1332:
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1327:{\displaystyle {\begin{array}{lcr}R_{i,1}=\gamma _{1,0}+\gamma _{1,1}{\hat {\beta }}_{i,F_{1}}+\gamma _{1,2}{\hat {\beta }}_{i,F_{2}}+\cdots +\gamma _{1,m}{\hat {\beta }}_{i,F_{m}}+\epsilon _{i,1}\\R_{i,2}=\gamma _{2,0}+\gamma _{2,1}{\hat {\beta }}_{i,F_{1}}+\gamma _{2,2}{\hat {\beta }}_{i,F_{2}}+\cdots +\gamma _{2,m}{\hat {\beta }}_{i,F_{m}}+\epsilon _{i,2}\\\vdots \\R_{i,T}=\gamma _{T,0}+\gamma _{T,1}{\hat {\beta }}_{i,F_{1}}+\gamma _{T,2}{\hat {\beta }}_{i,F_{2}}+\cdots +\gamma _{T,m}{\hat {\beta }}_{i,F_{m}}+\epsilon _{i,T}\end{array}}}
71:
1600:
641:{\displaystyle {\begin{array}{lcr}R_{1,t}=\alpha _{1}+\beta _{1,F_{1}}F_{1,t}+\beta _{1,F_{2}}F_{2,t}+\cdots +\beta _{1,F_{m}}F_{m,t}+\epsilon _{1,t}\\R_{2,t}=\alpha _{2}+\beta _{2,F_{1}}F_{1,t}+\beta _{2,F_{2}}F_{2,t}+\cdots +\beta _{2,F_{m}}F_{m,t}+\epsilon _{2,t}\\\vdots \\R_{n,t}=\alpha _{n}+\beta _{n,F_{1}}F_{1,t}+\beta _{n,F_{2}}F_{2,t}+\cdots +\beta _{n,F_{m}}F_{m,t}+\epsilon _{n,t}\end{array}}}
1352:
This means Fama MacBeth regressions may be inappropriate to use in many corporate finance settings where project holding periods tend to be long. For alternative methods of correcting standard errors for time series and cross-sectional correlation in the error term look into double clustering by firm
1348:
corrected only for cross-sectional correlation. The standard errors from this method do not correct for time-series autocorrelation. This is usually not a problem for stock trading since stocks have weak time-series autocorrelation in daily and weekly holding periods, but autocorrelation is stronger
1340:
and James D. MacBeth (1973) demonstrated that the residuals of risk-return regressions and the observed "fair game" properties of the coefficients are consistent with an "efficient capital market" (quotes in the original).
1551:
1588:
1641:
1573:—Page by M. Petersen discussing the estimation of Fama–MacBeth and clustered standard errors in various statistical packages (
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1570:
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1410:
1508:
Petersen, Mitchell (2009). "Estimating
Standard Errors in Finance Panel Data Sets: Comparing Approaches".
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time periods against the previously estimated betas to determine the risk premium for each factor.
1675:
1519:
1419:
1408:
Fama, Eugene F.; MacBeth, James D. (1973). "Risk, Return, and
Equilibrium: Empirical Tests".
8:
1463:
Fama, E. F.; French, K. R. (1988). "Permanent and temporary components of stock prices".
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Fama-MacBeth and
Cluster-Robust (by Firm and Time) Standard Errors in R
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52:
1552:"EconTerms - Glossary of Economic Research "Fama–MacBeth Regression""
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67:
proposed risk factors to determine each asset's beta exposures.
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51:
The method works with multiple assets across time (
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55:). The parameters are estimated in two steps:
43:that are expected to determine asset prices.
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23:is a method used to estimate parameters for
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1344:Note that Fama MacBeth regressions provide
650:Then regress all asset returns for each of
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1571:Software estimation of standard errors
1368:Standard errors in regression analysis
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1392:"Fama-MacBeth Two-Step Regression"
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31:(CAPM). The method estimates the
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16:Method for estimating parameters
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1:
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1614:. You can help Knowledge by
1466:Journal of Political Economy
1411:Journal of Political Economy
7:
1511:Review of Financial Studies
1363:Capital asset pricing model
1356:
29:capital asset pricing model
10:
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1671:Economic theories stubs
21:Fama–MacBeth regression
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63:asset returns against
59:First regress each of
1610:related article is a
1349:over long horizons.
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1558:on 28 September 2007
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25:asset pricing models
1390:IHS EViews (2014).
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1518:(1): 435–480.
1500:
1479:10.1086/261535
1473:(2): 246–273.
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1434:10.1086/260061
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1418:(3): 607–636.
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1616:expanding it
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1560:. Retrieved
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41:risk factors
27:such as the
20:
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47:Methodology
37:risk premia
1655:Categories
1562:2 November
1374:References
1353:and year.
53:panel data
1520:CiteSeerX
1495:153814656
1420:CiteSeerX
1306:ϵ
1277:^
1274:β
1255:γ
1248:⋯
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155:β
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100:α
1450:13725978
1357:See also
39:for any
1487:1833108
1442:1831028
1522:
1493:
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1448:
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1606:This
1575:Stata
1491:S2CID
1483:JSTOR
1446:S2CID
1438:JSTOR
1395:(PDF)
33:betas
1612:stub
1564:2006
35:and
19:The
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1530:doi
1475:doi
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889:i
885:R
875:1
872:,
869:i
861:+
854:m
850:F
846:,
843:i
824:m
821:,
818:1
810:+
804:+
797:2
793:F
789:,
786:i
767:2
764:,
761:1
753:+
746:1
742:F
738:,
735:i
716:1
713:,
710:1
702:+
697:0
694:,
691:1
683:=
678:1
675:,
672:i
668:R
652:T
630:t
627:,
624:n
616:+
611:t
608:,
605:m
601:F
593:m
589:F
585:,
582:n
574:+
568:+
563:t
560:,
557:2
553:F
545:2
541:F
537:,
534:n
526:+
521:t
518:,
515:1
511:F
503:1
499:F
495:,
492:n
484:+
479:n
471:=
466:t
463:,
460:n
456:R
439:t
436:,
433:2
425:+
420:t
417:,
414:m
410:F
402:m
398:F
394:,
391:2
383:+
377:+
372:t
369:,
366:2
362:F
354:2
350:F
346:,
343:2
335:+
330:t
327:,
324:1
320:F
312:1
308:F
304:,
301:2
293:+
288:2
280:=
275:t
272:,
269:2
265:R
255:t
252:,
249:1
241:+
236:t
233:,
230:m
226:F
218:m
214:F
210:,
207:1
199:+
193:+
188:t
185:,
182:2
178:F
170:2
166:F
162:,
159:1
151:+
146:t
143:,
140:1
136:F
128:1
124:F
120:,
117:1
109:+
104:1
96:=
91:t
88:,
85:1
81:R
65:m
61:n
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