return to []() since pdf building failed

Author: HumphreyYang

lectures/_config.yml

@@ -124,6 +124,8 @@ sphinx:
       schelling:     https://intro.quantecon.org/schelling.html
       scalar_dynam:  https://intro.quantecon.org/scalar_dynam.html
       complex_and_trig: https://intro.quantecon.org/complex_and_trig.html
+      doubts_or_variability: https://python-advanced.quantecon.org/doubts_or_variability.html
+      risk_aversion_or_mistaken_beliefs: https://python-advanced.quantecon.org/risk_aversion_or_mistaken_beliefs.html
     # sphinx-proof
     proof_minimal_theme: true
     # sphinx-exercise

lectures/affine_risk_prices.md

@@ -45,7 +45,7 @@ among expected returns across assets.
 
 Empirical difficulties with this specification (the equity premium puzzle, the
 risk-free rate puzzle, and the Hansen-Jagannathan bounds discussed in
-{doc}`advanced:doubts_or_variability`) motivate the alternative approach
+[Doubts or Variability](https://python-advanced.quantecon.org/doubts_or_variability.html)) motivate the alternative approach
 described in this lecture.
 
 Put bluntly, the model to be studied in this lecture  declares the Lucas asset pricing model's stochastic discount factor to be a failure.
@@ -71,7 +71,7 @@ Key applications we study include:
    ({cite:t}`AngPiazzesi2003`).
 3. *Risk-neutral probabilities*: a change-of-measure representation of the pricing equation.
 4. *Distorted beliefs*: reinterpreting risk price estimates when agents hold systematically
-   biased forecasts ({cite:t}`piazzesi2015trend`); see also {doc}`advanced:risk_aversion_or_mistaken_beliefs`.
+   biased forecasts ({cite:t}`piazzesi2015trend`); see also [Risk Aversion or Mistaken Beliefs](https://python-advanced.quantecon.org/risk_aversion_or_mistaken_beliefs.html).
 
 We start with the following imports:
 
@@ -1387,7 +1387,7 @@ Disentangling belief distortions from genuine risk prices requires additional
 data, for example, the survey forecasts used by
 {cite:t}`piazzesi2015trend`.
 
-Our {doc}`advanced:risk_aversion_or_mistaken_beliefs` lecture
+Our [Risk Aversion or Mistaken Beliefs](https://python-advanced.quantecon.org/risk_aversion_or_mistaken_beliefs.html) lecture
 explores this confounding in greater depth.
 
 ## Concluding remarks
@@ -1409,7 +1409,7 @@ Key features are:
    {cite:t}`piazzesi2015trend`.
 
 The model also connects directly to the Hansen–Jagannathan bounds studied in
-{doc}`advanced:doubts_or_variability` and to robust
+[Doubts or Variability](https://python-advanced.quantecon.org/doubts_or_variability.html) and to robust
 control interpretations of the stochastic discount factor described in other
 chapters of {cite:t}`Ljungqvist2012`.
 

lectures/survival_recursive_preferences.md

@@ -124,7 +124,7 @@ $$ (eq:felicity)
 where $\nu$ is the endogenous discount rate.
 
 ```{note}
-In discrete time, Epstein-Zin preferences aggregate current consumption with a certainty equivalent of future utility via a CES aggregator (see {doc}`advanced:doubts_or_variability`).
+In discrete time, Epstein-Zin preferences aggregate current consumption with a certainty equivalent of future utility via a CES aggregator (see [Doubts or Variability](https://python-advanced.quantecon.org/doubts_or_variability.html)).
 
 In continuous time there is no "next-period $V_{t+1}$," so {cite:t}`Duffie_Epstein1992a` recast the recursion as a felicity function $F(C,\nu)$ that depends on the agent's own continuation-value rate $\nu$.