and stock conditional return volatility as a function of changes in sentiment, proxied by six indicators from the Tel Aviv Stock Exchange. We find that changes in sentiment affect conditional volatilities at different magnitudes and often in an opposite manner in the two markets, subject to market states. We are the first to measure bonds conditional volatility of retail investors sentiment thanks to a unique dataset of corporate bond returns from a limit-order-book with highly active retail traders. This market structure differs from the prevalent OTC platforms, where institutional investors are active yet less prone to sentiment.Comment: 32 Pages, 4 Table

Does Risk Seeking Drive Asset Prices? A stochastic dominance analysis of aggregate investor preferences

We investigate whether risk seeking or non-concave utility functions can help to explain the cross-sectional pattern of stock returns. For this purpose, we analyze the stochastic dominance efficiency classification of the value-weighted market portfolio relative to benchmark portfolios based on market capitalization, book-to-market equity ratio and momentum. We use various existing and novel stochastic dominance criteria that account for the possibility that investors exhibit local risk seeking behavior. Our results suggest that Markowitz type utility functions, with risk aversion for losses and risk seeking for gains, can capture the cross-sectional pattern of stock returns. The low average yield on big caps, growth stocks and past losers may reflect investors' twin desire for downside protection in bear markets and upside potential in bull markets

Does Risk Seeking drive Asset Prices?

We investigate whether risk seeking or non-concave utility functions can help to explain the cross-sectional pattern0 of stock returns. For this purpose, we analyze the stochastic dominance efficiency classification of the value-weighted market portfolio relative to benchmark portfolios based on market capitalization, book-to-market equity ratio and momentum. We use various existing and novel stochastic dominance criteria that account for the possibility that investors exhibit local risk seeking behavior. Our results suggest that Markowitz type utility functions, with risk aversion for losses and risk seeking for gains, can capture the cross-sectional pattern of stock returns. The low average yield on big caps, growth stocks and past losers may reflect investors' twin desire for downside protection in bear markets and upside potential in bull markets

Herding, Heterogeneity, and Momentum Trading of Institutional Investors Across Asset Classes

This paper examines herding, heterogeneity, and momentum trading of institutional investors in Israel across a broad variety of financial assets. While previous studies typically focus on stocks only, we examine herding patterns, heterogeneity, and momentum trading of institutional investors in five asset classes. We find that during the sample period (1/2002 – 12/2011) large investors tended to herd more than medium and small-size investors. In contrast, small investors used momentum trading patterns more than medium and large-size investors. Homogeneity was found among large investors, especially pension funds, and during the first half of the 2000s, when investors purchased corporate bonds at the expense of government bonds. This phenomenon ended upon the beginning of the subprime crisis and against the backdrop of the financial difficulties of the bond issuers. In those years, panicked investors withdrew funds from the most liquid institutions (study funds), while infusing funds to pension and provident funds due to legally binding arrangements. We attribute some of the heterogeneous trading of the institutional investors, to those factors