Abstract:Based on daily prices (amtliche Kurse) we estimate effective spreads of securities traded at the Berlin Stock Exchange in 1880, 1890, 1900 and 1910. Several extensions of the Roll measure are applied. We find surprisingly tight effective spreads for the historical data, comparable with similar measures of the MDAX and DAX at the end of the 20th century. Copyright Oxford University Press Science+Business Media, LLC 2006
“… See Asparouhova, Bessembinder, and Kalcheva (2010), Bharath, Pasquariello, and Wu (2009), Gehrig and Fohlin (2006), Kim et al (2007), Lesmond, Schill, and Zhou (2004), or Lipson and Mortal (2009) for estimates of spreads for periods before the availability of intraday data. See Amihud, Lauterbach, and Mendelson (2003), Chakrabarti et al (2005), or Griffin, Kelly, and Nardari (2010) for examples of the application of Roll spread estimators to international data. …”
We develop a bid‐ask spread estimator from daily high and low prices. Daily high (low) prices are almost always buy (sell) trades. Hence, the high–low ratio reflects both the stock's variance and its bid‐ask spread. Although the variance component of the high–low ratio is proportional to the return interval, the spread component is not. This allows us to derive a spread estimator as a function of high–low ratios over 1‐day and 2‐day intervals. The estimator is easy to calculate, can be applied in a variety of research areas, and generally outperforms other low‐frequency estimators.
“… See Asparouhova, Bessembinder, and Kalcheva (2010), Bharath, Pasquariello, and Wu (2009), Gehrig and Fohlin (2006), Kim et al (2007), Lesmond, Schill, and Zhou (2004), or Lipson and Mortal (2009) for estimates of spreads for periods before the availability of intraday data. See Amihud, Lauterbach, and Mendelson (2003), Chakrabarti et al (2005), or Griffin, Kelly, and Nardari (2010) for examples of the application of Roll spread estimators to international data. …”
We develop a bid‐ask spread estimator from daily high and low prices. Daily high (low) prices are almost always buy (sell) trades. Hence, the high–low ratio reflects both the stock's variance and its bid‐ask spread. Although the variance component of the high–low ratio is proportional to the return interval, the spread component is not. This allows us to derive a spread estimator as a function of high–low ratios over 1‐day and 2‐day intervals. The estimator is easy to calculate, can be applied in a variety of research areas, and generally outperforms other low‐frequency estimators.
“…Note that Fohlin actually states that the ratio of the value of OTC trading to exchange trading increases by about 10 per cent a year.29 Two facts about the pre-World War I German stock market support this interpretation of the costs of the daily batch auction Gehrig and Fohlin (2006). find that the daily volatility of returns on the Berlin exchange was comparable to that on modern markets, whereasDeLong and Becht (1992) find that the monthly volatility of a Berlin index exhibits extremely low volatility compared to both contemporary and modern markets.…”
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confidence: 99%
“…Data from World Federation of Exchanges, Monthly Report, November 2015.27 The pricing process dates from the latter years of the 19th century and is described inGehrig and Fohlin (2006). For the process in the 1980s, seeBank of England (1984).…”
“…For bid–ask spreads, see Gehrig and Fohlin, ‘Trading costs’; for closed end funds, see Chambers and Esteves, ‘First global emerging markets investor’, and a new working paper by Campbell and Rogers, ‘Rise and returns of investment trusts’; and for IPO underpricing, see Chambers and Dimson, ‘IPO underpricing’; Burhop, ‘Underpricing of initial public offerings’; and Lehmann, ‘Taking firms to the stock market’.…”
It is often thought that the arrival of the Black–Scholes–Merton (BSM) model of option pricing in the early 1970s allowed traders to understand how to price and value options with greater precision. However, our study suggests that interwar commodity options traders may have been able to intuit ‘fair’ value and to adjust their prices to changes in the market environment well before the advent of this innovative model. A scarcity of historical price data has limited empirical tests of option price efficiency well before BSM to studies of stock options in the 1870s and the early twentieth century which revealed contrasting findings. This study deals with option pricing in a different market—commodities—during the interwar period. We conclude that option prices were closer to their BSM theoretical values than prior studies suggest. Institutional differences between interwar commodity options markets and stock options markets in the 1870s and the early twentieth century may partly account for this result. Furthermore, we find that interwar option prices were no more mispriced than in modern times, and were as sensitive to changes in volatility—the key valuation parameter in the BSM model.
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